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Archive for the ‘Coronavirus Gene Expression’ Category

Vaccinology in the Age of Pandemics:
Strategies Against COVID-19 & Other Global Threats

Reporter: Aviva Lev-Ari, PhD, RN

 

June 15–16, 2020 | 11:00AM–3:30PM ET | 3:00–7:30PM UTC | 5:00–9:30PM CEST*
*Program is subject to change

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As the world faces the greatest global pandemic of our lifetimes, the critical importance of vaccine development has come to the forefront of scientific and public audiences alike. Over the course of history, vaccination has enabled us to conquer devastating diseases from measles to smallpox, but new challenges arise when addressing an emerging pandemic in real time. This virtual meeting will assemble the world’s leading vaccinology and global health experts to present the latest advances in vaccine design and development. Finally, this virtual conference will discuss how to best apply these strategies in the context of the current pandemic.

The field of vaccinology has made great leaps in recent years, providing novel technologies and approaches that can be leveraged to our advantage against the novel coronavirus, COVID-19. Incredible advances in science and technology now make it technically possible to develop vaccines against many new targets. Meanwhile, innovative approaches to vaccine development are tackling challenges of emerging infections and implementation in low-income countries. These advances, among many others, will guide the way towards a safe and effective COVID-19 vaccine. Additionally, these new scientific advances will set the stage for success against this pandemic, as vaccinologists race against the ever-rising global death toll.

This virtual meeting program will cover many important facets of vaccine science, technology and strategy, including:

  • transformative new technologies, including structure-based design, adjuvants, nucleic acid vaccines (especially RNA), viral vectors, systems biology, and controlled human infections
  • scientific underpinnings of new vaccinology strategies, including advances in the fields of human immunology, genomics, synthetic biology, molecular structure of antigens and antigen-antibody complexes, germinal centers, and microbiome
  • multidisciplinary technologies and strategies, including efforts of Coalition for Epidemic Preparedness Innovations (CEPI), Bill & Melinda Gates Foundation and Wellcome Trust, which will change the way vaccines are developed

Program is intended for scientific researchers and clinical audiences.

Join us for this landmark virtual event, brought to you by Keystone Symposia.

Regular Registration Rate: $50 USD

#VKSvaxcovid19

SPEAKERS

Program Details

Keynote Speaker


Anthony S. Fauci, MD
Anthony S. Fauci, MD
NIAID, National Institutes of Health
Transforming Vaccinology: Considerations for the Next Decade

Speaking at this eSymposia


Galit Alter

MIT and Harvard University

Yasmine Belkaid

NIAID, National Institutes of Health

Anthony S. Fauci, MD

Anthony S. Fauci

NIAID, National Institutes of Health

Barney S. Graham

NIAID, National Institutes of Health

Richard Hatchett

Coalition for Epidemic Preparedness Innovations, CEPI

Neil P. King

University of Washington

Antonio Lanzavecchia

Institute for Research in Biomedicine

Ulrike Protzer

Technische Universität München

Bali Pulendran

Stanford University School of Medicine

Rino Rappuoli

GlaxoSmithKline Vaccines

Federica Sallusto

Università della Svizzera Italiana & ETH Zurich

Robert A. Seder

NIAID, National Institutes of Health

Christine Shaw

Moderna

Gabriel D. Victora

Gabriel D. Victora

Rockefeller University

Hedda Wardemann

German Cancer Research Center

Catherine J. Wu

Dana-Farber Cancer Institute

SOURCE

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Crowdsourcing Difficult-to-Collect Epidemiological Data in Pandemics: Lessons from Ebola to the current COVID-19 Pandemic

 

Curator: Stephen J. Williams, Ph.D.

 

At the onset of the COVID-19 pandemic, epidemiological data from the origin of the Sars-Cov2 outbreak, notably from the Wuhan region in China, was sparse.  In fact, official individual patient data rarely become available early on in an outbreak, when that data is needed most. Epidemiological data was just emerging from China as countries like Italy, Spain, and the United States started to experience a rapid emergence of the outbreak in their respective countries.  China, made of 31 geographical provinces, is a vast and complex country, with both large urban and rural areas.

 

 

 

As a result of this geographical diversity and differences in healthcare coverage across the country, epidemiological data can be challenging.  For instance, cancer incidence data for regions and whole country is difficult to calculate as there are not many regional cancer data collection efforts, contrasted with the cancer statistics collected in the United States, which is meticulously collected by cancer registries in each region, state and municipality.  Therefore, countries like China must depend on hospital record data and autopsy reports in order to back-extrapolate cancer incidence data.  This is the case in some developed countries like Italy where cancer registry is administered by a local government and may not be as extensive (for example in the Napoli region of Italy).

 

 

 

 

 

 

Population density China by province. Source https://www.unicef.cn/en/figure-13-population-density-province-2017

 

 

 

Epidemiologists, in areas in which data collection may be challenging, are relying on alternate means of data collection such as using devices connected to the internet-of-things such as mobile devices, or in some cases, social media is becoming useful to obtain health related data.  Such as effort to acquire pharmacovigilance data, patient engagement, and oral chemotherapeutic adherence using the social media site Twitter has been discussed in earlier posts: (see below)

Twitter is Becoming a Powerful Tool in Science and Medicine at https://pharmaceuticalintelligence.com/2014/11/06/twitter-is-becoming-a-powerful-tool-in-science-and-medicine/

 

 

 

 

 

Now epidemiologists are finding crowd-sourced data from social media and social networks becoming useful in collecting COVID-19 related data in those countries where health data collection efforts may be sub-optimal.  In a recent paper in The Lancet Digital Health [1], authors Kaiyuan Sun, Jenny Chen, and Cecile Viboud present data from the COVID-19 outbreak in China using information collected over social network sites as well as public news outlets and find strong correlations with later-released government statistics, showing the usefulness in such social and crowd-sourcing strategies to collect pertinent time-sensitive data.  In particular, the authors aim was to investigate this strategy of data collection to reduce the time delays between infection and detection, isolation and reporting of cases.

The paper is summarized below:

Kaiyuan Sun, PhD Jenny Chen, BScn Cécile Viboud, PhD . (2020).  Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study.  The Lancet: Digital Health; Volume 2, Issue 4, E201-E208.

Summary

Background

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

Methods

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

Findings

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35–60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

Interpretation

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

A Few notes on Methodology:

  • The authors used crowd-sourced reports from DXY.cn, a social network for Chinese physicians, health-care professionals, pharmacies and health-care facilities. This online platform provides real time coverage of the COVID-19 outbreak in China
  • More data was curated from news media, television and includes time-stamped information on COVID-19 cases
  • These reports are publicly available, de-identified patient data
  • No patient consent was needed and no ethics approval was required
  • Data was collected between January 20, 2020 and January 31,2020
  • Sex, age, province of identification, travel history, dates of symptom development was collected
  • Additional data was collected for other international sites of the pandemic including Cambodia, Canada, France, Germany, Hong Kong, India, Italy, Japan, Malaysia, Nepal, Russia, Singapore, UK, and USA
  • All patients in database had laboratory confirmation of infection

 

Results

  • 507 patient data was collected with 153 visited and 152 resident of Wuhan
  • Reported cases were skewed toward males however the overall population curve is skewed toward males in China
  • Most cases (26%) were from Beijing (urban area) while an equal amount were from rural areas combined (Shaanzi and Yunnan)
  • Age distribution of COVID cases were skewed toward older age groups with median age of 45 HOWEVER there were surprisingly a statistically high amount of cases less than 5 years of age
  • Outbreak progression based on the crowd-sourced patient line was consistent with the data published by the China Center for Disease Control
  • Median reporting delay in the authors crowd-sourcing data was 5 days
  • Crowd-sourced data was able to detect apparent rapid growth of newly reported cases during the collection period in several provinces outside of Hubei province, which is consistent with local government data

The following graphs show age distribution for China in 2017 and predicted for 2050.

projected age distribution China 2050. Source https://chinapower.csis.org/aging-problem/

 

 

 

 

 

 

 

 

 

 

 

 

The authors have previously used this curation of news methodology to analyze the Ebola outbreak[2].

A further use of the crowd-sourced database was availability of travel histories for patients returning from Wuhan and onset of symptoms, allowing for estimation of incubation periods.

The following published literature has also used these datasets:

Backer JA, Klinkenberg D, Wallinga J: Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020, 25(5).

Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, Azman AS, Reich NG, Lessler J: The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of internal medicine 2020, 172(9):577-582.

Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KSM, Lau EHY, Wong JY et al: Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. The New England journal of medicine 2020, 382(13):1199-1207.

Dataset is available on the Laboratory for the Modeling of Biological and Socio-technical systems website of Northeastern University at https://www.mobs-lab.org/.

References

  1. Sun K, Chen J, Viboud C: Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study. The Lancet Digital health 2020, 2(4):e201-e208.
  2. Cleaton JM, Viboud C, Simonsen L, Hurtado AM, Chowell G: Characterizing Ebola Transmission Patterns Based on Internet News Reports. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2016, 62(1):24-31.

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Powerful AI Tools Being Developed for the COVID-19 Fight

Curator: Stephen J. Williams, Ph.D.

 

Source: https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/

IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19

April 3, 2020 | Written by: 

IBM Research has been actively developing new cloud and AI-powered technologies that can help researchers across a variety of scientific disciplines accelerate the process of discovery. As the COVID-19 pandemic unfolds, we continue to ask how these technologies and our scientific knowledge can help in the global battle against coronavirus.

Today, we are making available multiple novel, free resources from across IBM to help healthcare researchers, doctors and scientists around the world accelerate COVID-19 drug discovery: from gathering insights, to applying the latest virus genomic information and identifying potential targets for treatments, to creating new drug molecule candidates.

Though some of the resources are still in exploratory stages, IBM is making them available to qualifying researchers at no charge to aid the international scientific investigation of COVID-19.

Today’s announcement follows our recent leadership in launching the U.S. COVID-19 High Performance Computing Consortium, which is harnessing massive computing power in the effort to help confront the coronavirus.

Streamlining the Search for Information

Healthcare agencies and governments around the world have quickly amassed medical and other relevant data about the pandemic. And, there are already vast troves of medical research that could prove relevant to COVID-19. Yet, as with any large volume of disparate data sources, it is difficult to efficiently aggregate and analyze that data in ways that can yield scientific insights.

To help researchers access structured and unstructured data quickly, we are offering a cloud-based AI research resource that has been trained on a corpus of thousands of scientific papers contained in the COVID-19 Open Research Dataset (CORD-19), prepared by the White House and a coalition of research groups, and licensed databases from the DrugBankClinicaltrials.gov and GenBank. This tool uses our advanced AI and allows researchers to pose specific queries to the collections of papers and to extract critical COVID-19 knowledge quickly. Please note, access to this resource will be granted only to qualified researchers. To learn more and request access, please click here.

Aiding the Hunt for Treatments

The traditional drug discovery pipeline relies on a library of compounds that are screened, improved, and tested to determine safety and efficacy. In dealing with new pathogens such as SARS-CoV-2, there is the potential to enhance the compound libraries with additional novel compounds. To help address this need, IBM Research has recently created a new, AI-generative framework which can rapidly identify novel peptides, proteins, drug candidates and materials.

We have applied this AI technology against three COVID-19 targets to identify 3,000 new small molecules as potential COVID-19 therapeutic candidates. IBM is releasing these molecules under an open license, and researchers can study them via a new interactive molecular explorer tool to understand their characteristics and relationship to COVID-19 and identify candidates that might have desirable properties to be further pursued in drug development.

To streamline efforts to identify new treatments for COVID-19, we are also making the IBM Functional Genomics Platform available for free for the duration of the pandemic. Built to discover the molecular features in viral and bacterial genomes, this cloud-based repository and research tool includes genes, proteins and other molecular targets from sequenced viral and bacterial organisms in one place with connections pre-computed to help accelerate discovery of molecular targets required for drug design, test development and treatment.

Select IBM collaborators from government agencies, academic institutions and other organizations already use this platform for bacterial genomic study. And now, those working on COVID-19 can request the IBM Functional Genomics Platform interface to explore the genomic features of the virus. Access to the IBM Functional Genomics Platform will be prioritized for those conducting COVID-19 research. To learn more and request access, please click here.

Drug and Disease Information

Clinicians and healthcare professionals on the frontlines of care will also have free access to hundreds of pieces of evidence-based, curated COVID-19 and infectious disease content from IBM Micromedex and EBSCO DynaMed. Using these two rich decision support solutions, users will have access to drug and disease information in a single and comprehensive search. Clinicians can also provide patients with consumer-friendly patient education handouts with relevant, actionable medical information. IBM Micromedex is one of the largest online reference databases for medication information and is used by more than 4,500 hospitals and health systems worldwide. EBSCO DynaMed provides peer-reviewed clinical content, including systematic literature reviews in 28 specialties for comprehensive disease topics, health conditions and abnormal findings, to highly focused topics on evaluation, differential diagnosis and management.

The scientific community is working hard to make important new discoveries relevant to the treatment of COVID-19, and we’re hopeful that releasing these novel tools will help accelerate this global effort. This work also outlines our long-term vision for the future of accelerated discovery, where multi-disciplinary scientists and clinicians work together to rapidly and effectively create next generation therapeutics, aided by novel AI-powered technologies.

Learn more about IBM’s response to COVID-19: IBM.com/COVID19.

Source: https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/

DiA Imaging Analysis Receives Grant to Accelerate Global Access to its AI Ultrasound Solutions in the Fight Against COVID-19

Source: https://www.grantnews.com/news-articles/?rkey=20200512UN05506&filter=12337

Grant will allow company to accelerate access to its AI solutions and use of ultrasound in COVID-19 emergency settings

TEL AVIV, IsraelMay 12, 2020 /PRNewswire-PRWeb/ — DiA Imaging Analysis, a leading provider of AI based ultrasound analysis solutions, today announced that it has received a government grant from the Israel Innovation Authority (IIA) to develop solutions for ultrasound imaging analysis of COVID-19 patients using Artificial Intelligence (AI).Using ultrasound in point of care emergency settings has gained momentum since the outbreak of COVID-19 pandemic. In these settings, which include makeshift hospital COVID-19 departments and triage “tents,” portable ultrasound offers clinicians diagnostic decision support, with the added advantage of being easier to disinfect and eliminating the need to transport patients from one room to another.However, analyzing ultrasound images is a process that it is still mostly done visually, leading to a growing market need for automated solutions and decision support.As the leading provider of AI solutions for ultrasound analysis and backed by Connecticut Innovations, DiA makes ultrasound analysis smarter and accessible to both new and expert ultrasound users with various levels of experience. The company’s flagship LVivo Cardio Toolbox for AI-based cardiac ultrasound analysis enables clinicians to automatically generate objective clinical analysis, with increased accuracy and efficiency to support decisions about patient treatment and care.

The IIA grant provides a budget of millions NIS to increase access to DiA’s solutions for users in Israel and globally, and accelerate R&D with a focus on new AI solutions for COVID-19 patient management. DiA solutions are vendor-neutral and platform agnostic, as well as powered to run in low processing, mobile environments like handheld ultrasound.Recent data highlights the importance of looking at the heart during the progression of COVID-19, with one study citing 20% of patients hospitalized with COVID-19 showing signs of heart damage and increased mortality rates in those patients. DiA’s LVivo cardiac analysis solutions automatically generate objective, quantified cardiac ultrasound results to enable point-of-care clinicians to assess cardiac function on the spot, near patients’ bedside.

According to Dr. Ami Applebaum, the Chairman of the Board of the IIA, “The purpose of IIA’s call was to bring solutions to global markets for fighting COVID-19, with an emphasis on relevancy, fast time to market and collaborations promising continuity of the Israeli economy. DiA meets these requirements with AI innovation for ultrasound.”DiA has received several FDA/CE clearances and established distribution partnerships with industry leading companies including GE Healthcare, IBM Watson and Konica Minolta, currently serving thousands of end users worldwide.”We see growing use of ultrasound in point of care settings, and an urgent need for automated, objective solutions that provide decision support in real time,” said Hila Goldman-Aslan, CEO and Co-founder of DiA Imaging Analysis, “Our AI solutions meet this need by immediately helping clinicians on the frontlines to quickly and easily assess COVID-19 patients’ hearts to help guide care delivery.”

About DiA Imaging Analysis:
DiA Imaging Analysis provides advanced AI-based ultrasound analysis technology that makes ultrasound accessible to all. DiA’s automated tools deliver fast and accurate clinical indications to support the decision-making process and offer better patient care. DiA’s AI-based technology uses advanced pattern recognition and machine-learning algorithms to automatically imitate the way the human eye detects image borders and identifies motion. Using DiA’s tools provides automated and objective AI tools, helps reduce variability among users, and increases efficiency. It allows clinicians with various levels of experience to quickly and easily analyze ultrasound images.

For additional information, please visit http://www.dia-analysis.com.

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2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

Reporter: Aviva Lev-Ari, PhD, RN

Collaborative innovation has never been more important

Join top leaders guiding the response, technology and people confronting this century’s greatest health challenge.

Priya Abani

CEO, AliveCor

General Keith Alexander

Co-CEO, IronNet; Former NSA Head

Stéphane Bancel

CEO, Moderna

Marc Casper

CEO, Thermo Fisher

Timothy Ferris, MD

CEO, MGPO; Professor, HMS

John Fernandez  

President, MEE; President, Ambulatory Care, Mass General Brigham

 

John Fish

CEO, Suffolk; BH Board Chair

JF Formela, MD

Partner, Atlas Venture

Jan Garfinkle

Manager Partner, Arboretum Ventures; Chair, NVCA

Phillip Gross

Managing Director, Adage Capital Management

Julia Hu

CEO, Lark Health

Anjali Kataria

CEO, Mytonomy

Roger Kitterman

VP, Managing Partner, Mass General Brigahm Fund

Jonathan Kraft

President, Kraft Group; Chair, MGH Board

Brooke LeVasseur

CEO, AristaMD

Mike Mahoney

CEO, Boston Scientific

Bernd Montag, PhD

CEO, Siemens Healthineers

Kieran Murphy

CEO, GE Healthcare

Elizabeth Nabel, MD

President, BH; Professor, HMS

Matt Sause

CEO, Roche Diagnostics

Peter Slavin, MD

President, MGH; Professor, HMS

Scott Sperling

Co-President, TH Lee; Chair, Mass General Brigham Board

Christopher Viehbacher

Managing Partner, Gurnet Point Capital

Michel Vounatsos

CEO, Biogen

Collaborative Innovation

Together we meet the challenge of the coronavirus and share our commitment to the future of medicine.

 

Anne Klibanski, MD

CEO, Mass General Brigham

Amy Abernethy, MD, PhD

Principal Deputy Commissioner and Acting CIO, FDA

PANEL

FDA Role in Managing Crisis and Anticipating the Next

Elizabeth Nabel, MD

President, Brigham Health; Professor of Medicine, HMS

PANEL

Care in the Next 18 Months 

Karen DeSalvo, MD

Chief Health Officer, Google Health

PANEL

Role of AI and Big Data in Fighting COVID-19 

Dawn Sugarman, PhD

Assistant Psychologist, Division of Alcohol, Drugs, and Addiction, McLean; Assistant Professor, Psychiatry, HMS

PANEL

Digital Therapeutics

Ann Prestipino

SVP; Incident Commander, MGH; Teaching Associate, HMS

PANEL

Real Time: Front Line Innovation

Hadine Joffe, MD

Vice Chair, Research, Psychiatry; Executive Director, Mary Horrigan Connors Center for Women’s Health and Gender Biology, BH; Paula Johnson Professor, Women’s Health, HMS

PANEL

Digital Therapeutics

Priya Abani

CEO, AliveCor

PANEL

Digital Therapeutics

Julia Hu

CEO, Lark Health

PANEL

Digital Therapeutics

Jan Garfinkle

Manager Partner, Arboretum Ventures; Chair NVCA

PANEL

Early Stage Investment Environment

Anjali Kataria

CEO, Mytonomy

PANEL

Patient Experience During the Pandemic

Brooke LeVasseur

CEO, AristaMD

PANEL

Digital Health Becomes a Pillar

Julie Lankiewicz

Head, Clinical Affairs & Health Economics Outcomes Research, Bose Health

PANEL

Emergency and Urgent Care

 

VIEW VIDEOS from the event

https://www.youtube.com/channel/UCauKpbsS_hUqQaPp8EVGYOg

 

From: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Date: Tuesday, May 12, 2020 at 6:48 AM

To: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Subject: REGISTRANT RECAP | World Medical Innovation Forum  

 

Dear World Forum Attendee, 

On behalf of Mass General Brigham CEO Anne Klibanski MD and Forum co-Chairs Gregg Meyer MD and Ravi Thadhani MD, many thanks for being among the nearly 11,000 registrants representing 93 countries, 46 states and 3200 organizations yesterday. A community was established around many pressing topics that  will continue long into the future. We hope you have a chance to examine the attached survey results. There are several revealing items that should be the basis for ongoing discussion. We expect to be in touch regularly during the year. Among the plans is a “First Look” video series highlighting top Mass General Brigham Harvard faculty as well as emerging Harvard investigators.  As promised, we  wanted to also share visual Forum session summaries.  You will be able to access the recordings on the Forum’s YouTube page . The first set will go up this morning

We hope you will join us for the 2021 Forum!  

Thanks again, Chris

e-Proceedings 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/04/22/world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-monday-may-11-815-a-m-515-p-m-et/

Tweets & Retweets 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/05/11/tweets-retweets-2020-world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-mond/

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2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

Reporter: Aviva Lev-Ari, PhD, RN

 

Thermo Fisher provides the technologies required to return to work as well as to combat a COVID-19 resurgence. CEO Marc Casper shares perspectives with MGB EVP Peter Markell.

Marc Casper

CEO, Thermo Fisher

Moderator

Peter Markell

EVP and CFO,

Mass General Brigham

 

VIEW VIDEOS from the event

https://www.youtube.com/channel/UCauKpbsS_hUqQaPp8EVGYOg

 

From: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Date: Tuesday, May 12, 2020 at 6:48 AM

To: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Subject: REGISTRANT RECAP | World Medical Innovation Forum  

 

Dear World Forum Attendee, 

On behalf of Mass General Brigham CEO Anne Klibanski MD and Forum co-Chairs Gregg Meyer MD and Ravi Thadhani MD, many thanks for being among the nearly 11,000 registrants representing 93 countries, 46 states and 3200 organizations yesterday. A community was established around many pressing topics that  will continue long into the future. We hope you have a chance to examine the attached survey results. There are several revealing items that should be the basis for ongoing discussion. We expect to be in touch regularly during the year. Among the plans is a “First Look” video series highlighting top Mass General Brigham Harvard faculty as well as emerging Harvard investigators.  As promised, we  wanted to also share visual Forum session summaries.  You will be able to access the recordings on the Forum’s YouTube page . The first set will go up this morning

We hope you will join us for the 2021 Forum!  

Thanks again, Chris

e-Proceedings 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/04/22/world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-monday-may-11-815-a-m-515-p-m-et/

Tweets & Retweets 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/05/11/tweets-retweets-2020-world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-mond/

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2020 World Medical Innovation Forum – COVID-19, AI  – Life Science and Digital Health Investments, MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

Reporter: Aviva Lev-Ari, PhD, RN

 

 

 

Life science and digital health investments have continued at a strong pace during the COVID-19 crisis. Senior investment leaders discuss what to expect. Will:

  • social distancing affect deal making?
  • key asset categories remain strong – venture, private equity, public offerings, acquisitions?
  • valuations hold up in some categories while others fall?

Moderator: Roger Kitterman, VP, Venture and Managing Partner, Partners Innovation Fund, Mass General Brigham


Jan Garfinkle
, Founder & Manager Partner, Arboretum Ventures, Chair NVCA

Phillip Gross, Managing Director, Adage Capital Management

Christopher Viehbacher, Managing Partner, Gurnet Point Capital

 

VIEW VIDEOS from the event

https://www.youtube.com/channel/UCauKpbsS_hUqQaPp8EVGYOg

From: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Date: Tuesday, May 12, 2020 at 6:48 AM

To: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Subject: REGISTRANT RECAP | World Medical Innovation Forum  

 

Dear World Forum Attendee, 

On behalf of Mass General Brigham CEO Anne Klibanski MD and Forum co-Chairs Gregg Meyer MD and Ravi Thadhani MD, many thanks for being among the nearly 11,000 registrants representing 93 countries, 46 states and 3200 organizations yesterday. A community was established around many pressing topics that  will continue long into the future. We hope you have a chance to examine the attached survey results. There are several revealing items that should be the basis for ongoing discussion. We expect to be in touch regularly during the year. Among the plans is a “First Look” video series highlighting top Mass General Brigham Harvard faculty as well as emerging Harvard investigators.  As promised, we  wanted to also share visual Forum session summaries.  You will be able to access the recordings on the Forum’s YouTube page . The first set will go up this morning

We hope you will join us for the 2021 Forum!  

Thanks again, Chris

e-Proceedings 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/04/22/world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-monday-may-11-815-a-m-515-p-m-et/

Tweets & Retweets 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/05/11/tweets-retweets-2020-world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-mond/

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Reporter: Stephen J. Williams, PhD

via Special COVID-19 Christopher Magazine

 

Special COVID-19 Christopher Magazine

Article ID #277: Special COVID-19 Christopher Magazine. Published on 5/10/2020

WordCloud Image Produced by Adam Tubman

Christopher-cover

Antonio Giordano, MD, PhD. explains what COVID is and how to contain the infection, pointing also to what will require attention next.

Please see this special release at http://online.fliphtml5.com/qlnw/zgau/#p=1

 

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Dr. Giordano Featured in Forbes Article on COVID-19 Antibody Tests in Italy and USA

Reporter: Stephen J. Williams, PhD

Article ID #276: Dr. Giordano Featured in Forbes Article on COVID-19 Antibody Tests in Italy and USA. Published on 5/10/2020

WordCloud Image Produced by Adam Tubman

via Dr. Giordano Featured in Forbes Article on COVID-19 Antibody Tests in Italy and USA

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The Genome Structure of CORONAVIRUS, SARS-CoV-2

“I awaited for this article for 60 days”

Aviva Lev-Ari, PhD, RN

Reporter: Aviva Lev-Ari, PhD, RN

 

UPDATED on 8/9/2020

 

The Genome Structure of CORONAVIRUS, SARS-CoV-2

Note:

  • The four letters of DNA are A, C, G and T.
  • In RNA molecules like the coronavirus genome, the T (thymine) is replaced with U (uracil).

Sources:

  • Fan Wu et al., Nature;
  • National Center for Biotechnology Information;
  • Dr. David Gordon, University of California, San Francisco;
  • Dr. Matthew B.   and Dr. Stuart Weston, University of Maryland School of Medicine;
  • Dr. Pleuni Pennings, San Francisco State University;
  • David Haussler and Jason Fernandes, U.C. Santa Cruz Genomics Institute; Journal of Virology;
  • Annual Review of Virology.

Model sources:

  • Coronavirus by Maria Voigt, RCSB Protein Data Bank headquartered at Rutgers University–New Brunswick;
  • Ribosome from Heena Khatter et al., Nature;
  • Proteins from Yang Zhang’s Research Group, University of Michigan.

Bad News Wrapped in Protein: Inside the Coronavirus Genome

A virus is “simply a piece of bad news wrapped up in protein,” the biologists Jean and Peter Medawar wrote in 1977.

In January, scientists deciphered a piece of very bad news: the genome of SARS-CoV-2, the virus that causes Covid-19. The sample came from a 41-year-old man who worked at the seafood market in Wuhan where the first cluster of cases appeared.

Researchers are now racing to make sense of this viral recipe, which could inspire drugs, vaccines and other tools to fight the ongoing pandemic.

A String of RNA

Viruses must hijack living cells to replicate and spread. When the coronavirus finds a suitable cell, it injects a strand of RNA that contains the entire coronavirus genome.

The genome of the new coronavirus is less than 30,000 “letters” long. (The human genome is over 3 billion.) Scientists have identified genes for as many as 29 proteins, which carry out a range of jobs from making copies of the coronavirus to suppressing the body’s immune responses.

The first sequence of RNA letters reads:

auuaaagguuuauaccuucccagguaacaaaccaaccaacuuucgaucucuuguagaucuguucucuaaacgaacuuuaaaaucuguguggcugucacucggcugcaugcuuagugcacucacgcaguauaauuaauaacuaauuacugucguugacaggacacgaguaacucgucuaucuucugcaggcugcuuacgguuucguccguguugcagccgaucaucagcacaucuagguuucguccgggugugaccgaaagguaag

This sequence recruits machinery inside the infected cell to read the RNA letters — acg and u — and translate them into coronavirus proteins.

The full coronavirus genome and the proteins it encodes are shown below.

A Chain of Proteins · ORF1ab

The first viral protein created inside the infected cell is actually a chain of 16 proteins joined together. Two of these proteins act like scissors, snipping the links between the different proteins and freeing them to do their jobs.

See graph at https://www.nytimes.com/interactive/2020/04/03/science/coronavirus-genome-bad-news-wrapped-in-protein.html

Research on other coronaviruses has given scientists a good understanding of what some of the SARS-CoV-2 proteins do. But other proteins are far more mysterious, and some might do nothing at all.

Cellular Saboteur · NSP1

This protein slows down the infected cell’s production of its own proteins. This sabotage forces the cell to make more virus proteins and prevents it from assembling antiviral proteins that could stop the virus.

auggagagccuugucccugguuucaacgagaaaacacacguccaacucaguuugccuguuuuacagguucgcgacgugcucguacguggcuuuggagacuccguggaggaggucuuaucagaggcacgucaacaucuuaaagauggcacuuguggcuuaguagaaguugaaaaaggcguuuugccucaacuugaacagcccuauguguucaucaaacguucggaugcucgaacugcaccucauggucauguuaugguugagcugguagcagaacucgaaggcauucaguacggucguaguggugagacacuugguguccuugucccucaugugggcgaaauaccaguggcuuaccgcaagguucuucuucguaagaacgguaauaaaggagcugguggccauaguuacggcgccgaucuaaagucauuugacuuaggcgacgagcuuggcacugauccuuaugaagauuuucaagaaaacuggaacacuaaacauagcagugguguuacccgugaacucaugcgugagcuuaacggaggg

Mystery Protein · NSP2

Scientists aren’t sure what NSP2 does. The other proteins it attaches to may offer some clues. Two of them help move molecule-filled bubbles called endosomes around the cell.

gcauacacucgcuaugucgauaacaacuucuguggcccugauggcuacccucuugagugcauuaaagaccuucuagcacgugcugguaaagcuucaugcacuuuguccgaacaacuggacuuuauugacacuaagagggguguauacugcugccgugaacaugagcaugaaauugcuugguacacggaacguucugaaaagagcuaugaauugcagacaccuuuugaaauuaaauuggcaaagaaauuugacaccuucaauggggaauguccaaauuuuguauuucccuuaaauuccauaaucaagacuauucaaccaaggguugaaaagaaaaagcuugauggcuuuauggguagaauucgaucugucuauccaguugcgucaccaaaugaaugcaaccaaaugugccuuucaacucucaugaagugugaucauuguggugaaacuucauggcagacgggcgauuuuguuaaagccacuugcgaauuuuguggcacugagaauuugacuaaagaaggugccacuacuugugguuacuuaccccaaaaugcuguuguuaaaauuuauuguccagcaugucacaauucagaaguaggaccugagcauagucuugccgaauaccauaaugaaucuggcuugaaaaccauucuucguaaggguggucgcacuauugccuuuggaggcuguguguucucuuauguugguugccauaacaagugugccuauuggguuccacgugcuagcgcuaacauagguuguaaccauacagguguuguuggagaagguuccgaaggucuuaaugacaaccuucuugaaauacuccaaaaagagaaagucaacaucaauauuguuggugacuuuaaacuuaaugaagagaucgccauuauuuuggcaucuuuuucugcuuccacaagugcuuuuguggaaacugugaaagguuuggauuauaaagcauucaaacaaauuguugaauccugugguaauuuuaaaguuacaaaaggaaaagcuaaaaaaggugccuggaauauuggugaacagaaaucaauacugaguccucuuuaugcauuugcaucagaggcugcucguguuguacgaucaauuuucucccgcacucuugaaacugcucaaaauucugugcguguuuuacagaaggccgcuauaacaauacuagauggaauuucacaguauucacugagacucauugaugcuaugauguucacaucugauuuggcuacuaacaaucuaguuguaauggccuacauuacaggugguguuguucaguugacuucgcaguggcuaacuaacaucuuuggcacuguuuaugaaaaacucaaacccguccuugauuggcuugaagagaaguuuaaggaagguguagaguuucuuagagacgguugggaaauuguuaaauuuaucucaaccugugcuugugaaauugucgguggacaaauugucaccugugcaaaggaaauuaaggagaguguucagacauucuuuaagcuuguaaauaaauuuuuggcuuugugugcugacucuaucauuauugguggagcuaaacuuaaagccuugaauuuaggugaaacauuugucacgcacucaaagggauuguacagaaaguguguuaaauccagagaagaaacuggccuacucaugccucuaaaagccccaaaagaaauuaucuucuuagagggagaaacacuucccacagaaguguuaacagaggaaguugucuugaaaacuggugauuuacaaccauuagaacaaccuacuagugaagcuguugaagcuccauugguugguacaccaguuuguauuaacgggcuuauguugcucgaaaucaaagacacagaaaaguacugugcccuugcaccuaauaugaugguaacaaacaauaccuucacacucaaaggcggu

Untagging and Cutting · NSP3

NSP3 is a large protein that has two important jobs. One is cutting loose other viral proteins so they can do their own tasks. It also alters many of the infected cell’s proteins.

Normally, a healthy cell tags old proteins for destruction. But the coronavirus can remove those tags, changing the balance of proteins and possibly reducing the cell’s ability to fight the virus.

gcaccaacaaagguuacuuuuggugaugacacugugauagaagugcaagguuacaagagugugaauaucacuuuugaacuugaugaaaggauugauaaaguacuuaaugagaagugcucugccuauacaguugaacucgguacagaaguaaaugaguucgccuguguuguggcagaugcugucauaaaaacuuugcaaccaguaucugaauuacuuacaccacugggcauugauuuagaugaguggaguauggcuacauacuacuuauuugaugagucuggugaguuuaaauuggcuucacauauguauuguucuuucuacccuccagaugaggaugaagaagaaggugauugugaagaagaagaguuugagccaucaacucaauaugaguaugguacugaagaugauuaccaagguaaaccuuuggaauuuggugccacuucugcugcucuucaaccugaagaagagcaagaagaagauugguuagaugaugauagucaacaaacuguuggucaacaagacggcagugaggacaaucagacaacuacuauucaaacaauuguugagguucaaccucaauuagagauggaacuuacaccaguuguucagacuauugaagugaauaguuuuagugguuauuuaaaacuuacugacaauguauacauuaaaaaugcagacauuguggaagaagcuaaaaagguaaaaccaacagugguuguuaaugcagccaauguuuaccuuaaacauggaggagguguugcaggagccuuaaauaaggcuacuaacaaugccaugcaaguugaaucugaugauuacauagcuacuaauggaccacuuaaagugggugguaguuguguuuuaagcggacacaaucuugcuaaacacugucuucauguugucggcccaaauguuaacaaaggugaagacauucaacuucuuaagagugcuuaugaaaauuuuaaucagcacgaaguucuacuugcaccauuauuaucagcugguauuuuuggugcugacccuauacauucuuuaagaguuuguguagauacuguucgcacaaaugucuacuuagcugucuuugauaaaaaucucuaugacaaacuuguuucaagcuuuuuggaaaugaagagugaaaagcaaguugaacaaaagaucgcugagauuccuaaagaggaaguuaagccauuuauaacugaaaguaaaccuucaguugaacagagaaaacaagaugauaagaaaaucaaagcuuguguugaagaaguuacaacaacucuggaagaaacuaaguuccucacagaaaacuuguuacuuuauauugacauuaauggcaaucuucauccagauucugccacucuuguuagugacauugacaucacuuucuuaaagaaagaugcuccauauauagugggugauguuguucaagaggguguuuuaacugcugugguuauaccuacuaaaaaggcugguggcacuacugaaaugcuagcgaaagcuuugagaaaagugccaacagacaauuauauaaccacuuacccgggucaggguuuaaaugguuacacuguagaggaggcaaagacagugcuuaaaaaguguaaaagugccuuuuacauucuaccaucuauuaucucuaaugagaagcaagaaauucuuggaacuguuucuuggaauuugcgagaaaugcuugcacaugcagaagaaacacgcaaauuaaugccugucuguguggaaacuaaagccauaguuucaacuauacagcguaaauauaaggguauuaaaauacaagagggugugguugauuauggugcuagauuuuacuuuuacaccaguaaaacaacuguagcgucacuuaucaacacacuuaacgaucuaaaugaaacucuuguuacaaugccacuuggcuauguaacacauggcuuaaauuuggaagaagcugcucgguauaugagaucucucaaagugccagcuacaguuucuguuucuucaccugaugcuguuacagcguauaaugguuaucuuacuucuucuucuaaaacaccugaagaacauuuuauugaaaccaucucacuugcugguuccuauaaagauugguccuauucuggacaaucuacacaacuagguauagaauuucuuaagagaggugauaaaaguguauauuacacuaguaauccuaccacauuccaccuagauggugaaguuaucaccuuugacaaucuuaagacacuucuuucuuugagagaagugaggacuauuaagguguuuacaacaguagacaacauuaaccuccacacgcaaguuguggacaugucaaugacauauggacaacaguuugguccaacuuauuuggauggagcugauguuacuaaaauaaaaccucauaauucacaugaagguaaaacauuuuauguuuuaccuaaugaugacacucuacguguugaggcuuuugaguacuaccacacaacugauccuaguuuucuggguagguacaugucagcauuaaaucacacuaaaaaguggaaauacccacaaguuaaugguuuaacuucuauuaaaugggcagauaacaacuguuaucuugccacugcauuguuaacacuccaacaaauagaguugaaguuuaauccaccugcucuacaagaugcuuauuacagagcaagggcuggugaagcugcuaacuuuugugcacuuaucuuagccuacuguaauaagacaguaggugaguuaggugauguuagagaaacaaugaguuacuuguuucaacaugccaauuuagauucuugcaaaagagucuugaacgugguguguaaaacuuguggacaacagcagacaacccuuaaggguguagaagcuguuauguacaugggcacacuuucuuaugaacaauuuaagaaagguguucagauaccuuguacgugugguaaacaagcuacaaaauaucuaguacaacaggagucaccuuuuguuaugaugucagcaccaccugcucaguaugaacuuaagcaugguacauuuacuugugcuagugaguacacugguaauuaccaguguggucacuauaaacauauaacuucuaaagaaacuuuguauugcauagacggugcuuuacuuacaaaguccucagaauacaaagguccuauuacggauguuuucuacaaagaaaacaguuacacaacaaccauaaaaccaguuacuuauaaauuggaugguguuguuuguacagaaauugacccuaaguuggacaauuauuauaagaaagacaauucuuauuucacagagcaaccaauugaucuuguaccaaaccaaccauauccaaacgcaagcuucgauaauuuuaaguuuguaugugauaauaucaaauuugcugaugauuuaaaccaguuaacugguuauaagaaaccugcuucaagagagcuuaaaguuacauuuuucccugacuuaaauggugaugugguggcuauugauuauaaacacuacacacccucuuuuaagaaaggagcuaaauuguuacauaaaccuauuguuuggcauguuaacaaugcaacuaauaaagccacguauaaaccaaauaccugguguauacguugucuuuggagcacaaaaccaguugaaacaucaaauucguuugauguacugaagucagaggacgcgcagggaauggauaaucuugccugcgaagaucuaaaaccagucucugaagaaguaguggaaaauccuaccauacagaaagacguucuugaguguaaugugaaaacuaccgaaguuguaggagacauuauacuuaaaccagcaaauaauaguuuaaaaauuacagaagagguuggccacacagaucuaauggcugcuuauguagacaauucuagucuuacuauuaagaaaccuaaugaauuaucuagaguauuagguuugaaaacccuugcuacucaugguuuagcugcuguuaauagugucccuugggauacuauagcuaauuaugcuaagccuuuucuuaacaaaguuguuaguacaacuacuaacauaguuacacgguguuuaaaccguguuuguacuaauuauaugccuuauuucuuuacuuuauugcuacaauuguguacuuuuacuagaaguacaaauucuagaauuaaagcaucuaugccgacuacuauagcaaagaauacuguuaagagugucgguaaauuuugucuagaggcuucauuuaauuauuugaagucaccuaauuuuucuaaacugauaaauauuauaauuugguuuuuacuauuaaguguuugccuagguucuuuaaucuacucaaccgcugcuuuagguguuuuaaugucuaauuuaggcaugccuucuuacuguacugguuacagagaaggcuauuugaacucuacuaaugucacuauugcaaccuacuguacugguucuauaccuuguaguguuugucuuagugguuuagauucuuuagacaccuauccuucuuuagaaacuauacaaauuaccauuucaucuuuuaaaugggauuuaacugcuuuuggcuuaguugcagagugguuuuuggcauauauucuuuucacuagguuuuucuauguacuuggauuggcugcaaucaugcaauuguuuuucagcuauuuugcaguacauuuuauuaguaauucuuggcuuaugugguuaauaauuaaucuuguacaaauggccccgauuucagcuaugguuagaauguacaucuucuuugcaucauuuuauuauguauggaaaaguuaugugcauguuguagacgguuguaauucaucaacuuguaugauguguuacaaacguaauagagcaacaagagucgaauguacaacuauuguuaaugguguuagaagguccuuuuaugucuaugcuaauggagguaaaggcuuuugcaaacuacacaauuggaauuguguuaauugugauacauucugugcugguaguacauuuauuagugaugaaguugcgagagacuugucacuacaguuuaaaagaccaauaaauccuacugaccagucuucuuacaucguugauaguguuacagugaagaaugguuccauccaucuuuacuuugauaaagcuggucaaaagacuuaugaaagacauucucucucucauuuuguuaacuuagacaaccugagagcuaauaacacuaaagguucauugccuauuaauguuauaguuuuugaugguaaaucaaaaugugaagaaucaucugcaaaaucagcgucuguuuacuacagucagcuuaugugucaaccuauacuguuacuagaucaggcauuagugucugauguuggugauagugcggaaguugcaguuaaaauguuugaugcuuacguuaauacguuuucaucaacuuuuaacguaccaauggaaaaacucaaaacacuaguugcaacugcagaagcugaacuugcaaagaauguguccuuagacaaugucuuaucuacuuuuauuucagcagcucggcaaggguuuguugauucagauguagaaacuaaagauguuguugaaugucuuaaauugucacaucaaucugacauagaaguuacuggcgauaguuguaauaacuauaugcucaccuauaacaaaguugaaaacaugacaccccgugaccuuggugcuuguauugacuguagugcgcgucauauuaaugcgcagguagcaaaaagucacaacauugcuuugauauggaacguuaaagauuucaugucauugucugaacaacuacgaaaacaaauacguagugcugcuaaaaagaauaacuuaccuuuuaaguugacaugugcaacuacuagacaaguuguuaauguuguaacaacaaagauagcacuuaaggguggu

Bubble Maker · NSP4

Combining with other proteins, NSP4 helps build fluid-filled bubbles within infected cells. Inside these bubbles, parts for new copies of the virus are constructed.

aaaauuguuaauaauugguugaagcaguuaauuaaaguuacacuuguguuccuuuuuguugcugcuauuuucuauuuaauaacaccuguucaugucaugucuaaacauacugacuuuucaagugaaaucauaggauacaaggcuauugaugguggugucacucgugacauagcaucuacagauacuuguuuugcuaacaaacaugcugauuuugacacaugguuuagccagcguggugguaguuauacuaaugacaaagcuugcccauugauugcugcagucauaacaagagaaguggguuuugucgugccugguuugccuggcacgauauuacgcacaacuaauggugacuuuuugcauuucuuaccuagaguuuuuagugcaguugguaacaucuguuacacaccaucaaaacuuauagaguacacugacuuugcaacaucagcuuguguuuuggcugcugaauguacaauuuuuaaagaugcuucugguaagccaguaccauauuguuaugauaccaauguacuagaagguucuguugcuuaugaaaguuuacgcccugacacacguuaugugcucauggauggcucuauuauucaauuuccuaacaccuaccuugaagguucuguuagagugguaacaacuuuugauucugaguacuguaggcacggcacuugugaaagaucagaagcugguguuuguguaucuacuagugguagauggguacuuaacaaugauuauuacagaucuuuaccaggaguuuucugugguguagaugcuguaaauuuacuuacuaauauguuuacaccacuaauucaaccuauuggugcuuuggacauaucagcaucuauaguagcuggugguauuguagcuaucguaguaacaugccuugccuacuauuuuaugagguuuagaagagcuuuuggugaauacagucauguaguugccuuuaauacuuuacuauuccuuaugucauucacuguacucuguuuaacaccaguuuacucauucuuaccugguguuuauucuguuauuuacuuguacuugacauuuuaucuuacuaaugauguuucuuuuuuagcacauauucaguggaugguuauguucacaccuuuaguaccuuucuggauaacaauugcuuauaucauuuguauuuccacaaagcauuucuauugguucuuuaguaauuaccuaaagagacguguagucuuuaaugguguuuccuuuaguacuuuugaagaagcugcgcugugcaccuuuuuguuaaauaaagaaauguaucuaaaguugcguagugaugugcuauuaccucuuacgcaauauaauagauacuuagcucuuuauaauaaguacaaguauuuuaguggagcaauggauacaacuagcuacagagaagcugcuuguugucaucucgcaaaggcucucaaugacuucaguaacucagguucugauguucuuuaccaaccaccacaaaccucuaucaccucagcuguuuugcag

Protein Scissors · NSP5

This protein makes most of the cuts that free other NSP proteins to carry out their own jobs.

agugguuuuagaaaaauggcauucccaucugguaaaguugaggguuguaugguacaaguaacuugugguacaacuacacuuaacggucuuuggcuugaugacguaguuuacuguccaagacaugugaucugcaccucugaagacaugcuuaacccuaauuaugaagauuuacucauucguaagucuaaucauaauuucuugguacaggcugguaauguucaacucaggguuauuggacauucuaugcaaaauuguguacuuaagcuuaagguugauacagccaauccuaagacaccuaaguauaaguuuguucgcauucaaccaggacagacuuuuucaguguuagcuuguuacaaugguucaccaucugguguuuaccaaugugcuaugaggcccaauuucacuauuaaggguucauuccuuaaugguucaugugguaguguugguuuuaacauagauuaugacugugucucuuuuuguuacaugcaccauauggaauuaccaacuggaguucaugcuggcacagacuuagaagguaacuuuuauggaccuuuuguugacaggcaaacagcacaagcagcugguacggacacaacuauuacaguuaauguuuuagcuugguuguacgcugcuguuauaaauggagacaggugguuucucaaucgauuuaccacaacucuuaaugacuuuaaccuuguggcuaugaaguacaauuaugaaccucuaacacaagaccauguugacauacuaggaccucuuucugcucaaacuggaauugccguuuuagauaugugugcuucauuaaaagaauuacugcaaaaugguaugaauggacguaccauauuggguagugcuuuauuagaagaugaauuuacaccuuuugauguuguuagacaaugcucagguguuacuuuccaa

Bubble Factory · NSP6

Works with NSP3 and NSP4 to make virus factory bubbles.

agugcagugaaaagaacaaucaaggguacacaccacugguuguuacucacaauuuugacuucacuuuuaguuuuaguccagaguacucaauggucuuuguucuuuuuuuuguaugaaaaugccuuuuuaccuuuugcuauggguauuauugcuaugucugcuuuugcaaugauguuugucaaacauaagcaugcauuucucuguuuguuuuuguuaccuucucuugccacuguagcuuauuuuaauauggucuauaugccugcuaguugggugaugcguauuaugacaugguuggauaugguugauacuaguuugucugguuuuaagcuaaaagacuguguuauguaugcaucagcuguaguguuacuaauccuuaugacagcaagaacuguguaugaugauggugcuaggagaguguggacacuuaugaaugucuugacacucguuuauaaaguuuauuaugguaaugcuuuagaucaagccauuuccaugugggcucuuauaaucucuguuacuucuaacuacucagguguaguuacaacugucauguuuuuggccagagguauuguuuuuauguguguugaguauugcccuauuuucuucauaacugguaauacacuucaguguauaaugcuaguuuauuguuucuuaggcuauuuuuguacuuguuacuuuggccucuuuuguuuacucaaccgcuacuuuagacugacucuugguguuuaugauuacuuaguuucuacacaggaguuuagauauaugaauucacagggacuacucccacccaagaauagcauagaugccuucaaacucaacauuaaauuguuggguguugguggcaaaccuuguaucaaaguagccacuguacag

Copy Assistants · NSP7 and NSP8

These two proteins help NSP12 make new copies of the RNA genome, which can ultimately end up inside new viruses.

ucuaaaaugucagauguaaagugcacaucaguagucuuacucucaguuuugcaacaacucagaguagaaucaucaucuaaauugugggcucaauguguccaguuacacaaugacauucucuuagcuaaagauacuacugaagccuuugaaaaaaugguuucacuacuuucuguuuugcuuuccaugcagggugcuguagacauaaacaagcuuugugaagaaaugcuggacaacagggcaaccuuacaa

gcuauagccucagaguuuaguucccuuccaucauaugcagcuuuugcuacugcucaagaagcuuaugagcaggcuguugcuaauggugauucugaaguuguucuuaaaaaguugaagaagucuuugaauguggcuaaaucugaauuugaccgugaugcagccaugcaacguaaguuggaaaagauggcugaucaagcuaugacccaaauguauaaacaggcuagaucugaggacaagagggcaaaaguuacuagugcuaugcagacaaugcuuuucacuaugcuuagaaaguuggauaaugaugcacucaacaacauuaucaacaaugcaagagaugguuguguucccuugaacauaauaccucuuacaacagcagccaaacuaaugguugucauaccagacuauaacacauauaaaaauacgugugaugguacaacauuuacuuaugcaucagcauugugggaaauccaacagguuguagaugcagauaguaaaauuguucaacuuagugaaauuaguauggacaauucaccuaauuuagcauggccucuuauuguaacagcuuuaagggccaauucugcugucaaauuacag

At the Heart of the Cell · NSP9

This protein infiltrates tiny channels in the infected cell’s nucleus, which holds our own genome. It may be able to influence the movement of molecules in and out of the nucleus — but for what purpose, no one knows.

aauaaugagcuuaguccuguugcacuacgacagaugucuugugcugccgguacuacacaaacugcuugcacugaugacaaugcguuagcuuacuacaacacaacaaagggagguagguuuguacuugcacuguuauccgauuuacaggauuugaaaugggcuagauucccuaagagugauggaacugguacuaucuauacagaacuggaaccaccuuguagguuuguuacagacacaccuaaagguccuaaagugaaguauuuauacuuuauuaaaggauuaaacaaccuaaauagagguaugguacuugguaguuuagcugccacaguacgucuacaa

Genetic Camouflage · NSP10

Human cells have antiviral proteins that find viral RNA and shred it. This protein works with NSP16 to camouflage the virus’s genes so that they don’t get attacked.

gcugguaaugcaacagaagugccugccaauucaacuguauuaucuuucugugcuuuugcuguagaugcugcuaaagcuuacaaagauuaucuagcuagugggggacaaccaaucacuaauuguguuaagauguuguguacacacacugguacuggucaggcaauaacaguuacaccggaagccaauauggaucaagaauccuuugguggugcaucguguugucuguacugccguugccacauagaucauccaaauccuaaaggauuuugugacuuaaaagguaaguauguacaaauaccuacaacuugugcuaaugacccuguggguuuuacacuuaaaaacacagucuguaccgucugcgguauguggaaagguuauggcuguaguugugaucaacuccgcgaacccaugcuucag

Copy Machine · NSP12

This protein assembles genetic letters into new virus genomes. Researchers have found that the antiviral remdesivir interferes with NSP12 in other coronaviruses, and trials are now underway to see if the drug can treat Covid-19.

The infected cell begins reading the RNA sequence for NSP12:

ucagcugaugcacaaucguuuuuaaac

Then it backtracks and reads c again, continuing as:

cggguuugcgguguaagugcagcccgucuuacaccgugcggcacaggcacuaguacugaugucguauacagggcuuuugacaucuacaaugauaaaguagcugguuuugcuaaauuccuaaaaacuaauuguugucgcuuccaagaaaaggacgaagaugacaauuuaauugauucuuacuuuguaguuaagagacacacuuucucuaacuaccaacaugaagaaacaauuuauaauuuacuuaaggauuguccagcuguugcuaaacaugacuucuuuaaguuuagaauagacggugacaugguaccacauauaucacgucaacgucuuacuaaauacacaauggcagaccucgucuaugcuuuaaggcauuuugaugaagguaauugugacacauuaaaagaaauacuugucacauacaauuguugugaugaugauuauuucaauaaaaaggacugguaugauuuuguagaaaacccagauauauuacgcguauacgccaacuuaggugaacguguacgccaagcuuuguuaaaaacaguacaauucugugaugccaugcgaaaugcugguauuguugguguacugacauuagauaaucaagaucucaaugguaacugguaugauuucggugauuucauacaaaccacgccagguaguggaguuccuguuguagauucuuauuauucauuguuaaugccuauauuaaccuugaccagggcuuuaacugcagagucacauguugacacugacuuaacaaagccuuacauuaagugggauuuguuaaaauaugacuucacggaagagagguuaaaacucuuugaccguuauuuuaaauauugggaucagacauaccacccaaauuguguuaacuguuuggaugacagaugcauucugcauugugcaaacuuuaauguuuuauucucuacaguguucccaccuacaaguuuuggaccacuagugagaaaaauauuuguugaugguguuccauuuguaguuucaacuggauaccacuucagagagcuagguguuguacauaaucaggauguaaacuuacauagcucuagacuuaguuuuaaggaauuacuuguguaugcugcugacccugcuaugcacgcugcuucugguaaucuauuacuagauaaacgcacuacgugcuuuucaguagcugcacuuacuaacaauguugcuuuucaaacugucaaacccgguaauuuuaacaaagacuucuaugacuuugcugugucuaaggguuucuuuaaggaaggaaguucuguugaauuaaaacacuucuucuuugcucaggaugguaaugcugcuaucagcgauuaugacuacuaucguuauaaucuaccaacaaugugugauaucagacaacuacuauuuguaguugaaguuguugauaaguacuuugauuguuacgaugguggcuguauuaaugcuaaccaagucaucgucaacaaccuagacaaaucagcugguuuuccauuuaauaaaugggguaaggcuagacuuuauuaugauucaaugaguuaugaggaucaagaugcacuuuucgcauauacaaaacguaaugucaucccuacuauaacucaaaugaaucuuaaguaugccauuagugcaaagaauagagcucgcaccguagcuggugucucuaucuguaguacuaugaccaauagacaguuucaucaaaaauuauugaaaucaauagccgccacuagaggagcuacuguaguaauuggaacaagcaaauucuauggugguuggcacaacauguuaaaaacuguuuauagugauguagaaaacccucaccuuauggguugggauuauccuaaaugugauagagccaugccuaacaugcuuagaauuauggccucacuuguucuugcucgcaaacauacaacguguuguagcuugucacaccguuucuauagauuagcuaaugagugugcucaaguauugagugaaauggucauguguggcgguucacuauauguuaaaccagguggaaccucaucaggagaugccacaacugcuuaugcuaauaguguuuuuaacauuugucaagcugucacggccaauguuaaugcacuuuuaucuacugaugguaacaaaauugccgauaaguauguccgcaauuuacaacacagacuuuaugagugucucuauagaaauagagauguugacacagacuuugugaaugaguuuuacgcauauuugcguaaacauuucucaaugaugauacucucugacgaugcuguuguguguuucaauagcacuuaugcaucucaaggucuaguggcuagcauaaagaacuuuaagucaguucuuuauuaucaaaacaauguuuuuaugucugaagcaaaauguuggacugagacugaccuuacuaaaggaccucaugaauuuugcucucaacauacaaugcuaguuaaacagggugaugauuauguguaccuuccuuacccagauccaucaagaauccuaggggccggcuguuuuguagaugauaucguaaaaacagaugguacacuuaugauugaacgguucgugucuuuagcuauagaugcuuacccacuuacuaaacauccuaaucaggaguaugcugaugucuuucauuuguacuuacaauacauaagaaagcuacaugaugaguuaacaggacacauguuagacauguauucuguuaugcuuacuaaugauaacacuucaagguauugggaaccugaguuuuaugaggcuauguacacaccgcauacagucuuacag

Another sequence, NSP11, overlaps part of the same stretch of RNA. But it’s not clear if the tiny protein encoded by this gene has any function at all.

Unwinding RNA · NSP13

Normally, virus RNA is wound into intricate twists and turns. Scientists suspect that NSP13 unwinds it so that other proteins can read its sequence and make new copies.

gcuguuggggcuuguguucuuugcaauucacagacuucauuaagauguggugcuugcauacguagaccauucuuauguuguaaaugcuguuacgaccaugucauaucaacaucacauaaauuagucuugucuguuaauccguauguuugcaaugcuccagguugugaugucacagaugugacucaacuuuacuuaggagguaugagcuauuauuguaaaucacauaaaccacccauuaguuuuccauugugugcuaauggacaaguuuuugguuuauauaaaaauacauguguugguagcgauaauguuacugacuuuaaugcaauugcaacaugugacuggacaaaugcuggugauuacauuuuagcuaacaccuguacugaaagacucaagcuuuuugcagcagaaacgcucaaagcuacugaggagacauuuaaacugucuuaugguauugcuacuguacgugaagugcugucugacagagaauuacaucuuucaugggaaguugguaaaccuagaccaccacuuaaccgaaauuaugucuuuacugguuaucguguaacuaaaaacaguaaaguacaaauaggagaguacaccuuugaaaaaggugacuauggugaugcuguuguuuaccgagguacaacaacuuacaaauuaaauguuggugauuauuuugugcugacaucacauacaguaaugccauuaagugcaccuacacuagugccacaagagcacuauguuagaauuacuggcuuauacccaacacucaauaucucagaugaguuuucuagcaauguugcaaauuaucaaaagguugguaugcaaaaguauucuacacuccagggaccaccugguacugguaagagucauuuugcuauuggccuagcucucuacuacccuucugcucgcauaguguauacagcuugcucucaugccgcuguugaugcacuaugugagaaggcauuaaaauauuugccuauagauaaauguaguagaauuauaccugcacgugcucguguagaguguuuugauaaauucaaagugaauucaacauuagaacaguaugucuuuuguacuguaaaugcauugccugagacgacagcagauauaguugucuuugaugaaauuucaauggccacaaauuaugauuugaguguugucaaugccagauuacgugcuaagcacuauguguacauuggcgacccugcucaauuaccugcaccacgcacauugcuaacuaagggcacacuagaaccagaauauuucaauucaguguguagacuuaugaaaacuauagguccagacauguuccucggaacuugucggcguuguccugcugaaauuguugacacugugagugcuuugguuuaugauaauaagcuuaaagcacauaaagacaaaucagcucaaugcuuuaaaauguuuuauaaggguguuaucacgcaugauguuucaucugcaauuaacaggccacaaauaggcgugguaagagaauuccuuacacguaacccugcuuggagaaaagcugucuuuauuucaccuuauaauucacagaaugcuguagccucaaagauuuugggacuaccaacucaaacuguugauucaucacagggcucagaauaugacuaugucauauucacucaaaccacugaaacagcucacucuuguaauguaaacagauuuaauguugcuauuaccagagcaaaaguaggcauacuuugcauaaugucugauagagaccuuuaugacaaguugcaauuuacaagucuugaaauuccacguaggaauguggcaacuuuacaa

Viral Proofreader · NSP14

As NSP12 duplicates the coronavirus genome, it sometimes adds a wrong letter to the new copy. NSP14 cuts out these errors, so that the correct letter can be added instead.

gcugaaaauguaacaggacucuuuaaagauuguaguaagguaaucacuggguuacauccuacacaggcaccuacacaccucaguguugacacuaaauucaaaacugaagguuuauguguugacauaccuggcauaccuaaggacaugaccuauagaagacucaucucuaugauggguuuuaaaaugaauuaucaaguuaaugguuacccuaacauguuuaucacccgcgaagaagcuauaagacauguacgugcauggauuggcuucgaugucgaggggugucaugcuacuagagaagcuguugguaccaauuuaccuuuacagcuagguuuuucuacagguguuaaccuaguugcuguaccuacagguuauguugauacaccuaauaauacagauuuuuccagaguuagugcuaaaccaccgccuggagaucaauuuaaacaccucauaccacuuauguacaaaggacuuccuuggaauguagugcguauaaagauuguacaaauguuaagugacacacuuaaaaaucucucugacagagucguauuugucuuaugggcacauggcuuugaguugacaucuaugaaguauuuugugaaaauaggaccugagcgcaccuguugucuaugugauagacgugccacaugcuuuuccacugcuucagacacuuaugccuguuggcaucauucuauuggauuugauuacgucuauaauccguuuaugauugauguucaacaaugggguuuuacagguaaccuacaaagcaaccaugaucuguauugucaaguccaugguaaugcacauguagcuaguugugaugcaaucaugacuaggugucuagcuguccacgagugcuuuguuaagcguguugacuggacuauugaauauccuauaauuggugaugaacugaagauuaaugcggcuuguagaaagguucaacacaugguuguuaaagcugcauuauuagcagacaaauucccaguucuucacgacauugguaacccuaaagcuauuaaguguguaccucaagcugauguagaauggaaguucuaugaugcacagccuuguagugacaaagcuuauaaaauagaagaauuauucuauucuuaugccacacauucugacaaauucacagaugguguaugccuauuuuggaauugcaaugucgauagauauccugcuaauuccauuguuuguagauuugacacuagagugcuaucuaaccuuaacuugccugguugugaugguggcaguuuguauguaaauaaacaugcauuccacacaccagcuuuugauaaaagugcuuuuguuaauuuaaaacaauuaccauuuuucuauuacucugacaguccaugugagucucauggaaaacaaguagugucagauauagauuauguaccacuaaagucugcuacguguauaacacguugcaauuuagguggugcugucuguagacaucaugcuaaugaguacagauuguaucucgaugcuuauaacaugaugaucucagcuggcuuuagcuuguggguuuacaaacaauuugauacuuauaaccucuggaacacuuuuacaagacuucag

Cleaning Up · NSP15

Researchers suspect that this protein chops up leftover virus RNA as a way to hide from the infected cell’s antiviral defenses.

agaguuuagaaaauguggcuuuuaauguuguaaauaagggacacuuugauggacaacagggugaaguaccaguuucuaucauuaauaacacuguuuacacaaaaguugaugguguugauguagaauuguuugaaaauaaaacaacauuaccuguuaauguagcauuugagcuuugggcuaagcgcaacauuaaaccaguaccagaggugaaaauacucaauaauuuggguguggacauugcugcuaauacugugaucugggacuacaaaagagaugcuccagcacauauaucuacuauugguguuuguucuaugacugacauagccaagaaaccaacugaaacgauuugugcaccacucacugucuuuuuugaugguagaguugauggucaaguagacuuauuuagaaaugcccguaaugguguucuuauuacagaagguaguguuaaagguuuacaaccaucuguaggucccaaacaagcuagucuuaauggagucacauuaauuggagaagccguaaaaacacaguucaauuauuauaagaaaguugaugguguuguccaacaauuaccugaaacuuacuuuacucagaguagaaauuuacaagaauuuaaacccaggagucaaauggaaauugauuucuuagaauuagcuauggaugaauucauugaacgguauaaauuagaaggcuaugccuucgaacauaucguuuauggagauuuuagucauagucaguuaggugguuuacaucuacugauuggacuagcuaaacguuuuaaggaaucaccuuuugaauuagaagauuuuauuccuauggacaguacaguuaaaaacuauuucauaacagaugcgcaaacagguucaucuaaguguguguguucuguuauugauuuauuacuugaugauuuuguugaaauaauaaaaucccaagauuuaucuguaguuucuaagguugucaaagugacuauugacuauacagaaauuucauuuaugcuuugguguaaagauggccauguagaaacauuuuacccaaaauuacaa

More Camouflage · NSP16

NSP16 works with NSP10 to help the virus’s genes hide from proteins that chop up viral RNA.

ucuagucaagcguggcaaccggguguugcuaugccuaaucuuuacaaaaugcaaagaaugcuauuagaaaagugugaccuucaaaauuauggugauagugcaacauuaccuaaaggcauaaugaugaaugucgcaaaauauacucaacugugucaauauuuaaacacauuaacauuagcuguacccuauaauaugagaguuauacauuuuggugcugguucugauaaaggaguugcaccagguacagcuguuuuaagacagugguugccuacggguacgcugcuugucgauucagaucuuaaugacuuugucucugaugcagauucaacuuugauuggugauugugcaacuguacauacagcuaauaaaugggaucucauuauuagugauauguacgacccuaagacuaaaaauguuacaaaagaaaaugacucuaaagaggguuuuuucacuuacauuuguggguuuauacaacaaaagcuagcucuuggagguuccguggcuauaaagauaacagaacauucuuggaaugcugaucuuuauaagcucaugggacacuucgcaugguggacagccuuuguuacuaaugugaaugcgucaucaucugaagcauuuuuaauuggauguaauuaucuuggcaaaccacgcgaacaaauagaugguuaugucaugcaugcaaauuacauauuuuggaggaauacaaauccaauucaguugucuuccuauucuuuauuugacaugaguaaauuuccccuuaaauuaagggguacugcuguuaugucuuuaaaagaaggucaaaucaaugauaugauuuuaucucuucuuaguaaagguagacuuauaauuagagaaaacaacagaguuguuauuucuagugauguucuuguuaacaacuaaacgaaca

Spike Protein · S

The spike protein is one of four structural proteins — SEM and N — that form the outer layer of the coronavirus and protect the RNA inside. Structural proteins also help assemble and release new copies of the virus.

The S proteins form prominent spikes on the surface of the virus by arranging themselves in groups of three. These crownlike spikes give coronaviruses their name.

Part of the spike can extend and attach to a protein called ACE2 (in yellow below), which appears on particular cells in the human airway. The virus can then invade the cell.

The gene for the spike protein in SARS-CoV-2 has an insertion of 12 genetic letters: ccucggcgggca. This mutation may help the spikes bind tightly to human cells — a crucial step in its evolution from a virus that infected bats and other species.

A number of scientific teams are now designing vaccines that could prevent the spikes from attaching to human cells.

auguuuguuuuucuuguuuuauugccacuagucucuagucaguguguuaaucuuacaaccagaacucaauuacccccugcauacacuaauucuuucacacgugguguuuauuacccugacaaaguuuucagauccucaguuuuacauucaacucaggacuuguucuuaccuuucuuuuccaauguuacuugguuccaugcuauacaugucucugggaccaaugguacuaagagguuugauaacccuguccuaccauuuaaugaugguguuuauuuugcuuccacugagaagucuaacauaauaagaggcuggauuuuugguacuacuuuagauucgaagacccagucccuacuuauuguuaauaacgcuacuaauguuguuauuaaagucugugaauuucaauuuuguaaugauccauuuuuggguguuuauuaccacaaaaacaacaaaaguuggauggaaagugaguucagaguuuauucuagugcgaauaauugcacuuuugaauaugucucucagccuuuucuuauggaccuugaaggaaaacaggguaauuucaaaaaucuuagggaauuuguguuuaagaauauugaugguuauuuuaaaauauauucuaagcacacgccuauuaauuuagugcgugaucucccucaggguuuuucggcuuuagaaccauugguagauuugccaauagguauuaacaucacuagguuucaaacuuuacuugcuuuacauagaaguuauuugacuccuggugauucuucuucagguuggacagcuggugcugcagcuuauuauguggguuaucuucaaccuaggacuuuucuauuaaaauauaaugaaaauggaaccauuacagaugcuguagacugugcacuugacccucucucagaaacaaaguguacguugaaauccuucacuguagaaaaaggaaucuaucaaacuucuaacuuuagaguccaaccaacagaaucuauuguuagauuuccuaauauuacaaacuugugcccuuuuggugaaguuuuuaacgccaccagauuugcaucuguuuaugcuuggaacaggaagagaaucagcaacuguguugcugauuauucuguccuauauaauuccgcaucauuuuccacuuuuaaguguuauggagugucuccuacuaaauuaaaugaucucugcuuuacuaaugucuaugcagauucauuuguaauuagaggugaugaagucagacaaaucgcuccagggcaaacuggaaagauugcugauuauaauuauaaauuaccagaugauuuuacaggcugcguuauagcuuggaauucuaacaaucuugauucuaagguuggugguaauuauaauuaccuguauagauuguuuaggaagucuaaucucaaaccuuuugagagagauauuucaacugaaaucuaucaggccgguagcacaccuuguaaugguguugaagguuuuaauuguuacuuuccuuuacaaucauaugguuuccaacccacuaaugguguugguuaccaaccauacagaguaguaguacuuucuuuugaacuucuacaugcaccagcaacuguuuguggaccuaaaaagucuacuaauuugguuaaaaacaaaugugucaauuucaacuucaaugguuuaacaggcacagguguucuuacugagucuaacaaaaaguuucugccuuuccaacaauuuggcagagacauugcugacacuacugaugcuguccgugauccacagacacuugagauucuugacauuacaccauguucuuuugguggugucaguguuauaacaccaggaacaaauacuucuaaccagguugcuguucuuuaucaggauguuaacugcacagaagucccuguugcuauucaugcagaucaacuuacuccuacuuggcguguuuauucuacagguucuaauguuuuucaaacacgugcaggcuguuuaauaggggcugaacaugucaacaacucauaugagugugacauacccauuggugcagguauaugcgcuaguuaucagacucagacuaauucuccucggcgggcacguaguguagcuagucaauccaucauugccuacacuaugucacuuggugcagaaaauucaguugcuuacucuaauaacucuauugccauacccacaaauuuuacuauuaguguuaccacagaaauucuaccagugucuaugaccaagacaucaguagauuguacaauguacauuuguggugauucaacugaaugcagcaaucuuuuguugcaauauggcaguuuuuguacacaauuaaaccgugcuuuaacuggaauagcuguugaacaagacaaaaacacccaagaaguuuuugcacaagucaaacaaauuuacaaaacaccaccaauuaaagauuuuggugguuuuaauuuuucacaaauauuaccagauccaucaaaaccaagcaagaggucauuuauugaagaucuacuuuucaacaaagugacacuugcagaugcuggcuucaucaaacaauauggugauugccuuggugauauugcugcuagagaccucauuugugcacaaaaguuuaacggccuuacuguuuugccaccuuugcucacagaugaaaugauugcucaauacacuucugcacuguuagcggguacaaucacuucugguuggaccuuuggugcaggugcugcauuacaaauaccauuugcuaugcaaauggcuuauagguuuaaugguauuggaguuacacagaauguucucuaugagaaccaaaaauugauugccaaccaauuuaauagugcuauuggcaaaauucaagacucacuuucuuccacagcaagugcacuuggaaaacuucaagauguggucaaccaaaaugcacaagcuuuaaacacgcuuguuaaacaacuuagcuccaauuuuggugcaauuucaaguguuuuaaaugauauccuuucacgucuugacaaaguugaggcugaagugcaaauugauagguugaucacaggcagacuucaaaguuugcagacauaugugacucaacaauuaauuagagcugcagaaaucagagcuucugcuaaucuugcugcuacuaaaaugucagaguguguacuuggacaaucaaaaagaguugauuuuuguggaaagggcuaucaucuuauguccuucccucagucagcaccucaugguguagucuucuugcaugugacuuaugucccugcacaagaaaagaacuucacaacugcuccugccauuugucaugauggaaaagcacacuuuccucgugaaggugucuuuguuucaaauggcacacacugguuuguaacacaaaggaauuuuuaugaaccacaaaucauuacuacagacaacacauuugugucugguaacugugauguuguaauaggaauugucaacaacacaguuuaugauccuuugcaaccugaauuagacucauucaaggaggaguuagauaaauauuuuaagaaucauacaucaccagauguugauuuaggugacaucucuggcauuaaugcuucaguuguaaacauucaaaaagaaauugaccgccucaaugagguugccaagaauuuaaaugaaucucucaucgaucuccaagaacuuggaaaguaugagcaguauauaaaauggccaugguacauuuggcuagguuuuauagcuggcuugauugccauaguaauggugacaauuaugcuuugcuguaugaccaguugcuguaguugucucaagggcuguuguucuuguggauccugcugcaaauuugaugaagacgacucugagccagugcucaaaggagucaaauuacauuacacauaaacgaacuu

Escape Artist · ORF3a

The SARS-CoV-2 genome also encodes a group of so-called “accessory proteins.” They help change the environment inside the infected cell to make it easier for the virus to replicate.

The ORF3a protein pokes a hole in the membrane of an infected cell, making it easier for new viruses to escape. It also triggers inflammation, one of the most dangerous symptoms of Covid-19.

auggauuuguuuaugagaaucuucacaauuggaacuguaacuuugaagcaaggugaaaucaaggaugcuacuccuucagauuuuguucgcgcuacugcaacgauaccgauacaagccucacucccuuucggauggcuuauuguuggcguugcacuucuugcuguuuuucagagcgcuuccaaaaucauaacccucaaaaagagauggcaacuagcacucuccaaggguguucacuuuguuugcaacuugcuguuguuguuuguaacaguuuacucacaccuuuugcucguugcugcuggccuugaagccccuuuucucuaucuuuaugcuuuagucuacuucuugcagaguauaaacuuuguaagaauaauaaugaggcuuuggcuuugcuggaaaugccguuccaaaaacccauuacuuuaugaugccaacuauuuucuuugcuggcauacuaauuguuacgacuauuguauaccuuacaauaguguaacuucuucaauugucauuacuucaggugauggcacaacaaguccuauuucugaacaugacuaccagauuggugguuauacugaaaaaugggaaucuggaguaaaagacuguguuguauuacacaguuacuucacuucagacuauuaccagcuguacucaacucaauugaguacagacacugguguugaacauguuaccuucuucaucuacaauaaaauuguugaugagccugaagaacauguccaaauucacacaaucgacgguucauccggaguuguuaauccaguaauggaaccaauuuaugaugaaccgacgacgacuacuagcgugccuuuguaagcacaagcugaugaguacgaacuu

ORF3b overlaps the same RNA, but scientists aren’t sure if SARS-CoV-2 uses this gene to make proteins.

Envelope Protein · E

The envelope protein is a structural protein that helps form the oily bubble of the virus. It may also have jobs to do once the virus is inside the cell. Researchers have found that it latches onto proteins that help turn our own genes on and off. It’s possible that pattern changes when the E protein interferes.

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Membrane Protein · M

Another structural protein that forms part of the outer coat of the virus.

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Signal Blocker · ORF6

This accessory protein blocks signals that the infected cell would send out to the immune system. It also blocks some of the cell’s own virus-fighting proteins, the same ones targeted by other viruses such as polio and influenza.

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Virus Liberator · ORF7a

When new viruses try to escape a cell, the cell can snare them with proteins called tetherin. Some research suggests that ORF7a cuts down an infected cell’s supply of tetherin, allowing more of the viruses to escape. Researchers have also found that the protein can trigger infected cells to commit suicide — which contributes to the damage Covid-19 causes to the lungs.

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ORF7b overlaps this same stretch of RNA, but it’s not clear what, if anything, the gene does.

Mystery Protein · ORF8

The gene for this accessory protein is dramatically different in SARS-CoV-2 than in other coronaviruses. Researchers are debating what it does.

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Nucleocapsid Protein · N

The N protein protects the virus RNA, keeping it stable inside the virus. Many N proteins link together in a long spiral, wrapping and coiling the RNA:

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The accessory proteins ORF9b and ORF9c overlap this same stretch of RNA. ORF9b blocks interferon, a key molecule in the defense against viruses, but it’s not clear if ORF9c is used at all.

Mystery Protein · ORF10

Close relatives of the SARS-CoV-2 virus don’t have the gene for this tiny accessory protein, so it’s hard to know what it’s for yet — or even if the virus makes proteins from it.

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End of the Line

The coronavirus genome ends with a snippet of RNA that stops the cell’s protein-making machinery. It then trails away as a repeating sequence of aaaaaaaaaaaaa

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Other related articles in this Open Access Online Scientific Journal include the following:

 

  • Structure-guided Drug Discovery: (1) The Coronavirus 3CL hydrolase (Mpro) enzyme (main protease) essential for proteolytic maturation of the virus and (2) viral protease, the RNA polymerase, the viral spike protein, a viral RNA as promising two targets for discovery of cleavage inhibitors of the viral spike polyprotein preventing the Coronavirus Virion the spread of infection

Curators and Reporters: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/12/structure-guided-drug-discovery-1-the-coronavirus-3cl-hydrolase-mpro-enzyme-main-protease-essential-for-proteolytic-maturation-of-the-virus-and-2-viral-protease-the-rna-polymerase-the-viral/

  • Predicting the Protein Structure of Coronavirus: Inhibition of Nsp15 can slow viral replication and Cryo-EM – Spike protein structure (experimentally verified) vs AI-predicted protein structures (not experimentally verified) of DeepMind (Parent: Google) aka AlphaFold

Curators: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/08/predicting-the-protein-structure-of-coronavirus-inhibition-of-nsp15-can-slow-viral-replication-and-cryo-em-spike-protein-structure-experimentally-verified-vs-ai-predicted-protein-structures-not/

  • Promise of Synthetic Biology for Covid-19 Vaccine

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/03/23/promise-of-synthetic-biology-for-covid-19-vaccine/

  • Glycobiology vs Proteomics: Glycobiologists Prespective in the effort to explain the origin, etiology and potential therapeutics for the Coronavirus Pandemic (COVID-19).

 Curator: Ofer Markman, PhD

https://pharmaceuticalintelligence.com/2020/03/26/glycobiology-vs-proteomics-glycobiologists-prespective-in-the-effort-to-explain-the-origin-etiology-and-potential-therapeutics-for-the-coronavirus-pandemic-covid-19/

  • Worldwide trial uses AI to quickly identify ideal Covid-19 treatments

Reporter : Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/04/09/worldwide-trial-uses-ai-to-quickly-identify-ideal-covid-19-treatments/

  • Updated listing of COVID-19 vaccine and therapeutic trials from NIH Clinical Trials.gov

Curator: Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2020/04/16/updated-listing-of-covid-19-vaccine-and-therapeutic-trials-from-nih-clinical-trials-gov/

  • Actemra, immunosuppressive which was designed to treat rheumatoid arthritis but also approved in 2017 to treat cytokine storms in cancer patients SAVED the sickest of all COVID-19 patients

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/04/14/actemra-immunosuppressive-which-was-designed-to-treat-rheumatoid-arthritis-but-also-approved-in-2017-to-treat-cytokine-storms-in-cancer-patients-saved-the-sickest-of-all-covid-19-patients/

  • Innate Immune Genes and Two Nasal Epithelial Cell Types: Expression of SARS-CoV-2 Entry Factors – COVID19 Cell Atlas

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/04/23/innate-immune-genes-and-two-nasal-epithelial-cell-types-expression-of-sars-cov-2-entry-factors-covid19-cell-atlas/

 

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Reporter: Stephen J. Williams, PhD

NCI Activities: COVID-19 and Cancer Research

Dinah S. Singer. NCI-DCB, Bethesda, MD @theNCI

  • at the NCI they are pivoting some of their clinical trials to address COVID related issues like trials on tocilizumab and producing longitudinal cohorts of cancer patients and COVID for further analysis and studies
  • vaccine and antibody efforts at NCI and they are asking all their cancer centers (Cancer COVID Consortium) collecting data
  • Moonshot is collecting metadata but now COVID data from cellular therapy patients
  • they are about to publish new grants related to COVID and adding option to investigators to use current funds to do COVID related options
  • she says if at home take the time to think, write manuscripts, analyze data BE A REVIEWER FOR JOURNALS,
  • SSMMART project from Moonshot is still active
  • so far NCI and NIH grant process is ongoing although the peer review process is slower
  • they have extended deadlines with NO justification required (extend 90 days)
  • also allowing flexibility on use of grant money and allowing more early investigator rules and lax on those rules
  • non competitive renewals (type 5) will allow restructuring of project; contact program administrator
  • she and NCI heard rumors of institutions shutting down cancer research she is stressing to them not to do that
  • non refundable travel costs may be charged to the grant
  • NCI contemplating on extending the early investigator time
  • for more information go to NIH and NCI COVID-19 pages which have more guidances updated regularly

Follow on Twitter at:

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@theNCI

#AACR20

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