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Proposal for New e-Book Architecture: Bi-Lingual eTOCs, English & Spanish with NLP and Deep Learning results of Medical Text AnalysisPhase 1: six volumes

Author: Aviva Lev-Ari, PhD, RN

UPDATED on 8/5/2021

Smart use of customizable software in conjunction with 1.0 LPBI IP assets and competencies:

Mission #1:  Natural Language Processing (NLP) – Team in USA & India – Medical Text Analysis with NLP – on LPBI 3.3 Giga Bytes of Content. Two NLP types: (a) Statistical NLP and (b) Deep Learning by Machine Learning using Wolfram Language for Biological Sciences


In Mission #1: Using Machine Learning (ML) algorithms for Text Analysis of our 3.3 Giga Bytes of English Text

Statistical Natural Language Processing (NLP). This yields

  • WordClouds, Bar Diagrams for each article and Tree Diagrams for collection of articles

Deep Learning (DL) for Semantic Analysis of the Text. This yields

  • Hyper-graphs for collections of articles using knowledge graphs in knowledge graph databases.

Mission #2:  Blockchain IT and NLP Processing API generating NLP visualization Products used by Knowledge Graphs stored in Graph Databases – Content monetization infrastructure B2B and B2C.

In Mission #2: The Transactions-enabled blockchain platform for Content Monetization of IP assets embodies the  development of a Blockchain information technology infrastructure that is transactions-enabled allowing payments for content digital products. On the blockchain we will store all the following Digital products:

1.0 LPBI four IP Asset Classes:

IP Asset Class I: Journal articles +6,070

IP Asset Class II: electronic Books in Medicine

IIa.     18 e-books in English

IIb.     18 Bi-Lingual electronic Table of Contents (eTOCs): Spanish & English

IIc..    18 e-Books – NLP visualization products

IId.     18 e-Books Expert written NLP results Interpretations: Spanish & English

IIe.     For 18 books all audio Podcasts in Spanish & English – selective content

IIf.     For each e-Series, A,B,C,D,E we plan to publish a volume containing the Bi-Lingual Spanish-English electronic Table of Contents in each e-Series for all the e-Books in the e-Series – an additional 5 Bi-Lingual e-Books.https://c0.pubmine.com/sf/0.0.3/html/safeframe.htmlREPORT THIS AD

IP Asset Class III.      e-Proceedings: 100 volumes

IP Asset Class V:       Gallery of Biological Images 6,200 to grow if NLP yields 10 graphs 📊 per article

2.0 LPBI all products of NLP, see Yields for Mission #1, above PLUS IP Asset Classes XI, XII, XIII, mentioned, below serve as a compelling justification for the selection of Blockchain Transactions Network architecture as our IS/IT platform.= among other alternatives.

  • IP Asset Class XI: New Digital Products as a result of Discovery 💡 of new digital products derived from and created for the new queries by users to be generated on the fly
  • IP Asset Class XII: All digital products of Mission #3, below and
  • P Asset Class XIII: All digital products of Mission #4, below

Mission #3:  New GENRE of Multimedia Scientific Books: These 18 LPBI e-Books will be the first on the Medical Books Market to contain Text Analysis with NLP of the original e-Books. BioMed e-Books – Book Republishing in new GENRE – Bi-Lingual and Multimedia Audio Podcast for Books in the 18-e-Books in five e-Series: A,B,C,D,E . The New book architecture for each Book:

  • Part A: Spanish and English electronic Table of Contents in Text and in Audio Podcast.
  • Part B: NLP & Expert Interpretation of the visualizations in Text and Podcast: English and Spanish,NLP results for the content of the e-Book
    • Hyper-graphs for each Chapter
    • Domain Knowledge Expert Interpretation of all NLP results:
    TO BE CREATED – English Text and Spanish TextTO BE CREATED – English Audio Podcast and Spanish Audio Podcast
  • Part C: Editorial of original book (Preface, Volume Introduction, Volume Summary and Epilogue) -English Audio Podcast

UPDATED on 8/4/2021

New GENRE of Scientific Books by LPBI:

Part 1: the original book’s electronic Table of Contents

Media Format:

1.1 Bi-Lingual: English and Spanish

1.2 Text to Sound – Audio Podcast in Spanish

Part 2: Text Analysis with AI by Yash Choudhary, IIT, Kanpur 

2.1 Statistical NLP for each Chapter, all chapters in the Book

2.2 Semantic NLP for each Chapter, all chapters in the Book

Media Format:

2.1 Statistical Graphs – Bar Diagrams and Tree Diagrams

2.2 Semantic Graphs – Hyper-graphs, one per chapter

2.3 Domain Knowledge Expert: Interpretation of 2.1 and 2.2

Media Format:

2.3.1 English Text Text to Sound – Podcast

2.3.2 Spanish Text – New translation to Spanish of the Expert’s Interpretation will need to be commissioned Text to Sound – English Podcast Text to Sound – Spanish Podcast

Part 3: The original Book Editorial: Preface, Volume Introduction, Volume Summary and Epilogue

Media Format:

English Text to Sound – English Audio Podcast

Blockchain relations:

Each of the above outputs: I.e.,

1. eTOCs in English2. eTOCs in Spanish For each of the 18 books: Phase 1: six books of the 18.

3. Every graph of Statistical NLP

4. Every graph of Semantic Deep Learning by Machine Learning, Wolfram Language for Biological Sciences

5. Expert Interpretation of 3 & 4, above In English Text, Spanish Text, English Podcast, Spanish Podcast

6. Editorial for the volume: English Text and English Podcast 

All of the above are discrete DIGITAL PRODUCTS WITH A LIST PRICE to become available for download on LPBI’s Blockchain platform for Content Monetization (is now under design) in LPBI Digital Store on a Digital Healthcare Marketplace. Discovery is performed by data science and & analytics among the data entities and their representation by nodes and edges in the knowledge graph.

Now read about

Knowledge graphs on Blockchain and in AI

UPDATED on 8/3/2021

On 7/25/2021 – LPBI announced that it will have the NEWLY to be published BioMed e-Books As A NEW Publishing GENRE of SCIENTIFIC BOOKS

We launched a NEW Genre for Scientific Books: Bi-Lingual: English – Spanish with the NLP Results of the Text Analysis by NLP and Domain Knowledge Expert Interpretations in Text and in Sound. The eTOCs in Spanish Audio, NLP results Interpretation in English Audio and in Spanish Audio and Editorial in English Audio.

Dr. Lev-Ari statement on 7/25/2021
  • Bi-Lingual electronic Table Of Contents (eTOCs), English & Spanish with Montero Language Services, Madrid as the Translator of eighteen Books’ Cover Pages and the 18 books electronic Table of Contents.
  • The Content promotion in the Spanish speaking Countries with GTO, Madrid as AD Agency.
  • NLPs results of Medical Text Analysis with domain knowledge expert Interpretations in Foreign Languages and in Audio: in Spanish and in other languages, forthcoming
  • Original English Book – Only Editorials (Preface, Introductions, Summaries and Epilogue) because the Bi-Lingual part has the eTOCs of the e-Book
  • This is a new genre and a new architecture of 18 MULTIMEDIA SCIENTIFIC e-Books with (a) NLP results of the Medical Text analysis with machine learning, (b) Expert Interpretation of the Visualization Results. Bi-Lingual Podcasts: (c) eTOCs and (d) Bi-Lingual Expert Interpretation in English and Spanish Text and audio Podcasts, and (e) Books’ Editorials in English Audio Podcast

UPDATED on 7/31/2021

BioMed e-Books – Book Republishing in new GENRE – Bi-Lingual and Multimedia Audio Podcast for Books in the 18-e-Books in five e-Series: A,B,C,D,E

New Genre e-Book Architecture has the following Book architecture:

  1. Bi-Lingual English to Spanish eTOCs
  2. NLP Results with Audio interpretation of results by Domain knowledge Expert in several languages
  3. English Editorial in Audio Podcast

STATE OF AFFAIRS for LPBI’s BioMed e-Series – 18 Books

• Currently we have a massive effort of Converting ALL the electronic Table of Contents of the 18 books from English Text to Spanish Text. Same for the 18 Cover Pages

We may decide to


• Domain Knowledge Expert INTERPRETATION of NLP RESULTS on six volumes:

Series B: Genomics – 2 volumes

Series C: Cancer – 2 volumes

Series A: Volume 1 – Nitric Oxide

Series E: Volume 4 – 3D BioPrinting

All above NLP interpretation of visualization products will be written by Domain knowledge experts as English Text:

  • Cancer & Genomics: Dr. Williams, LPBI USA
  • Cardiovascular: Dr. Vivek Lal, LPBI India

The Interpretations English Text will be subjected to:

• Conversion of English Text to Sound: English Audio Podcast

• Conversion of English Text to Spanish Text to Spanish Audio Podcast

• Other Languages Audio Podcast: Japanese, Russian

For the following FOUR VOLUMES: GENOMICS 1&2 and CANCER 1&2
We will have NLP – 10-Step Workflow protocol implemented on. Few additional e-Books will be added for that workflow.

WORKFLOW for a Ten-Steps Medical Text Analysis Operation using NLP on LPBI Medical and Life Sciences Content

Author: Aviva Lev-Ari, PhD, RN

TEAM of INTERNS are working on


  • Genomics Vol 1 • NLP by Amandeep
  • Genomics Vol 2 • NLP by Madison: ——-> Part 1,2,3,4 very big COMPLETED and ——-> Part 5,6,7,8 very small – Madison
  • Cancer Vol 1• NLP by Danielle: Chapters 1 – 6: COMPLETED and • NLP by Dr. Pati: Chapters 7 – 12: COMPLETED
  • Cancer Vol 2• NLP – Ms. Ingle, Chapters 1 – 10 
  • Cancer Vol 2• NLP – TBA Chapters 11 – 20 


A. Book’s Cover Page: One page English, One Page Spanish

B. Book’s electronic Table of Contents is Bi-Lingual: English and Spanish

– article Title in Spanish

article Title in English

– URL – original

– Author Name, PhD or MD – original


1. Originally we planned to publish the Spanish translation A and B, above followed by the English Book as on the Journal
2. The Book on Amazon.com contains 

2.1 abbreviated eTOCs – LIVE LINKS TO ARTICLES

2.2 each article inside the book as an MS Word file, thus

• Cancer Vol 1 is 2,400 pages

• Cancer Vol 2 is 3,747 pages

3. NOW Cancer Vol 1 – NLP is completed (Danielle and Dr. Pati) and the Spanish Translation A and B, above is completed

The NEW IDEA is To Publish these FOUR volumes in the following NEW BOOK Architecture FORMAT:

Cancer Volume 1: EXAMPLE for the new e-Book Architecture

• Cover Page English

• Cover Page Spanish
• eTOCs Bi-Lingual: The Spanish Translation by Montero
• Medical Text Analysis using Wolfram NLP by Danielle Smolyar and Dr. Premalata Pati

1. WordClouds are already in the articles


2.1 Article title and Bar Diagram in PPT

2.2 for Each Chapter a Hyper-graph and a Tree Diagram – 2 GRAPHS

2.3 Dr. Williams Interpretation on 2.2 in English Text 

2.4 To have a Podcast for 2.3 in English and in Spanish 

2.5 PlugIn was Installed on 7/30/2021 and we have now access to 50 languages – Text to Sound Conversion

Followed by 

• Book eTOCs in English with all the editorials: 

Volume Introduction

Volume Summary



For Genomics Vol 1&2 and Cancer Vol 1&2 

These volumes will be re-published as

  1. Medical Text Analysis – NLP 10-Steps Workflow Operation of the ORIGINAL BOOK content

• Intern(s) name(s) as Performers of NLP on the original Text appears on the book and all their NLP work is included in the book

2. English and Spanish Cover Page by Montero

3. Bi-Lingual English and Spanish eTOCs by Montero

4. English Book as in the Journal (NOT AS ON AMAZON.com)

This is an EXAMPLE of an LPBI Book in the new Book Architecture format

Genomics Volume 2 will be RE-Published in a new Format having the following three parts:

Part A:        Bi-Lingual electronic Table of Contents (eTOCs)

Spanish Translation by Montero Language Services, Madrid, Spain

  • Under consideration: Spanish Audio Podcast of the Spanish eTOCs


Part B:        Ten-Steps Medical Text Analysis Workflow Operation using NLP on the Original Text in

Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology


NLP performed by Madison Davis 

Interpretation of NLP results: English Text by Domain Knowledge Expert: Dr. Stephen J. Williams

  • Under consideration: Spanish Podcast and other Languages forthcoming

Part C:        Text and Podcast of e-Book’s Editorials – the English Text in


Preface and Introduction to Genomics Volume 2: Voices of Aviva Lev-Ari & Stephen Williams

  • Introduction to Part 1: NGS – Voice of Dr. Williams
  • Summary to Part 1: NGS – Voice of Dr. Williams
  • Introduction to Part 2: CRISPR – Voice of Dr. Williams
  • Summary to Part 2: CRISPR – Voice of Dr. Williams
  • Introduction to Part 3: AI in Medicine – Voice of Aviva Lev-Ari and Dr. Williams
  • 3.5 on Machine Learning Algorithms in Medicine by Dr. Dror Nir
  • Summary to Part 3: AI in Medicine – Voice of Aviva Lev-Ari and Dr. Williams
  • Introduction to Part 4: Single Cell Genomics – Voice of Dr. Williams
  • Summary to Part 4: Single Cell Genomics – Voice of Dr. Williams
  • Introduction to Part 5: Genomics Modeling in Evolution – Voice of Professor Feldman
  • Summary to Part 5: Genomics Modeling in Evolution – Voice of Professor Feldman
  • Introduction to Part 6: Simulation Modeling – Voice of Dr. Williams
  • Summary to Part 6: Simulation Modeling – Voice of Dr.  Williams
  • Introduction to Part 7: Applications of Genomics: Genotypes, Phenotypes and Complex Diseases – Voice of Dr. Williams
  • Summary to Part 7: Applications of Genomics: Genotypes, Phenotypes and Complex Diseases – Voice of Dr. Williams
  • Introduction to Part 8: Epigenomics and Genomic Regulation – Voice of Dr. Williams
  • Summary to Part 8: Epigenomics and Genomic Regulation – Voice of Dr. Williams

https://c0.pubmine.com/sf/0.0.3/html/safeframe.htmlREPORT THIS AD

Summary to Volume 2 – Voice of Aviva Lev-Ari and Professor Williams  

Epilogue – Voice of Aviva Lev-Ari and Professor Williams

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Standard Operating Procedures for Text to Audio Conversion – How to create a Podcast and Embed it on a Post or on a Page

Author: Ethan Coomber, Research Assistant III, Data Science and Podcast Library Development 


Most recent update: 7-12-21

*As of the writing of these steps, the Anchor feature that converts articles to podcasts is relatively new. As of my most recent communication with representatives of Anchor, they are planning on adding features that would simplify this process.

Converting an Article to a Podcast

  • The first thing you will need to do is create an account on Anchor who has recently partnered with WordPress to allow users to link their accounts and convert articles into podcasts. The link to do so is below.
    • https://anchor.fm/wordpressdotcom
      • It is important to note that Anchor will not let you link to a WordPress account if you create a generic account it must be an account linked with WordPress. This link should allow you to do so.
  • Once you have linked your account, you will want to go to the tab for “Episodes”.
  • On the episodes tab, there should be a button that allows you to import articles from your WordPress account.
  • Unfortunately, as of this update, Anchor does not have a feature to allow users to search for a specific article. I have spoken with workers from Anchor who have told me they will work on implementing this feature right away so check and see if they have finished implementing a search bar or some other way to filter. As of this update, the articles are loaded in chronologically with the most recent articles appearing on the first page.
    • If you are looking to convert an article that was recently published on WordPress, it should appear on this page or one of the first few.
    • One option you have to try to find specific articles is to use the (command F) feature of a mac or the (control F) feature of windows. This allows you to search for a specific keyword within a page.
      • With the publishing date of the article you are looking for in mind, you should be able to find the article within a few minutes. Articles that were published earlier will take longer to find than articles published in the last couple weeks. Many of the articles have dates in their titles so as you go through the pages, you will be able to tell if you have passed your articles if the dates in the titles are from before when the one you are looking for was published. Similarly, you will know you have not arrived yet if the titles are from dates after the one you are looking for.
      • Each time you go to a new page, you will need to press the (command F) function, and then the (return) with the title (or a keyword or phrase from the title you are looking for) in the search bar. This will quickly search the page and tell you if the title you are looking for is there. If no results are found, you know you can go to the next one.
        • I have found this speeds up the process as I get in a rhythm of pressing the button for the next page and then quickly searching the page I am on.
        • If you do not press (command F) function, and then the (return), the search tool will not update and tell you if the word you are looking for is in the page.
        • You may want to play around with these features with an article on the first page or two to make sure you understand before searching for an article published several years ago.
  • Once you have found the article you are looking for, you will then press the large create episode button.
  • You will then be presented with the option to “Automatically convert to audio” or “Record” yourself.
  • If you would like to quickly automatically convert the article, select that option.
  • There are several voices you will then be able to select from. You choose the one you like most.
  • Anchor then converts the entire article.
    • As of now there is no way to select only a portion of the text to convert so the entire article (including headers and captions) will be converted.
  • Once the article is converted, you will then press the “Save and continue” button.
  • Several optional features will then pop up. If you would like to add a song or messages to your podcast, this is the place where you would do it. Once the podcast is how you would like it, you then press the “Save changes” button.
  • If you would like to update the episodes “Cover art”. Select the pencil to the right of the podcast.
  • Scroll to the bottom and upload whatever image you would like.

Embedding a Podcast into an article

  • Once you have published an article on Anchor, you are now able to embed it within your article for viewers to listen and read at the same time.
  • When on Anchor, make sure you are on the Dashboard. There, you should see a button that says “View public site”. Click this button.
  • You will then be directed to a page that gives several options. You will then press the button that says “Listen on Spotify”
  • This will then take you to a page on Spotify instead of Anchor. Here, you will see all articles published using your anchor account. It may take a couple minutes for recently converted articles to show up on this page.
  • Once you see your podcast title, when you hover your mouse over the podcast, a box with an arrow pointing upwards will appear in the bottom right of your highlighted podcast. When you click this button, it will copy a link to your podcast on Spotify. You will use this link to embed your podcast.
  • Returning back to your WordPress article, insert a block where you would like your podcast to be embedded. When you press the plus button to insert a block, choose the browse all option. Scroll all the way down to embeds and select the one with the Spotify icon.
  • You will then be able to past the link you previously copied from Spotify, and your podcast will now be embedded.

Editing a previously published podcast

  • Anchor stores all previously published podcasts in the Episodes tab.
  • Once you are in Episodes, select the button in the bottom right that says “Last”. This will take you to where all published podcasts are.
  • If you would like to edit a podcast, click the three dots to the right of the podcast and select “View episode details”
  • This is where you can edit and save your podcast.

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BurstIQ and The National Center for Advancing Translational Sciences (NCATS) At The National Institutes of Health (NIH) Collaborate to Apply Blockchain to Intellectual Property Management

Reporter: Aviva Lev-Ari, PhD, RN

The collaboration between National Center for Advancing Translational Sciences (NCATS) at NIH and BurstIQ

will transform how IP-sensitive data is managed and shared across the NCATS’ network

DENVER, May 25, 2021 /PRNewswire/ —BurstIQ, the leading provider of blockchain-based data exchange solutions, announced today that the company has entered into a research collaboration agreement with The National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH) to address the protection of intellectual property associated with NCATS’ work on translational science.


The collaboration focuses on development of artificial intelligence/machine learning models for modulating investigators’ data access within collaborative research environments. The segmentation, encryption, and secure storage of chemical information happens seamlessly and data access is enforced with minimal manual intervention and management. The technology enables evidence-based synthesis route design with the help of electronic laboratory notebooks (eLNs) while protecting IP-sensitive chemical information of active research projects.

The collaboration leverages BurstIQ’s groundbreaking blockchain-based secure data exchange platform, which allows governments and organizations to manage the ownership and sharing of sensitive data using dynamic consent and multi-level governance. The platform combines blockchain, best-in-class data security, and orchestration, allowing organizations to build and manage secure data networks in which highly sensitive data can be seamlessly contributed, verified and shared with ownership, governance, and automation built in.

The initial project will integrate BurstIQ’s blockchain platform with NCATS/NIH’s computational infrastructure that is designed to streamline the translational research process so that new treatments and cures for disease can be delivered to patients faster.

“For research communities, the ability to maintain intellectual property ownership is critical,” says Frank Ricotta, CEO of BurstIQ. “In the past, this has been a barrier to collaborative research. This collaboration with NCATS is designed break down this barrier and make it possible for researchers to share ideas and information with each other confidently, which will truly accelerate the pace of discovery.”

To learn more about BurstIQ’s collaboration with NCATS and how the companies are working together to drive collaborative research, please contact us at info@burstiq.com.

About BurstIQ™ 
BurstIQ is the leading provider of blockchain-enabled data solutions for the identity, healthcare, and life sciences industries. The company’s secure data exchange network allows organizations to build secure networks to manage the ownership and sharing of sensitive data, with ownership, consent, governance, and workflow orchestration built in. The platform combines blockchain, Big Data, and best-in-class security to build multi-dimensional profiles of people, places, and things and empower the interactions between them. The result is a global, secure data network that allows health systems, payers, digital health companies, pharma & life science companies, and governments to collaborate, share, discover, and build the impossible.
For more information visit: Website | Facebook | Twitter | LinkedIn

BurstIQ: Amber Hartley
P: 888-355-7345
E:  310625@email4pr.com
W: www.burstIQ.com 



BurstIQ technology of Blockchain Transactions Network is the selected IT design for LPBI considering its own IP asset classes:

  • +6,000 articles
  • 18 e-Books in Medicine
  • 100 e-Proceedings and Tweet Collections
  • +5,100 Gallery of Biological Images

Detained descriptions provided here


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2021 Virtual World Medical Innovation Forum, Mass General Brigham, Gene and Cell Therapy, VIRTUAL May 19–21, 2021

The 2021 Virtual World Medical Innovation Forum will focus on the growing impact of gene and cell therapy.Senior healthcare leaders from all over look to shape and debate the area of gene and cell therapy. Our shared belief: no matter the magnitude of change, responsible healthcare is centered on a shared commitment to collaborative innovation–industry, academia, and practitioners working together to improve patients’ lives.

About the World Medical Innovation Forum

Mass General Brigham is pleased to present the World Medical Innovation Forum (WMIF) virtual event Wednesday, May 19 – Friday, May 21. This interactive web event features expert discussions of gene and cell therapy (GCT) and its potential to change the future of medicine through its disease-treating and potentially curative properties. The agenda features 150+ executive speakers from the healthcare industry, venture, startups, life sciences manufacturing, consumer health and the front lines of care, including many Harvard Medical School-affiliated researchers and clinicians. The annual in-person Forum will resume live in Boston in 2022. The World Medical Innovation Forum is presented by Mass General Brigham Innovation, the global business development unit supporting the research requirements of 7,200 Harvard Medical School faculty and research hospitals including Massachusetts General, Brigham and Women’s, Massachusetts Eye and Ear, Spaulding Rehab and McLean Hospital. Follow us on Twitter: twitter.com/@MGBInnovation

Accelerating the Future of Medicine with Gene and Cell Therapy What Comes Next


Virtual | May 19–21, 2021



Leaders in Pharmaceutical Business Intelligence (LPBI) Group

will cover the event in Real Time

Aviva Lev-Ari, PhD, RN

Founder LPBI 1.0 & LPBI 2.0

member_60221522 copy

will be in virtual attendance producing the e-Proceedings

and the Tweet Collection of this Global event expecting +15,000 attendees



LPBI’s Eighteen Books in Medicine



Among them, books on Gene and Cell Therapy include the following:

Topics for May 19 – 21 include:

Impact on Patient Care – Therapeutic and Potentially Curative GCT Developments

GCT Delivery, Manufacturing – What’s Next

GCT Platform Development

Oncolytic Viruses – Cancer applications, start-ups

Regenerative Medicine/Stem Cells

Future of CAR-T

M&A Shaping GCT’s Future

Market Priorities

Venture Investing in GCT

China’s GCT Juggernaut

Disease and Patient Focus: Benign blood disorders, diabetes, neurodegenerative diseases

Click here for the current WMIF agenda  


Fireside Chats: 1:1 interviews with industry CEOs/C-Suite leaders including Novartis Gene Therapies, ThermoFisher, Bayer AG, FDA

First Look: 18 briefings on emerging GCT research from Mass General Brigham scientists

Virtual Poster Session: 40 research posters and presenters on potential GCT discoveries from Mass General Brigham

Announcement of the Disruptive Dozen, 12 GCT technologies likely to break through in the next few years

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Cryo-EM disclosed how the D614G mutation changes SARS-CoV-2 spike protein structure.

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

SARS-CoV-2, the virus that causes COVID-19, has had a major impact on human health globally; infecting a massive quantity of people around 136,046,262 (John Hopkins University); causing severe disease and associated long-term health sequelae; resulting in death and excess mortality, especially among older and prone populations; altering routine healthcare services; disruptions to travel, trade, education, and many other societal functions; and more broadly having a negative impact on peoples physical and mental health.

It’s need of the hour to answer the questions like what allows the variants of SARS-CoV-2 first detected in the UK, South Africa, and Brazil to spread so quickly? How can current COVID-19 vaccines better protect against them?

Scientists from the Harvard Medical School and the Boston Children’s Hospital help answer these urgent questions. The team reports its findings in the journal “Science a paper entitled Structural impact on SARS-CoV-2 spike protein by D614G substitution. The mutation rate of the SARS-CoV-2 virus has rapidly evolved over the past few months, especially at the Spike (S) protein region of the virus, where the maximum number of mutations have been observed by the virologists.

Bing Chen, HMS professor of pediatrics at Boston Children’s, and colleagues analyzed the changes in the structure of the spike proteins with the genetic change by D614G mutation by all three variants. Hence they assessed the structure of the coronavirus spike protein down to the atomic level and revealed the reason for the quick spreading of these variants.

This model shows the structure of the spike protein in its closed configuration, in its original D614 form (left) and its mutant form (G614). In the mutant spike protein, the 630 loop (in red) stabilizes the spike, preventing it from flipping open prematurely and rendering SARS-CoV-2 more infectious.

Fig. 1. Cryo-EM structures of the full-length SARS-CoV-2 S protein carrying G614.

(A) Three structures of the G614 S trimer, representing a closed, three RBD-down conformation, an RBD-intermediate conformation and a one RBD-up conformation, were modeled based on corresponding cryo-EM density maps at 3.1-3.5Å resolution. Three protomers (a, b, c) are colored in red, blue and green, respectively. RBD locations are indicated. (B) Top views of superposition of three structures of the G614 S in (A) in ribbon representation with the structure of the prefusion trimer of the D614 S (PDB ID: 6XR8), shown in yellow. NTD and RBD of each protomer are indicated. Side views of the superposition are shown in fig. S8.

IMAGE SOURCE: Bing Chen, Ph.D., Boston Children’s Hospital, https://science.sciencemag.org/content/early/2021/03/16/science.abf2303

The work

The mutant spikes were imaged by Cryo-Electron microscopy (cryo-EM), which has resolution down to the atomic level. They found that the D614G mutation (substitution of in a single amino acid “letter” in the genetic code for the spike protein) makes the spike more stable as compared with the original SARS-CoV-2 virus. As a result, more functional spikes are available to bind to our cells’ ACE2 receptors, making the virus more contagious.

Fig. 2. Cryo-EM revealed how the D614G mutation changes SARS-CoV-2 spike protein structure.

IMAGE SOURCE:  Zhang J, et al., Science

Say the original virus has 100 spikes,” Chen explained. “Because of the shape instability, you may have just 50 percent of them functional. In the G614 variants, you may have 90 percent that is functional. So even though they don’t bind as well, the chances are greater and you will have an infection

Forthcoming directions by Bing Chen and Team

The findings suggest the current approved COVID-19 vaccines and any vaccines in the works should include the genetic code for this mutation. Chen has quoted:

Since most of the vaccines so far—including the Moderna, Pfizer–BioNTech, Johnson & Johnson, and AstraZeneca vaccines are based on the original spike protein, adding the D614G mutation could make the vaccines better able to elicit protective neutralizing antibodies against the viral variants

Chen proposes that redesigned vaccines incorporate the code for this mutant spike protein. He believes the more stable spike shape should make any vaccine based on the spike more likely to elicit protective antibodies. Chen also has his sights set on therapeutics. He and his colleagues are further applying structural biology to better understand how SARS-CoV-2 binds to the ACE2 receptor. That could point the way to drugs that would block the virus from gaining entry to our cells.

In January, the team showed that a structurally engineered “decoy” ACE2 protein binds to SARS-CoV-2 200 times more strongly than the body’s own ACE2. The decoy potently inhibited the virus in cell culture, suggesting it could be an anti-COVID-19 treatment. Chen is now working to advance this research into animal models.

Main Source:


Substitution for aspartic acid by glycine at position 614 in the spike (S) protein of severe acute respiratory syndrome coronavirus 2 appears to facilitate rapid viral spread. The G614 strain and its recent variants are now the dominant circulating forms. We report here cryo-EM structures of a full-length G614 S trimer, which adopts three distinct prefusion conformations differing primarily by the position of one receptor-binding domain. A loop disordered in the D614 S trimer wedges between domains within a protomer in the G614 spike. This added interaction appears to prevent premature dissociation of the G614 trimer, effectively increasing the number of functional spikes and enhancing infectivity, and to modulate structural rearrangements for membrane fusion. These findings extend our understanding of viral entry and suggest an improved immunogen for vaccine development.


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COVID-19 Sequel: Neurological Impact of Social isolation been linked to poorer physical and mental health

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Comparing COVID-19 Vaccine Schedule Combinations, or “Com-COV” – First-of-its-Kind Study will explore the Impact of using eight different Combinations of Doses and Dosing Intervals for Different COVID-19 Vaccines

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