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Systems Biology Analysis of Transcription Networks, Artificial Intelligence, and High-End Computing Coming to Fruition in Personalized Oncology

Posted in Artificial Intelligence in CANCER, Artificial Intelligence in Health Care - Tools & Innovations, Artificial Intelligence in Medicine - Applications in Therapeutics, Big Data, BioIT: BioInformatics, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cell Biology, Cell Biology, Signaling & Cell Circuits, Clinical & Translational, Clinical Genomics, Genomic Expression, Intelligent Information Systems, tagged activation of transcription factors, Artificial intelligence, Artificial Intelligence & Clinical Trials, Biological Networks, Columbia University Medical Center, DarwinHealth, mutational analysis, RNA-Seq, transcription control on July 14, 2020| Leave a Comment »

Systems Biology analysis of Transcription Networks, Artificial Intelligence, and High-End Computing Coming to Fruition in Personalized Oncology

Curator: Stephen J. Williams, Ph.D.

In the June 2020 issue of the journal Science, writer Roxanne Khamsi has an interesting article “Computing Cancer’s Weak Spots; An algorithm to unmask tumors’ molecular linchpins is tested in patients”[1], describing some early successes in the incorporation of cancer genome sequencing in conjunction with artificial intelligence algorithms toward a personalized clinical treatment decision for various tumor types. In 2016, oncologists Amy Tiersten collaborated with systems biologist Andrea Califano and cell biologist Jose Silva at Mount Sinai Hospital to develop a systems biology approach to determine that the drug ruxolitinib, a STAT3 inhibitor, would be effective for one of her patient’s aggressively recurring, Herceptin-resistant breast tumor. Dr. Califano, instead of defining networks of driver mutations, focused on identifying a few transcription factors that act as ‘linchpins’ or master controllers of transcriptional networks withing tumor cells, and in doing so hoping to, in essence, ‘bottleneck’ the transcriptional machinery of potential oncogenic products. As Dr. Castilano states

“targeting those master regulators and you will stop cancer in its tracks, no matter what mutation initially caused it.”

It is important to note that this approach also relies on the ability to sequence tumors by RNA-seq to determine the underlying mutations which alter which master regulators are pertinent in any one tumor. And given the wide tumor heterogeneity in tumor samples, this sequencing effort may have to involve multiple biopsies (as discussed in earlier posts on tumor heterogeneity in renal cancer).

As stated in the article, Califano co-founded a company called Darwin-Health in 2015 to guide doctors by identifying the key transcription factors in a patient’s tumor and suggesting personalized therapeutics to those identified molecular targets (OncoTarget™). He had collaborated with the Jackson Laboratory and most recently Columbia University to conduct a $15 million 3000 patient clinical trial. This was a bit of a stretch from his initial training as a physicist and, in 1986, IBM hired him for some artificial intelligence projects. He then landed in 2003 at Columbia and has been working on identifying these transcriptional nodes that govern cancer survival and tumorigenicity. Dr. Califano had figured that the number of genetic mutations which potentially could be drivers were too vast:

A 2018 study which analyzed more than 9000 tumor samples reported over 1.5 million mutations[2]

and impossible to develop therapeutics against. He reasoned that you would just have to identify the common connections between these pathways or transcriptional nodes and termed them master regulators.

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples

Chen H, Li C, Peng X, et al. Cell. 2018;173(2):386-399.e12.

Abstract

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on “chromatin-state” to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.

A diagram of how concentrating on these transcriptional linchpins or nodes may be more therapeutically advantageous as only one pharmacologic agent is needed versus multiple agents to inhibit the various upstream pathways:

From: Khamsi R: Computing cancer’s weak spots. Science 2020, 368(6496):1174-1177.

VIPER Algorithm (Virtual Inference of Protein activity by Enriched Regulon Analysis)

The algorithm that Califano and DarwinHealth developed is a systems biology approach using a tumor’s RNASeq data to determine controlling nodes of transcription. They have recently used the VIPER algorithm to look at RNA-Seq data from more than 10,000 tumor samples from TCGA and identified 407 transcription factor genes that acted as these linchpins across all tumor types. Only 20 to 25 of them were implicated in just one tumor type so these potential nodes are common in many forms of cancer.

Other institutions like the Cold Spring Harbor Laboratories have been using VIPER in their patient tumor analysis. Linchpins for other tumor types have been found. For instance, VIPER identified transcription factors IKZF1 and IKF3 as linchpins in multiple myeloma. But currently approved therapeutics are hard to come by for targets with are transcription factors, as most pharma has concentrated on inhibiting an easier target like kinases and their associated activity. In general, developing transcription factor inhibitors in more difficult an undertaking for multiple reasons.

Network-based inference of protein activity helps functionalize the genetic landscape of cancer. Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, Califano A:. Nature genetics 2016, 48(8):838-847 [3]

Abstract

Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given patient is crucial for developing personalized treatment plans. However, accurate inference of aberrant protein activity in biological samples is still challenging as genetic alterations are only partially predictive and direct measurements of protein activity are generally not feasible. To address this problem we introduce and experimentally validate a new algorithm, VIPER (Virtual Inference of Protein-activity by Enriched Regulon analysis), for the accurate assessment of protein activity from gene expression data. We use VIPER to evaluate the functional relevance of genetic alterations in regulatory proteins across all TCGA samples. In addition to accurately inferring aberrant protein activity induced by established mutations, we also identify a significant fraction of tumors with aberrant activity of druggable oncoproteins—despite a lack of mutations, and vice-versa. In vitro assays confirmed that VIPER-inferred protein activity outperforms mutational analysis in predicting sensitivity to targeted inhibitors.

Figure 1

Schematic overview of the VIPER algorithm From: Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, Califano A: Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nature genetics 2016, 48(8):838-847.

(a) Molecular layers profiled by different technologies. Transcriptomics measures steady-state mRNA levels; Proteomics quantifies protein levels, including some defined post-translational isoforms; VIPER infers protein activity based on the protein’s regulon, reflecting the abundance of the active protein isoform, including post-translational modifications, proper subcellular localization and interaction with co-factors. (b) Representation of VIPER workflow. A regulatory model is generated from ARACNe-inferred context-specific interactome and Mode of Regulation computed from the correlation between regulator and target genes. Single-sample gene expression signatures are computed from genome-wide expression data, and transformed into regulatory protein activity profiles by the aREA algorithm. (c) Three possible scenarios for the aREA analysis, including increased, decreased or no change in protein activity. The gene expression signature and its absolute value (|GES|) are indicated by color scale bars, induced and repressed target genes according to the regulatory model are indicated by blue and red vertical lines. (d) Pleiotropy Correction is performed by evaluating whether the enrichment of a given regulon (R₄) is driven by genes co-regulated by a second regulator (R₄∩R₁). (e) Benchmark results for VIPER analysis based on multiple-samples gene expression signatures (msVIPER) and single-sample gene expression signatures (VIPER). Boxplots show the accuracy (relative rank for the silenced protein), and the specificity (fraction of proteins inferred as differentially active at p < 0.05) for the 6 benchmark experiments (see Table 2). Different colors indicate different implementations of the aREA algorithm, including 2-tail (2T) and 3-tail (3T), Interaction Confidence (IC) and Pleiotropy Correction (PC).

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

Posted in Antibody Responses Predict Antigen Exposure, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, COVID-19, Immunodiagnostics, Immunology, Innovation in Immunology Diagnostics, MHC Repertoires for Antigen Prediction, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Viral diseases, Virology - Vector-borne DIsease, tagged BioIT: BioInformatics, Biological Engineering, Biological Networks, Biomarkers & Medical Diagnostics, Cancer Informatics, Clinical & Translational, clinical genomics, Commercialization, COVID-19, Gene Regulation and Evolution, Genetics & Pharmaceutical, Immunotherapy, Innovation in Immunology Diagnostics, Innovations, Intellectual property, Investment in Technological Breakthrough, NGS, Pharmaceutical R&D Informatics, Population Health Management, Proteomics, SARS-CoV, SARS-CoV-2, Universal Immune Cell Therapies (uICT), Virus Infective Acute Respiratory Syndrome: SARS-CoV | Tagged COVID-19 on March 12, 2020| Leave a Comment »

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

Therapeutical options to coronavirus (2019-nCoV) include consideration of the following:

(a) Monoclonal and polyclonal antibodies

(b) Vaccines

(c) Small molecule treatments (e.g., chloroquinolone and derivatives), including compounds already approved for other indications

(d) Immuno-therapies derived from human or other sources

Structure of the nCoV trimeric spike

The World Health Organization has declared the outbreak of a novel coronavirus (2019-nCoV) to be a public health emergency of international concern. The virus binds to host cells through its trimeric spike glycoprotein, making this protein a key target for potential therapies and diagnostics. Wrapp et al. determined a 3.5-angstrom-resolution structure of the 2019-nCoV trimeric spike protein by cryo–electron microscopy. Using biophysical assays, the authors show that this protein binds at least 10 times more tightly than the corresponding spike protein of severe acute respiratory syndrome (SARS)–CoV to their common host cell receptor. They also tested three antibodies known to bind to the SARS-CoV spike protein but did not detect binding to the 2019-nCoV spike protein. These studies provide valuable information to guide the development of medical counter-measures for 2019-nCoV. [Bold Face Added by ALA]

Science, this issue p. 1260

Abstract

The outbreak of a novel coronavirus (2019-nCoV) represents a pandemic threat that has been declared a public health emergency of international concern. The CoV spike (S) glycoprotein is a key target for vaccines, therapeutic antibodies, and diagnostics. To facilitate medical countermeasure development, we determined a 3.5-angstrom-resolution cryo–electron microscopy structure of the 2019-nCoV S trimer in the prefusion conformation. The predominant state of the trimer has one of the three receptor-binding domains (RBDs) rotated up in a receptor-accessible conformation. We also provide biophysical and structural evidence that the 2019-nCoV S protein binds angiotensin-converting enzyme 2 (ACE2) with higher affinity than does severe acute respiratory syndrome (SARS)-CoV S. Additionally, we tested several published SARS-CoV RBD-specific monoclonal antibodies and found that they do not have appreciable binding to 2019-nCoV S, suggesting that antibody cross-reactivity may be limited between the two RBDs. The structure of 2019-nCoV S should enable the rapid development and evaluation of medical countermeasures to address the ongoing public health crisis.

Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation

Daniel Wrapp¹,*,
Nianshuang Wang¹,*,
Kizzmekia S. Corbett²,
Jory A. Goldsmith¹,
Ching-Lin Hsieh¹,
Olubukola Abiona²,
Barney S. Graham²,
Jason S. McLellan ¹,†

Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA.
²Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.

↵†Corresponding author. Email: jmclellan@austin.utexas.edu

↵* These authors contributed equally to this work.

Science 13 Mar 2020:
Vol. 367, Issue 6483, pp. 1260-1263
DOI: 10.1126/science.abb2507

02/04/2020

New Coronavirus Protease Structure Available

PDB data provide a starting point for structure-guided drug discovery

A high-resolution crystal structure of COVID-19 (2019-nCoV) coronavirus 3CL hydrolase (Mpro) has been determined by Zihe Rao and Haitao Yang’s research team at ShanghaiTech University. Rapid public release of this structure of the main protease of the virus (PDB 6lu7) will enable research on this newly-recognized human pathogen.

Recent emergence of the COVID-19 coronavirus has resulted in a WHO-declared public health emergency of international concern. Research efforts around the world are working towards establishing a greater understanding of this particular virus and developing treatments and vaccines to prevent further spread.

https://doi.org/10.2210/pdb6lu7/pdb

While PDB entry 6lu7 is currently the only public-domain 3D structure from this specific coronavirus, the PDB contains structures of the corresponding enzyme from other coronaviruses. The 2003 outbreak of the closely-related Severe Acute Respiratory Syndrome-related coronavirus (SARS) led to the first 3D structures, and today there are more than 200 PDB structures of SARS proteins. Structural information from these related proteins could be vital in furthering our understanding of coronaviruses and in discovery and development of new treatments and vaccines to contain the current outbreak.

The coronavirus 3CL hydrolase (Mpro) enzyme, also known as the main protease, is essential for proteolytic maturation of the virus. It is thought to be a promising target for discovery of small-molecule drugs that would inhibit cleavage of the viral polyprotein and prevent spread of the infection.

Comparison of the protein sequence of the COVID-19 coronavirus 3CL hydrolase (Mpro) against the PDB archive identified 95 PDB proteins with at least 90% sequence identity. Furthermore, these related protein structures contain approximately 30 distinct small molecule inhibitors, which could guide discovery of new drugs. Of particular significance for drug discovery is the very high amino acid sequence identity (96%) between the COVID-19 coronavirus 3CL hydrolase (Mpro) and the SARS virus main protease (PDB 1q2w). Summary data about these closely-related PDB structures are available (CSV) to help researchers more easily find this information. In addition, the PDB houses 3D structure data for more than 20 unique SARS proteins represented in more than 200 PDB structures, including a second viral protease, the RNA polymerase, the viral spike protein, a viral RNA, and other proteins (CSV).

Public release of the COVID-19 coronavirus 3CL hydrolase (Mpro), at a time when this information can prove most vital and valuable, highlights the importance of open and timely availability of scientific data. The wwPDB strives to ensure that 3D biological structure data remain freely accessible for all, while maintaining as comprehensive and accurate an archive as possible. We hope that this new structure, and those from related viruses, will help researchers and clinicians address the COVID-19 coronavirus global public health emergency.

Update: Released COVID-19-related PDB structures include

PDB structure 6lu7 (X. Liu, B. Zhang, Z. Jin, H. Yang, Z. Rao Crystal structure of COVID-19 main protease in complex with an inhibitor N3 doi: 10.2210/pdb6lu7/pdb) Released 2020-02-05

PDB structure 6vsb (D. Wrapp, N. Wang, K.S. Corbett, J.A. Goldsmith, C.-L. Hsieh, O. Abiona, B.S. Graham, J.S. McLellan (2020) Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation Science doi: 10.1126/science.abb2507) Released 2020-02-26

PDB structure 6lxt (Y. Zhu, F. Sun Structure of post fusion core of 2019-nCoV S2 subunit doi: 10.2210/pdb6lxt/pdb) Released 2020-02-26

PDB structure 6lvn (Y. Zhu, F. Sun Structure of the 2019-nCoV HR2 Domain doi: 10.2210/pdb6lvn/pdb) Released 2020-02-26

PDB structure 6vw1
J. Shang, G. Ye, K. Shi, Y.S. Wan, H. Aihara, F. Li Structural basis for receptor recognition by the novel coronavirus from Wuhan doi: 10.2210/pdb6vw1/pdb
Released 2020-03-04

PDB structure 6vww
Y. Kim, R. Jedrzejczak, N. Maltseva, M. Endres, A. Godzik, K. Michalska, A. Joachimiak, Center for Structural Genomics of Infectious Diseases Crystal Structure of NSP15 Endoribonuclease from SARS CoV-2 doi: 10.2210/pdb6vww/pdb
Released 2020-03-04

PDB structure 6y2e
L. Zhang, X. Sun, R. Hilgenfeld Crystal structure of the free enzyme of the SARS-CoV-2 (2019-nCoV) main protease doi: 10.2210/pdb6y2e/pdb
Released 2020-03-04

PDB structure 6y2f
L. Zhang, X. Sun, R. Hilgenfeld Crystal structure (monoclinic form) of the complex resulting from the reaction between SARS-CoV-2 (2019-nCoV) main protease and tert-butyl (1-((S)-1-(((S)-4-(benzylamino)-3,4-dioxo-1-((S)-2-oxopyrrolidin-3-yl)butan-2-yl)amino)-3-cyclopropyl-1-oxopropan-2-yl)-2-oxo-1,2-dihydropyridin-3-yl)carbamate (alpha-ketoamide 13b) doi: 10.2210/pdb6y2f/pdb
Released 2020-03-04

PDB structure 6y2g
L. Zhang, X. Sun, R. Hilgenfeld Crystal structure (orthorhombic form) of the complex resulting from the reaction between SARS-CoV-2 (2019-nCoV) main protease and tert-butyl (1-((S)-1-(((S)-4-(benzylamino)-3,4-dioxo-1-((S)-2-oxopyrrolidin-3-yl)butan-2-yl)amino)-3-cyclopropyl-1-oxopropan-2-yl)-2-oxo-1,2-dihydropyridin-3-yl)carbamate (alpha-ketoamide 13b) doi: 10.2210/pdb6y2g/pdb
Released 2020-03-04

SOURCE – 02/04/2020

https://www.wwpdb.org/news/news?year=2020&fbclid=IwAR0mFKQD7KX29hkJcnV0MxeAe_1themx7KuBDo8txaMiYHJ08JvNN0cisug#5e39e03fa5007a04a313edc3

Coronavirus Disease 2019 (COVID-19) and Cardiovascular Disease

Kevin J. Clerkin , Justin A. Fried, Jayant Raikhelkar, Gabriel Sayer, Jan M. Griffin, Amirali Masoumi, Sneha S. Jain, Daniel Burkhoff, Deepa Kumaraiah, LeRoy Rabbani, Allan Schwartz

and

Nir Uriel

Originally published 21 Mar 2020 https://doi.org/10.1161/CIRCULATIONAHA.120.046941 Circulation. ;0:null

Abstract

Coronavirus disease 2019 (COVID-19) is a global pandemic impacting nearly 170 countries/regions and more than 285,000 patients worldwide. COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which invades cells through the angiotensin converting enzyme 2 (ACE2) receptor. Among those with COVID-19, there is a higher prevalence of cardiovascular disease and more than 7% of patients suffer myocardial injury from the infection (22% of the critically ill). Despite ACE2 serving as the portal for infection, the role of ACE inhibitors or angiotensin receptor blockers requires further investigation. COVID-19 poses a challenge for heart transplantation, impacting donor selection, immunosuppression, and post-transplant management. Thankfully there are a number of promising therapies under active investigation to both treat and prevent COVID-19. Key Words: COVID-19; myocardial injury; pandemic; heart transplant

SOURCE

https://www.ahajournals.org/doi/pdf/10.1161/CIRCULATIONAHA.120.046941

ACE2

Towler P, Staker B, Prasad SG, Menon S, Tang J, Parsons T, Ryan D, Fisher M, Williams D, Dales NA, Patane MA, Pantoliano MW (Apr 2004). “ACE2 X-ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis”. The Journal of Biological Chemistry. 279 (17): 17996–8007. doi:10.1074/jbc.M311191200. PMID 14754895.

Turner AJ, Tipnis SR, Guy JL, Rice G, Hooper NM (Apr 2002). “ACEH/ACE2 is a novel mammalian metallocarboxypeptidase and a homologue of angiotensin-converting enzyme insensitive to ACE inhibitors”. Canadian Journal of Physiology and Pharmacology. 80 (4): 346–53. doi:10.1139/y02-021. PMID 12025971.

Zhang, Haibo; Penninger, Josef M.; Li, Yimin; Zhong, Nanshan; Slutsky, Arthur S. (3 March 2020). “Angiotensin-converting enzyme 2 (ACE2) as a SARS-CoV-2 receptor: molecular mechanisms and potential therapeutic target”. Intensive Care Medicine. Springer Science and Business Media LLC. doi:10.1007/s00134-020-05985-9. ISSN 0342-4642. PMID 32125455.

^ Gurwitz, David (2020). “Angiotensin receptor blockers as tentative SARS‐CoV‐2 therapeutics”. Drug Development Research. doi:10.1002/ddr.21656. PMID 32129518.

Angiotensin converting enzyme 2 (ACE2)

is an exopeptidase that catalyses the conversion of angiotensin I to the nonapeptide angiotensin[1-9]^[5] or the conversion of angiotensin II to angiotensin 1-7.^[6]^[7] ACE2 has direct effects on cardiac function^a and is expressed predominantly in vascular endothelial cells of the heart and the kidneys.^[8] ACE2 is not sensitive to the ACE inhibitor drugs used to treat hypertension.^[9]

ACE2 receptors have been shown to be the entry point into human cells for some coronaviruses, including the SARS virus.^[10] A number of studies have identified that the entry point is the same for SARS-CoV-2,^[11] the virus that causes COVID-19.^[12]^[13]^[14]^[15]

Some have suggested that a decrease in ACE2 could be protective against Covid-19 disease^[16], but others have suggested the opposite, that Angiotensin II receptor blocker drugs could be protective against Covid-19 disease via increasing ACE2, and that these hypotheses need to be tested by datamining of clinical patient records.^[17]

REFERENCES

https://en.wikipedia.org/wiki/Angiotensin-converting_enzyme_2

FOLDING@HOME TAKES UP THE FIGHT AGAINST COVID-19 / 2019-NCOV

February 27, 2020

by Greg Bowman

We need your help! Folding@home is joining researchers around the world working to better understand the 2019 Coronavirus (2019-nCoV) to accelerate the open science effort to develop new life-saving therapies. By downloading Folding@Home, you can donate your unused computational resources to the Folding@home Consortium, where researchers working to advance our understanding of the structures of potential drug targets for 2019-nCoV that could aid in the design of new therapies. The data you help us generate will be quickly and openly disseminated as part of an open science collaboration of multiple laboratories around the world, giving researchers new tools that may unlock new opportunities for developing lifesaving drugs.

2019-nCoV is a close cousin to SARS coronavirus (SARS-CoV), and acts in a similar way. For both coronaviruses, the first step of infection occurs in the lungs, when a protein on the surface of the virus binds to a receptor protein on a lung cell. This viral protein is called the spike protein, depicted in red in the image below, and the receptor is known as ACE2. A therapeutic antibody is a type of protein that can block the viral protein from binding to its receptor, therefore preventing the virus from infecting the lung cell. A therapeutic antibody has already been developed for SARS-CoV, but to develop therapeutic antibodies or small molecules for 2019-nCoV, scientists need to better understand the structure of the viral spike protein and how it binds to the human ACE2 receptor required for viral entry into human cells.

Proteins are not stagnant—they wiggle and fold and unfold to take on numerous shapes. We need to study not only one shape of the viral spike protein, but all the ways the protein wiggles and folds into alternative shapes in order to best understand how it interacts with the ACE2 receptor, so that an antibody can be designed. Low-resolution structures of the SARS-CoV spike protein exist and we know the mutations that differ between SARS-CoV and 2019-nCoV. Given this information, we are uniquely positioned to help model the structure of the 2019-nCoV spike protein and identify sites that can be targeted by a therapeutic antibody. We can build computational models that accomplish this goal, but it takes a lot of computing power.

This is where you come in! With many computers working towards the same goal, we aim to help develop a therapeutic remedy as quickly as possible. By downloading Folding@home here [LINK] and selecting to contribute to “Any Disease”, you can help provide us with the computational power required to tackle this problem. One protein from 2019-nCoV, a protease encoded by the viral RNA, has already been crystallized. Although the 2019-nCoV spike protein of interest has not yet been resolved bound to ACE2, our objective is to use the homologous structure of the SARS-CoV spike protein to identify therapeutic antibody targets.

This illustration, created at the Centers for Disease Control and Prevention (CDC), reveals ultrastructural morphology exhibited by coronaviruses. Note the spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed electron microscopically. A novel coronavirus virus was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China in 2019.

Image and Caption Credit: Alissa Eckert, MS; Dan Higgins, MAM available at https://phil.cdc.gov/Details.aspx?pid=23311

Structures of the closely related SARS-CoV spike protein bound by therapeutic antibodies may help rapidly design better therapies. The three monomers of the SARS-CoV spike protein are shown in different shades of red; the antibody is depicted in green. [PDB: 6NB7 https://www.rcsb.org/structure/6nb7]

(post authored by Ariana Brenner Clerkin)

References:

PDB 6lu7 structure summary ‹ Protein Data Bank in Europe (PDBe) ‹ EMBL-EBI https://www.ebi.ac.uk/pdbe/entry/pdb/6lu7 (accessed Feb 5, 2020).

Tian, X.; Li, C.; Huang, A.; Xia, S.; Lu, S.; Shi, Z.; Lu, L.; Jiang, S.; Yang, Z.; Wu, Y.; et al. Potent Binding of 2019 Novel Coronavirus Spike Protein by a SARS Coronavirus-Specific Human Monoclonal Antibody; preprint; Microbiology, 2020. https://doi.org/10.1101/2020.01.28.923011.

Walls, A. C.; Xiong, X.; Park, Y. J.; Tortorici, M. A.; Snijder, J.; Quispe, J.; Cameroni, E.; Gopal, R.; Dai, M.; Lanzavecchia, A.; et al. Unexpected Receptor Functional Mimicry Elucidates Activation of Coronavirus Fusion. Cell 2019, 176, 1026-1039.e15. https://doi.org/10.2210/pdb6nb7/pdb.

SOURCE

https://foldingathome.org/2020/02/27/foldinghome-takes-up-the-fight-against-covid-19-2019-ncov/

UPDATED 3/13/2020

I am reposting the following Science blog post from Derrick Lowe as is and ask people go browse through the comments on his Science blog In the Pipeline because, as Dr. Lowe states that in this current crisis it is important to disseminate good information as quickly as possible so wanted the readers here to have the ability to read his great posting on this matter of Covid-19. Also i would like to direct readers to the journal Science opinion letter concerning how important it is to rebuild the trust in good science and the scientific process. The full link for the following In the Pipeline post is: https://blogs.sciencemag.org/pipeline/archives/2020/03/06/covid-19-small-molecule-therapies-reviewed

A Summary of current potential repurposed therapeutics for COVID-19 Infection from In The Pipeline: A Science blog from Derick Lowe

Covid-19 Small Molecule Therapies Reviewed

By Derek Lowe 6 March, 2020

Let’s take inventory on the therapies that are being developed for the coronavirus epidemic. Here is a very thorough list of at Biocentury, and I should note that (like Stat and several other organizations) they’re making all their Covid-19 content free to all readers during this crisis. I’d like to zoom in today on the potential small-molecule therapies, since some of these have the most immediate prospects for use in the real world.

The ones at the front of the line are repurposed drugs that are already approved for human use, for a lot of obvious reasons. The Biocentury list doesn’t cover these, but here’s an article at Nature Biotechnology that goes into detail. Clinical trials are a huge time sink – they sort of have to be, in most cases, if they’re going to be any good – and if you’ve already done all that stuff it’s a huge leg up, even if the drug itself is not exactly a perfect fit for the disease. So what do we have? The compound that is most advanced is probably remdesivir from Gilead, at right. This has been in development for a few years as an RNA virus therapy – it was originally developed for Ebola, and has been tried out against a whole list of single-strand RNA viruses. That includes the related coronaviruses SARS and MERS, so Covid-19 was an obvious fit.

The compound is a prodrug – that phosphoramide gets cleaved off completely, leaving the active 5-OH compound GS-44-1524. It mechanism of action is to get incorporated into viral RNA, since it’s taken up by RNA polymerase and it largely seems to evade proofreading. This causes RNA termination trouble later on, since that alpha-nitrile C-nucleoside is not exactly what the virus is expecting in its genome at that point, and thus viral replication is inhibited.

There are five clinical trials underway (here’s an overview at Biocentury). The NIH has an adaptive-design Phase II trial that has already started in Nebraska, with doses to be changed according to Bayesian readouts along the way. There are two Phase III trials underway at China-Japan Friendship Hospital in Hubei, double-blinded and placebo-controlled (since placebo is, as far as drug therapy goes, the current standard of care). And Gilead themselves are starting two open-label trials, one with no control arm and one with an (unblinded) standard-of-care comparison arm. Those might read out first, depending on when they get off the ground, but will be only rough readouts due to the fast-and-loose trial design. The two Hubei trials and the NIH one will add some rigor to the process, but I’m not sure when they’re going to report. My personal opinion is that I like the chances of this drug more than anything else on this list, but it’s still unlikely to be a game-changer.

There’s an RNA polymerase inhibitor (favipiravir) from Toyama, at right, that’s in a trial in China. It’s a thought – a broad-spectrum agent of this sort would be the sort of thing to try. But unfortunately, from what I can see, it has already turned up as ineffective in in vitro tests. The human trial that’s underway is honestly the sort of thing that would only happen under circumstances like the present: a developing epidemic with a new pathogen and no real standard of care. I hold out little hope for this one, but given that there’s nothing else at present, it probably should be tried. As you’ll see, this is far from the only situation like this.

One of the screens of known drugs in China that also flagged remdesivir noted that the old antimalarial drug chloroquine seemed to be effective in vitro. It had been reported some years back as a possible antiviral, working through more than one mechanism, probably both at viral entry and intracellularly thereafter. That part shouldn’t be surprising – chloroquine’s actual mode(s) of action against malaria parasites are still not completely worked out, either, and some of what people thought they knew about it has turned out to be wrong. There are several trials underway with it at Chinese facilities, some in combination with other agents like remdesivir. Chloroquine has of course been taken for many decades as an antimalarial, but it has a number of liabilities, including seizures, hearing damage, retinopathy and sudden effects on blood glucose. So it’s going to be important to establish just how effective it is and what doses will be needed. Just as with vaccine candidates, it’s possible to do more harm with a rushed treatment than the disease is doing itself

There are several other known antiviral drugs are being tried in China, but I don’t have too much hope for those, either. The neuraminidase inhibitors such as oseltamivir (better known as Tamiflu) were tried against SARS and were ineffective; there is no reason to expect anything versus Covid-19 although these drugs are a component of some drug cocktail trials. The HIV protease therapies such as darunavir and the combination therapy Kaletra are in trials, but that’s also a rather desperate long shot, since there’s no particular reason to think that they will have any such protease inhibition against what this new virus has to offer (and indeed, such agents weren’t much help against SARS in the end, either). The classic interferon/ribavirin combination seems to have had some activity against SARS and MERS, and is in two trials from what I can see. That’s not an awful idea by any means, but it’s not a great one, either: if your viral disease has interferon/ribavirin as a front line therapy, it generally means that there’s nothing really good available. No, unless we get really lucky none of these ideas are going to slow the disease down much.

There are a few other repurposed-protease-inhibitors ideas out there, such as this one. (Edit: I had seen this paper but couldn’t track it down, so thanks to those who sent it along). This paper suggests that the TMPRSS2 protease is important for viral entry on the human-cell-side of the process, a pathway that has been noted for other coronaviruses. And it points out that there is a an approved inhibitor (in Japan) for this enzyme (camostat), so that would definitely seem to be worth a trial, probably in combination with remdesivir.

That’s about it for the existing small molecules, from what I can see. What about new ones? Don’t hold your breath, is all I can say. A drug discovery program from scratch against a new pathogen is, as many readers here well know, not a trivial exercise. As this Bloomberg article details, many such efforts in the past (small molecules and vaccines alike) have come to grief because by the time they had anything to deliver the epidemic itself had passed. Indeed, Gilead’s remdesivir had already been dropped as a potential Ebola therapy.

You will either need to have a target in mind up front or go phenotypic. For the former, what you’d see are better characterizations of the viral protease and more extensive screens against it. Two other big target areas are viral entry (which involves the “spike” proteins on the virus surface and the ACE2 protein on human cells) and viral replication. To the former, it’s worth quickly noting that ACE2 is so much unlike the more familiar ACE protein that none of the cardiovascular ACE inhibitors do anything to it at all. And targeting the latter mechanisms is how remdesivir was developed as a possible Ebola agent, but as you can see, that took time, too. Phenotypic screens are perfectly reasonable against viral pathogens as well, but you’ll need to put time and effort into that assay up front, just as with any phenotypic effort, because as anyone who does that sort of work will tell you, a bad phenotypic screen is a complete waste of everyone’s time.

One of the key steps for either route is identifying an animal model. While animal models of infectious disease can be extremely well translated to human therapy, that doesn’t happen by accident: you need to choose the right animal. Viruses in general (and coronaviruses are no exception) vary widely in their effects in different species, and not just across the gaps of bird/reptile/human and the like. No, you’ll run into things where even the usual set of small mammals are acting differently from each other, with some of them not even getting sick at all. This current virus may well have gone through a couple of other mammalian species before landing on us, but you’ll note that dogs (to pick one) don’t seem to have any problem with it.

All this means that any new-target new-chemical-matter effort against Covid-19 (or any new pathogen) is going to take years, and there is just no way around that. Update: see here for just such an effort to start finding fragment hits for the viral protease. This puts small molecules in a very bimodal distribution: you have the existing drugs that might be repurposed, and are presumably available right now. Nothing else is! At the other end, for completely new therapies you have the usual prospects of drug discovery: years from now, lots of money, low success rate, good luck to all of us. The gap between these two could in theory be filled by vaccines and antibody therapies (if everything goes really, really well) but those are very much their own area and will be dealt with in a separate post.

Either way, the odds are that we (and I mean “we as a species” here) are going to be fighting this epidemic without any particularly amazing pharmacological weapons. Eventually we’ll have some, but I would advise people, pundits, and politicians not to get all excited about the prospects for some new therapies to come riding up over the hill to help us out. The odds of that happening in time to do anything about the current outbreak are very small. We will be going for months, years, with the therapeutic options we have right now. Look around you: what we have today is what we have to work with.