In late 2019, a novel coronavirus (SARS-CoV-2) was identified from Wuhan, China, and in the following months, the virus quickly spread around the world. With the unprecedented global crisis that quickly ensued and the biomedical, societal, and economic impact that soon followed, researchers are quickly developing vaccines and treatments to tackle this healthcare crisis. This collaborative effort of researchers from different backgrounds for the sharing of data and perspectives to shed light on cross-disciplinary approaches to this problem.
Here at ASDRP, the COVID-19 Task Force is a consortium of research advisors and groups from a broad range of disciplines - biochemistry, data science, organic chemistry, molecular biology, and more. The consortium's main goal is to generate high-level discussions between interdisciplinary groups to collectively formulate new solutions, spanning biology, chemistry, and computer science. With advisors utilizing their different areas of expertise, students will find this experience to be both informative and meaningful, giving them a chance to be a part of a team that is dedicated to making an immediate change.
Sponsored projects at ASDRP include efforts in de novo drug design, computational modeling and high-throughput screening of compounds as potential therapeutics against SARS-CoV-2; devlopment of siRNA gene silencing technologies to suppress viral replication; and utilization of data science and machine learning to perform analysis of the impact of the novel coronavirus on science and on society. Our researchers will be exposed to varying perspectives in our cohort meetings and will utilize these different viewpoints in pioneering cutting-edge research on the novel coronavirus. A collaboration of research advisors are collectively using virtual screening means and molecular biology tools to identify and develop biologics such as siRNA therapies as well as antiretroviral drug repurposing in efforts of accelerating preclinical drug discovery against SARS-CoV2. *Since ASDRP operates at a Biosafety Level 1, no live/viable SARS-CoV-2 specimens will be handled in our laboratory.
Current Areas of Current COVID-19 Research
Sentiment Analysis of COVID-19 Social Media Responses
Field: Data Science, Machine Learning
Today’s media places a large on social media reactions to news events. However, there is little
study on how accurate these reactions are to the reality, rather than to the same media stories about it. This study aims to try to see how accurately Tweets about COVID-19 reflect the reality of the situation. Since COVID-19 is a global crisis that spreads across geographic regions at different rates, it is a unique opportunity to study this type of behavior. Social media responses (such as tweets) can be classified as COVID-19 relevant or not. Correlating this against data on the spread of the disease, or against geographical increase in quarantine procedures, give insight into how social media responds to the effects of the virus.
High-throughput virtual screening of targeted compound libraries towards identification of ligands to key SARS-CoV-2 viral proteins
Field: Molecular Biology / Biochemistry
Drug repurposing has the potential to expedite the discovery process by using commercially available compounds. Based on previous studies, we selected emodin, remdesivir, and hydroxychloroquine as candidates for our search. SARS-CoV-2 infects cells by using Angiotensin-Converting Enzyme 2 (ACE-2) as an entry receptor; emodin and hydroxychloroquine were suggested to be inhibitors of this interaction. Remdesivir acts as a ribonucleoside analog and interferes with the viral RNA polymerase of SARS-CoV-2. So far, we have discovered multiple ligands for each compound that had a higher binding affinity than their original candidates.
Development of a Machine Learning Platform towards Antiviral Therapy Discovery
Field: Machine Learning, Biochemistry
Downing & Njoo
This project is jointly handled by computer science and biochemistry research students. We are working on a machine learning platform for rapid screening of libraries of chemical entities that have the potential of serving as inhibitors of the interaction between the coronavirus spike glycoprotein and the human Angiotensin-Converting Enzyme 2 (ACE2), which is the putative means of entry of SARS-CoV-2 into cells. Moreover, we are currently working towards building in methods for qualifying libraries of chemical entities in highly simplified molecular descriptors, which we envision will be greatly enabling in the efficiency by which compounds can be screened. This will eventually inform the future development of small molecule therapies.
De novo design and high throughput virtual screening of peptidomimetic covalent inhibitors of the SARS-CoV-2 main protease
Field: Medicinal Chemistry
Investigator: Njoo & Brah
Electron-deficient Michael acceptors have been previously reported in application to irreversible, covalent inhibition of cysteine proteases. Here, we report a highly charge-dependent structure-activity relationship (SAR) of dehydroalanine-peptoid-based covalent inhibitors of the SARS-CoV-2 main protease, which is responsible for production of viral components, and we are close to completion of the SAR generated from an initial screen of 384 compounds, all of which can be chemically synthesized in < 10 steps. The initial SAR reported by our June preprint will serve as the basis for structure-informed and reactivity-guided design of next-generation protease inhibitors.
Projection of Geographic Distribution of COVID-19 Infections
Field: Data Science, Computer Science
Here, we use public data sources and computer modeling to build models that give projections for COVID-19 infection rates in certain geographic locations. We will extend to other geographies or dig deeper to see what kind of policies at the county or city level seem to be affecting the decline the most. This work will be carried out with a combination of approaches in data science and computer science.
Identification of polynucleotide sequences for potential application in ddRNAi (DNA-directed RNA interference) gene-silencing approaches for Sars-CoV2 infected cells
Field: Molecular Biology
ddRNAi, or DNA-directed RNA interference, is a gene-silencing method that uses DNA constructs to hijack the pre-existing animal cell’s RNA interference pathways. Here, we developed an RNA fragment that may silence a gene in the SARS-CoV-2 genome, which inhibits viral replication, thereby inhibiting the virus’ spread. We designed a novel ddRNAi strand that inhibits gene expression in SARS-CoV-2 infected cells. Our designed siRNA strand does not share any complete similarities with the known human genome and corresponds to the SARS-CoV-2 virus genome at 9841-9859 bp.
COVID-19 Consortium Investigators
Data Science & Machine Learning
Data Science & Machine Learning
Molecular & Cell Biology
Computer Science & Data Science
Structural Biology & Biochemistry
Molecular & Cell Biology
Organic Chemistry & Chemical Biology
Data Science & Machine Learning
COVID-19 Research at ASDRP
November 20, 2020
The Njoo group becomes the first high school research group to publish a peer-reviewed paper on COVID-19 drug discovery, targeting the main protease using in silico biophysical modeling methods. Article online here: https://doi.org/10.47611/jsrhs.v9i2.1082
August 23, 2020
At the Summer 2020 symposium, researchers from the Guo group (psychology), Brah group (biophysics), Gandhi group (biochemistry), Subramaniam group (data science), Mui group (machine learning) and McMahan group (computer science) present original research on COVID-19 and its impacts on science and society.
June 15, 2020
The Suresh group reports the design and identification of a ddRNAi (RNA interference) strategy for potentlally treating COVID-infected cells, which aims to suppress expression of key viral proteins in vivo. [Preprint]
June 9, 2020
Researchers from the Njoo group submitted a manuscript of ASDRP's first COVID-19 research article to a journal in the design and high-throughput virtual screening of inhibitors of the SARS-CoV-2 main protease. [Preprint]
June 2, 2020
Student researchers from four of our academic year research groups (Suresh, Downing, Le, and Njoo) were featured on the front page of the Tri-City Voice newspaper this week for their work on computational development of novel molecular strategies towards inhibition of the growth cycle of SARS-CoV-2. [Full Article]
May 14, 2020
Today, the four joint investigators and over forty student researchers published online the first press release describing current research efforts at ASDRP towards development of novel drugs and molecular strategies in treating COVID-19. [Full Press Release]
March 2, 2020
A collection of our student researchers embark today on a computational drug discovery campaign in identification of compounds that may inhibit the viral replication cycle of SARS-CoV-2.