An Integrated Computational and Experimental Approach to Identifying Inhibitors for SARS-CoV-2 3CL Protease

The newly evolved SARS-CoV-2 has caused the COVID-19 pandemic, and the SARS-CoV-2 main protease 3CLpro is essential for the rapid replication of the virus. Inhibiting this protease may open an alternative avenue toward therapeutic intervention. In this work, a computational docking approach was developed to identify potential small-molecule inhibitors for SARS-CoV-2 3CLpro. Totally 288 potential hits were identified from a half-million bioactive chemicals via a protein-ligand docking protocol. To further evaluate the docking results, a quantitative structure activity relationship (QSAR) model of 3CLpro inhibitors was developed based on existing small molecule inhibitors of the 3CLproSARS– CoV– 1 and their corresponding IC50 data. The QSAR model assesses the physicochemical properties of identified compounds and estimates their inhibitory effects on 3CLproSARS– CoV– 2. Seventy-one potential inhibitors of 3CLpro were selected through these computational approaches and further evaluated via an enzyme activity assay. The results show that two chemicals, i.e., 5-((1-([1,1′-biphenyl]-4-yl)-2,5-dimethyl-1H-pyrrol-3-yl)methylene)pyrimidine-2,4,6(1H,3H,5H)-trione and N-(4-((3-(4-chlorophenylsulfonamido)quinoxalin-2-yl)amino)phenyl)acetamide, effectively inhibited 3CLpro SARS-CoV-2 with IC50’s of 19 ± 3 μM and 38 ± 3 μM, respectively. The compounds contain two basic structures, pyrimidinetrione and quinoxaline, which were newly found in 3CLpro inhibitor structures and are of high interest for lead optimization. The findings from this work, such as 3CLpro inhibitor candidates and the QSAR model, will be helpful to accelerate the discovery of inhibitors for related coronaviruses that may carry proteases with similar structures to SARS-CoV-2 3CLpro

Use of Structure-And Ligand-Based Drug Design Tools for the Discovery of Small Molecule Inhibitors of Cysteine Proteases for the Treatment of Malaria and Sars Infection

A wide array of molecular modeling tools were utilized to design and develop inhibitors against cysteine protease of P. Falciparum Malaria and Severe Acute Respiratory Syndrome (SARS). A number of potent inhibitors were developed against cysteine protease and hemoglobinase of P. falciparum , referred as Falcipains (FPs), by the structure-based virtual screening of the focused libraries enriched in soft-electrophiles containing compounds. Twenty one diverse, non-peptidic, low micromolar hits were identified. A combined data mining and combinatorial library synthesis approach was performed to discover analogs of virtual screening hits and establish the structure-activity relationships (SAR). However, the resulting SAR of the identified hits was unusually steep in some cases and could not be explained by a traditional analysis of the interactions (electrostatics, van der Waals or H-bond). To gain insights, a statistical thermodynamic analysis of explicit solvent in the ligand binding domain of FP-2 and FP-3 was performed that explained some of the complex trends in the SAR. Furthermore, the moderate potency of a subset of FP-2 hits was elucidated using quantum mechanics calculations that shoreduced reactivity of the electrophilic center of these hits. In addition, solvent thermodynamics and reactivity analysis also helped to elucidate the complex trends in SAR of peptidomimetic inhibitors of FP-2 and FP-3 synthesized in our laboratory. Multi nanosecond explicit solvent molecular dynamics simulations were carried out using the docking poses of the known inhibitors in the binding site of SARS-3CLpro, a cysteine protease important for replication of SARS virus, to study the overall stability of the binding site interactions as well as identify important changes in the interaction profile that were not apparent from the docking study. Analysis of the simulation studies led to the identification of certain protein-ligand interaction patterns which would be useful in further structure based design efforts against cysteine protease (3CLpro) of SARS

Massively-Parallel Computational Identification of Novel Broad Spectrum Antivirals to Combat Coronavirus Infection

Philosophiae Doctor - PhDGiven the significant disease burden caused by human coronaviruses, the discovery of an effective antiviral strategy is paramount, however there is still no effective therapy to combat infection. This thesis details the in silica exploration of ligand libraries to identify candidate lead compounds that, based on multiple criteria, have a high probability of inhibiting the 3 chymotrypsin-like protease (3CUro) of human coronaviruses. Atomistic models of the 3CUro were obtained from the Protein Data Bank or theoretical models were successfully generated by homology modelling. These structures served the basis of both structure- and ligand-based drug design studies. Consensus molecular docking and pharmacophore modelling protocols were adapted to explore the ZINC Drugs-Now dataset in a high throughput virtual screening strategy to identify ligands which computationally bound to the active site of the 3CUro . Molecular dynamics was further utilized to confirm the binding mode and interactions observed in the static structure- and ligand-based techniques were correct via analysis of various parameters in a IOns simulation. Molecular docking and pharmacophore models identified a total of 19 ligands which displayed the potential to computationally bind to all 3CUro included in the study. Strategies employed to identify these lead compounds also indicated that a known inhibitor of the SARS-Co V 3CUro also has potential as a broad spectrum lead compound. Further analysis by molecular dynamic simulations largely confirmed the binding mode and ligand orientations identified by the former techniques. The comprehensive approach used in this study improves the probability of identifying experimental actives and represents a cost effective pipeline for the often expensive and time consuming process of lead discovery. These identified lead compounds represent an ideal starting point for assays to confirm in vitro activity, where experimentally confirmed actives will be proceeded to subsequent studies on lead optimization

3C-like protease inhibitors against coronaviruses

Master of Science in Biomedical SciencesDepartment of Diagnostic Medicine/PathobiologyYunjeong KimCoronaviruses are pathogens that cause diverse diseases in humans and animals. The studies in this dissertation are focused on feline coronavirus (FCoV), ferret coronavirus (FRCoV) and mink coronavirus (MCoV). FCoV and FRCoV infections typically cause enteritis in cats and ferrets, respectively. However, a 100% fatal systemic disease called feline infectious peritonitis (FIP) can develop in some FCoV infected cats and a fatal systemic disease resembling FIP can develop in some FRCoV infected ferrets. MCoV causes enteritis which results in significant economic loss to mink farmers. No effective vaccine or treatment is available despite the increasing importance of these viral diseases. We have previously reported the synthesis of inhibitors against 3C-like protease (3CLpro) of FCoV and demonstrated the antiviral efficacy of a 3CLpro inhibitor for treating FIP. FRCoV and MCoV 3CLpro are closely related to FCoV 3CLpro. Therefore, we investigated the structure-function relationships of our 3CLpro inhibitors to identify the struc-tural requirements of inhibitors for FRCoV and MCoV. This is the first report of antiviral com-pounds against FRCoV and MCoV. We have previously conducted a field trial with a potent 3CLpro inhibitor, GC376, in cats with naturally occurring FIP. Comparison of the FCoV 3CLpro amino acid sequences from the pre- and post-treatment samples in one cat showed amino acid changes in 3CLpro. Hence, we generated recombinant 3CLpros carrying the amino acid changes and characterized the effects of these amino acid changes in FCoV 3CLpro on its susceptibility to GC376. We observed that these amino acid changes did not markedly affect the activity of GC376 in fluorescence resonance energy transfer (FRET) assay, explaining the absence of clinical drug resistance in this cat during the field trial

Bioinformatics in China: A Personal Perspective

Biochemical Research MethodsMathematical & Computational BiologySCI(E)PubMed3EDITORIAL MATERIAL4e1000020

A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.

The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale in silico screening platform, VirtualFlow, to search for inhibitors that target SARS-CoV-2. In this unprecedented structure-based virtual campaign, we screened roughly 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets. In addition to targeting the active sites of viral enzymes, we also targeted critical auxiliary sites such as functionally important protein-protein interactions