High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor

Abstract Background: The novel coronavirus (2019-nCoV) causes a severe respiratory illness that was unknown in the human before. Its alarmingly quick transmission to many countries across the world resulted in a worldwide health emergency. It has caused a notable percentage of morbidity and mortality. Therefore, an imminent need for drugs to combat this disease has been increased. Global collaborative efforts from scientists are underway to find a therapy to treat infections and reduce death cases. Herbal medicines and purified natural products have been reported to have antiviral activity against Coronaviruses (CoVs).Methods: In this study, a High Throughput Virtual Screening (HTVS) protocol was used as a fast method on the discovery of novel drug candidates as the COVID-19 main protease inhibitors. Over 180,000 natural product-based compounds were obtained from the ZINC database and virtually screened against the COVID-19 main protease. In this study, the Glide docking program was applied for high throughput virtual screening. Extra precision (XP) and in a combination of Prime module, induced-fit docking (IFD) approach was also used. Additionally, the ADME properties of all compounds were analyzed, and the final selection was carried out based on the Lipinski rule of five. Results: The nineteen compounds were selected and introduced as new potential inhibitors. The compound ZINC08765174 (1-[3-(1H-indol-3-yl) propanoyl]-N-(4-phenylbutan-2-yl)piperidine-3-carboxamide) showed a strong binding affinity (-11.5 kcal/mol) to the crucial residues of COVID-19 main protease comparing to peramivir (-9.8 kcal/mol) as a positive control.Conclusions: The excellent ADME properties proposed the opportunity of this compound to be a promising candidate for the treatment of COVID-19.

Download Full-text

Natural products as inhibitors of COVID-19 main protease–A virtual screening by molecular docking

Pharmaceutical Sciences ◽

10.34172/ps.2021.11 ◽

2021 ◽

Author(s):

Marzieh Omrani ◽

Mohammad Bayati ◽

Parvaneh Mehrbod ◽

Kamal Asmari Bardazard ◽

Samad Nejad-Ebrahimi

Keyword(s):

Natural Products ◽

Virtual Screening ◽

High Throughput ◽

Herbal Medicines ◽

Respiratory Illness ◽

Fast Method ◽

Main Protease ◽

Glide Docking ◽

Adme Properties ◽

High Throughput Virtual Screening

Background: The novel coronavirus (2019-nCoV) causes a severe respiratory illness unknown to a human before. Its alarmingly quick transmission to many countries across the world has resulted in a global health emergency. Therefore, an imminent need for drugs to combat this disease has been increased. Worldwide collaborative efforts from scientists are underway to determine a therapy to treat COVID-19 infections and reduce mortality rates. Since herbal medicines and purified natural products have been reported to have antiviral activity against Coronaviruses (CoVs), this in silico evaluation was performed for identifying potential natural compounds with promising inhibitory activities against COVID-19. Methods: In this study, a High Throughput Virtual Screening (HTVS) protocol was used as a fast method for discovering novel drug candidates as potential COVID-19 main protease (Mpro) inhibitors. Over 180,000 natural product-based compounds were obtained from the ZINC database and virtually screened against the COVID-19 Mpro. In this study, the Glide docking program was applied for high throughput virtual screening. Also, Extra precision (XP) has been used following the induced-fit docking (IFD) approach. The ADME properties of all compounds were analyzed and a final selection was made based on the Lipinski rule of five. Also, molecular dynamics (MD) simulations were conducted for a virtual complex of the best scoring compound with COVID-19 protease. Results: Nineteen compounds were introduced as new potential inhibitors. Compound ZINC08765174 (1-[3-(1H-indol-3-yl) propanoyl]-N-(4-phenylbutan-2-yl)piperidine-3-carboxamide showed a strong binding affinity (-11.5 kcal/mol) to the COVID-19 Mpro comparing to peramivir (-9.8 kcal/mol) as a positive control. Conclusions: Based on these findings, nineteen compounds were proposed as possible new COVID-19 inhibitors, of which ZINC08765174 had a high affinity to Mpro. Furthermore, the promising ADME properties of the selected compounds emphasize their potential as attractive candidates for the treatments of COVID-19.

Download Full-text

Reactivity-guided de novo molecular design and high throughput virtual screening of a targeted library of peptidomimetic compounds reveals charge-based structure-activity relationship of potential covalent inhibitors of the main protease of SARS-CoV-2

Journal of Student Research ◽

10.47611/jsrhs.v9i2.1082 ◽

2020 ◽

Vol 9 (2) ◽

Author(s):

Stephanie Sun ◽

Kavya Anand ◽

Ishani Ashok ◽

Bhavesh Ashok ◽

Ayush Bajaj ◽

...

Keyword(s):

Virtual Screening ◽

Small Molecules ◽

High Throughput ◽

Active Site ◽

De Novo ◽

Cysteine Residue ◽

Host Cells ◽

Main Protease ◽

Covalent Inhibitors ◽

High Throughput Virtual Screening

In December of 2019, a novel coronavirus was first identified in Wuhan, China, and has since spread around the world, leaving a largely unsolved biomedical problem in its wake. Upon entry into host cells, the main protease is essential for the replication of viral RNA, which is what allows the virus to replicate inside humans. Inhibition of the main protease has been investigated as a potential strategy for inhibition of the viral replication cycle. Here, we designed a combinatorial library of small molecules and performed high-throughput virtual screening to identify a series of hit compounds that may serve as potential inhibitors of the main protease. In our design of covalent inhibitors of the coronavirus protease, we modeled a library of 361 peptidomimetic Michael acceptor small molecules, which are designed to engage the nucleophilic cysteine residue in the active site of the protease in an irreversible 1,4-conjugate addition. We then employed a variety of computational tools to determine the binding affinity of our designed compounds when bound to the protease active site, where we determined that cationic side chains are potentially beneficial for inhibition of SARS-CoV-2.

Download Full-text

High Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Non-Covalent Inhibitor

10.1101/2021.03.27.437323 ◽

2021 ◽

Author(s):

Austin Clyde ◽

Stephanie Galanie ◽

Daniel W. Kneller ◽

Heng Ma ◽

Yadu Babuji ◽

...

Keyword(s):

Virtual Screening ◽

Binding Site ◽

High Throughput ◽

Hydrophobic Interactions ◽

Md Simulations ◽

X Ray ◽

X Ray Crystallography ◽

Biochemical Assays ◽

Main Protease ◽

High Throughput Virtual Screening

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel non-covalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (Mpro) by employing a scalable high throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this Mpro inhibitor with an inhibition constant (Ki) of 2.9 µM [95% CI 2.2, 4.0]. Further, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of Mpro forming stable hydrogen bond and hydrophobic interactions. We then used multiple µs-timescale molecular dynamics (MD) simulations, and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by Mpro, involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits Mpro and offers a springboard for further therapeutic design. Significance Statement The ongoing novel coronavirus pandemic (COVID-19) has prompted a global race towards finding effective therapeutics that can target the various viral proteins. Despite many virtual screening campaigns in development, the discovery of validated inhibitors for SARS-CoV-2 protein targets has been limited. We discover a novel inhibitor against the SARS-CoV-2 main protease. Our integrated platform applies downstream biochemical assays, X-ray crystallography, and atomistic simulations to obtain a comprehensive characterization of its inhibitory mechanism. Inhibiting Mpro can lead to significant biomedical advances in targeting SARS-CoV-2 treatment, as it plays a crucial role in viral replication.

Download Full-text

In silico drug designing for COVID-19: an approach of high-throughput virtual screening, molecular, and essential dynamics simulations

Journal of Biomolecular Structure and Dynamics ◽

10.1080/07391102.2021.1897681 ◽

2021 ◽

pp. 1-15

Author(s):

Rakesh Kumar ◽

Rahul Kumar ◽

Pranay Tanwar

Keyword(s):

Virtual Screening ◽

High Throughput ◽

In Silico ◽

Essential Dynamics ◽

Drug Designing ◽

Dynamics Simulations ◽

High Throughput Virtual Screening

Download Full-text

Novel thermally activated delayed fluorescence materials by high-throughput virtual screening: going beyond donor–acceptor design

Journal of Materials Chemistry C ◽

10.1039/d1tc00002k ◽

2021 ◽

Vol 9 (9) ◽

pp. 3324-3333 ◽

Cited By ~ 1

Author(s):

Ke Zhao ◽

Ömer H. Omar ◽

Tahereh Nematiaram ◽

Daniele Padula ◽

Alessandro Troisi

Keyword(s):

Virtual Screening ◽

Quantum Chemistry ◽

High Throughput ◽

Delayed Fluorescence ◽

Thermally Activated Delayed Fluorescence ◽

Thermally Activated ◽

Quantum Chemistry Calculations ◽

Donor Acceptor ◽

Molecular Semiconductors ◽

High Throughput Virtual Screening

125 potential TADF candidates are identified through quantum chemistry calculations of 700 molecules derived from a database of 40 000 molecular semiconductors. Most of them are new and some do not belong to the class of donor–acceptor molecules.

Download Full-text

A novel compound active against SARS-CoV-2 targeting Uridylate-specific endoribonuclease (NendoU/NSP15): In silico and in vitro investigations

RSC Medicinal Chemistry ◽

10.1039/d1md00202c ◽

2021 ◽

Author(s):

Sumit Kumar ◽

Yash Gupta ◽

Samantha Zak ◽

Charu Upadhyay ◽

Neha Sharma ◽

...

Keyword(s):

Virtual Screening ◽

High Throughput ◽

In Silico ◽

Specific Enzyme ◽

Cyclic Phosphates ◽

High Throughput Virtual Screening

NendoU (NSP15) is an Mn(2+)-dependent, uridylate-specific enzyme, which leaves 2'-3'-cyclic phosphates 5' to the cleaved bond. Our in-house library was subjected to high throughput virtual screening (HTVS) to identify compounds...

Download Full-text

Accelerating the discovery of energetic melt-castable materials by a high-throughput virtual screening and experimental approach

Journal of Materials Chemistry A ◽

10.1039/d1ta04441a ◽

2021 ◽

Author(s):

Siwei Song ◽

Fang Chen ◽

Yi Wang ◽

Kangcai Wang ◽

Mi Yan ◽

...

Keyword(s):

Machine Learning ◽

Virtual Screening ◽

High Throughput ◽

Experimental Approach ◽

Chemical Data ◽

Research Paradigm ◽

New Materials ◽

High Throughput Virtual Screening

With the growth of chemical data, computation power and algorithms, machine learning-assisted high-throughput virtual screening (ML-assisted HTVS) is revolutionizing the research paradigm of new materials. Herein, a combined ML-assisted HTVS...

Download Full-text