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

2021 ◽  
Author(s):  
Marzieh Omrani ◽  
Mohammad Bayati ◽  
Parvaneh Mehrbod ◽  
Kamal Asmari Bardazard ◽  
Samad Nejad-Ebrahimi

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.

2020 ◽  
Author(s):  
Marzieh omrani ◽  
Mohammad Bayati ◽  
Parvaneh Mehrbod ◽  
Samad Nejad-Ebrahimi

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.


2020 ◽  
Vol 15 (9) ◽  
pp. 1934578X2095326
Author(s):  
Jai-Sing Yang ◽  
Jo-Hua Chiang ◽  
Shih‑Chang Tsai ◽  
Yuan-Man Hsu ◽  
Da-Tian Bau ◽  
...  

The coronavirus disease 2019 (COVID‐19) outbreak caused by the 2019 novel coronavirus (2019-nCOV) is becoming increasingly serious. In March 2019, the Food and Drug Administration (FDA) designated remdesivir for compassionate use to treat COVID-19. Thus, the development of novel antiviral agents, antibodies, and vaccines against COVID-19 is an urgent research subject. Many laboratories and research organizations are actively investing in the development of new compounds for COVID-19. Through in silico high-throughput virtual screening, we have recently identified compounds from the compound library of Natural Products Research Laboratories (NPRL) that can bind to COVID-19 3Lpro polyprotein and block COVID-19 3Lpro activity through in silico high-throughput virtual screening. Curcuminoid derivatives (including NPRL334, NPRL339, NPRL342, NPRL346, NPRL407, NPRL415, NPRL420, NPRL472, and NPRL473) display strong binding affinity to COVID-19 3Lpro polyprotein. The binding site of curcuminoid derivatives to COVID-19 3Lpro polyprotein is the same as that of the FDA-approved human immunodeficiency virus protease inhibitor (lopinavir) to COVID-19 3Lpro polyprotein. The binding affinity of curcuminoid derivatives to COVID-19 3Lpro is stronger than that of lopinavir and curcumin. Among curcuminoid derivatives, NPRL-334 revealed the strongest binding affinity to COVID-19 3Lpro polyprotein and is speculated to have an anti-COVID-19 effect. In vitro and in vivo ongoing experiments are currently underway to confirm the present findings. This study sheds light on the drug design for COVID-19 3Lpro polyprotein. Basing on lead compound development, we provide new insights on inhibiting COVID-19 attachment to cells, reducing COVID-19 infection rate and drug side effects, and increasing therapeutic success rate.


Pharmaceutics ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 59
Author(s):  
Muthu Kumar Thirunavukkarasu ◽  
Utid Suriya ◽  
Thanyada Rungrotmongkol ◽  
Ramanathan Karuppasamy

The RAS–RAF–MEK–ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector. Even though MEK inhibitors are under investigation in many cancers, drug resistance continues to be the principal limiting factor to achieving cures in patients with cancer. Hence, we accomplished a high-throughput virtual screening to overcome this bottleneck by the discovery of dual-targeting therapy in cancer treatment. Here, a total of 11,808 DrugBank molecules were assessed through high-throughput virtual screening for their activity against MEK. Further, the Glide docking, MLSF and prime-MM/GBSA methods were implemented to extract the potential lead compounds from the database. Two compounds, DB012661 and DB07642, were outperformed in all the screening analyses. Further, the study results reveal that the lead compounds also have a significant binding capability with the co-target PIM1. Finally, the SIE-based free energy calculation reveals that the binding of compounds was majorly affected by the van der Waals interactions with MEK receptor. Overall, the in silico binding efficacy of these lead compounds against both MEK and PIM1 could be of significant therapeutic interest to overcome drug resistance in the near future.


2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Stephanie Sun ◽  
Kavya Anand ◽  
Ishani Ashok ◽  
Bhavesh Ashok ◽  
Ayush Bajaj ◽  
...  

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.   


2021 ◽  
Author(s):  
Austin Clyde ◽  
Stephanie Galanie ◽  
Daniel W. Kneller ◽  
Heng Ma ◽  
Yadu Babuji ◽  
...  

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.


2021 ◽  
Vol 9 (9) ◽  
pp. 3324-3333 ◽  
Author(s):  
Ke Zhao ◽  
Ömer H. Omar ◽  
Tahereh Nematiaram ◽  
Daniele Padula ◽  
Alessandro Troisi

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.


2021 ◽  
Author(s):  
Sumit Kumar ◽  
Yash Gupta ◽  
Samantha Zak ◽  
Charu Upadhyay ◽  
Neha Sharma ◽  
...  

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...


Author(s):  
Siwei Song ◽  
Fang Chen ◽  
Yi Wang ◽  
Kangcai Wang ◽  
Mi Yan ◽  
...  

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...


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