Fragment‐based <i>in silico</i> design of SARS‐CoV‐2 main protease inhibitors

Ahmad, Sarfraz; Mirza, Muhammad Usman; Kee, Lee Yean; Nazir, Mamoona; Rahman, Noorsaadah Abdul; Trant, John F.; Abdullah, Iskandar

doi:10.1111/cbdd.13914

Cited by 13 publications

(7 citation statements)

References 61 publications

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“…AMBER18 was used to perform MD simulations of the docked solutions [115]. The same MD simulation protocol was adopted in the current study as described in previous studies [22,94,[126][127][128]. The Antechamber package of AmberTools was employed to generate the general AMBER force field (GAFF) parameters for the studied ligands using AM1-BCC charge definitions.…”

Section: Simulationsmentioning

confidence: 99%

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Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

et al. 2022

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Rift valley fever virus (RVFV) is the causative agent of a viral zoonosis that causes a significant clinical burden in domestic and wild ruminants. Major outbreaks of the virus occur in livestock, and contaminated animal products or arthropod vectors can transmit the virus to humans. The viral RNA-dependent RNA polymerase (RdRp; L protein) of the RVFV is responsible for viral replication and is thus an appealing drug target because no effective and specific vaccine against this virus is available. The current study reported the structural elucidation of the RVFV-L protein by in-depth homology modeling since no crystal structure is available yet. The inhibitory binding modes of known potent L protein inhibitors were analyzed. Based on the results, further molecular docking-based virtual screening of Selleckchem Nucleoside Analogue Library (156 compounds) was performed to find potential new inhibitors against the RVFV L protein. ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity analysis of these compounds was also performed. Besides, the binding mechanism and stability of identified compounds were confirmed by a 50 ns molecular dynamic (MD) simulation followed by MM/PBSA binding free energy calculations. Homology modeling determined a stable multi-domain structure of L protein. An analysis of known L protein inhibitors, including Monensin, Mycophenolic acid, and Ribavirin, provide insights into the binding mechanism and reveals key residues of the L protein binding pocket. The screening results revealed that the top three compounds, A-317491, Khasianine, and VER155008, exhibited a high affinity at the L protein binding pocket. ADME analysis revealed good pharmacodynamics and pharmacokinetic profiles of these compounds. Furthermore, MD simulation and binding free energy analysis endorsed the binding stability of potential compounds with L protein. In a nutshell, the present study determined potential compounds that may aid in the rational design of novel inhibitors of the RVFV L protein as anti-RVFV drugs.

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Section: Simulationsmentioning

confidence: 99%

“…The rational drug design process is greatly accelerated by using different computeraided drug designing applications for in silico drug screening [20][21][22][23][24][25][26][27]. A virtual screeningbased drug discovery strategy has been identified as one of the most effective ways to discover and develop new drugs [28].…”

Section: Introductionmentioning

confidence: 99%

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

et al. 2022

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“…The active site of Mpro consists of a catalytic dyad of Cys145 and His41. Other anchoring residues important in ligand interactions in cocrystallized structures include Thr25, Thr26, Asn142, Gly143, Ser144, Met165, Glu166, and Gln189 [26].…”

Section: Introductionmentioning

confidence: 99%

Dock-able linear and homodetic di, tri, tetra and pentapeptide library from canonical amino acids: SARS-CoV-2 Mpro as a case study

Ahmad

Mirza

Trant

2023

Preprint

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Peptide-based therapeutics are increasingly coming to the forefront of biomedicine with their promise of high specificity and low toxicity. Although noncanonical residues can always be used, employing only the natural 20 residues restricts the chemical space to a finite dimension allowing for comprehensive in silico screening. Towards this goal, the dataset comprising all possible di, tri, and tetrapeptide combinations of the canonical residues has been previously reported. However, with increasing computational power, the comprehensive set of pentapeptides are now also feasible for screening as are the comprehensive set of cyclic peptides comprising four or five residues. Here, we provide both the complete and prefiltered libraries of all di, tri, tetra, and pentapeptide sequences from 20 canonical amino acids and their homodetic (N-to-C-terminal) cyclic homologues. The libraries in the FASTA, SMILES, and SDF-3D formats can be readily used for screening against protein targets. Access to this dataset will accelerate small peptide screening workflows and encourage their use in drug discovery campaigns. As a case study, the developed library was screened against SARS-CoV-2 Mpro to identify potential small peptide inhibitors.

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“…In FBDD method, a group of low molecular weight polar fragments/compounds is screened against a specific target [ 17 ]. Usually, the screening methods are biophysical methods including X-ray crystallography, nuclear magnetic resonance, differential scanning fluorimetry, isothermal titration calorimetry, and surface plasmon resonance [ 18 ]. One of the critical factors favoring the FBDD’s success is the smaller size of the fragment-like compound compared to the size of the drug-like compounds.…”

Section: Introductionmentioning

confidence: 99%

Fragment-based design of SARS-CoV-2 Mpro inhibitors

2022

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The SARS-CoV-2 virus has been identified as a causative agent for COVID-19 pandemic. About more than 6.3 million fatalities have been attributed to COVID-19 worldwide to date. Finding a viable cure for the illness is urgently needed in light of the present pandemic. The prominence of main protease in the life cycle of virus shapes the main protease as a viable target for design and development of antiviral agents to combat COVID-19. The current study presents the fragment linking strategy to design the novel Mpro inhibitors for COVID-19. A total of 293,451 fragments from diversified libraries have been screened for their binding affinity towards Mpro enzyme. The best 1600 fragment hits were subjected to fragment joining to achieve 100 new molecules using Schrödinger software. The resulting molecules were further screened for their Mpro binding affinity, ADMET, and drug-likeness features. The best 13 molecules were selected, and the first 6 compounds were investigated for their ligand-receptor complex stability through a molecular dynamics study using GROMACS software. The resulting molecules have the potential to be further evaluated for COVID-19 drug discovery.

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Fragment‐based in silico design of SARS‐CoV‐2 main protease inhibitors

Cited by 13 publications

References 61 publications

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

Dock-able linear and homodetic di, tri, tetra and pentapeptide library from canonical amino acids: SARS-CoV-2 Mpro as a case study

Fragment-based design of SARS-CoV-2 Mpro inhibitors

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