Dataset Information

Identification of potential inhibitors against SARS-CoV-2 by targeting proteins responsible for envelope formation and virion assembly using docking based virtual screening, and pharmacokinetics approaches.

ABSTRACT: WHO has declared the outbreak of COVID-19 as a public health emergency of international concern. The ever-growing new cases have called for an urgent emergency for specific anti-COVID-19 drugs. Three structural proteins (Membrane, Envelope and Nucleocapsid protein) play an essential role in the assembly and formation of the infectious virion particles. Thus, the present study was designed to identify potential drug candidates from the unique collection of 548 anti-viral compounds (natural and synthetic anti-viral), which target SARS-CoV-2 structural proteins. High-end molecular docking analysis was performed to characterize the binding affinity of the selected drugs-the ligand, with the SARS-CoV-2 structural proteins, while high-level Simulation studies analyzed the stability of drug-protein interactions. The present study identified rutin, a bioflavonoid and the antibiotic, doxycycline, as the most potent inhibitor of SARS-CoV-2 envelope protein. Caffeic acid and ferulic acid were found to inhibit SARS-CoV-2 membrane protein while the anti-viral agent's simeprevir and grazoprevir showed a high binding affinity for nucleocapsid protein. All these compounds not only showed excellent pharmacokinetic properties, absorption, metabolism, minimal toxicity and bioavailability but were also remain stabilized at the active site of proteins during the MD simulation. Thus, the identified lead compounds may act as potential molecules for the development of effective drugs against SARS-CoV-2 by inhibiting the envelope formation, virion assembly and viral pathogenesis.

SUBMITTER: Bhowmik D

PROVIDER: S-EPMC7335633 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Identification of potential inhibitors against SARS-CoV-2 by targeting proteins responsible for envelope formation and virion assembly using docking based virtual screening, and pharmacokinetics approaches.

Bhowmik Deep D Nandi Rajat R Jagadeesan Rahul R Kumar Niranjan N Prakash Amresh A Kumar Diwakar D

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 20200705

WHO has declared the outbreak of COVID-19 as a public health emergency of international concern. The ever-growing new cases have called for an urgent emergency for specific anti-COVID-19 drugs. Three structural proteins (Membrane, Envelope and Nucleocapsid protein) play an essential role in the assembly and formation of the infectious virion particles. Thus, the present study was designed to identify potential drug candidates from the unique collection of 548 anti-viral compounds (natural and sy ...[more]

PMID: 32640381

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Project description:The antagonist-bound crystal structure of the nociceptin receptor (NOP), from the opioid receptor family, was recently reported along with those of the other opioid receptors bound to opioid antagonists. We recently reported the first homology model of the 'active-state' of the NOP receptor, which when docked with 'agonist' ligands showed differences in the TM helices and residues, consistent with GPCR activation after agonist binding. In this study, we explored the use of the active-state NOP homology model for structure-based virtual screening to discover NOP ligands containing new chemical scaffolds. Several NOP agonist and antagonist ligands previously reported are based on a common piperidine scaffold. Given the structure-activity relationships for known NOP ligands, we developed a hybrid method that combines a structure-based and ligand-based approach, utilizing the active-state NOP receptor as well as the pharmacophoric features of known NOP ligands, to identify novel NOP binding scaffolds by virtual screening. Multiple conformations of the NOP active site including the flexible second extracellular loop (EL2) loop were generated by simulated annealing and ranked using enrichment factor (EF) analysis and a ligand-decoy dataset containing known NOP agonist ligands. The enrichment factors were further improved by combining shape-based screening of this ligand-decoy dataset and calculation of consensus scores. This combined structure-based and ligand-based EF analysis yielded higher enrichment factors than the individual methods, suggesting the effectiveness of the hybrid approach. Virtual screening of the CNS Permeable subset of the ZINC database was carried out using the above-mentioned hybrid approach in a tiered fashion utilizing a ligand pharmacophore-based filtering step, followed by structure-based virtual screening using the refined NOP active-state models from the enrichment analysis. Determination of the NOP receptor binding affinity of a selected set of top-scoring hits resulted in identification of several compounds with measurable binding affinity at the NOP receptor, one of which had a new chemotype for NOP receptor binding. The hybrid ligand-based and structure-based methodology demonstrates an effective approach for virtual screening that leverages existing SAR and receptor structure information for identifying novel hits for NOP receptor binding. The refined active-state NOP homology models obtained from the enrichment studies can be further used for structure-based optimization of these new chemotypes to obtain potent and selective NOP receptor ligands for therapeutic development.

Project description:Protein conformational change is an important consideration in ligand-docking screens, but it is difficult to predict. A simple way to account for protein flexibility is to soften the criterion for steric fit between ligand and receptor. A more comprehensive but more expensive method would be to sample multiple receptor conformations explicitly. Here, these two approaches are compared. A "soft" scoring function was created by attenuating the repulsive term in the Lennard-Jones potential, allowing for a closer approach between ligand and protein. The standard, "hard" Lennard-Jones potential was used for docking to multiple receptor conformations. The Available Chemicals Directory (ACD) was screened against two cavity sites in the T4 lysozyme. These sites undergo small but significant conformational changes on ligand binding, making them good systems for soft docking. The ACD was also screened against the drug target aldose reductase, which can undergo large conformational changes on ligand binding. We evaluated the ability of the scoring functions to identify known ligands from among the over 200 000 decoy molecules in the database. The soft potential was always better at identifying known ligands than the hard scoring function when only a single receptor conformation was used. Conversely, the soft function was worse at identifying known leads than the hard function when multiple receptor conformations were used. This was true even for the cavity sites and was especially true for aldose reductase. To test the multiple-conformation method predictively, we screened the ACD for molecules that preferentially docked to the expanded conformation of aldose reductase, known to bind larger ligands. Six novel molecules that ranked among the top 0.66% of hits from the multiple-conformation calculation, but ranked relatively poorly in the soft docking calculation, were tested experimentally for enzyme inhibition. Four of these six inhibited the enzyme, the best with an IC(50) of 8 microM. Although ligands can get better scores in soft docking, the same is also true for decoys. The improved ranking of such decoys can come at the expense of true ligands.

Dataset Information

Identification of potential inhibitors against SARS-CoV-2 by targeting proteins responsible for envelope formation and virion assembly using docking based virtual screening, and pharmacokinetics approaches.

Publications

Identification of potential inhibitors against SARS-CoV-2 by targeting proteins responsible for envelope formation and virion assembly using docking based virtual screening, and pharmacokinetics approaches.

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