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Standardization of virtual-screening and post-processing protocols relevant to in-silico drug discovery.

ABSTRACT: Structure-based drug discovery has emerged as a powerful tool in computational drug discovery and has gained rapid acceleration due to the development of better algorithms for high-end computation in an affordable time. Molecular docking and virtual screening methods are routinely used for the purpose but computing the ligand binding energies with inbuilt scoring functions accurately is still a limitation. Although, MMPBSA and MMGBSA are routinely employed tools for achieving accurate binding free energies, they are applied on well-equilibrated explicitly solvated systems and are computationally expensive and time-consuming. This study compares different post-processing protocols performed on an in-silico screened benchmarked P. falciparum Dihydrofolate reductase (PfDHFR) dataset with AutoDockVina. The docked and implicitly solvated complexes were subjected to (1) rescoring, (2) energy minimization and (3) Binding Estimation After Refinement (BEAR) algorithm. Subsequently, binding free energies were computed using three different tools-MMPBSA, MMGBSA and "g_mmpbsa". Surprisingly, rescoring alone displays lower accuracy than the inherent scoring function of the AutoDockVina. However, encouraging results were seen after post-processing with the other two protocols. The results suggest that MMPBSA applied on energy minimized conformations is able to achieve 42-fold reductions in computational time as opposed to the BEAR algorithm with comparable accuracy.

SUBMITTER: Gupta S

PROVIDER: S-EPMC6269327 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Standardization of virtual-screening and post-processing protocols relevant to in-silico drug discovery.

Gupta Sunita S Lynn Andrew M AM Gupta Vibha V

3 Biotech 20181130 12

Structure-based drug discovery has emerged as a powerful tool in computational drug discovery and has gained rapid acceleration due to the development of better algorithms for high-end computation in an affordable time. Molecular docking and virtual screening methods are routinely used for the purpose but computing the ligand binding energies with inbuilt scoring functions accurately is still a limitation. Although, MMPBSA and MMGBSA are routinely employed tools for achieving accurate binding fr ...[more]

PMID: 30555765

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Project description:Adlay (Coix larchryma-jobi L.) was the commonly used Traditional Chinese Medicine (TCM) with high content of seed storage protein. The hydrolyzed bioactive oligopeptides of adlay have been proven to be anti-hypertensive effective components. However, the structures and anti-hypertensive mechanism of bioactive oligopeptides from adlay were not clear. To discover the definite anti-hypertensive oligopeptides from adlay, in silico proteolysis and virtual screening were implemented to obtain potential oligopeptides, which were further identified by biochemistry assay and molecular dynamics simulation. In this paper, ten sequences of adlay prolamins were collected and in silico hydrolyzed to construct the oligopeptide library with 134 oligopeptides. This library was reverse screened by anti-hypertensive pharmacophore database, which was constructed by our research team and contained ten anti-hypertensive targets. Angiotensin-I converting enzyme (ACE) was identified as the main potential target for the anti-hypertensive activity of adlay oligopeptides. Three crystal structures of ACE were utilized for docking studies and 19 oligopeptides were finally identified with potential ACE inhibitory activity. According to mapping features and evaluation indexes of pharmacophore and docking, three oligopeptides were selected for biochemistry assay. An oligopeptide sequence, NPATY (IC50 = 61.88 ± 2.77 µM), was identified as the ACE inhibitor by reverse-phase high performance liquid chromatography (RP-HPLC) assay. Molecular dynamics simulation of NPATY was further utilized to analyze interactive bonds and key residues. ALA354 was identified as a key residue of ACE inhibitors. Hydrophobic effect of VAL518 and electrostatic effects of HIS383, HIS387, HIS513 and Zn2+ were also regarded as playing a key role in inhibiting ACE activities. This study provides a research strategy to explore the pharmacological mechanism of Traditional Chinese Medicine (TCM) proteins based on in silico proteolysis and virtual screening, which could be beneficial to reveal the pharmacological action of TCM proteins and provide new lead compounds for peptides-based drug design.

Dataset Information

Standardization of virtual-screening and post-processing protocols relevant to in-silico drug discovery.

Publications

Standardization of virtual-screening and post-processing protocols relevant to in-silico drug discovery.

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