Docking (molecular)

About: Docking (molecular) is a research topic. Over the lifetime, 15375 publications have been published within this topic receiving 307552 citations. The topic is also known as: interaction simulation & molecular docking.

Identification and Characterization of Two Structurally Related Dipeptides that Enhance Catalytic Efficiency of Neurolysin.

Abstract: Neurolysin (Nln) is a recently recognized endogenous mechanism functioning to preserve the brain from ischemic injury. To further understand the pathophysiological function of this peptidase in stroke and other neurological disorders, the present study was designed to identify small molecule activators of Nln. Using a computational approach, the structure of Nln was explored, followed by docking and in silico screening of ~140,000 molecules from the National Cancer Institute Developmental Therapeutics Program database. Top ranking compounds were evaluated in a Nln enzymatic assay, and two hit histidine-dipeptides were further studied in detail. The identified dipeptides enhanced the rate of synthetic substrate hydrolysis by recombinant (human and rat) and mouse brain-purified Nln in a concentration-dependent manner (micromolar A50 and Amax {greater than or equal to} 300%), but had negligible effect on activity of closely related peptidases. Both dipeptides also enhanced hydrolysis of Nln endogenous substrates neurotensin, angiotensin I and bradykinin, and increased efficiency of the synthetic substrate hydrolysis (Vmax/Km ratio) in a concentration-dependent manner. The dipeptides and competitive inhibitor dynorphin A(1-13) did not affect each other9s affinity for Nln, suggesting differing nature of their respective binding sites. Lastly, drug affinity responsive target stability (DARTS) and differential scanning fluorimetry (DSF) assays confirmed concentration-dependent interaction of Nln with the activator molecule. This is the first study demonstrating that Nln activity can be enhanced by small molecules, although the peptidic nature and low potency of the activators limit their application. The identified dipeptides provide a chemical scaffold to develop high-potency, drug-like molecules as research tools and potential drug leads. Significance Statement This study describes discovery of two molecules that selectively enhance activity of peptidase neurolysin (Nln) – a newly recognized cerebroprotective mechanism in the post-stroke brain. The identified molecules will serve as a chemical scaffold for development of drug-like molecules to further study Nln, and may become lead structures for a new class of drugs. In addition, our conceptual and methodological framework and research findings might be used for other peptidases and enzymes, activation of which bears therapeutic potential.

A multiscale approach to predict the binding mode of metallo beta-lactamase inhibitors.

Abstract: Antibiotic resistance is a major threat to global public health. β-lactamases, which catalyze breakdown of β-lactam antibiotics, are a principal cause. Metallo β-lactamases (MBLs) represent a particular challenge because they hydrolyze almost all β-lactams and to date no MBL inhibitor has been approved for clinical use. Molecular simulations can aid drug discovery, e.g. predicting inhibitor complexes, but empirical molecular mechanics (MM) methods often perform poorly for metalloproteins. Here we present a multiscale approach to model thiol inhibitor binding to IMP-1, a clinically important MBL containing two catalytic zinc ions, and predict the binding mode of a 2-mercaptomethyl thiazolidine (MMTZ) inhibitor. Inhibitors were first docked into the IMP-1 active site, testing different docking programs and scoring functions on multiple crystal structures. Complexes were then subjected to molecular dynamics (MD) simulations and subsequently refined through QM/MM optimization with a density functional theory (DFT) method, B3LYP/6-31G(d), increasing the accuracy of the method with successive steps. This workflow was tested on two IMP-1:MMTZ complexes, for which it reproduced crystallographically observed binding, and applied to predict the binding mode of a third MMTZ inhibitor for which a complex structure was crystallographically intractable. We also tested a 12-6-4 non-bonded interaction model in MD simulations and optimization with a SCC-DFTB QM/MM approach. The results show the limitations of empirical models for treating these systems and indicate the need for higher level calculations, e.g. DFT/MM, for reliable structural predictions. This work demonstrates a reliable computational pipeline that can be applied to inhibitor design for MBLs and other zinc-metalloenzyme systems. This article is protected by copyright. All rights reserved.

Insights on the structure-function relationship of human multidrug resistance protein 7 (MRP7/ABCC10) from molecular dynamics simulations and docking studies.

Abstract: ATP-binding cassette (ABC) transporters superfamily mediates multidrug resistance in cancer by extruding structurally distinct chemotherapeutic agents, causing failure in chemotherapy. Among the 49 ABC transporters, multidrug resistance protein 7 (MRP7 or ABCC10) is relatively new and has been identified as the efflux pump of multiple anticancer agents including Vinca alkaloids and taxanes. Herein, we construct and validate a homology model for human MRP7 based on the cryo-EM structures of MRP1. Structure-function relationship of MRP7 was obtained from molecular dynamics simulations and docking studies and was in accordance with previous studies of ABC transporters. The motion patterns correlated with efflux mechanism were discussed. Additionally, predicted substrate- and modulator-binding sites of MRP7 were described for the first time, which provided rational insights in understanding the drug binding and functional regulation in MRP7. Our findings will benefit the high-throughput virtual screening and development of MRP7 modulators in the future.

Coumarins and Quinolones as Effective Multiple Targeted Agents Versus Covid-19: An in Silico Study.

Abstract: Background The Covid-19 virus emerged a few months ago in China and infections rapidly escalated into a pandemic Objective To date, there is no selective antiviral agent for the management of pathologies associated with covid-19 and the need for an effective agent against it is essential Method In this work two home-made databases from synthetic quinolines and coumarins were virtually docked against viral proteases (3CL and PL), human cell surface proteases (TMPRSS2 and furin) and spike proteins (S1 and S2) Chloroquine, a reference drug without a clear mechanism against coronavirus was also docked on mentioned targets and the binding affinities compared with title compounds Result The best compounds of synthetic coumarins and quinolines for each target were determined All compounds against all targets showed binding affinity between -580 to -899 kcal/mol in comparison with the FDA-approved drug, Chloroquine, with binding affinity of -57 to -798 kcal/mol Two compounds, quinoline-1 and coumarin-24, were found to be effective on three targets - S2, TMPRSS2 and furin - simultaneously, with good predicted affinity between -754 to -885 kcal/mol In silico ADME studies also confirmed good oral absorption for them Furthermore, PASS prediction was calculated and coumarin-24 had higher probable activity (Pa) than probable inactivity (Pi) with acceptable protease inhibitory as well as good antiviral activity against Hepatitis C virus (HCV), Human immunodeficiency virus (HIV) and influenza Conclusion Quinoline-1 and Coumarin-24 have the potential to be used against Covid-19 Hence these agents could be useful in combating covid-19 infection after further in vitro and in vivo studies