Literature DB >> 25751016

Dynamics based pharmacophore models for screening potential inhibitors of mycobacterial cyclopropane synthase.

Chinmayee Choudhury1,2, U Deva Priyakumar1, G Narahari Sastry2.   

Abstract

The therapeutic challenges in the treatment of tuberculosis demand multidisciplinary approaches for the identification of potential drug targets as well as fast and accurate techniques to screen huge chemical libraries. Mycobacterial cyclopropane synthase (CmaA1) has been shown to be essential for the survival of the bacteria due to its critical role in the synthesis of mycolic acids. The present study proposes pharmacophore models based on the structure of CmaA1 taking into account its various states in the cyclopropanation process, and their dynamic nature as assessed using molecular dynamics (MD) simulations. The qualities of these pharmacophore models were validated by mapping 23 molecules that have been previously reported to exhibit inhibitory activities on CmaA1. Additionally, 1398 compounds that have been shown to be inactive for tuberculosis were collected from the ChEMBL database and were screened against the models for validation. The models were further validated by comparing the results from pharmacophore mapping with the results obtained from docking these molecules with the respective protein structures. The best models are suggested by validating all the models based on their screening abilities and by comparing with docking results. The models generated from the MD trajectories were found to perform better than the one generated based on the crystal structure demonstrating the importance of incorporating receptor flexibility in drug design.

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Year:  2015        PMID: 25751016     DOI: 10.1021/ci500737b

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  8 in total

1.  Comparing pharmacophore models derived from crystallography and NMR ensembles.

Authors:  Phani Ghanakota; Heather A Carlson
Journal:  J Comput Aided Mol Des       Date:  2017-10-19       Impact factor: 3.686

2.  Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies.

Authors:  Ma'mon M Hatmal; Shadi Jaber; Mutasem O Taha
Journal:  J Comput Aided Mol Des       Date:  2016-10-08       Impact factor: 3.686

3.  Drug repositioning for anti-tuberculosis drugs: an in silico polypharmacology approach.

Authors:  Sita Sirisha Madugula; Selvaraman Nagamani; Esther Jamir; Lipsa Priyadarsinee; G Narahari Sastry
Journal:  Mol Divers       Date:  2021-09-01       Impact factor: 2.943

Review 4.  Residue-based pharmacophore approaches to study protein-protein interactions.

Authors:  Rojan Shrestha; Jorge Eduardo Fajardo; Andras Fiser
Journal:  Curr Opin Struct Biol       Date:  2021-01-22       Impact factor: 6.809

5.  In Silico Strategy for Targeting the mTOR Kinase at Rapamycin Binding Site by Small Molecules.

Authors:  Serena Vittorio; Rosaria Gitto; Ilenia Adornato; Emilio Russo; Laura De Luca
Journal:  Molecules       Date:  2021-02-19       Impact factor: 4.411

6.  Mycobacterium tuberculosis Cell Wall Permeability Model Generation Using Chemoinformatics and Machine Learning Approaches.

Authors:  Selvaraman Nagamani; G Narahari Sastry
Journal:  ACS Omega       Date:  2021-06-25

Review 7.  Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics.

Authors:  Ashutosh Srivastava; Tetsuro Nagai; Arpita Srivastava; Osamu Miyashita; Florence Tama
Journal:  Int J Mol Sci       Date:  2018-10-30       Impact factor: 5.923

8.  Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations.

Authors:  Pavel Polishchuk; Alina Kutlushina; Dayana Bashirova; Olena Mokshyna; Timur Madzhidov
Journal:  Int J Mol Sci       Date:  2019-11-20       Impact factor: 5.923

  8 in total

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