Literature DB >> 24050138

Induced fit docking, and the use of QM/MM methods in docking.

Mengang Xu, Markus A Lill.   

Abstract

Docking methods are popular computational techniques in drug discovery to identify new active molecules that bind to a given biological target. Although widely used, the predictive reliability of docking methods is often limited by the inability to accurately and efficiently model protein flexibility and quantify binding strength. We highlight several emerging concepts that address those methodological issues including a discussion on the incorporation of QM/MM methodologies in the scoring process.

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Year:  2013        PMID: 24050138      PMCID: PMC3719877          DOI: 10.1016/j.ddtec.2013.02.003

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  37 in total

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Review 2.  Flexible ligand docking to multiple receptor conformations: a practical alternative.

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5.  A QM/MM study of the binding of RAPTA ligands to cathepsin B.

Authors:  Antonella Ciancetta; Samuel Genheden; Ulf Ryde
Journal:  J Comput Aided Mol Des       Date:  2011-06-24       Impact factor: 3.686

6.  CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity.

Authors:  Fedor N Novikov; Alexey A Zeifman; Oleg V Stroganov; Viktor S Stroylov; Val Kulkov; Ghermes G Chilov
Journal:  J Chem Inf Model       Date:  2011-06-03       Impact factor: 4.956

7.  Quantum mechanical pairwise decomposition analysis of protein kinase B inhibitors: validating a new tool for guiding drug design.

Authors:  Xiaohua Zhang; Alan C Gibbs; Charles H Reynolds; Martin B Peters; Lance M Westerhoff
Journal:  J Chem Inf Model       Date:  2010-04-26       Impact factor: 4.956

8.  Target Flexibility in RNA-Ligand Docking Modeled by Elastic Potential Grids.

Authors:  Dennis M Krüger; Johannes Bergs; Sina Kazemi; Holger Gohlke
Journal:  ACS Med Chem Lett       Date:  2011-04-12       Impact factor: 4.345

9.  Systematic exploitation of multiple receptor conformations for virtual ligand screening.

Authors:  Giovanni Bottegoni; Walter Rocchia; Manuel Rueda; Ruben Abagyan; Andrea Cavalli
Journal:  PLoS One       Date:  2011-05-17       Impact factor: 3.240

10.  CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions.

Authors:  Richard D Smith; James B Dunbar; Peter Man-Un Ung; Emilio X Esposito; Chao-Yie Yang; Shaomeng Wang; Heather A Carlson
Journal:  J Chem Inf Model       Date:  2011-08-29       Impact factor: 4.956

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  8 in total

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Review 2.  Modern approaches to accelerate discovery of new antischistosomal drugs.

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Review 3.  Quantum mechanics implementation in drug-design workflows: does it really help?

Authors:  Olayide A Arodola; Mahmoud Es Soliman
Journal:  Drug Des Devel Ther       Date:  2017-08-31       Impact factor: 4.162

Review 4.  Docking-based inverse virtual screening: methods, applications, and challenges.

Authors:  Xianjin Xu; Marshal Huang; Xiaoqin Zou
Journal:  Biophys Rep       Date:  2018-02-01

5.  In Silico Screening of Isocitrate Lyase for Novel Anti-Buruli Ulcer Natural Products Originating from Africa.

Authors:  Samuel K Kwofie; Bismark Dankwa; Emmanuel A Odame; Francis E Agamah; Lady P A Doe; Joshua Teye; Odame Agyapong; Whelton A Miller; Lydia Mosi; Michael D Wilson
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Review 6.  Chalcone Derivatives: Promising Starting Points for Drug Design.

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Review 7.  Current computational methods for predicting protein interactions of natural products.

Authors:  Aurélien F A Moumbock; Jianyu Li; Pankaj Mishra; Mingjie Gao; Stefan Günther
Journal:  Comput Struct Biotechnol J       Date:  2019-10-28       Impact factor: 7.271

8.  Anti-cancer potency by induced apoptosis by molecular docking P53, caspase, cyclin D1, cytotoxicity analysis and phagocytosis activity of trisindoline 1,3 and 4.

Authors:  Awik Puji Dyah Nurhayati; Andis Rihandoko; Arif Fadlan; Shabrina Syifa Ghaissani; Nurul Jadid; Edwin Setiawan
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  8 in total

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