Literature DB >> 19530660

Effect of input differences on the results of docking calculations.

Miklos Feher1, Christopher I Williams.   

Abstract

The sensitivity of docking calculations to the geometry of the input ligand was studied. It was found that even small changes in the ligand input conformation can lead to large differences in the geometries and scores of the resulting docked poses. The accuracy of docked poses produced from different ligand input structures-the X-ray structure, the minimized Corina structure, and structures generated from conformational searches and molecular dynamics ensembles-were also assessed. It was found that using the X-ray ligand conformation as docking input does not always produce the most accurate docked pose when compared with other sources of ligand input conformations. Furthermore, no one method of conformer generation is guaranteed to always produce the most accurate docking pose. The docking scores are also highly sensitive to the source of the input conformation, which might introduce some noise in compound ranking and in binding affinity predictions. It is concluded that for the purposes of reproducibility and optimal performance, the most prudent procedure is to use multiple input structures for docking. The implications of these results on docking validation studies are discussed.

Mesh:

Substances:

Year:  2009        PMID: 19530660     DOI: 10.1021/ci9000629

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


  15 in total

1.  pK(a) based protonation states and microspecies for protein-ligand docking.

Authors:  Tim ten Brink; Thomas E Exner
Journal:  J Comput Aided Mol Des       Date:  2010-09-30       Impact factor: 3.686

2.  Molecular motions in drug design: the coming age of the metadynamics method.

Authors:  Xevi Biarnés; Salvatore Bongarzone; Attilio Vittorio Vargiu; Paolo Carloni; Paolo Ruggerone
Journal:  J Comput Aided Mol Des       Date:  2011-02-17       Impact factor: 3.686

3.  Fisetin inhibits human melanoma cell growth through direct binding to p70S6K and mTOR: findings from 3-D melanoma skin equivalents and computational modeling.

Authors:  Deeba N Syed; Jean-Christopher Chamcheu; Mohammad Imran Khan; Mario Sechi; Rahul K Lall; Vaqar M Adhami; Hasan Mukhtar
Journal:  Biochem Pharmacol       Date:  2014-03-24       Impact factor: 5.858

4.  Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study.

Authors:  Nagakumar Bharatham; Kavitha Bharatham; Anang A Shelat; Donald Bashford
Journal:  J Chem Inf Model       Date:  2014-01-21       Impact factor: 4.956

5.  The R.E.D. tools: advances in RESP and ESP charge derivation and force field library building.

Authors:  François-Yves Dupradeau; Adrien Pigache; Thomas Zaffran; Corentin Savineau; Rodolphe Lelong; Nicolas Grivel; Dimitri Lelong; Wilfried Rosanski; Piotr Cieplak
Journal:  Phys Chem Chem Phys       Date:  2010-06-23       Impact factor: 3.676

Review 6.  Bioinformatics and variability in drug response: a protein structural perspective.

Authors:  Jennifer L Lahti; Grace W Tang; Emidio Capriotti; Tianyun Liu; Russ B Altman
Journal:  J R Soc Interface       Date:  2012-05-02       Impact factor: 4.118

7.  Computational Study on the Conformations of Mitragynine and Mitragynaline.

Authors:  Haining Liu; Christopher R McCurdy; Robert J Doerksen
Journal:  Theochem       Date:  2010-04-15

8.  Ceftriaxone blocks the polymerization of α-synuclein and exerts neuroprotective effects in vitro.

Authors:  Paolo Ruzza; Giuliano Siligardi; Rohanah Hussain; Anna Marchiani; Mehmet Islami; Luigi Bubacco; Giovanna Delogu; Davide Fabbri; Maria A Dettori; Mario Sechi; Nicolino Pala; Ylenia Spissu; Rossana Migheli; Pier A Serra; GianPietro Sechi
Journal:  ACS Chem Neurosci       Date:  2013-10-24       Impact factor: 4.418

9.  Variability in docking success rates due to dataset preparation.

Authors:  Christopher R Corbeil; Christopher I Williams; Paul Labute
Journal:  J Comput Aided Mol Des       Date:  2012-05-08       Impact factor: 3.686

10.  In silico prediction of estrogen receptor subtype binding affinity and selectivity using statistical methods and molecular docking with 2-arylnaphthalenes and 2-arylquinolines.

Authors:  Zhizhong Wang; Yan Li; Chunzhi Ai; Yonghua Wang
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.