Literature DB >> 21361385

ReverseScreen3D: a structure-based ligand matching method to identify protein targets.

Sarah L Kinnings1, Richard M Jackson.   

Abstract

Ligand promiscuity, which is now recognized as an extremely common phenomenon, is a major underlying cause of drug toxicity. We have developed a new reverse virtual screening (VS) method called ReverseScreen3D, which can be used to predict the potential protein targets of a query compound of interest. The method uses a 2D fingerprint-based method to select a ligand template from each unique binding site of each protein within a target database. The target database contains only the structurally determined bioactive conformations of known ligands. The 2D comparison is followed by a 3D structural comparison to the selected query ligand using a geometric matching method, in order to prioritize each target binding site in the database. We have evaluated the performance of the ReverseScreen2D and 3D methods using a diverse set of small molecule protein inhibitors known to have multiple targets, and have shown that they are able to provide a highly significant enrichment of true targets in the database. Furthermore, we have shown that the 3D structural comparison improves early enrichment when compared with the 2D method alone, and that the 3D method performs well even in the absence of 2D similarity to the template ligands. By carrying out further experimental screening on the prioritized list of targets, it may be possible to determine the potential targets of a new compound or determine the off-targets of an existing drug. The ReverseScreen3D method has been incorporated into a Web server, which is freely available at http://www.modelling.leeds.ac.uk/ReverseScreen3D .

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21361385     DOI: 10.1021/ci1003174

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


  14 in total

1.  Prediction of protein targets of kinetin using in silico and in vitro methods: a case study on spinach seed germination mechanism.

Authors:  Sivakumar Prasanth Kumar; Vilas R Parmar; Yogesh T Jasrai; Himanshu A Pandya
Journal:  J Chem Biol       Date:  2015-05-12

2.  An in silico insight into novel therapeutic interaction of LTNF peptide-LT10 and design of structure based peptidomimetics for putative anti-diabetic activity.

Authors:  Sonali Gopichand Chavan; Deepti Dileep Deobagkar
Journal:  PLoS One       Date:  2015-03-27       Impact factor: 3.240

3.  Elucidation of molecular targets of bioactive principles of black cumin relevant to its anti-tumour functionality - An Insilico target fishing approach.

Authors:  Amulyashree Sridhar; Sadegh Saremy; Biplab Bhattacharjee
Journal:  Bioinformation       Date:  2014-11-27

Review 4.  Building a virtual ligand screening pipeline using free software: a survey.

Authors:  Enrico Glaab
Journal:  Brief Bioinform       Date:  2015-06-20       Impact factor: 11.622

5.  Evaluation of 6-chloro-N-[3,4-disubstituted-1,3-thiazol-2(3H)-ylidene]-1,3-benzothiazol-2-amine Using Drug Design Concept for Their Targeted Activity Against Colon Cancer Cell Lines HCT-116, HCT15, and HT29.

Authors:  Ming-Li Zhu; Cui-Yue Wang; Cheng-Mian Xu; Wei-Ping Bi; Xiu-Ying ZHou
Journal:  Med Sci Monit       Date:  2017-03-05

6.  The scoring bias in reverse docking and the score normalization strategy to improve success rate of target fishing.

Authors:  Qiyao Luo; Liang Zhao; Jianxing Hu; Hongwei Jin; Zhenming Liu; Liangren Zhang
Journal:  PLoS One       Date:  2017-02-14       Impact factor: 3.240

Review 7.  Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases.

Authors:  Ahmet Sureyya Rifaioglu; Heval Atas; Maria Jesus Martin; Rengul Cetin-Atalay; Volkan Atalay; Tunca Doğan
Journal:  Brief Bioinform       Date:  2019-09-27       Impact factor: 11.622

8.  Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

Authors:  Stéphanie Pérot; Leslie Regad; Christelle Reynès; Olivier Spérandio; Maria A Miteva; Bruno O Villoutreix; Anne-Claude Camproux
Journal:  PLoS One       Date:  2013-06-20       Impact factor: 3.240

9.  Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME.

Authors:  George Nicola; Michael R Berthold; Michael P Hedrick; Michael K Gilson
Journal:  Database (Oxford)       Date:  2015-09-16       Impact factor: 3.451

10.  EGFR tyrosine kinase targeted compounds: in vitro antitumor activity and molecular modeling studies of new benzothiazole and pyrimido[2,1-b]benzothiazole derivatives.

Authors:  Moustafa T Gabr; Nadia S El-Gohary; Eman R El-Bendary; Mohamed M El-Kerdawy
Journal:  EXCLI J       Date:  2014-05-26       Impact factor: 4.068

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.