Literature DB >> 23713772

Protein-protein interface analysis and hot spots identification for chemical ligand design.

Jing Chen, Xiaomin Ma, Yaxia Yuan, Jianfeng Pei, Luhua Lai1.   

Abstract

Rational design for chemical compounds targeting protein-protein interactions has grown from a dream to reality after a decade of efforts. There are an increasing number of successful examples, though major challenges remain in the field. In this paper, we will first give a brief review of the available methods that can be used to analyze protein-protein interface and predict hot spots for chemical ligand design. New developments of binding sites detection, ligandability and hot spots prediction from the author's group will also be described. Pocket V.3 is an improved program for identifying hot spots in protein-protein interface using only an apo protein structure. It has been developed based on Pocket V.2 that can derive receptor-based pharmacophore model for ligand binding cavity. Given similarities and differences between the essence of pharmacophore and hot spots for guiding design of chemical compounds, not only energetic but also spatial properties of protein-protein interface are used in Pocket V.3 for dealing with protein-protein interface. In order to illustrate the capability of Pocket V.3, two datasets have been used. One is taken from ASEdb and BID having experimental alanine scanning results for testing hot spots prediction. The other is taken from the 2P2I database containing complex structures of protein-ligand binding at the original protein-protein interface for testing hot spots application in ligand design.

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Year:  2014        PMID: 23713772     DOI: 10.2174/13816128113199990065

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  6 in total

1.  PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database.

Authors:  Xia Wang; Yihang Shen; Shiwei Wang; Shiliang Li; Weilin Zhang; Xiaofeng Liu; Luhua Lai; Jianfeng Pei; Honglin Li
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

2.  BIPSPI: a method for the prediction of partner-specific protein-protein interfaces.

Authors:  Ruben Sanchez-Garcia; C O S Sorzano; J M Carazo; Joan Segura
Journal:  Bioinformatics       Date:  2019-02-01       Impact factor: 6.937

3.  Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations.

Authors:  Ji Young Lee; James M Krieger; Hongchun Li; Ivet Bahar
Journal:  Protein Sci       Date:  2019-12-04       Impact factor: 6.725

4.  ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement.

Authors:  Haoqi Wang; Nirmitee Mulgaonkar; Lisa M Pérez; Sandun Fernando
Journal:  ACS Omega       Date:  2022-04-05

5.  CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

Authors:  Youjun Xu; Shiwei Wang; Qiwan Hu; Shuaishi Gao; Xiaomin Ma; Weilin Zhang; Yihang Shen; Fangjin Chen; Luhua Lai; Jianfeng Pei
Journal:  Nucleic Acids Res       Date:  2018-07-02       Impact factor: 16.971

Review 6.  In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs.

Authors:  Zarko Gagic; Dusan Ruzic; Nemanja Djokovic; Teodora Djikic; Katarina Nikolic
Journal:  Front Chem       Date:  2020-01-08       Impact factor: 5.221

  6 in total

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