Literature DB >> 31276391

CoDockPP: A Multistage Approach for Global and Site-Specific Protein-Protein Docking.

Ren Kong1, Feng Wang2, Jian Zhang3, Fengfei Wang1, Shan Chang1.   

Abstract

Protein-protein docking technology is an effective approach to study the molecular mechanism of essential biological processes mediated by complex protein-protein interactions. The fast Fourier transform (FFT) correlation approach makes a good balance between the exhaustive global sampling and the computational efficiency for protein-protein docking. However, it is difficult to integrate the precise knowledge-based scoring function and site constraint information into the FFT-based approach. New docking strategies with the capability of combining both global sampling and precise scoring are strongly needed. We propose a multistage protein-protein docking strategy called CoDockPP. This program takes full advantage of the sampling efficiency of the FFT-based method to choose the valid ligand protein poses with good surface complementarity. The retained poses are transformed to the real Cartesian space for the implementation of site constraints and atomic scoring. Site constraints and a rapid table lookup scoring are applied to gradually reduce the candidate poses to a tractable number. To enhance the accuracy of docking prediction, the best fast-scoring states are expanded the local sampling points and then these neighbor poses are further evaluated by the precise knowledge-based scoring function. By testing on protein-protein docking benchmark 5.0, CoDockPP remarkably improves the success rate and hit count in both ab initio docking and site-specific docking, especially in difficult cases. The server is free and open to all users with no login requirement at http://codockpp.schanglab.org.cn .

Entities:  

Year:  2019        PMID: 31276391     DOI: 10.1021/acs.jcim.9b00445

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


  7 in total

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2.  Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking.

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Authors:  Shravan B Rathod; Pravin B Prajapati; Lata B Punjabi; Kuntal N Prajapati; Neha Chauhan; Mohmedyasin F Mansuri
Journal:  In Silico Pharmacol       Date:  2020-11-09

4.  Screening and Identification of HBV Epitopes Restricted by Multiple Prevalent HLA-A Allotypes.

Authors:  Yan Ding; Zining Zhou; Xingyu Li; Chen Zhao; Xiaoxiao Jin; Xiaotao Liu; Yandan Wu; Xueyin Mei; Jian Li; Jie Qiu; Chuanlai Shen
Journal:  Front Immunol       Date:  2022-04-07       Impact factor: 8.786

5.  HLA3D: an integrated structure-based computational toolkit for immunotherapy.

Authors:  Xingyu Li; Xue Lin; Xueyin Mei; Pin Chen; Anna Liu; Weicheng Liang; Shan Chang; Jian Li
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 11.622

6.  Novel Binding Mechanisms of Fusion Broad Range Anti-Infective Protein Ricin A Chain Mutant-Pokeweed Antiviral Protein 1 (RTAM-PAP1) against SARS-CoV-2 Key Proteins in Silico.

Authors:  Yasser Hassan; Sherry Ogg; Hui Ge
Journal:  Toxins (Basel)       Date:  2020-09-17       Impact factor: 4.546

7.  Bioinformatic Analysis of Genome-Predicted Bat Cathelicidins.

Authors:  José Manuel Pérez de la Lastra; Patricia Asensio-Calavia; Sergio González-Acosta; Victoria Baca-González; Antonio Morales-delaNuez
Journal:  Molecules       Date:  2021-03-23       Impact factor: 4.411

  7 in total

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