Literature DB >> 16376595

Multiple target screening method for robust and accurate in silico ligand screening.

Yoshifumi Fukunishi1, Yoshiaki Mikami, Satoru Kubota, Haruki Nakamura.   

Abstract

We developed a new in silico multiple target screening (MTS) method, based on a multi-receptor versus multi-ligand docking affinity matrixes, and examined its robustness against changes in the scoring system. According to this method, compounds in a database are docked to multiple proteins. The compounds among these proteins that are likely bind to the target protein are selected as the members of the candidate-hit compound group. Then, the compounds in the group are sorted into descending order using the docking score: the first (n-th) compound is expected to be the most (n-th) probable hit compound. This method was applied to the analysis of a set of 142 receptors and 142 compounds using a receptor-ligand docking program, Sievgene [Y. Fukunishi, Y. Mikami, H. Nakamura, Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening, J. Mol. Graphics Modelling, 24 (2005) 34-45], and the results demonstrated that this method achieves a high hit ratio compared to uniform sampling. We prepared two new scores: the DeltaG score, designed to reproduce the protein-ligand binding free energy, and the hit-optimized score, designed to maximize the hit ratio of in silico screening. Using the Sievgene docking score, DeltaG score and hit-optimized score, the MTS method is more robust than the multiple active-site correction scoring method [G.P.A. Vigers, J.P. Rizzi, Multiple active site corrections for docking and virtual screening, J. Med. Chem., 47 (2004) 80-89].

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Year:  2005        PMID: 16376595     DOI: 10.1016/j.jmgm.2005.11.006

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  8 in total

1.  Prediction of ligand-binding sites of proteins by molecular docking calculation for a random ligand library.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Protein Sci       Date:  2011-01       Impact factor: 6.725

2.  A virtual active compound produced from the negative image of a ligand-binding pocket, and its application to in-silico drug screening.

Authors:  Yoshifumi Fukunishi; Satoru Kubota; Chisato Kanai; Haruki Nakamura
Journal:  J Comput Aided Mol Des       Date:  2006-06-21       Impact factor: 3.686

3.  A method to enhance the hit ratio by a combination of structure-based drug screening and ligand-based screening.

Authors:  Katsumi Omagari; Daisuke Mitomo; Satoru Kubota; Haruki Nakamura; Yoshifumi Fukunishi
Journal:  Adv Appl Bioinform Chem       Date:  2008-08-12

4.  Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications.

Authors:  Yoshifumi Fukunishi; Yasunobu Yamashita; Tadaaki Mashimo; Haruki Nakamura
Journal:  Mol Inform       Date:  2018-02-14       Impact factor: 3.353

5.  A similarity search using molecular topological graphs.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  J Biomed Biotechnol       Date:  2009-12-13

6.  Improved estimation of protein-ligand binding free energy by using the ligand-entropy and mobility of water molecules.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Pharmaceuticals (Basel)       Date:  2013-04-26

7.  Statistical estimation of the protein-ligand binding free energy based on direct protein-ligand interaction obtained by molecular dynamics simulation.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Pharmaceuticals (Basel)       Date:  2012-09-28

8.  A prospective compound screening contest identified broader inhibitors for Sirtuin 1.

Authors:  Shuntaro Chiba; Masahito Ohue; Anastasiia Gryniukova; Petro Borysko; Sergey Zozulya; Nobuaki Yasuo; Ryunosuke Yoshino; Kazuyoshi Ikeda; Woong-Hee Shin; Daisuke Kihara; Mitsuo Iwadate; Hideaki Umeyama; Takaaki Ichikawa; Reiji Teramoto; Kun-Yi Hsin; Vipul Gupta; Hiroaki Kitano; Mika Sakamoto; Akiko Higuchi; Nobuaki Miura; Kei Yura; Masahiro Mochizuki; Chandrasekaran Ramakrishnan; A Mary Thangakani; D Velmurugan; M Michael Gromiha; Itsuo Nakane; Nanako Uchida; Hayase Hakariya; Modong Tan; Hironori K Nakamura; Shogo D Suzuki; Tomoki Ito; Masahiro Kawatani; Kentaroh Kudoh; Sakurako Takashina; Kazuki Z Yamamoto; Yoshitaka Moriwaki; Keita Oda; Daisuke Kobayashi; Tatsuya Okuno; Shintaro Minami; George Chikenji; Philip Prathipati; Chioko Nagao; Attayeb Mohsen; Mari Ito; Kenji Mizuguchi; Teruki Honma; Takashi Ishida; Takatsugu Hirokawa; Yutaka Akiyama; Masakazu Sekijima
Journal:  Sci Rep       Date:  2019-12-20       Impact factor: 4.379

  8 in total

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