Literature DB >> 16995738

Noise reduction method for molecular interaction energy: application to in silico drug screening and in silico target protein screening.

Yoshifumi Fukunishi1, Satoru Kubota, Haruki Nakamura.   

Abstract

We developed a new method to improve the accuracy of molecular interaction data using a molecular interaction matrix. This method was applied to enhance the database enrichment of in silico drug screening and in silico target protein screening using a protein-compound affinity matrix calculated by a protein-compound docking software. Our assumption was that the protein-compound binding free energy of a compound could be improved by a linear combination of its docking scores with many different proteins. We proposed two approaches to determine the coefficients of the linear combination. The first approach is based on similarity among the proteins, and the second is a machine-learning approach based on the known active compounds. These methods were applied to in silico screening of the active compounds of several target proteins and in silico target protein screening.

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Year:  2006        PMID: 16995738     DOI: 10.1021/ci060152z

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


  10 in total

Review 1.  Chemogenomic approaches to rational drug design.

Authors:  D Rognan
Journal:  Br J Pharmacol       Date:  2007-05-29       Impact factor: 8.739

2.  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

3.  Quantitative Structure-activity Relationship (QSAR) Models for Docking Score Correction.

Authors:  Yoshifumi Fukunishi; Satoshi Yamasaki; Isao Yasumatsu; Koh Takeuchi; Takashi Kurosawa; Haruki Nakamura
Journal:  Mol Inform       Date:  2016-04-29       Impact factor: 3.353

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.  Sertraline, chlorprothixene, and chlorpromazine characteristically interact with the REST-binding site of the corepressor mSin3, showing medulloblastoma cell growth inhibitory activities.

Authors:  Jun-Ichi Kurita; Yuuka Hirao; Hirofumi Nakano; Yoshifumi Fukunishi; Yoshifumi Nishimura
Journal:  Sci Rep       Date:  2018-09-13       Impact factor: 4.379

6.  Potential repurposing of four FDA approved compounds with antiplasmodial activity identified through proteome scale computational drug discovery and in vitro assay.

Authors:  Bakary N'tji Diallo; Tarryn Swart; Heinrich C Hoppe; Özlem Tastan Bishop; Kevin Lobb
Journal:  Sci Rep       Date:  2021-01-14       Impact factor: 4.379

7.  A similarity search using molecular topological graphs.

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

8.  AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening.

Authors:  Tania Pencheva; David Lagorce; Ilza Pajeva; Bruno O Villoutreix; Maria A Miteva
Journal:  BMC Bioinformatics       Date:  2008-10-16       Impact factor: 3.169

9.  Integration of ligand-based drug screening with structure-based drug screening by combining maximum volume overlapping score with ligand docking.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Pharmaceuticals (Basel)       Date:  2012-12-04

10.  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

  10 in total

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