Literature DB >> 16426058

VISCANA: visualized cluster analysis of protein-ligand interaction based on the ab initio fragment molecular orbital method for virtual ligand screening.

Shinji Amari1, Masahiro Aizawa, Junwei Zhang, Kaori Fukuzawa, Yuji Mochizuki, Yoshio Iwasawa, Kotoko Nakata, Hiroshi Chuman, Tatsuya Nakano.   

Abstract

We have developed a visualized cluster analysis of protein-ligand interaction (VISCANA) that analyzes the pattern of the interaction of the receptor and ligand on the basis of quantum theory for virtual ligand screening. Kitaura et al. (Chem. Phys. Lett. 1999, 312, 319-324.) have proposed an ab initio fragment molecular orbital (FMO) method by which large molecules such as proteins can be easily treated with chemical accuracy. In the FMO method, a total energy of the molecule is evaluated by summation of fragment energies and interfragment interaction energies (IFIEs). In this paper, we have proposed a cluster analysis using the dissimilarity that is defined as the squared Euclidean distance between IFIEs of two ligands. Although the result of an ordered table by clustering is still a massive collection of numbers, we combine a clustering method with a graphical representation of the IFIEs by representing each data point with colors that quantitatively and qualitatively reflect the IFIEs. We applied VISCANA to a docking study of pharmacophores of the human estrogen receptor alpha ligand-binding domain (57 amino acid residues). By using VISCANA, we could classify even structurally different ligands into functionally similar clusters according to the interaction pattern of a ligand and amino acid residues of the receptor protein. In addition, VISCANA could estimate the correct docking conformation by analyzing patterns of the receptor-ligand interactions of some conformations through the docking calculation.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16426058     DOI: 10.1021/ci050262q

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


  11 in total

1.  ATPbind: Accurate Protein-ATP Binding Site Prediction by Combining Sequence-Profiling and Structure-Based Comparisons.

Authors:  Jun Hu; Yang Li; Yang Zhang; Dong-Jun Yu
Journal:  J Chem Inf Model       Date:  2018-02-08       Impact factor: 4.956

2.  Coulomb and CH-π interactions in (6-4) photolyase-DNA complex dominate DNA binding and repair abilities.

Authors:  Yuma Terai; Ryuma Sato; Takahiro Yumiba; Ryuhei Harada; Kohei Shimizu; Tatsuya Toga; Tomoko Ishikawa-Fujiwara; Takeshi Todo; Shigenori Iwai; Yasuteru Shigeta; Junpei Yamamoto
Journal:  Nucleic Acids Res       Date:  2018-07-27       Impact factor: 16.971

3.  Insights towards sulfonamide drug specificity in α-carbonic anhydrases.

Authors:  Mayank Aggarwal; Bhargav Kondeti; Robert McKenna
Journal:  Bioorg Med Chem       Date:  2012-08-28       Impact factor: 3.641

4.  How frequently do clusters occur in hierarchical clustering analysis? A graph theoretical approach to studying ties in proximity.

Authors:  Wilmer Leal; Eugenio J Llanos; Guillermo Restrepo; Carlos F Suárez; Manuel Elkin Patarroyo
Journal:  J Cheminform       Date:  2016-01-25       Impact factor: 5.514

5.  TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features.

Authors:  Daniel L Clinciu; Yen-Fu Chen; Cheng-Neng Ko; Chi-Chun Lo; Jinn-Moon Yang
Journal:  BMC Genomics       Date:  2010-12-02       Impact factor: 3.969

6.  Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method.

Authors:  Michael P Mazanetz; Osamu Ichihara; Richard J Law; Mark Whittaker
Journal:  J Cheminform       Date:  2011-01-10       Impact factor: 5.514

Review 7.  Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

Authors:  Daniel Barry Roche; Danielle Allison Brackenridge; Liam James McGuffin
Journal:  Int J Mol Sci       Date:  2015-12-15       Impact factor: 5.923

8.  Interaction analyses of SARS-CoV-2 spike protein based on fragment molecular orbital calculations.

Authors:  Kazuki Akisawa; Ryo Hatada; Koji Okuwaki; Yuji Mochizuki; Kaori Fukuzawa; Yuto Komeiji; Shigenori Tanaka
Journal:  RSC Adv       Date:  2021-01-14       Impact factor: 3.361

9.  Molecular recognition of SARS-CoV-2 spike glycoprotein: quantum chemical hot spot and epitope analyses.

Authors:  Chiduru Watanabe; Yoshio Okiyama; Shigenori Tanaka; Kaori Fukuzawa; Teruki Honma
Journal:  Chem Sci       Date:  2021-03-02       Impact factor: 9.825

Review 10.  Exploring the computational methods for protein-ligand binding site prediction.

Authors:  Jingtian Zhao; Yang Cao; Le Zhang
Journal:  Comput Struct Biotechnol J       Date:  2020-02-17       Impact factor: 7.271

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.