Literature DB >> 14632469

4D-QSAR analysis of a series of antifungal p450 inhibitors and 3D-pharmacophore comparisons as a function of alignment.

Jianzhong Liu1, Dahua Pan, Yufeng Tseng, Anton J Hopfinger.   

Abstract

A training set of 55 antifungal p450 analogue inhibitors was used to construct receptor-independent four-dimensional quantitative structure-activity relationship (RI 4D-QSAR) models. Ten different alignments were used to build the models, and one alignment yields a significantly better model than the other alignments. Two different methodologies were used to measure the similarity of the best 4D-QSAR models of each alignment. One method compares the residual of fit between pairs of models using the cross-correlation coefficient of their residuals of fit as a similarity measure. The other method compares the spatial distributions of the IPE types (3D-pharmacophores) of pairs of 4D-QSAR models from different alignments. Optimum models from several different alignments have nearly the same correlation coefficients, r(2), and cross-validation correlation coefficients, xv-r(2), yet the 3D-pharmacophores of these models are very different from one another. The highest 3D-pharmacophore similarity correlation coefficient between any pair of 4D-QSAR models from the 10 alignments considered is only 0.216. However, the best 4D-QSAR models of each alignment do contain some proximate common pharmacorphore sites. A test set of 10 compounds was used to validate the predictivity of the best 4D-QSAR models of each alignment. The "best" model from the 10 alignments has the highest predictivity. The inferred active sites mapped out by the 4D-QSAR models suggest that hydrogen bond interactions are not prevalent when this class of P450 analogue inhibitors binds to the receptor active site. This feature of the 4D-QSAR models is in agreement with the crystal structure results that indicate no ligand-receptor hydrogen bonds are formed.

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Year:  2003        PMID: 14632469     DOI: 10.1021/ci034142z

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  7 in total

1.  Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors.

Authors:  Jianzhong Liu; Petra S Kern; G Frank Gerberick; Osvaldo A Santos-Filho; Emilio X Esposito; Anton J Hopfinger; Yufeng J Tseng
Journal:  J Comput Aided Mol Des       Date:  2008-03-13       Impact factor: 3.686

Review 2.  Modeling kinetics of subcellular disposition of chemicals.

Authors:  Stefan Balaz
Journal:  Chem Rev       Date:  2009-05       Impact factor: 60.622

3.  Rigorous treatment of multispecies multimode ligand-receptor interactions in 3D-QSAR: CoMFA analysis of thyroxine analogs binding to transthyretin.

Authors:  Senthil Natesan; Tiansheng Wang; Viera Lukacova; Vladimir Bartus; Akash Khandelwal; Stefan Balaz
Journal:  J Chem Inf Model       Date:  2011-04-08       Impact factor: 4.956

4.  Improved quantitative structure-activity relationship models to predict antioxidant activity of flavonoids in chemical, enzymatic, and cellular systems.

Authors:  Andrei I Khlebnikov; Igor A Schepetkin; Nina G Domina; Liliya N Kirpotina; Mark T Quinn
Journal:  Bioorg Med Chem       Date:  2006-11-29       Impact factor: 3.641

5.  Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.

Authors:  Yovani Marrero-Ponce; Eugenio R Martínez-Albelo; Gerardo M Casañola-Martín; Juan A Castillo-Garit; Yunaimy Echevería-Díaz; Vicente Romero Zaldivar; Jan Tygat; José E Rodriguez Borges; Ramón García-Domenech; Francisco Torrens; Facundo Pérez-Giménez
Journal:  Mol Divers       Date:  2010-01-10       Impact factor: 2.943

6.  QSPR Modeling and Experimental Determination of the Antioxidant Activity of Some Polycyclic Compounds in the Radical-Chain Oxidation Reaction of Organic Substrates.

Authors:  Veronika Khairullina; Yuliya Martynova; Irina Safarova; Gulnaz Sharipova; Anatoly Gerchikov; Regina Limantseva; Rimma Savchenko
Journal:  Molecules       Date:  2022-10-02       Impact factor: 4.927

Review 7.  Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?

Authors:  Andrzej Bak
Journal:  Int J Mol Sci       Date:  2021-05-14       Impact factor: 5.923

  7 in total

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