Rational choice of bioactive conformations through use of conformation analysis and 3-way partial least squares modeling

Abstract Comparative molecular field analysis (CoMFA) has become widely used in three-dimensional (3D) QSAR studies. Although CoMFA has been of general use, there are some critical problems in the proper application. A major problem of CoMFA, including most other 3D QSAR methodologies, is that the results are dependent on the chosen bioactive conformations and the corresponding alignment rules of molecules. Recently, we have proposed a novel method with a 3-way PLS formulation for solving the conformation/alignment problem in 3D QSAR studies [K. Hasegawa, M. Arakawa, K. Funatsu, Chemom. Intell. Lab. Syst., 47 (1999) 33–40]. The purpose of the present study is to demonstrate the general utility of our approach by applying to a real CoMFA data set. The data set of Protein-Tyrosine Kinase (PTK) inhibitors was used as a test sample. The possible 3D conformations of all molecules were generated by conformational analysis and they were characterized by field variables of CoMFA. To each unique conformation of the most active compound, one sample-variable sheet comprising of the most similar conformations was defined. The 3-way arrays for 3-way PLS analysis were created by collecting all sample-variable sheets. From the regression coefficient values of the 3-way PLS model, conformations largely contributing to inhibitory activity were selected and the resulting final CoMFA model could give the reasonable 3D coefficient contour maps.

[1]  Deborah A. Loughney,et al.  A comparison of progestin and androgen receptor binding using the CoMFA technique , 1992, J. Comput. Aided Mol. Des..

[2]  Tudor I. Oprea,et al.  Three-dimensional QSAR of human immunodeficiency virus (I) protease inhibitors. 1. A CoMFA study employing experimentally-determined alignment rules. , 1993, Journal of medicinal chemistry.

[3]  R. Leardi Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection , 1994 .

[4]  G Klebe,et al.  On the prediction of binding properties of drug molecules by comparative molecular field analysis. , 1993, Journal of medicinal chemistry.

[5]  Hugo Kubinyi,et al.  3D QSAR in drug design : theory, methods and applications , 2000 .

[6]  I. Kuntz Structure-Based Strategies for Drug Design and Discovery , 1992, Science.

[7]  Ulf Norinder,et al.  3D‐QSAR investigation of the tripos benchmark steroids and some protein‐tyrosine kinase inhibitors of styrene type using the TDQ approach , 1996 .

[8]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[9]  Age K. Smilde,et al.  Comments on multilinear PLS , 1997 .

[10]  Kimito Funatsu,et al.  GA Strategy for Variable Selection in QSAR Studies: GA-Based Region Selection for CoMFA Modeling , 1998, J. Chem. Inf. Comput. Sci..

[11]  George W. A. Milne,et al.  QSAR of conformationally flexible molecules: Comparative Molecular Field Analysis of protein-tyrosine kinase inhibitors , 1992, J. Comput. Aided Mol. Des..

[12]  A. Levitzki,et al.  Blocking of EGF-dependent cell proliferation by EGF receptor kinase inhibitors , 1988, Science.

[13]  J. Devillers Genetic algorithms in molecular modeling , 1996 .

[14]  J. Sufrin,et al.  Steric mapping of the L-methionine binding site of ATP:L-methionine S-adenosyltransferase. , 1981, Molecular pharmacology.

[15]  Kimito Funatsu,et al.  3D-QSAR study of insecticidal neonicotinoid compounds based on 3-way partial least squares model , 1999 .

[16]  R. Bro Multiway calibration. Multilinear PLS , 1996 .

[17]  Kimito Funatsu,et al.  GA Strategy for Variable Selection in QSAR Studies: Application of GA-Based Region Selection to a 3D-QSAR Study of Acetylcholinesterase Inhibitors , 1999, J. Chem. Inf. Comput. Sci..

[18]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[19]  C. Hansch,et al.  p-σ-π Analysis. A Method for the Correlation of Biological Activity and Chemical Structure , 1964 .

[20]  H. Kubinyi,et al.  3D QSAR in drug design. , 2002 .

[21]  K. Funatsu,et al.  Nonlinear CoMFA using QPLS as a Novel 3D-QSAR Approach , 1997 .

[22]  H Hanhijärvi,et al.  Comparative molecular field analysis of some clodronic acid esters. , 1991, Journal of medicinal chemistry.