FILO (Field Interaction Ligand Optimization): A simplex strategy for searching the optimal ligand interaction field in drug design

A method (FILO, Field Interaction Ligand Optimization) for obtaining the optimal molecular interaction field was developed on the basis of the Simplex optimization procedure applied to a matrix of interaction energies obtained by performing a GRID computation on a suitable data set. The FILO procedure was tested on a set of nine HIV-1 protease inhibitors with known crystal structures. The results of FILO consist of the optimal molecular interaction field of a putative new ligand with optimal binding affinity. The final FILO model yields R2 and R2CV values of 0.993 and 0.936, respectively, and finds eight negative and four positive interaction nodes for the OH probe taken as an example. The eight H bonding interactions pointed out by FILO identified well the binding site AA-residues Gly A27, Asp A29, water 501, Gly B48 and Asp A25 of HIV-1 protease.

[1]  G J Williams,et al.  The Protein Data Bank: a computer-based archival file for macromolecular structures. , 1977, Journal of molecular biology.

[2]  M. Murcko,et al.  Crystal Structure of HIV-1 Protease in Complex with Vx-478, a Potent and Orally Bioavailable Inhibitor of the Enzyme , 1995 .

[3]  D. Walters,et al.  Genetically evolved receptor models: a computational approach to construction of receptor models. , 1994, Journal of medicinal chemistry.

[4]  C. B. Lucasius,et al.  Understanding and using genetic algorithms Part 2. Representation, configuration and hybridization , 1994 .

[5]  Dale J. Kempf,et al.  Influence of Stereochemistry on Activity and Binding Modes for C2 Symmetry-Based Diol Inhibitors of HIV-1 Protease , 1994 .

[6]  A. Doweyko,et al.  Three-dimensional pharmacophores from binding data. , 1994, Journal of medicinal chemistry.

[7]  D. Rogers,et al.  Receptor surface models. 2. Application to quantitative structure-activity relationships studies. , 1995, Journal of medicinal chemistry.

[8]  M. Hahn Receptor surface models. 1. Definition and construction. , 1995, Journal of medicinal chemistry.

[9]  James P. Snyder,et al.  Pseudoreceptor Modeling: The Construction of Three-Dimensional Receptor Surrogates , 1995 .

[10]  G. Cruciani,et al.  Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D‐QSAR Problems , 1993 .

[11]  A. Vedani,et al.  Pseudo-receptor modeling: a new concept for the three-dimensional construction of receptor binding sites. , 1993, Journal of receptor research.

[12]  R. DesJarlais,et al.  A check on rational drug design: crystal structure of a complex of human immunodeficiency virus type 1 protease with a novel gamma-turn mimetic inhibitor. , 1995, Journal of medicinal chemistry.

[13]  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.

[14]  P. Goodford A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.

[15]  A M Hassell,et al.  Hydroxyethylene isostere inhibitors of human immunodeficiency virus-1 protease: structure-activity analysis using enzyme kinetics, X-ray crystallography, and infected T-cell assays. , 1992, Biochemistry.

[16]  P Murray-Rust,et al.  X-ray crystallographic studies of a series of penicillin-derived asymmetric inhibitors of HIV-1 protease. , 1994, Biochemistry.

[17]  R. DesJarlais,et al.  Inhibition of human immunodeficiency virus-1 protease by a C2-symmetric phosphinate. Synthesis and crystallographic analysis. , 1993, Biochemistry.

[18]  M Pastor,et al.  Smart region definition: a new way to improve the predictive ability and interpretability of three-dimensional quantitative structure-activity relationships. , 1997, Journal of medicinal chemistry.

[19]  Gerd Folkers,et al.  PrGen: Pseudoreceptor Modeling Using Receptor‐mediated Ligand Alignment and Pharmacophore Equilibration , 1998 .