title: Towards a MIP-based alignment and docking in computer-aided drug design.
abstract: Structural alignment of ligands in their biological conformation is a crucial step in the building of pharmacophoric models in structure-based drug design. In addition, docking algorithms are limited in some cases by the quality of the scoring functions and the limited flexibility of the environment that the different programs allow. On the other hand, GRID molecular interaction potentials (MIPs) have been used for a long time in 3D-QSAR studies. However, in most of these studies the alignment of the molecules is performed on the basis of geometrical or physico-chemical criteria that differ from the MIPs used in the partial least squares statistical analysis. We have previously developed a method to use the same scoring function for the molecular alignment and for 3D-QSAR studies. This methodology, based on the use of GRID potentials, consists in the weighted averaging of similarities of the relevant MIPs of the molecules to be aligned. Here we present a method to obtain the weights for the different GRID probes in the average based on the structural information on protein-ligand complexes for relevant systems. The method, implemented in MIPSIM, is shown to yield good accuracy in the prediction of the alignments for two systems: a set of three inhibitors of dihydrofolate reductase and a set of fifteen non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). The smooth GRID potentials are shown to capture the flexible character of the active site, as opposed to traditional docking scoring energy functions.
authors.affiliation: Research Group on Biomedical Informatics (GRIB)-IMIM/UPF, Barcelona, Spain.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Barbany
authors.forename: Hugo
authors.initials: H
authors.lastname: Gutiérrez-de-Terán
authors.forename: Ferran
authors.initials: F
authors.lastname: Sanz
authors.forename: Jordi
authors.initials: J
authors.lastname: Villà-Freixa
mesh_terms: D001665:Binding Sites; D017076:Computer-Aided Design; D015195:Drug Design; D005493:Folic Acid Antagonists / Q000737:chemistry / Q000378:metabolism; D054303:HIV Reverse Transcriptase / Q000737:chemistry / Q000378:metabolism; D008024:Ligands; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding / Q000502:physiology; D011487:Protein Conformation; D021281:Quantitative Structure-Activity Relationship; D018894:Reverse Transcriptase Inhibitors / Q000737:chemistry / Q000378:metabolism; D012984:Software; D013762:Tetrahydrofolate Dehydrogenase / Q000737:chemistry / Q000378:metabolism; D013816:Thermodynamics
chemical_list: D005493:Folic Acid Antagonists; D008024:Ligands; D018894:Reverse Transcriptase Inhibitors; D013762:Tetrahydrofolate Dehydrogenase; D054303:HIV Reverse Transcriptase