title: Cross-validated R2-guided region selection for comparative molecular field analysis: a simple method to achieve consistent results.
abstract: Comparative Molecular Field Analysis (CoMFA) is one of the most powerful modern tools for quantitative structure-activity relationship studies. The CoMFA predictability is conventionally characterized by a cross-validated correlation coefficient R2 (q2). Our CoMFA investigation of 4 datasets, including 7 cephalotaxine esters, 20 5-HT1A receptor ligands, 59 inhibitors of HIV protease, and 21 steroids reveals that the q2 value is sensitive to the overall orientation of superimposed molecules on a computer terminal and can vary by as much as 0.5q2 units when the orientation is varied by systematic rotation. To optimize CoMFA, we have developed a new routine, cross-validated R2-guided region selection (q2-GRS). We first subdivide the rectangular lattice obtained initially with conventional CoMFA into 125 small boxes and perform 125 independent analyses using probe atoms placed within each box with the step size of 1.0 A. We then select only those small boxes for which a q2 is higher than a specified optimal cutoff value. Finally, we repeat CoMFA with the union of small boxes selected at the previous step. Four datasets described above were used to validate this new q2-GRS routine. In each case we have obtained an orientation-independent, high q2, exceeding the one obtained with the conventional CoMFA. This method shall be used routinely in the future CoMFA studies to guarantee the reproducibility of the reported q2 values.
authors.affiliation: Laboratory for Molecular Modeling, School of Pharmacy, University of North Carolina, Chapel Hill 27599, USA.
authors.forename: S J
authors.initials: SJ
authors.lastname: Cho
authors.forename: A
authors.initials: A
authors.lastname: Tropsha
mesh_terms: D000465:Algorithms; D015195:Drug Design; D017320:HIV Protease Inhibitors / Q000737:chemistry; D006248:Harringtonines / Q000737:chemistry; D000077863:Homoharringtonine; D008024:Ligands; D011985:Receptors, Serotonin / Q000187:drug effects; D012984:Software; D013256:Steroids / Q000737:chemistry; D013329:Structure-Activity Relationship
chemical_list: D017320:HIV Protease Inhibitors; D006248:Harringtonines; D008024:Ligands; D011985:Receptors, Serotonin; D013256:Steroids; D000077863:Homoharringtonine