MOLECULAR SIMILARITY INDEXES IN A COMPARATIVE-ANALYSIS (COMSIA) OF DRUG MOLECULES TO CORRELATE AND PREDICT THEIR BIOLOGICAL-ACTIVITY

An alternative approach is reported to compute property fields based o n similarity indices of drug molecules that have been brought into a c ommon alignment. The fields of different physicochemical properties us e a Gaussian-type distance dependence, and no singularities occur at t he atomic positions. Accordingly, no arbitrary definitions of cutoff l imits and deficiencies due to different slopes of the fields are encou ntered. The fields are evaluated by a PLS analysis similar to the CoMF A formalism. Two data sets of steroids binding to the corticosteroid-b inding-globulin and thermolysin inhibitors were analyzed in terms of t he conventional CoMFA method (Lennard-Jones and Coulomb potential fiel ds) and the new comparative molecular similarity indices analysis(CoMS IA). Models of comparative statistical significance were obtained. Fie ld contribution maps were produced for the different models. Due to cu toff settings in the CoMFA fields and the steepness of the potentials close to the molecular surface, the CoMFA maps are often rather fragme ntary and not contiguously connected. This makes their interpretation difficult. The maps obtained by the new CoMSIA approach are superior a nd easier to interpret. Whereas the CoMFA maps denote regions apart fr om the molecules where interactions with a putative environment are to be expected, the CoMSIA maps highlight those regions within the area occupied by the ligand skeletons that require a particular physicochem ical property important for activity. This is a more significant guide to trace the features that really matter especially with respect to t he design of novel compounds.