ABSTRACT
Here we describe the development of novel methods for compound evaluation and prioritization based on the structure-activity relationship matrix (SARM) framework. The SARM data structure allows automatic and exhaustive extraction of SAR patterns from data sets and their organization into a chemically intuitive scaffold/functional-group format. While SARMs have been used in the retrospective analysis of SAR discontinuity and identifying underexplored regions of chemistry space, there have been only a few attempts to apply SARMs prospectively in the prioritization of "close-in" analogs. In this work, three new ways of prioritizing virtual compounds based on SARMs are described: (1) matrix pattern-based prioritization, (2) similarity weighted, matrix pattern-based prioritization, and (3) analysis of variance based prioritization (ANV). All of these methods yielded high predictive power for six benchmark data sets (prediction accuracy R2 range from 0.63 to 0.82), yielding confidence in their application to new design ideas. In particular, the ANV method outperformed the previously reported SARM based method for five out of the six data sets tested. The impact of various SARM parameters were investigated and the reasons why SARM-based compound prioritization methods provide higher predictive power are discussed.
Subject(s)
Drug Discovery/methods , Informatics/methods , Structure-Activity RelationshipABSTRACT
BACKGROUND: The BD ProbeTec ET System is based on isothermal strand displacement amplification (SDA) of target nucleic acid coupled with homogeneous real-time detection using fluorescent probes. We have developed a novel, rapid method using this platform that incorporates a universal detection format for identification of single-nucleotide polymorphisms (SNPs) and other genotypic variations. METHOD: The system uses a common pair of fluorescent Detector Probes in conjunction with unlabeled allele-specific Adapter Primers and a universal buffer chemistry to permit analysis of multiple SNP loci under generic assay conditions. We used Detector Probes labeled with different dyes to facilitate differentiation of two alternative alleles in a single reaction with no postamplification manipulation. We analyzed six SNPs within the human beta(2)-adrenergic receptor (beta(2)AR) gene, using whole blood, buccal swabs, and urine samples, and compared results with those obtained by DNA sequencing. RESULTS: Unprocessed whole blood was successfully genotyped with as little as 0.1-1 micro L of sample per reaction. All six beta(2)AR assays were able to accommodate >/==" BORDER="0">20 micro L of unprocessed whole blood. For the 14 individuals tested, genotypes determined with the six beta(2)AR assays agreed with DNA sequencing results. CONCLUSION: SDA-based allelic differentiation on the BD ProbeTec ET System can detect SNPs rapidly, using whole blood, buccal swabs, or urine.