Quantitative Series Enrichment Analysis (QSEA): a novel procedure for 3D-QSAR analysis

Abstract

A novel procedure is proposed for 3D-QSAR analysis. The composition of 16 published QSAR datasets has been examined using Quantitative Series Enrichment Analysis (QSEA). The procedure is based on topomer technologies. A heatmap display in combination with topomer CoMFA and a novel series trajectory analysis revealed critical information for the assembly of structures into meaningful series. Global and local centroid structures can be determined from a similarity distance matrix and build the origins for stepwise model building by increasing the similarity radius around the centroid nucleus. The results indicate that the new procedure allows determination of whether compounds belong to an emerging structure-activity relationship and which compounds can be predicted within reliable limits.

Toluidinesulfonamide Hypoxia-Induced Factor 1 Inhibitors: Alleviating Drug–Drug Interactions through Use of PubChem Data and Comparative Molecular Field Analysis Guided Synthesis

“…Apart from the inconclusive result from HQSAR, these models did not allow for structural interpretation. Therefore, we explored the use of the quantitative series enrichment analysis (QSEA) method for deriving local 3D-SAR from chemical biology data . In QSEA, the ligands of the data set are organized around its centroid, and topomer CoMFA models are being created, starting with the centroid compound and its two nearest neighbors and then iteratively expanding the training set one by one with the next similar compound, each time creating a new topomer CoMFA.…”

Template CoMFA Applied to 116 Biological Targets

“…A first example of such a topomer-enabled approach is QSEA. 13 As another example, one set of studies underway is calibrating how adding a few templates will automatically generate models more statistically comparable to the 3D-QSAR models published, inherently "multitemplate", for such thoroughly studied targets as ACE, 4 D2A, 14 and thermolysin. 15 If this approach shows promise, then targets for future exploration, having broadest therapeutic relevance, include ion channels and cytochromes.…”

“…However, perhaps only now with template CoMFA is it practical to generate such multiple 3D-QSAR models, by varying and extending the templates, including their relative alignments, and also the training set compositions. A first example of such a topomer-enabled approach is QSEA . As another example, one set of studies underway is calibrating how adding a few templates will automatically generate models more statistically comparable to the 3D-QSAR models published, inherently “multitemplate”, for such thoroughly studied targets as ACE, D2A, and thermolysin .…”

The inevitable QSAR renaissance

“…And fortunately, the almost unprecedentedly accurate predictions so far reported in lead optimization projects using “topomer CoMFA”, specifically a standard deviation of 0.6 between predicted and found pA50’s, over 144 made-and-tested compounds from four different organizations [13–16], if continued, should further encourage its widespread application. The exceptional speed and objectivity of the topomer CoMFA protocol is also inspiring new methodological opportunities, such as virtual screening for R-groups (see footnote 3), with hits being accompanied by potency predictions, and “QSEA” [15, 17], which simplifies exploration of a so far oft-neglected issue, how a specific QSAR varies with its training set composition. Also emergent at this writing is “template CoMFA” [18], which provides the CADD expert with control over the conformation(s) used to generate a 3D-QSAR, for example in the form of a receptor-bound conformation, while retaining the desirable attributes of topomer CoMFA.…”