Abductive reasoning applied to modeling chemical biology can only be made possible if both quality datasets and versatile cheminformatics and molecular modeling methods are available. Identifying compounds that are susceptible to metabolic degradation via CYP450 pathways, and identifying which major isoform is responsible is an ongoing problem. Here we demonstrate using a combination of 2D and 3D cheminformatics and modeling tools built into MOE (Molecular Operating Environment) how a rational workflow can be developed to predict CYP450 isoform specificity and even reactivity.<br/>Using a combination of carefully curated in vitro Cytochrome P450 data ( from the NCBI, the FDA, Flockhart's tables and the SuperCyp database) and a variety of modeling techniques implemented in MOE (binary classification trees, 2D-molecular fingerprints, binary QSAR, pharmacophores and molecular docking models) we developed efficient computational approaches to identify putative CYP450 interacting ligands using very simple models that required no more than 1-3 descriptors with accuracies &gt; 75%. In addition, reactivity models that use fingerprints derived from reactive functional groups (both MACCS-key and SmartCYP) were used to differentiate substrates from inhibitors, or more generally the propensity for CYP450 ligand reactivity.<br/><br/>The simple ligand-based and structure-based models can be used to develop tiered molecular triage workflows in KNIME using the MOE extensions for KNIME to interrogate large datasets of compounds for potential CYP450 binders with sub-type profiling capabilities, and propensity for biotransofrmation. We add that these multi-target approaches can be directly generalized to other protein families in which isoform-specificity and poly-pharmacological interactions are of interest. These studies place emphasis on the need for accurate curated data in addition to versatile and inter-operable modeling platforms, such as MOE, that enable multi-dimensional modeling approaches for interrogating chemical biology for large scale molecular profiling.

Multi-target molecular profiling using MOE: A CYP450 isoform selectivity case study

254th National Meeting (2017)

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