Enrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2

dc.contributor.authorWang, Bo
dc.contributor.authorBuchman, Cameron D.
dc.contributor.authorLi, Liwei
dc.contributor.authorHurley, Thomas D.
dc.contributor.authorMeroueh, Samy O.
dc.contributor.departmentDepartment of Biochemistry & Molecular Biology, IU School of Medicineen_US
dc.date.accessioned2016-02-24T15:09:08Z
dc.date.available2016-02-24T15:09:08Z
dc.date.issued2014-07-28
dc.description.abstractMolecular recognition is a complex process that involves a large ensemble of structures of the receptor and ligand. Yet, most structure-based virtual screening is carried out on a single structure typically from X-ray crystallography. Explicit-solvent molecular dynamics (MD) simulations offer an opportunity to sample multiple conformational states of a protein. Here we evaluate our recently developed scoring method SVMSP in its ability to enrich chemical libraries docked to MD structures of seven proteins from the Directory of Useful Decoys (DUD). SVMSP is a target-specific rescoring method that combines machine learning with statistical potentials. We find that enrichment power as measured by the area under the ROC curve (ROC-AUC) is not affected by increasing the number of MD structures. Among individual MD snapshots, many exhibited enrichment that was significantly better than the crystal structure, but no correlation between enrichment and structural deviation from crystal structure was found. We followed an innovative approach by training SVMSP scoring models using MD structures (SVMSPMD). The resulting models were applied to two difficult cases (p38 and CDK2) for which enrichment was not better than random. We found remarkable increase in enrichment power, particularly for p38, where the ROC-AUC increased by 0.30 to 0.85. Finally, we explored approaches for a priori identification of MD snapshots with high enrichment power from an MD simulation in the absence of active compounds. We found that the use of randomly selected compounds docked to the target of interest using SVMSP led to notable enrichment for EGFR and Src MD snapshots. SVMSP rescoring of protein–compound MD structures was applied for the search of small-molecule inhibitors of the mitochondrial enzyme aldehyde dehydrogenase 2 (ALDH2). Rank-ordering of a commercial library of 50 000 compounds docked to MD structures of ALDH2 led to five small-molecule inhibitors. Four compounds had IC50s below 5 μM. These compounds serve as leads for the design and synthesis of more potent and selective ALDH2 inhibitors.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationWang, B., Buchman, C. D., Li, L., Hurley, T. D., & Meroueh, S. O. (2014). Enrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2. Journal of Chemical Information and Modeling, 54(7), 2105–2116. http://doi.org/10.1021/ci5002026en_US
dc.identifier.issn1549-9596en_US
dc.identifier.urihttps://hdl.handle.net/1805/8468
dc.language.isoen_USen_US
dc.publisherAmerican Chemical Societyen_US
dc.relation.isversionof10.1021/ci5002026en_US
dc.relation.journalJournal of Chemical Information and Modelingen_US
dc.rightsIUPUI Open Access Policyen_US
dc.sourcePublisheren_US
dc.subjectAldehyde Dehydrogenaseen_US
dc.subjectchemistryen_US
dc.subjectmetabolismen_US
dc.subjectMolecular Docking Simulationen_US
dc.subjectSmall Molecule Librariesen_US
dc.titleEnrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2en_US
dc.typeArticleen_US
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