J Chem Inf Model - Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2.


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Molecular 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 50000 compounds docked to MD structures of ALDH2 led to five small-molecule inhibitors. Four compounds had IC50s below 5 ?M. These compounds serve as leads for the design and synthesis of more potent and selective ALDH2 inhibitors.

Resumo Limpo

molecular recognit complex process involv larg ensembl structur receptor ligand yet structurebas virtual screen carri singl structur typic xray crystallographi explicitsolv molecular dynam md simul offer opportun sampl multipl conform state protein evalu recent develop score method svmsp abil enrich chemic librari dock md structur seven protein directori use decoy dud svmsp targetspecif rescor method combin machin learn statist potenti find enrich power measur area roc curv rocauc affect increas number md structur among individu md snapshot mani exhibit enrich signific better crystal structur correl enrich structur deviat crystal structur found follow innov approach train svmsp score model use md structur svmspmd result model appli two difficult case p cdk enrich better random found remark increas enrich power particular p rocauc increas final explor approach apriori identif md snapshot high enrich power md simul absenc activ compound found use random select compound dock target interest use svmsp led notabl enrich egfr src md snapshot svmsp rescor proteincompound md structur appli search smallmolecul inhibitor mitochondri enzym aldehyd dehydrogenas aldh rankord commerci librari compound dock md structur aldh led five smallmolecul inhibitor four compound ic m compound serv lead design synthesi potent select aldh inhibitor

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