1. Protein Flexibility in Virtual Screening: The BACE-1 Case Study
- Author
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Vincenza Andrisano, Valeria La Pietra, David S. Goodsell, Angela De Simone, Sandro Cosconati, Luciana Marinelli, Francesca Mancini, Arthur J. Olson, Ettore Novellino, Francesco Saverio Di Leva, S., Cosconati, Marinelli, Luciana, Di Leva, Francesco Saverio, LA PIETRA, Valeria, A., De Simone, F., Mancini, V., Andrisano, Novellino, Ettore, D. S., Goodsell, A. J., Olson, Cosconati S., Marinelli L., Di Leva F.S., La Pietra V., De Simone A., Mancini F., Andrisano V., Novellino E., Goodsell D.S., Olson A.J., Cosconati, Sandro, Marinelli, L, Di Leva, F, La Pietra, V, De Simone, A, Mancini, F, Andrisano, V, Novellino, E, Goodsell, D, and Olson, A. J.
- Subjects
STRUCTURE-BASED DESIGN ,FLEXIBLE SIDE-CHAINS ,MEMAPSIN-2 BETA-SECRETASE ,APP CLEAVING ENZYME ,DRUG DESIGN ,MOLECULAR RECOGNITION ,ALZHEIMERS-DISEASE ,LIGAND DOCKING ,SOFT DOCKING ,ACTIVE-SITE ,Protein Conformation ,General Chemical Engineering ,Library and Information Sciences ,Machine learning ,computer.software_genre ,Crystallography, X-Ray ,Ligands ,Molecular Docking Simulation ,Article ,Antiparkinson Agents ,User-Computer Interface ,Alzheimer Disease ,High-Throughput Screening Assays ,Drug Discovery ,Fluorescence Resonance Energy Transfer ,Aspartic Acid Endopeptidases ,Humans ,Simulation ,Virtual screening ,Binding Sites ,Chemistry ,business.industry ,Drug discovery ,General Chemistry ,Grid ,Computer Science Applications ,Weighting ,Thermodynamics ,Artificial intelligence ,Amyloid Precursor Protein Secretases ,business ,computer ,Algorithms ,Databases, Chemical ,Protein Binding - Abstract
Simulating protein flexibility is a major issue in the docking-based drug-design process for which a single methodological solution does not exist. In our search of new anti-Alzheimer ligands, we were faced with the challenge of including receptor plasticity in a virtual screening campaign aimed at finding new β-secretase inhibitors. To this aim, we incorporated protein flexibility in our simulations by using an ensemble of static X-ray enzyme structures to screen the National Cancer Institute database. A unified description of the protein motion was also generated by computing and combining a set of grid maps using an energy weighting scheme. Such a description was used in an energy-weighted virtual screening experiment on the same molecular database. Assessment of the enrichment factors from these two virtual screening approaches demonstrated comparable predictive powers, with the energy-weighted method being faster than the ensemble method. The in vitro evaluation demonstrated that out of the 32 tested ligands, 17 featured the predicted enzyme inhibiting property. Such an impressive success rate (53.1%) demonstrates the enhanced power of the two methodologies and suggests that energy-weighted virtual screening is a more than valid alternative to ensemble virtual screening given its reduced computational demands and comparable performance. © 2012 American Chemical Society.
- Published
- 2012