Maria E Mavrogeni1, Filippos Pronios1, Danae Zareifi2, Sofia Vasilakaki1, Olivier Lozach3, Leonidas Alexopoulos4, Laurent Meijer5, Vassilios Myrianthopoulos1,6, Emmanuel Mikros1,6. 1. Department of Pharmaceutical Chemistry, School of Pharmacy, University of Athens, Panepistimiopolis Zografou, 157 71 Athens, Greece. 2. ProtATonce Ltd, Dimokritos Science Park, Agia Paraskevi, 153 43 Athens, Greece. 3. Laboratoire Chimie Electrochimie Moléculaires et Chimie Analytique, University of Brest, 29238 Brest, France. 4. School of Mechanical Engineering, National Technical University of Athens, 157 80 Athens, Greece. 5. ManRos Therapeutics, Perharidy Research Center, 29680 Roscoff, Bretagne, France. 6. 'Athena' Research & Innovation Center, 151 25 Athens, Greece.
Abstract
BACKGROUND: Virtual screening is vital for contemporary drug discovery but striking performance fluctuations are commonly encountered, thus hampering error-free use. Results and Methodology: A conceptual framework is suggested for combining screening algorithms characterized by orthogonality (docking-scoring calculations, 3D shape similarity, 2D fingerprint similarity) into a simple, efficient and expansible python-based consensus ranking scheme. An original experimental dataset is created for comparing individual screening methods versus the novel approach. Its utilization leads to identification and phosphoproteomic evaluation of a cell-active DYRK1α inhibitor. CONCLUSION: Consensus ranking considerably stabilizes screening performance at reasonable computational cost, whereas individual screens are heavily dependent on calculation settings. Results indicate that the novel approach, currently available as a free online tool, is highly suitable for prospective screening by nonexperts.
BACKGROUND: Virtual screening is vital for contemporary drug discovery but striking performance fluctuations are commonly encountered, thus hampering error-free use. Results and Methodology: A conceptual framework is suggested for combining screening algorithms characterized by orthogonality (docking-scoring calculations, 3D shape similarity, 2D fingerprint similarity) into a simple, efficient and expansible python-based consensus ranking scheme. An original experimental dataset is created for comparing individual screening methods versus the novel approach. Its utilization leads to identification and phosphoproteomic evaluation of a cell-active DYRK1α inhibitor. CONCLUSION: Consensus ranking considerably stabilizes screening performance at reasonable computational cost, whereas individual screens are heavily dependent on calculation settings. Results indicate that the novel approach, currently available as a free online tool, is highly suitable for prospective screening by nonexperts.
Authors: Thomas A Halgren; Robert B Murphy; Richard A Friesner; Hege S Beard; Leah L Frye; W Thomas Pollard; Jay L Banks Journal: J Med Chem Date: 2004-03-25 Impact factor: 7.446
Authors: Richard A Friesner; Jay L Banks; Robert B Murphy; Thomas A Halgren; Jasna J Klicic; Daniel T Mainz; Matthew P Repasky; Eric H Knoll; Mee Shelley; Jason K Perry; David E Shaw; Perry Francis; Peter S Shenkin Journal: J Med Chem Date: 2004-03-25 Impact factor: 7.446
Authors: F Vázquez; G Hastings; M A Ortega; T F Lane; S Oikemus; M Lombardo; M L Iruela-Arispe Journal: J Biol Chem Date: 1999-08-13 Impact factor: 5.157
Authors: Stéphane Bach; Marie Knockaert; Jens Reinhardt; Olivier Lozach; Sophie Schmitt; Blandine Baratte; Marcel Koken; Stephen P Coburn; Lin Tang; Tao Jiang; Dong-Cai Liang; Hervé Galons; Jean-Francois Dierick; Lorenzo A Pinna; Flavio Meggio; Frank Totzke; Christoph Schächtele; Andrea S Lerman; Amancio Carnero; Yongqin Wan; Nathanael Gray; Laurent Meijer Journal: J Biol Chem Date: 2005-06-23 Impact factor: 5.157