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BIOVIA DISCOVERY STUDIO® 2016 COMPREHENSIVE MODELING and SIMULATIONS for LIFE SCIENCES Datasheet

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BIOVIA DISCOVERY STUDIO® 2016 COMPREHENSIVE MODELING and SIMULATIONS for LIFE SCIENCES Datasheet BIOVIA DISCOVERY STUDIO® 2016 COMPREHENSIVE MODELING AND SIMULATIONS FOR LIFE SCIENCES Datasheet ACCURATELY Drug discovery is a multi-objective optimization. Scientists have to optimize both biochemical potency and characteristics such as ADME and toxicity. The latest PREDICT LIGAND release of BIOVIA’s predictive science application, Discovery Studio®, continues the BINDING evolution of new science in its market-leading CHARMm molecular simulations engine. Built on BIOVIA Foundation™, Discovery Studio® is uniquely positioned as ENERGIES the most comprehensive, collaborative modeling and simulation application for Life Sciences discovery research. DISCOVERY STUDIO 2016 Part of the 2016 BIOVIA product release series, Discovery Studio 2016 continues to deliver key new CHARMm-based molecular simulations. NEW AND ENHANCED SCIENCE • New! Steered Molecular Dynamics: Developed and validated in academia by members of the CHARMM Developer community2,3, the CHARMM AFM (Atomic Force Microscopy) function has been included in the latest release of Discovery Studio CHARMm • Apply a pull force to a molecular system to: • Estimate the ligand binding free energy • Study the conformational details of the ligand unbinding process • Investigate protein unfolding or conformational • Major DMol3 Performance Improvement: The latest release changes of the density functional theory program DMol3, version • Two protocols have been included to enable the simulation 2016, includes dramatic performance improvements, both in of protein or protein-ligand complexes while applying terms of memory usage and core scaling: steering forces to the system: • Improved control over the use of memory and disk access • Steered Molecular Dynamics (SMD) gives performance gains • Calculate Free Energy from Steering Forces • New parallel scaling library gives large performance gains on multicore computers • Parallelization of storage space for grid-based quantities provides significant reduction of the memory used per core in highly parallel situations • Tkatchenko-Scheffler dispersion corrections have been extended to more elements in the Periodic Table • TopKat® QMRF Reports6: All TopKat Toxicity Models have been submitted to the European Commission Joint Research Center (JRC) for publication as QSAR Model Report Format (QMRF) documents PARTNER SCIENCE • CHARMm: Incorporates the latest release of the academic CHARMM, version c40b11 Figure 1. Explicit solvent based Steered Molecular Dynamics (SMD) • GOLD Support: Dock Ligands (GOLD) now includes support simulation of 2-propylphenol in complex with T4 lysozyme (PDB for the latest release of CCDC GOLD, version 5.37 ID: 3HTB) showing the pull force vector between the protein and 8 the ligand. • NAMD: Distributed with the CPU edition, version 2.9 • MODELER: Incorporates the latest release of the academic • Improved Conformer Minimization Performance: The MODELLER, version 9.159 CHARMm-based ligand-conformation minimization speed was improved by over an order of magnitude DATABASES • Protocols such as, ‘Generate Conformations’ and ‘Calculate • The RCSB ligand database was updated for the RCSB Binding Energies’ benefit from this enhancement Structure Search protocol (October 2015, 20861 entries) • ANTIBODY has been updated to include the latest antibody • Additional CHARMm Forcefield Improvements template structures from the PDB • Updated ‘Assign Forcefield Types (Prototype)’ protocol: Phosphoserine, phosphotyrosine, and phosphothreonine PLATFORM patches have been added to the charmm36 forcefield to • Compatibility: Discovery Studio 2016 is built on and supports allow proper typing of those residues the latest release of BIOVIA Pipeline Pilot, version 2016 • Atoms are now reordered to be consistent with the CHARMm atom order to enable input to subsequent CHARMm simulation tasks REFERENCES 1. Brooks B. R., Brooks III C. L., Mackerell A. D., Karplus M., et al, J. Comp. Chem., 2009, 30, 1545-1615. 2. Paci E., et al., J. Mol. Biol., 2001, 314, 589-605. 3. Paci E. & Karplus M., Proc. Nat. Acad. Sci., 2000, 97, 6521-6526. 4. Delley B., J. Chem. Phys., 1990, 92, 508. 5. Delley B., J. Chem. Phys., 2000, 113, 7756. 6. http://qsardb.jrc.it/qmrf/ 7. GOLD is available from the Cambridge Crystallographic Data Centre: http://www.ccdc.cam.ac.uk/products/life_sciences/gold/ A valid GOLD license is required to run GOLD and GOLDscore. 8. Phillips J.C., Braun R., Wang W., Gumbart J., Tajkhorshid E., Villa E., Chipot C, Skeel C.D., Kale L., and Schulten K., J. Comp. Chem., 2005, 26, 1781-1802. 9. Eswar N., Marti-Renom M. A. Webb B., Madhusudhan M. S., Eramian D., Shen M., Pieper U., Sali A., Current Protocols in Bioinformatics, John Wiley & Sons, Inc., 2006, Supplement 15, 5.6.1-5.6.30. 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