Discovery Studio

In this article, we will delve into the fascinating world of Discovery Studio, exploring its different facets and meanings. Discovery Studio is a topic that has aroused the interest of many people throughout history, since it has a relevance that transcends borders and cultures. From its origins to its influence today, Discovery Studio has been the subject of study and debate, generating endless opinions and reflections. Along these lines, we will delve into the complexity of Discovery Studio, analyzing its impact in different contexts and its relevance in today's society.

Discovery Studio is a suite of software for simulating small molecule and macromolecule systems. It is developed and distributed by Dassault Systemes BIOVIA[1] (formerly Accelrys).

The product suite has a strong academic collaboration programme,[2] supporting scientific research and makes use of a number of software algorithms developed originally in the scientific community, including CHARMM,[3] MODELLER,[4] DELPHI,[5] ZDOCK,[6] DMol3[7][8] and more.

Scope

Discovery Studio provides software applications covering the following areas:

See also

References

  1. ^ https://www.3dsbiovia.com/ [bare URL]
  2. ^ http://accelrys.com/innovation/academic-collaborator-program/ [bare URL]
  3. ^ Brooks B. R., Brooks III C. L., Mackerell A. D., Nilsson L., Petrella R. J., Roux B., Won Y., Archontis G., Bartels C., Boresch S., Caflisch A., Caves L., Cui Q., Dinner A. R., Feig M., Fischer S., Gao J., Hodoscek M., Im W., Kuczera K., Lazaridis T., Ma J., Ovchinnikov V., Paci E., Pastor R. W., Post C. B., Pu J. Z., Schaefer M., Tidor B., Venable R. M., Woodcock H. L., Wu X., Yang W., York D. M. and Karplus M. CHARMM: The Biomolecular simulation Program, J. Comput. Chem. 2009, 30, 1545-1615.
  4. ^ Eswar N., Marti-Renom M.A., Webb B., Madhusudhan M.S., Eramian D., Shen M., Pieper U., Sali A. Comparative Protein Structure Modeling With MODELLER. Current Protocols in Bioinformatics, John Wiley & Sons, Inc., 2006, Supplement 15, 5.6.1-5.6.30.
  5. ^ W.Rocchia, E.Alexov, and B.Honig. Extending the Applicability of the Nonlinear Poisson-Boltzmann Equation: Multiple Dielectric Constants and Multivalent Ions. J. Phys. Chem. B, 2001, 105, 6507-6514.
  6. ^ Chen R., Weng Z. ZDOCK: An Initial-stage Protein-Docking Algorithm. Proteins 2003, 52, 80-87.
  7. ^ Matsuzawa N., Seto J., DixonD. A., J. Phys. Chem. A, 1997, 101, 9391.
  8. ^ Delley Bi, J. Chem. Phys., 1990, 92, 508; ibid, 1991, 94, 7245; ibid, 2000, 7756.
  9. ^ Sutter A., Jiabo L., Maynard A.J., Goupil A., Luu T., Katalin N., New Features that Improve the Pharmacophore Tools from Accelrys
  10. ^ Luu T., Malcolm N., Nadassy K., Pharmacophore Modeling Methods in Focused Library Selection -Applications in the Context of a New Classification Scheme, Comb. Chem. & High Thr. Screening, 2011, 14(6), pp. 488-499(12)
  11. ^ Haider M.K., Bertrand H.-O., Hubbard R.E., Predicting Fragment Binding Poses Using a Combined MCSS MM-GBSA Approach, J. Chem. Inf. Model., 2011, 51 (5), pp 1092–1105
  12. ^ Corradia V., Mancinib M, Santuccib M.A., Carlomagnoc T., Sanfelicec D., Moria M., Vignarolia G., Falchia F., Manettia F., Radia M., Botta M., Computational techniques are valuable tools for the discovery of protein–protein interaction inhibitors: The 14-3-3σ case
  13. ^ Almagro J.C., Beavers M.P., Hernandez-Guzman F., Maier J., Shaulsky J., Butenhof K., Labute P., Thorsteinson N., Kelly K., Teplyakov A., Luo J., Sweet R., Gilliland G.L., Antibody modeling assessment, Proteins: Structure, Function, and Bioinformatics, 2011, 79(11), pages 3050–3066.

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