Discovery Studio

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:

Simulations
- Including Molecular Mechanics, Molecular Dynamics, Quantum Mechanics
- For molecular mechanics based simulations: Include implicit and explicit-based solvent models and membrane models
- Also includes the ability to perform hybrid QM/MM calculations
Ligand Design
- Including tools for enumerating molecular libraries and library optimization
Pharmacophore modeling
- Including creation, validation and virtual screening^[9]^[10]
Structure-based Design
- Including tools for fragment-based placement and refinement,^[11] receptor-ligand docking and pose refinement, de novo design
Macromolecule design and validation
Macromolecule engineering
- Specialist tools for protein-protein docking^[12]
- Specialist tools for Antibody design^[13] and optimization
- Specialist tools for membrane-bound proteins, including GPCRs
QSAR
- Covering methods such as multiple linear regression, partial least squares, recursive partitioning, Genetic Function approximation and 3D field-based QSAR
ADME
Predictive toxicity

References

^ https://www.3dsbiovia.com/ ^{[bare URL]}
^ http://accelrys.com/innovation/academic-collaborator-program/ ^{[bare URL]}
^ 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.
^ 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.
^ 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.
^ Chen R., Weng Z. ZDOCK: An Initial-stage Protein-Docking Algorithm. Proteins 2003, 52, 80-87.
^ Matsuzawa N., Seto J., DixonD. A., J. Phys. Chem. A, 1997, 101, 9391.
^ Delley Bi, J. Chem. Phys., 1990, 92, 508; ibid, 1991, 94, 7245; ibid, 2000, 7756.
^ Sutter A., Jiabo L., Maynard A.J., Goupil A., Luu T., Katalin N., New Features that Improve the Pharmacophore Tools from Accelrys
^ 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)
^ 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
^ 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しぐま case
^ 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.

External links

Accelrys.com
Discovery Studio
Supporting free software tools: Discovery Studio Visualizer and ActiveX Controls

Recent News Articles

[1] ttps://www.3dsbiovia.com/ ^{[bare URL]}

[2] ttp://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しぐま 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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Discovery Studio

Contents

Scope

See also

References

External links

Recent News Articles