Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization
SILCS-MC validation highlights Full text
New SILCS-MC Study Demonstrates Improved Performance with Machine Learning Optimization
New SILCS-MC Study Demonstrates Improved Performance with Machine Learning Optimization May 16, 2019, Baltimore, MD – SilcsBio, a company that develops commercial software and related services for structure-based drug design, today announced that established Site-identification by ligand competitive saturation-Monte Carlo (SILCS-MC) approaches were applied to seven protein targets and 551 ligands, correctly predicting[…]
SilcsBio, LLC Announces Release of CGenFF 2.3.0
Baltimore, MD, 26 April, 2019 In ongoing efforts to improve the coverage of the CGenFF program, version 2.3.0 of the CGenFF program improves support for a variety of molecules via explicit parametrization of the molecules outlined below and features improvements for halogen-protein interactions. Molecules explicitly parametrized The functional groups in these molecules were previously accessible[…]
SilcsBio, LLC Receives NIH Funding to Expand Offerings in Biologics
FOR IMMEDIATE RELEASE: April 11, 2019 Ken Malone SilcsBio, LLC 410.929.2305 Ken.Malone@silcsbio.com SilcsBio, LLC Receives NIH Funding to Expand Offerings in Biologics Baltimore, Maryland: SilcsBio, LLC announced today a $225,000 award from the National Institutes of Health to expand on its broadly used software, SILCS, to enable its use with biological therapeutics, especially for[…]
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