REGISTRATION LINK: https://connect.discoveracs.org/CENWebinar_SilcsBio_9_14_23?partnerref=SilcsBio

CADD in an industrial setting requires high accuracy with maximum 
throughput to drive the drug discovery process. The SILCS technology, 
in conjunction with the CGenFF program, attains this at an unprecedented 
level through the use of pre-computed FragMaps that can be used throughout
the drug discovery and optimization process. This includes the ability to 
iteratively improve the predictability of the FragMaps during the 
optimization process as well as extract atomic detail contributions to
ligand binding that can facilitate interpretation of experimental data, 
offering an additional competitive advantage. 

The inclusion of contributions from protein or RNA flexibility, desolvation 
contributions of the protein and RNA as well as the ligands and 
ligand-protein interactions in the precomputed SILCS FragMaps yields the 
combination of high accuracy and computational efficiency. This information
 content offers the ability to identify novel allosteric sites, perform 
virtual screening through both pharmacophore and SILCS docking approaches, 
rapidly estimate relative ligand binding affinities without requirement of
 an experimental structure of the lead compound. Beyond small molecule drug
 development the comprehensive nature of the SILCS FragMaps allows for 
analysis of protein-protein interactions that may be combined with docking
 of excipients, buffers and ions to the full protein surface to guide the 
formulation of protein-based biologics including monoclonal antibodies. 

Key Learning Objectives:
- SILCS is based on pre-computation of an ensemble, termed FragMaps, 
offering a 1000-fold or more savings in time and resources over competing
CADD technologies at a level of accuracy consistent with FEP.
- Pre-computed FragMaps can be utilized iteratively throughout all aspects
of a medicinal chemistry campaign including the ability to iteratively 
improve the predictability of the FragMaps.
- SILCS FragMaps include contributions from protein flexibility and 
desolvation allowing for the identification of novel allosteric binding
sites as well as taking into account local protein or RNA conformational 
changes to binding estimates.

Who Should Attend:
- Computational chemists working in drug design and development
- Medicinal chemists interested in applying an accessible CADD technology 
during ligand design
- Formulation scientists working in protein-based biologics therapeutic 
development

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