SilcsBio

Great to see the SILCS technology in action!

Looking for SILCS-Covalent Beta Testers! We’ve recently developed a new covalent workflow module aimed at enhancing covalent drug discovery. You can view our publication here: https://lnkd.in/e_pfyimd This module utilizes the SILCS method to not only identify reactive nucleophilic residues but also evaluate warhead groups and drug-like molecules for covalent drug development. We’re currently looking for beta testers. If interested, reach out to [email protected] for more information and incentives we can offer.

Here, we used SILCS simulations and machine learning to improve upon SILCS-Hotspots, a general tool for identifying druggable sites on proteins: https://lnkd.in/gg3eGXVx SILCS simulations, a type of computational fragment-based drug design, are a highly efficient way to sample protein-drug interactions. This is my first story as a postdoc at UMB, thanks to all the co-authors and PI Alexander MacKerell.

I'm not exactly sure what to call this new installation.

Adding on to last weeks post regarding the 2022 paper "In silico identification of a β2-adrenoceptor allosteric site that selectively augments canonical β2AR-Gs signaling and function", virtual screening using SILCS was also used. The study used SILCS to comprehensively explore the β2AR structure, leading to the discovery of a novel allosteric binding site. This virtual screening approach, leveraging SILCS-Pharm and SILCS-MC Pose Refinement, not only mapped the receptor’s intermediate conformations but also identified new drug-like molecules that can modulate β2AR activity. #compchem #virtualscreening?

In this 2022 paper "In silico identification of a β2-adrenoceptor allosteric site that selectively augments canonical β2AR-Gs signaling and function", SILCS was used to identify a novel allosteric site on the β2-adrenoceptor. This allows for selective enhancement of β2AR-Gs signaling, offering potential for targeted therapeutic interventions with fewer side effects. This study shows the applicability of SILCS to membrane proteins, as protein flexibility is taken into account during the simulations." #compchem #SILCS #membraneproteins

Check out one of our most recent papers on a covalent method for drug design. In this paper we enhance both precision and effectiveness. Our approach uses computational methods to: Identify Reactive Sites: Accurate detection of reactive cysteines using SILCS-Monte Carlo simulations. Optimize Warhead Groups: Machine learning models rank the effectiveness of various warhead groups. Integrated Workflow: SILCS-Covalent combines these techniques for comprehensive drug discovery insights. https://lnkd.in/evFg_3i2

The first step when using the SILCS technology is to run a SILCS simulation and generate a FragMap. See the image below to see the resulting FragMap. The colored regions below indicate favorable binding for just a few of the different chemical functional groups we map. Green = Generic Apolar Blue = Generic Donor Red = Generic Acceptor

We've recently launched our new video tutorial series. Click on the link below to explore a range of SilcsBio tutorials, from visualizing SILCS FragMaps to setting up a virtual screening project. Our developers guide you through the various modules within the SilcsBio Universe, offering expert insights and hands-on demonstrations. https://lnkd.in/gMD3k9RQ #compchem #videotutorials #virtualscreening

SilcsBio 2024.2 Version is officially released. Check out the new features here: https://lnkd.in/dgi-asCc