AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine/threonine-protein kinase B-raf

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P15056

UPID:

BRAF_HUMAN

Alternative names:

Proto-oncogene B-Raf; p94; v-Raf murine sarcoma viral oncogene homolog B1

Alternative UPACC:

P15056; A4D1T4; B6HY61; B6HY62; B6HY63; B6HY64; B6HY65; B6HY66; Q13878; Q3MIN6; Q9UDP8; Q9Y6T3

Background:

Serine/threonine-protein kinase B-raf, also known as Proto-oncogene B-Raf, plays a pivotal role in mediating cell growth and division signals. It activates the MAP kinase signal transduction pathway, crucial for cell proliferation, differentiation, and survival. Its involvement in phosphorylating MAP2K1 and PFKFB2 underscores its significance in cellular signaling.

Therapeutic significance:

B-Raf's aberrant activity is linked to various cancers, including colorectal, lung, and non-Hodgkin lymphoma, highlighting its potential as a therapeutic target. Understanding B-Raf's role could pave the way for innovative treatments, particularly in cancers where it's implicated.

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