AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Immunoglobulin heavy variable 3-30-3

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P0DP02

UPID:

HVC33_HUMAN

Alternative names:

-

Alternative UPACC:

P0DP02

Background:

Immunoglobulin heavy variable 3-30-3 plays a pivotal role in the immune response, being integral to the antigen recognition process. This protein is part of the variable domain of immunoglobulin heavy chains, crucial for the specificity of antibodies in the humoral immune system. It is involved in the recognition and elimination of antigens, facilitated by its ability to undergo somatic hypermutations, enhancing its affinity for specific antigens.

Therapeutic significance:

Understanding the role of Immunoglobulin heavy variable 3-30-3 could open doors to potential therapeutic strategies. Its central function in antigen recognition and antibody specificity makes it a compelling target for the development of novel immunotherapies, aiming to harness the body's own immune system to fight diseases more effectively.

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