AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-related protein Rab-33B

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H082

UPID:

RB33B_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H082; B2R987; Q4W5B0

Background:

Ras-related protein Rab-33B plays a pivotal role in protein transport, specifically in coordination with RAB6A to regulate intra-Golgi retrograde trafficking. It also modulates autophagosome formation, highlighting its importance in autophagy. This protein's involvement in critical cellular processes underscores its significance in maintaining cellular homeostasis.

Therapeutic significance:

Ras-related protein Rab-33B is linked to Smith-McCort dysplasia 2, a rare autosomal recessive osteochondrodysplasia characterized by short limbs, trunk with barrel-shaped chest, and distinctive skeletal abnormalities without affecting intelligence. Understanding the role of Ras-related protein Rab-33B could open doors to potential therapeutic strategies for treating this condition.

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