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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 utilise our cutting-edge, exclusive workflow to develop 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

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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