AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-related protein Rab-1A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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

P62820

UPID:

RAB1A_HUMAN

Alternative names:

YPT1-related protein

Alternative UPACC:

P62820; P11476; Q6FIE7; Q96N61; Q9Y3T2

Background:

Ras-related protein Rab-1A, also known as YPT1-related protein, is a pivotal regulator of intracellular membrane trafficking. It orchestrates the journey of transport vesicles from their formation to their fusion with membranes. This protein transitions between an inactive GDP-bound form and an active GTP-bound form, recruiting various effectors for vesicle formation, movement, tethering, and fusion. Rab-1A is instrumental in directing vesicular protein transport from the endoplasmic reticulum to the Golgi and subsequently to the cell surface, influencing IL-8 and growth hormone secretion, Golgi morphology, CASR membrane presence, cell adhesion, migration, autophagosome assembly, and defense against pathogens.

Therapeutic significance:

Understanding the role of Ras-related protein Rab-1A could open doors to potential therapeutic strategies.

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