Focused On-demand Library for X-linked retinitis pigmentosa GTPase regulator

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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.







Alternative names:


Alternative UPACC:

Q92834; B1ARN3; E9PE28; O00702; O00737; Q3KN84; Q8N5T6; Q93039; Q9HD29; Q9UMR1


The X-linked retinitis pigmentosa GTPase regulator plays a pivotal role in ciliogenesis, photoreceptor integrity, and possibly in spermatogenesis and intraflagellar transport processes. Its function as a guanine-nucleotide releasing factor and in regulating actin stress filaments and cell contractility underscores its importance in cellular structure and movement.

Therapeutic significance:

Given its critical involvement in a spectrum of retinal dystrophies, including Retinitis pigmentosa 3, X-linked retinitis pigmentosa with sinorespiratory infections, Cone-rod dystrophy X-linked 1, and X-linked atrophic macular degeneration, targeting the X-linked retinitis pigmentosa GTPase regulator offers a promising avenue for therapeutic intervention in these debilitating visual impairments.

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