Focused On-demand Libraries - Receptor.AI 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening 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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q6ZSZ5

UPID:
ARHGI_HUMAN

ALTERNATIVE NAMES:
114 kDa Rho-specific guanine nucleotide exchange factor; Septin-associated RhoGEF

ALTERNATIVE UPACC:
Q6ZSZ5; A8MV62; B5ME81; I3L1I5; O60274; Q6DD92

BACKGROUND:
The protein Rho guanine nucleotide exchange factor 18, with alternative names 114 kDa Rho-specific guanine nucleotide exchange factor and Septin-associated RhoGEF, is crucial for actin stress fiber formation and reactive oxygen species production through its action as a GEF for RhoA and RAC1 GTPases. It is essential for the regulation of the circumferential actomyosin belt in epithelial cells, mediated by EPB41L4B.

THERAPEUTIC SIGNIFICANCE:
Implicated in the development of Retinitis pigmentosa 78, a condition marked by retinal pigment deposits and photoreceptor cell loss, Rho guanine nucleotide exchange factor 18 represents a significant target for research. Understanding its role could lead to breakthroughs in treatment strategies for this and potentially other related disorders.

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