AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for CXADR-like membrane protein

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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Q9H6B4

UPID:

CLMP_HUMAN

Alternative names:

Adipocyte adhesion molecule; Coxsackie- and adenovirus receptor-like membrane protein

Alternative UPACC:

Q9H6B4

Background:

The CXADR-like membrane protein, also known as Adipocyte adhesion molecule and Coxsackie- and adenovirus receptor-like membrane protein, plays a crucial role in cell-cell adhesion and is pivotal for normal small intestine development. Its involvement in adipocyte differentiation suggests a significant role in the development of obesity.

Therapeutic significance:

Congenital short bowel syndrome (CSBS), a condition marked by a significantly shortened small intestine leading to malabsorption and severe malnutrition, is associated with mutations affecting this protein. Understanding the role of CXADR-like membrane protein could pave the way for innovative treatments for CSBS, potentially improving survival rates and quality of life for affected individuals.

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