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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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


 

Fig. 1. The screening 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 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
A1X283

UPID:
SPD2B_HUMAN

ALTERNATIVE NAMES:
Adapter protein HOFI; Factor for adipocyte differentiation 49; Tyrosine kinase substrate with four SH3 domains

ALTERNATIVE UPACC:
A1X283; B6F0V2; Q9P2Q1

BACKGROUND:
The SH3 and PX domain-containing protein 2B, with alternative names such as Adapter protein HOFI and Factor for adipocyte differentiation 49, is integral to the formation of invadopodia and podosomes, and the degradation of the extracellular matrix. It binds to matrix metalloproteinases, NADPH oxidases, and phosphoinositides, facilitating reactive oxygen species generation and localization, essential for adipocyte differentiation.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Frank-Ter Haar syndrome, a condition marked by distinct physical deformities, the study of SH3 and PX domain-containing protein 2B holds promise for uncovering novel therapeutic avenues. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and drug development.

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