Focused On-demand Libraries - Receptor.AI 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 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 employ our advanced, specialised process to create targeted 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
P47224

UPID:
MSS4_HUMAN

ALTERNATIVE NAMES:
Rab-interacting factor

ALTERNATIVE UPACC:
P47224; B2R4P4; Q92992

BACKGROUND:
Guanine nucleotide exchange factor MSS4, known alternatively as Rab-interacting factor, plays a crucial role in the regulation of vesicular transport through its action on the SEC4/YPT1/RAB subfamily. By facilitating the release of GDP from proteins such as YPT1, RAB3A, and RAB10, with a higher specificity towards SEC4, it underscores the importance of precise regulatory mechanisms in vesicular trafficking, essential for cellular function and integrity.

THERAPEUTIC SIGNIFICANCE:
The exploration of Guanine nucleotide exchange factor MSS4's function offers a promising pathway to developing novel therapeutic strategies. Given its central role in vesicular transport, a process vital to cellular homeostasis, targeting this protein could lead to breakthroughs in treating conditions associated with vesicular transport dysregulation.

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