Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening 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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9Y4U1

UPID:
MMAC_HUMAN

ALTERNATIVE NAMES:
Alkylcobalamin:glutathione S-alkyltransferase; CblC; Cyanocobalamin reductase (cyanide-eliminating); Methylmalonic aciduria and homocystinuria type C protein

ALTERNATIVE UPACC:
Q9Y4U1; Q5T157; Q9BRQ7

BACKGROUND:
The Cyanocobalamin reductase / alkylcobalamin dealkylase, known as CblC, is integral to processing vitamin B12 from its inactive dietary form to active cofactors. It operates in a multiprotein complex, facilitating the transport and conversion of cobalamin, which is vital for cellular functions such as DNA synthesis and energy production.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Cyanocobalamin reductase could open doors to potential therapeutic strategies. Its involvement in the metabolic disorder Methylmalonic aciduria and homocystinuria, cblC type, due to gene variants, emphasizes the importance of exploring this protein for innovative treatments.

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