AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cyanocobalamin reductase / alkylcobalamin dealkylase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised 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

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:

Cyanocobalamin reductase, also known as CblC, plays a pivotal role in vitamin B12 metabolism. It catalyzes the conversion of dietary cyanocobalamin into its active forms, methylcobalamin and adenosylcobalamin, essential for methionine biosynthesis and the TCA cycle. This protein forms a complex with ABCD4 and LMBRD1 for cobalamin transport across the lysosomal membrane, ensuring efficient cellular utilization.

Therapeutic significance:

Mutations in the CblC protein are linked to Methylmalonic aciduria and homocystinuria, cblC type, a disorder affecting cobalamin metabolism. This connection highlights the protein's critical role in metabolic pathways and underscores the potential for targeted therapeutic strategies to address the underlying genetic variants.

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