Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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
Q8TEV9

UPID:
SMCR8_HUMAN

ALTERNATIVE NAMES:
Smith-Magenis syndrome chromosomal region candidate gene 8 protein

ALTERNATIVE UPACC:
Q8TEV9; A5PKZ5; Q3ZCN0; Q6PJL3

BACKGROUND:
Guanine nucleotide exchange protein SMCR8, also known as Smith-Magenis syndrome chromosomal region candidate gene 8 protein, is integral to the C9orf72-SMCR8 complex. This complex, with its GEF activity, is essential for autophagy regulation, promoting the maturation of autophagosomes by activating RAB8A and RAB39B. It also serves as a negative autophagy initiation regulator and enhances mTORC1 signaling by promoting substrate phosphorylation. The protein's involvement in these critical cellular pathways underscores its biological significance.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Guanine nucleotide exchange protein SMCR8 could open doors to potential therapeutic strategies.

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