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 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
Q8NEZ2

UPID:
VP37A_HUMAN

ALTERNATIVE NAMES:
ESCRT-I complex subunit VPS37A; Hepatocellular carcinoma-related protein 1

ALTERNATIVE UPACC:
Q8NEZ2; Q336D5; Q6NW27; Q8N3D7; Q8TBL7; Q96DL9

BACKGROUND:
The protein VPS37A, known for its alternative names ESCRT-I complex subunit VPS37A and Hepatocellular carcinoma-related protein 1, is a key component of the ESCRT-I complex. It is involved in the regulation of vesicular trafficking, specifically the sorting of endocytic ubiquitinated cargos into multivesicular bodies, which is crucial for cellular processes such as growth and differentiation.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Spastic paraplegia 53, a condition marked by progressive weakness and spasticity of the lower limbs, VPS37A represents a promising target for therapeutic intervention. Exploring the function of VPS37A could lead to novel therapeutic approaches for this and potentially other related disorders.

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