Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


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.


Our top-notch dedicated system is used to design specialised 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
Q96FM1

UPID:
PGAP3_HUMAN

ALTERNATIVE NAMES:
COS16 homolog; Gene coamplified with ERBB2 protein; PER1-like domain-containing protein 1

ALTERNATIVE UPACC:
Q96FM1; B4DGK7; Q86Z03; Q8NBJ8

BACKGROUND:
The protein Post-GPI attachment to proteins factor 3, known by alternative names such as COS16 homolog and Gene coamplified with ERBB2 protein, is integral to the lipid remodeling steps of GPI-anchor maturation. It ensures the presence of 2 saturated fatty chains at the sn-2 position of GPI-anchors, a critical step for the functional anchoring of proteins to cell membranes.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in the pathogenesis of Hyperphosphatasia with impaired intellectual development syndrome 4, a disorder marked by profound developmental delay and elevated serum alkaline phosphatase, Post-GPI attachment to proteins factor 3 presents a promising target for drug discovery. Understanding its function could lead to innovative therapeutic approaches.

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