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 high-tech, dedicated method is applied to construct 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q969F9

UPID:
HPS3_HUMAN

ALTERNATIVE NAMES:
Hermansky-Pudlak syndrome 3 protein

ALTERNATIVE UPACC:
Q969F9; A8K6G6; Q8WTV6; Q96AP1; Q96MR3; Q9H608

BACKGROUND:
BLOC-2 complex member HPS3, alternatively named Hermansky-Pudlak syndrome 3 protein, is integral to melanosome biogenesis and maturation. Its function underscores the complex interplay of genetic factors in organelle formation, crucial for cellular processes such as pigmentation.

THERAPEUTIC SIGNIFICANCE:
Mutations affecting the HPS3 gene cause Hermansky-Pudlak syndrome 3, manifesting in oculocutaneous albinism, bleeding disorders, and lysosomal storage defects. Targeting the molecular pathways involving HPS3 offers a promising avenue for therapeutic intervention, especially for mitigating pulmonary complications that significantly impact patient survival.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.