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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q8NDX2

UPID:
VGLU3_HUMAN

ALTERNATIVE NAMES:
Solute carrier family 17 member 8

ALTERNATIVE UPACC:
Q8NDX2; B3KXZ6; B7ZKV4; Q17RQ8

BACKGROUND:
The protein Vesicular glutamate transporter 3, alternatively known as Solute carrier family 17 member 8, plays a critical role in neurotransmitter regulation by transporting L-glutamate and ions across cell membranes. Its activities are essential for maintaining synaptic vesicle acidification and neurotransmitter release, thereby facilitating efficient neural communication. VGLUT3's unique ability to operate as both an uniporter and symporter underscores its significance in neural physiology.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in autosomal dominant deafness, 25 (DFNA25), a form of sensorineural hearing loss, VGLUT3 emerges as a key target in the development of treatments for hearing impairments. The exploration of VGLUT3's functions and mechanisms offers promising avenues for novel therapeutic interventions, emphasizing the importance of continued research in this area.

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