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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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
Q9UPI3

UPID:
FLVC2_HUMAN

ALTERNATIVE NAMES:
Calcium-chelate transporter; Feline leukemia virus subgroup C receptor-related protein 2

ALTERNATIVE UPACC:
Q9UPI3; B7Z485; Q53ZT9; Q96JY3; Q9NX90

BACKGROUND:
FLVCR2, known for its alternative names Calcium-chelate transporter and Feline leukemia virus subgroup C receptor-related protein 2, is integral to heme homeostasis. It senses and responds to heme levels, influencing mitochondrial functions, ATP production, and thermogenesis. Its mechanism involves interaction and regulation of electron transfer chain complexes and ATP2A2, crucial for energy metabolism.

THERAPEUTIC SIGNIFICANCE:
The disease Proliferative vasculopathy and hydranencephaly-hydrocephaly syndrome, characterized by severe brain and retinal abnormalities, is caused by variants in the FLVCR2 gene. Exploring the function of FLVCR2 offers a promising pathway to developing treatments for this and potentially other related disorders.

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