Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P61328

UPID:
FGF12_HUMAN

ALTERNATIVE NAMES:
Fibroblast growth factor homologous factor 1; Myocyte-activating factor

ALTERNATIVE UPACC:
P61328; B2R6B7; B2R976; O35339; P70376; Q8TBG5; Q92912; Q93001

BACKGROUND:
The protein Fibroblast growth factor 12, known alternatively as Fibroblast growth factor homologous factor 1 and Myocyte-activating factor, is integral to the development and function of the nervous system. It enhances neuronal excitability by positively regulating the activity of voltage-gated sodium channels, particularly through elevating the fast inactivation of the neuronal sodium channel SCN8A.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Developmental and epileptic encephalopathy 47, characterized by refractory seizures and cognitive delays, Fibroblast growth factor 12 represents a promising target for therapeutic intervention. Exploring the functions of FGF12 offers a pathway to novel treatments for this and potentially other neurological disorders.

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.