Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


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 employ our advanced, specialised process to create 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 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
O43837

UPID:
IDH3B_HUMAN

ALTERNATIVE NAMES:
Isocitric dehydrogenase subunit beta; NAD(+)-specific ICDH subunit beta

ALTERNATIVE UPACC:
O43837; B2RDR1; D3DVX2; D3DVX3; O95106; Q5JXS8; Q9NQ06; Q9NQ07; Q9NUZ0; Q9UEX0; Q9UG99

BACKGROUND:
The Isocitrate dehydrogenase [NAD] subunit beta, mitochondrial, functions as a key player in the citric acid cycle by ensuring the effective decarboxylation of isocitrate to alpha-ketoglutarate. This process is vital for energy production in cells. The enzyme's activity is dependent on the assembly of its subunits, highlighting its structural and functional complexity.

THERAPEUTIC SIGNIFICANCE:
The association of Isocitrate dehydrogenase [NAD] subunit beta with Retinitis pigmentosa 46 underscores its potential as a target for therapeutic intervention. By elucidating the mechanisms through which this protein influences disease progression, researchers can pave the way for innovative treatments that could restore vision or halt the advancement of this debilitating condition.

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.