Focused On-demand Library for Basigin

Details

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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
P35613

UPID:
BASI_HUMAN

ALTERNATIVE NAMES:
5F7; Collagenase stimulatory factor; Extracellular matrix metalloproteinase inducer; Hepatoma-associated antigen; Leukocyte activation antigen M6; OK blood group antigen; Tumor cell-derived collagenase stimulatory factor

ALTERNATIVE UPACC:
P35613; A6NJW1; D3YLG5; Q7Z796; Q8IZL7

BACKGROUND:
The protein Basigin, known by alternative names such as CD147 and EMMPRIN, is integral to several critical biological functions. It is essential for normal retinal maturation, acting as a key player in the survival mechanism of retinal cone photoreceptors. Basigin's role extends to facilitating erythrocyte invasion by P. falciparum, making it a critical factor in malaria infection. Moreover, it is involved in immune cell signaling, angiogenesis, and tumor progression, highlighting its complex role in both health and disease.

THERAPEUTIC SIGNIFICANCE:
The multifaceted role of Basigin in biological systems makes it an intriguing subject for scientific inquiry and therapeutic development. Its involvement in processes ranging from retinal development to tumor growth and pathogen infection underscores the potential for Basigin-targeted therapies to address a wide spectrum of diseases. Exploring Basigin's functions further could lead to groundbreaking advances in medical treatment.

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