Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Q9H2X3

UPID:
CLC4M_HUMAN

ALTERNATIVE NAMES:
CD209 antigen-like protein 1; DC-SIGN-related protein; Dendritic cell-specific ICAM-3-grabbing non-integrin 2; Liver/lymph node-specific ICAM-3-grabbing non-integrin

ALTERNATIVE UPACC:
Q9H2X3; A6NKI4; A8K8B3; Q69F40; Q969M4; Q96QP3; Q96QP4; Q96QP5; Q96QP6; Q9BXS3; Q9H2Q9; Q9H8F0; Q9Y2A8

BACKGROUND:
The protein C-type lectin domain family 4 member M, also referred to as DC-SIGN-related protein, is pivotal in peripheral immune surveillance. It acts as an attachment receptor for numerous viruses, including SARS-CoV, West-nile virus, and Marburg virus, facilitating their endocytosis and subsequent degradation. This protein's interaction with pathogens through mannose-like carbohydrates underscores its significance in immune defense mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of C-type lectin domain family 4 member M offers promising avenues for therapeutic intervention. Its broad spectrum as an attachment receptor for various pathogens positions it as a key target in the development of novel antiviral therapies.

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