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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Q9ULC4

UPID:
MCTS1_HUMAN

ALTERNATIVE NAMES:
Multiple copies T-cell malignancies

ALTERNATIVE UPACC:
Q9ULC4; B4DGY2; Q502X6

BACKGROUND:
The protein Malignant T-cell-amplified sequence 1, with alternative names including Multiple copies T-cell malignancies, is integral to cell cycle control, enhancing translation initiation and modulating DNA damage signaling. It accelerates cell division by influencing CDK4/6 and cyclin D1, facilitates mRNA translation affecting protein levels without altering mRNA abundance, and is implicated in lymphoid tumor growth and breast cancer by affecting apoptosis and angiogenesis. Its involvement in proteasome-mediated p53 degradation underscores its potential impact on tumor suppression.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Malignant T-cell-amplified sequence 1 offers a promising avenue for developing novel therapeutic approaches.

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