Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


We use our state-of-the-art dedicated workflow for designing focused 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
Q14766

UPID:
LTBP1_HUMAN

ALTERNATIVE NAMES:
Transforming growth factor beta-1-binding protein 1

ALTERNATIVE UPACC:
Q14766; A1L3V1; P22064; Q53SD8; Q53SF3; Q53SG1; Q59HF7; Q8TD95

BACKGROUND:
The protein Latent-transforming growth factor beta-binding protein 1, with alternative names such as Transforming growth factor beta-1-binding protein 1, plays a pivotal role in maintaining the latency of TGF-beta. This regulation is crucial for preventing premature TGF-beta activation, which is essential for various cellular processes including proliferation and differentiation.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in regulating TGF-beta, a pathway implicated in numerous diseases, exploring the therapeutic potential of Latent-transforming growth factor beta-binding protein 1 is promising. Understanding the role of this protein could open doors to potential therapeutic strategies for diseases linked to TGF-beta dysregulation.

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