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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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 utilise our cutting-edge, exclusive workflow to develop focused 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
P56279

UPID:
TCL1A_HUMAN

ALTERNATIVE NAMES:
Oncogene TCL-1; Protein p14 TCL1

ALTERNATIVE UPACC:
P56279; Q6IBK7

BACKGROUND:
The protein T-cell leukemia/lymphoma protein 1A, with alternative names Oncogene TCL-1 and Protein p14 TCL1, is integral to enhancing AKT kinase activity. It facilitates the phosphorylation and activation of AKT1, AKT2, and AKT3, and is essential for the nuclear translocation of AKT1. These functions are critical for promoting cell proliferation, ensuring mitochondrial stability, and enhancing cell survival.

THERAPEUTIC SIGNIFICANCE:
The exploration of T-cell leukemia/lymphoma protein 1A's function offers a promising avenue for the development of novel therapeutic approaches. Its key role in cellular survival and proliferation pathways makes it an attractive target for drug discovery efforts aimed at treating diseases characterized by abnormal cell growth and survival.

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