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 methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
P45378

UPID:
TNNT3_HUMAN

ALTERNATIVE NAMES:
Beta-TnTF; Fast skeletal muscle troponin T

ALTERNATIVE UPACC:
P45378; A8MQ76; A8MSW1; B3KPX3; B7WP64; B7ZL26; B7ZVV9; Q12975; Q12976; Q12977; Q12978; Q17RG9; Q6FH29; Q6N056; Q86TH6

BACKGROUND:
The protein Troponin T, fast skeletal muscle, with alternative names Beta-TnTF and Fast skeletal muscle troponin T, is integral to muscle function. It binds to tropomyosin, playing a critical role in the calcium-regulated control of muscle contraction. This regulatory mechanism is essential for the precise and efficient movement of muscles.

THERAPEUTIC SIGNIFICANCE:
Linked to the development of Arthrogryposis, distal, 2B2, a disease characterized by limb contractures, Troponin T, fast skeletal muscle's study offers insights into novel therapeutic avenues. Understanding its function could lead to breakthroughs in treating or managing this genetically inherited condition.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.