Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We employ our advanced, specialised process to create 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P20226

UPID:
TBP_HUMAN

ALTERNATIVE NAMES:
TATA sequence-binding protein; TATA-binding factor; TATA-box factor; Transcription initiation factor TFIID TBP subunit

ALTERNATIVE UPACC:
P20226; B4E3B3; F5H869; Q16845; Q6IBM6; Q9UC02

BACKGROUND:
TATA-box-binding protein, a core element of the TFIID complex, plays a crucial role in the initiation of transcription across different RNA polymerases. By binding to promoter DNA, TBP facilitates the formation of the pre-initiation complex, essential for gene expression. Its involvement in transcription regulation is underscored by its association with TAFs and participation in RNA polymerase I and III mediated transcription.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in transcription and direct association with Spinocerebellar ataxia 17, TBP presents a significant target for therapeutic intervention. Exploring the molecular mechanisms of TATA-box-binding protein offers promising avenues for developing treatments for cerebellar disorders and enhancing our understanding of transcription-related diseases.

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