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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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
P07814

UPID:
SYEP_HUMAN

ALTERNATIVE NAMES:
Bifunctional aminoacyl-tRNA synthetase; Cell proliferation-inducing gene 32 protein; Glutamatyl-prolyl-tRNA synthetase

ALTERNATIVE UPACC:
P07814; A0AVA9; B9EGH3; Q05BP6; Q05DF8; Q5DSM1; Q5H9S5; Q6PD57; Q86X73

BACKGROUND:
Bifunctional glutamate/proline--tRNA ligase, with alternative names such as Bifunctional aminoacyl-tRNA synthetase, is pivotal in the aminoacyl-tRNA synthetase multienzyme complex. It catalyzes amino acids' attachment to tRNA, crucial for protein synthesis. Its role extends to the mTORC1 signaling pathway, promoting fatty acid uptake in adipocytes, showcasing its multifunctional nature.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Bifunctional glutamate/proline--tRNA ligase could open doors to potential therapeutic strategies for treating Leukodystrophy, hypomyelinating, 15, by exploring its genetic implications and impact on protein synthesis.

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