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.


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.


We use our state-of-the-art dedicated workflow for designing focused 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
Q8IUX7

UPID:
AEBP1_HUMAN

ALTERNATIVE NAMES:
Aortic carboxypeptidase-like protein

ALTERNATIVE UPACC:
Q8IUX7; Q14113; Q59ER7; Q6ZSC7; Q7KZ79

BACKGROUND:
Adipocyte enhancer-binding protein 1, with its alternative name Aortic carboxypeptidase-like protein, is pivotal in collagen fibrillogenesis, indicating its significant role in extracellular matrix organization. This protein not only aids in adipocyte proliferation but also plays a key role in macrophage inflammatory responses by regulating NF-kappa-B activity. Its function as a transcriptional repressor further highlights its multifaceted role in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given its association with Ehlers-Danlos syndrome, classic-like, 2, a disorder marked by connective tissue abnormalities, Adipocyte enhancer-binding protein 1 presents a promising target for therapeutic intervention. Exploring its functions and mechanisms could lead to innovative treatments for this syndrome, potentially improving patient outcomes and quality of life.

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