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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


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
Q9NY30

UPID:
BTG4_HUMAN

ALTERNATIVE NAMES:
BTG family member 4; Protein PC3b

ALTERNATIVE UPACC:
Q9NY30; Q8NEH7

BACKGROUND:
The function of Protein BTG4, alternatively named BTG family member 4 or Protein PC3b, is integral to the process of embryonic development. It serves as an adapter, facilitating the connection between CNOT7 of the CCR4-NOT complex and EIF4E. This is essential for the degradation of maternal mRNAs during the maturation of oocytes and the early stages of fertilization, playing a key role in the maternal-zygotic transition, zygotic division, and the initiation of development in embryos.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in the disease oocyte/zygote/embryo maturation arrest 8, a disorder leading to autosomal recessive infertility, Protein BTG4 presents a significant target for therapeutic intervention. Exploring the functions of Protein BTG4 could lead to innovative treatments for infertility by addressing the underlying causes of embryonic development impairments.

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