AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Caveolae-associated protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

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

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q6NZI2

UPID:

CAVN1_HUMAN

Alternative names:

Cavin-1; Polymerase I and transcript release factor

Alternative UPACC:

Q6NZI2; B2RAW7; O00535; Q6GMY1; Q96H74; Q9BT85; Q9HAP4

Background:

Caveolae-associated protein 1, also known as Cavin-1 and Polymerase I and transcript release factor, is pivotal in caveolae formation and organization across all tissues. It is a core component of the CAVIN complex, crucial for caveolae biogenesis in the presence of caveolin-1. Cavin-1 significantly influences ribosomal transcriptional activity in adipocytes and facilitates the formation of the ribosomal transcriptional loop. Its role extends to promoting the dissociation of transcription complexes, thereby enhancing RNA polymerase I and pre-RNA release.

Therapeutic significance:

Cavin-1's involvement in Congenital generalized lipodystrophy 4, characterized by lipodystrophy, muscular dystrophy, and cardiac anomalies, underscores its therapeutic potential. Understanding the role of Caveolae-associated protein 1 could open doors to potential therapeutic strategies for treating not only Congenital generalized lipodystrophy 4 but also other metabolic and muscular disorders.

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