AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Bcl-2-related protein A1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q16548

UPID:

B2LA1_HUMAN

Alternative names:

Bcl-2-like protein 5; Hemopoietic-specific early response protein; Protein BFL-1; Protein GRS

Alternative UPACC:

Q16548; Q6FGZ4; Q6FH19; Q86W13; Q99524

Background:

Bcl-2-related protein A1, also known as Bcl-2-like protein 5, Hemopoietic-specific early response protein, Protein BFL-1, and Protein GRS, plays a crucial role in cellular survival mechanisms. It retards apoptosis induced by IL-3 deprivation and may function in the response of hemopoietic cells to external signals. Additionally, it maintains endothelial survival during infection and can inhibit apoptosis in mammary epithelial cells under serum starvation.

Therapeutic significance:

Understanding the role of Bcl-2-related protein A1 could open doors to potential therapeutic strategies. Its ability to inhibit apoptosis in various cellular contexts suggests its potential as a target for therapeutic intervention in diseases where cell survival is compromised.

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