AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Apoptosis-inducing factor 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q96NN9

UPID:

AIFM3_HUMAN

Alternative names:

Apoptosis-inducing factor-like protein

Alternative UPACC:

Q96NN9; B7WP37; D3DX37; D3DX38; Q6ZT44; Q8N1V3; Q8N5E0

Background:

Apoptosis-inducing factor 3, also known as Apoptosis-inducing factor-like protein, plays a pivotal role in cellular processes by inducing apoptosis through a caspase-dependent pathway. This protein is instrumental in reducing mitochondrial membrane potential, a critical step in the apoptosis mechanism.

Therapeutic significance:

Understanding the role of Apoptosis-inducing factor 3 could open doors to potential therapeutic strategies. Its ability to regulate cell death positions it as a key target for interventions in diseases where apoptosis is dysregulated.

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