AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Acyl-coenzyme A diphosphatase FITM2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

Our top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Q8N6M3

UPID:

FITM2_HUMAN

Alternative names:

Fat storage-inducing transmembrane protein 2; Fat-inducing protein 2

Alternative UPACC:

Q8N6M3; A1L492; B9EGQ4; Q5TE59; Q9H3Y1

Background:

Acyl-coenzyme A diphosphatase FITM2, also known as Fat storage-inducing transmembrane protein 2, plays a crucial role in lipid metabolism. It hydrolyzes fatty acyl-CoA, facilitating the biogenesis of lipid droplets (LDs), essential for lipid and energy homeostasis. FITM2's activity in the endoplasmic reticulum is pivotal for maintaining its structure and directly influences LD formation by interacting with diacylglycerol (DAGs) and triacylglycerol.

Therapeutic significance:

Given its involvement in Siddiqi syndrome, a disorder marked by sensorineural hearing impairment and developmental delays, FITM2 presents a target for therapeutic intervention. Understanding the role of Acyl-coenzyme A diphosphatase FITM2 could open doors to potential therapeutic strategies, especially in treating metabolic and neurodevelopmental disorders.

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