AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for ELMO domain-containing protein 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 use our state-of-the-art dedicated workflow for designing focused 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.

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

Q96FG2

UPID:

ELMD3_HUMAN

Alternative names:

RNA-binding motif and ELMO domain-containing protein 1; RNA-binding motif protein 29; RNA-binding protein 29

Alternative UPACC:

Q96FG2; B8ZZD6; D6W5K4; Q2M1K3; Q2XSU3; Q2XSU4; Q8NAC1; Q8TCK4; Q8WV70; Q8WY75; Q9H6Q8

Background:

ELMO domain-containing protein 3, also known as RNA-binding motif and ELMO domain-containing protein 1, RNA-binding motif protein 29, and RNA-binding protein 29, plays a crucial role in cellular processes as a GTPase-activating protein (GAP) for ARL2, albeit with low specific activity. Its unique structure and function underscore its importance in the cellular machinery.

Therapeutic significance:

Linked to autosomal recessive deafness 88 and autosomal dominant deafness 81, ELMO domain-containing protein 3's involvement in severe to profound mixed conductive and sensorineural hearing loss, as well as postlingual onset of slowly progressive deafness, highlights its potential as a target for therapeutic intervention. Understanding the role of ELMO domain-containing protein 3 could open doors to potential therapeutic strategies.

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