AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Differentially expressed in FDCP 6 homolog

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.

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 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.

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.

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

Q9H4E7

UPID:

DEFI6_HUMAN

Alternative names:

IRF4-binding protein

Alternative UPACC:

Q9H4E7; Q86VF4

Background:

The Differentially Expressed in FDCP 6 homolog, also known as IRF4-binding protein, is a pivotal player in cellular signaling. It acts as a guanine nucleotide exchange factor, crucial for the activation of Rho GTPases such as RAC1, RhoA, and CDC42. These roles are essential for cell morphology, immune homeostasis, and T-cell regulation, particularly through the trafficking and availability of CTLA-4 on the T-cell surface.

Therapeutic significance:

Linked to Immunodeficiency 87 and autoimmunity, this protein's malfunction is associated with increased susceptibility to infections and autoimmune manifestations. Understanding its role could lead to novel therapeutic strategies targeting T-cell function defects and improving immune homeostasis.

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