Focused On-demand Libraries - Receptor.AI 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.


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


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Receptor.AI
 
UPACC
Q9P2W1

UPID:
HOP2_HUMAN

ALTERNATIVE NAMES:
Nuclear receptor coactivator GT198; PSMC3-interacting protein; Proteasome 26S ATPase subunit 3-interacting protein; Tat-binding protein 1-interacting protein

ALTERNATIVE UPACC:
Q9P2W1; C5ILB7; Q14458; Q8WXG2; Q96HA2

BACKGROUND:
The Homologous-pairing protein 2 homolog, identified by alternative names such as PSMC3-interacting protein, is integral for DNA strand exchange in meiotic recombination. It stabilizes RAD51 and DMC1 filaments, essential for homologous pairing, and acts as a coactivator of hormone-dependent transcription.

THERAPEUTIC SIGNIFICANCE:
Given its association with Ovarian dysgenesis 3, characterized by uterine hypoplasia and streak gonads, the exploration of Homologous-pairing protein 2 homolog's function offers promising avenues for therapeutic intervention.

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