Focused On-demand Libraries - Receptor.AI 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 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.


We use our state-of-the-art dedicated workflow for designing focused 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
Q9Y6N7

UPID:
ROBO1_HUMAN

ALTERNATIVE NAMES:
Deleted in U twenty twenty; H-Robo-1

ALTERNATIVE UPACC:
Q9Y6N7; B2RXI1; D3DU36; E9PD49; Q1RMC7; Q7Z300; Q9BUS7

BACKGROUND:
The protein Roundabout homolog 1, with aliases Deleted in U twenty twenty and H-Robo-1, is crucial for axonal guidance and cellular migration during neuronal development. It serves as a receptor for SLIT1 and SLIT2, influencing cellular responses to guidance cues. Additionally, it interacts with MYO9B to inhibit RHOA GTPase activity, facilitating cell migration and playing a role in lung development.

THERAPEUTIC SIGNIFICANCE:
Implicated in diseases such as Neurooculorenal syndrome, congenital Nystagmus 8, and combined or isolated Pituitary hormone deficiency, Roundabout homolog 1 presents a significant target for therapeutic intervention. The exploration of Roundabout homolog 1's functions offers promising avenues for developing treatments for these complex disorders.

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