Focused On-demand Library for RNA-binding protein 10

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

Fig. 1. The sreening 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

Reaxense

upacc

P98175

UPID:

RBM10_HUMAN

Alternative names:

G patch domain-containing protein 9; RNA-binding motif protein 10; RNA-binding protein S1-1

Alternative UPACC:

P98175; A0A0A0MR66; C4AM81; Q14136; Q5JRR2; Q9BTE4; Q9BTX0; Q9NTB1

Background:

RNA-binding protein 10, also known as G patch domain-containing protein 9 and RNA-binding motif protein 10, plays a crucial role in post-transcriptional processing, particularly in mRNA splicing. It exhibits a strong affinity for RNA homopolymers, favoring poly(G) and poly(U) over poly(A), and is known to bind specific miRNA hairpins.

Therapeutic significance:

Linked to TARP syndrome, characterized by a combination of Robin sequence, talipes equinovarus, and cardiac defects, RNA-binding protein 10's involvement in this genetic disorder underscores its potential as a target for therapeutic intervention. Understanding the role of RNA-binding protein 10 could open doors to potential therapeutic strategies.