Focused On-demand Library for Dysferlin

Focused On-demand Libraries - Reaxense 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.

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.

Our top-notch dedicated system is used to design specialised 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

O75923

UPID:

DYSF_HUMAN

Alternative names:

Dystrophy-associated fer-1-like protein; Fer-1-like protein 1

Alternative UPACC:

O75923; A0FK00; B1PZ70; B1PZ71; B1PZ72; B1PZ73; B1PZ74; B1PZ75; B1PZ76; B1PZ77; B1PZ78; B1PZ79; B1PZ80; B1PZ81; B3KQB9; O75696; Q09EX5; Q0H395; Q53QY3; Q53TD2; Q8TEL8; Q9UEN7

Background:

Dysferlin, encoded by the gene with accession number O75923, plays a pivotal role as a key calcium ion sensor facilitating the Ca(2+)-triggered synaptic vesicle-plasma membrane fusion. It is instrumental in the sarcolemma repair mechanism in skeletal muscle and cardiomyocytes, enabling rapid membrane resealing after mechanical stress. Dysferlin's alternative names include Dystrophy-associated fer-1-like protein and Fer-1-like protein 1.

Therapeutic significance:

Dysferlin's involvement in muscular dystrophies such as Limb-girdle muscular dystrophy, autosomal recessive 2, Miyoshi muscular dystrophy 1, and Distal myopathy with anterior tibial onset underscores its therapeutic significance. Understanding Dysferlin's function could lead to innovative therapeutic strategies targeting these debilitating conditions.