Focused On-demand Library for Kelch-like protein 41

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

O60662

UPID:

KLH41_HUMAN

Alternative names:

Kel-like protein 23; Kelch repeat and BTB domain-containing protein 10; Kelch-related protein 1; Sarcosin

Alternative UPACC:

O60662; Q53R42

Background:

Kelch-like protein 41, also known as Kel-like protein 23, Kelch repeat and BTB domain-containing protein 10, Kelch-related protein 1, and Sarcosin, plays a pivotal role in skeletal muscle development and differentiation. It is instrumental in the regulation of myoblast proliferation and differentiation, contributing to myofibril assembly by promoting the lateral fusion of thin fibrils into mature, wide myofibrils. This protein is essential for pseudopod elongation in transformed cells.

Therapeutic significance:

Kelch-like protein 41 is linked to Nemaline myopathy 9, a muscular disorder characterized by muscle weakness and abnormal structures in muscle fibers. Understanding the role of Kelch-like protein 41 could open doors to potential therapeutic strategies for treating this condition, highlighting its importance in muscle pathology and offering a promising avenue for drug discovery.