Focused On-demand Library for Myoblast determination protein 1

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 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.

Our top-notch dedicated system is used to design specialised 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P15172

UPID:

MYOD1_HUMAN

Alternative names:

Class C basic helix-loop-helix protein 1; Myogenic factor 3

Alternative UPACC:

P15172; O75321

Background:

Myoblast determination protein 1, also known as Class C basic helix-loop-helix protein 1 or Myogenic factor 3, plays a pivotal role in muscle differentiation. It acts as a transcriptional activator, promoting the transcription of muscle-specific target genes. This protein, in concert with MYF5 and MYOG, occupies the muscle-specific gene promoter core region during myogenesis, driving fibroblasts to differentiate into myoblasts.

Therapeutic significance:

Linked to Congenital myopathy 17, a disorder characterized by muscle weakness and respiratory insufficiency, understanding the role of Myoblast determination protein 1 could open doors to potential therapeutic strategies. Its involvement in muscle differentiation pathways offers a promising target for therapeutic intervention.