Focused On-demand Library for Myoblast determination protein 1

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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.


We utilise our cutting-edge, exclusive workflow to develop 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 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
Receptor.AI
 
UPACC
P15172

UPID:
MYOD1_HUMAN

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

ALTERNATIVE UPACC:
P15172; O75321

BACKGROUND:
The Myoblast determination protein 1, known alternatively as Myogenic factor 3, is a crucial transcriptional activator in muscle differentiation. It interacts with MYF5 and MYOG to initiate transcription of muscle-specific genes, a key step in myogenesis. Additionally, it has the ability to convert fibroblasts into myoblasts, highlighting its significant role in muscle development.

THERAPEUTIC SIGNIFICANCE:
Given its association with Congenital myopathy 17, a disease marked by severe muscle weakness and respiratory challenges, Myoblast determination protein 1 represents a critical target for drug discovery. Its central role in muscle gene transcription and differentiation underscores its therapeutic potential.

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