AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myocyte-specific enhancer factor 2A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

We utilise our cutting-edge, exclusive workflow to develop 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q02078

UPID:

MEF2A_HUMAN

Alternative names:

Serum response factor-like protein 1

Alternative UPACC:

Q02078; B4DFQ7; F6XG23; O43814; Q14223; Q14224; Q59GX4; Q7Z6C9; Q96D14

Background:

Myocyte-specific enhancer factor 2A (MEF2A), also known as Serum response factor-like protein 1, plays a pivotal role in muscle-specific gene regulation, growth factor-induced gene activation, and neuronal differentiation. It binds to the MEF2 element, influencing skeletal and cardiac muscle development, neuronal survival, and synaptic differentiation through diverse signaling pathways, including p38 MAPK.

Therapeutic significance:

MEF2A's involvement in coronary artery disease, autosomal dominant, 1, underscores its potential as a therapeutic target. Understanding the role of MEF2A could open doors to potential therapeutic strategies for heart diseases and neuronal disorders.

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