AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myocardin-related transcription factor A

Available from Reaxense
Predicted by Alphafold

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Q969V6

UPID:

MRTFA_HUMAN

Alternative names:

MKL/myocardin-like protein 1; Megakaryoblastic leukemia 1 protein; Megakaryocytic acute leukemia protein

Alternative UPACC:

Q969V6; Q8TCL1; Q96SC5; Q96SC6; Q9P2B0

Background:

Myocardin-related transcription factor A (MRTFA), also known as MKL/myocardin-like protein 1, plays a pivotal role in regulating cytoskeletal gene expression. This is achieved through its association with the serum response factor (SRF), responding to Rho GTPase-induced changes in cellular actin dynamics. MRTFA's interaction with globular actin (G-actin) and filamentous actin (F-actin) in the nucleus modulates the activity of the MRTFA-SRF complex, crucial for development, morphogenesis, and cell migration.

Therapeutic significance:

MRTFA's involvement in Immunodeficiency 66, a disorder characterized by recurrent viral infections and impaired neutrophil migration, underscores its therapeutic potential. Understanding the role of MRTFA could open doors to potential therapeutic strategies, particularly in enhancing immune responses and correcting cytoskeletal abnormalities.

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