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

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 employ our advanced, specialised process to create 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.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

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.