Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening 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.


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
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:
The protein Myocardin-related transcription factor A, known alternatively as Megakaryoblastic leukemia 1 protein, is integral to cytoskeletal gene regulation. It functions as a transcription coactivator with the serum response factor (SRF), linking cytoskeletal dynamics to gene expression. This regulation is mediated through MRTFA's binding to actin, adjusting the MRTFA-SRF complex's activity based on cellular actin concentration, thereby influencing cell development and migration.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Immunodeficiency 66, where defects in cytoskeletal actin dynamics lead to impaired neutrophil migration and recurrent infections, MRTFA presents a promising target for therapeutic intervention. Exploring MRTFA's function further could lead to innovative treatments aimed at improving immune function and managing cytoskeletal disorders.

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