AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myosin-7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our high-tech, dedicated method is applied to construct 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.

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

P12883

UPID:

MYH7_HUMAN

Alternative names:

Myosin heavy chain 7; Myosin heavy chain slow isoform; Myosin heavy chain, cardiac muscle beta isoform

Alternative UPACC:

P12883; A2TDB6; B6D424; Q14836; Q14837; Q14904; Q16579; Q2M1Y6; Q92679; Q9H1D5; Q9UDA2; Q9UMM8

Background:

Myosin-7, known alternatively as Myosin heavy chain 7, Myosin heavy chain slow isoform, and Myosin heavy chain, cardiac muscle beta isoform, plays a pivotal role in muscle contraction. It is an actin-based motor molecule with ATPase activity, essential for the contraction of skeletal and cardiac muscle by forming bipolar thick filaments.

Therapeutic significance:

Myosin-7 is implicated in several hereditary disorders, including familial hypertrophic cardiomyopathy, dilated cardiomyopathy, congenital myopathies, and left ventricular non-compaction. These conditions highlight the protein's critical role in cardiac and skeletal muscle function, suggesting that targeting Myosin-7 could lead to novel treatments for these debilitating diseases.

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