AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myosin-4

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Q9Y623

UPID:

MYH4_HUMAN

Alternative names:

Myosin heavy chain 2b; Myosin heavy chain 4; Myosin heavy chain IIb; Myosin heavy chain, skeletal muscle, fetal

Alternative UPACC:

Q9Y623

Background:

Myosin-4, known by alternative names such as Myosin heavy chain 2b, Myosin heavy chain 4, Myosin heavy chain IIb, and Myosin heavy chain, skeletal muscle, fetal, plays a pivotal role in muscle contraction. This protein is essential for the movement and strength of muscles, showcasing its fundamental role in the musculoskeletal system.

Therapeutic significance:

Understanding the role of Myosin-4 could open doors to potential therapeutic strategies. Its critical function in muscle contraction positions it as a key target for interventions in muscle-related disorders, offering a promising avenue for drug discovery and development.

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