AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-actinin-2

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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.

Our top-notch dedicated system is used to design specialised 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.

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

Reaxense

upacc

P35609

UPID:

ACTN2_HUMAN

Alternative names:

Alpha-actinin skeletal muscle isoform 2; F-actin cross-linking protein

Alternative UPACC:

P35609; B1ANE4; B2RCS5; Q86TF4; Q86TI8

Background:

Alpha-actinin-2, also known as the skeletal muscle isoform 2 or F-actin cross-linking protein, plays a crucial role in the structural integrity of muscle cells by anchoring actin to various intracellular structures. This protein is pivotal in maintaining the cytoskeletal architecture, facilitating cellular movement, and muscle contraction.

Therapeutic significance:

Mutations in Alpha-actinin-2 are linked to severe diseases such as familial hypertrophic cardiomyopathy, dilated cardiomyopathy, congenital myopathy, and adult-onset distal myopathy. These conditions underscore the protein's critical role in cardiac and skeletal muscle function, presenting it as a potential target for therapeutic intervention in muscle-related diseases.

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