AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Mitochondrial fission 1 protein

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.

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

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.

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

Q9Y3D6

UPID:

FIS1_HUMAN

Alternative names:

FIS1 homolog; Tetratricopeptide repeat protein 11

Alternative UPACC:

Q9Y3D6; Q9BTP3

Background:

Mitochondrial fission 1 protein, also known as FIS1 homolog and Tetratricopeptide repeat protein 11, plays a pivotal role in mitochondrial dynamics, including the fragmentation of the mitochondrial network and its perinuclear clustering. It is involved in the recruitment of the fission mediator dynamin-related protein 1 to the mitochondrial surface, contributing to mitochondrial and peroxisomal fission. This protein's function is crucial for mitochondrial homeostasis, mitophagy, and apoptosis, highlighted by its ability to induce cytochrome c release, leading to apoptosis.

Therapeutic significance:

Understanding the role of Mitochondrial fission 1 protein could open doors to potential therapeutic strategies.

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