AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Mitochondrial inner membrane protease subunit 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Q96T52

UPID:

IMP2L_HUMAN

Alternative names:

IMP2-like protein

Alternative UPACC:

Q96T52; Q75MF1; Q75MN9; Q75MP0; Q75MS5; Q75MS8; Q96HJ2

Background:

Mitochondrial inner membrane protease subunit 2, also known as IMP2-like protein, plays a crucial role in mitochondrial function. It catalyzes the removal of transit peptides, facilitating the targeting of proteins from the mitochondrial matrix across the inner membrane into the inter-membrane space. A key substrate of this protease is the nuclear-encoded protein DIABLO, integral to apoptosis regulation.

Therapeutic significance:

Given its involvement in Gilles de la Tourette syndrome, a neurologic disorder characterized by motor and vocal tics, understanding the role of Mitochondrial inner membrane protease subunit 2 could lead to novel therapeutic strategies for managing this complex condition.

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