Focused On-demand Library for Mitochondrial-processing peptidase subunit alpha

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.

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

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Q10713

UPID:

MPPA_HUMAN

Alternative names:

Alpha-MPP; Inactive zinc metalloprotease alpha; P-55

Alternative UPACC:

Q10713; B4DKL3; E7ET61; Q16639; Q5SXM9; Q8N513

Background:

Mitochondrial-processing peptidase subunit alpha, also known as Alpha-MPP, plays a crucial role in mitochondrial biogenesis. It acts as a substrate recognition and binding subunit of the mitochondrial processing protease (MPP), essential for cleaving mitochondrial sequences from newly imported precursor proteins. This process is vital for the proper functioning of mitochondria, the powerhouse of the cell.

Therapeutic significance:

The protein is implicated in Spinocerebellar ataxia, autosomal recessive, 2 (SCAR2), a disorder characterized by impaired motor development, ataxic gait, and cognitive challenges. Understanding the role of Mitochondrial-processing peptidase subunit alpha could open doors to potential therapeutic strategies for SCAR2 and related mitochondrial dysfunctions.