AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Lipase maturation factor 1

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.

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 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

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Q96S06

UPID:

LMF1_HUMAN

Alternative names:

Transmembrane protein 112

Alternative UPACC:

Q96S06; B3KS80; Q68CJ3; Q96FJ4; Q9H6G4; Q9H9K7

Background:

Lipase maturation factor 1 (LMF1), also known as Transmembrane protein 112, plays a crucial role in the maturation of specific proteins within the endoplasmic reticulum. It is essential for the maturation and transport of active lipoprotein lipase (LPL) through the secretory pathway, with each LMF1 molecule chaperoning over 50 molecules of LPL.

Therapeutic significance:

LMF1's involvement in Combined lipase deficiency, characterized by repeated episodes of pancreatitis, tuberous xanthomas, and lipodystrophy, highlights its therapeutic significance. This condition results from a deficiency of both lipoprotein lipase (LPL) and hepatic triglyceride lipase (HTGL), linked to variants affecting the LMF1 gene.

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