Focused On-demand Library for Tripeptidyl-peptidase 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted 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.







Alternative names:

Cell growth-inhibiting gene 1 protein; Lysosomal pepstatin-insensitive protease; Tripeptidyl aminopeptidase; Tripeptidyl-peptidase I

Alternative UPACC:

O14773; Q53HT1; Q5JAK6; Q6UX56; Q71JP6; Q96C37


Tripeptidyl-peptidase 1, known by alternative names such as Cell growth-inhibiting gene 1 protein and Lysosomal pepstatin-insensitive protease, plays a crucial role in lysosomal degradation. It exhibits tripeptidyl-peptidase I activity, essential for breaking down proteins into tripeptides, a process vital for cellular metabolism and homeostasis.

Therapeutic significance:

Tripeptidyl-peptidase 1 is implicated in severe disorders like Ceroid lipofuscinosis, neuronal, 2, and Spinocerebellar ataxia, autosomal recessive, 7. These conditions underscore the enzyme's critical role in neurological health and highlight its potential as a target for therapeutic intervention.

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