AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein O-mannosyl-transferase TMTC3

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q6ZXV5

UPID:

TMTC3_HUMAN

Alternative names:

Protein SMILE; Transmembrane and TPR repeat-containing protein 3

Alternative UPACC:

Q6ZXV5; Q5CZ86; Q5H9T6; Q68DQ6; Q68DX0; Q7Z332; Q8NC50

Background:

Protein O-mannosyl-transferase TMTC3, also known as Protein SMILE, plays a crucial role in transferring mannosyl residues to serine or threonine residues. This process is vital for the proper function of the cadherin superfamily, with TMTC3 specifically decorating cadherin domains with O-linked mannose glycans. Additionally, TMTC3 is involved in the regulation of proteasomal protein degradation in the endoplasmic reticulum (ER) and controls the ER stress response.

Therapeutic significance:

TMTC3's mutation is linked to Lissencephaly 8, characterized by severe neurological abnormalities. Understanding TMTC3's function could lead to novel therapeutic strategies for managing Lissencephaly 8 and potentially other related neurological disorders.

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