AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Trafficking protein particle complex subunit 4

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Q9Y296

UPID:

TPPC4_HUMAN

Alternative names:

Hematopoietic stem/progenitor cell protein 172; Synbindin; TRS23 homolog

Alternative UPACC:

Q9Y296; A8K3A5; B4DME1

Background:

Trafficking protein particle complex subunit 4, also known as Synbindin or TRS23 homolog, is a core component of the TRAPP complexes. It acts as a guanine nucleotide exchange factor for Rab1 GTPase, facilitating vesicular transport from the endoplasmic reticulum to the Golgi and autophagy. Its potential role in dendrite postsynaptic membrane trafficking underscores its importance in cellular processes.

Therapeutic significance:

The protein is linked to a neurodevelopmental disorder characterized by epilepsy, spasticity, and brain atrophy. Understanding the role of Trafficking protein particle complex subunit 4 could open doors to potential therapeutic strategies for this debilitating condition.

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