Focused On-demand Library for ER membrane protein complex subunit 7

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Q9NPA0

UPID:

EMC7_HUMAN

Alternative names:

Alternative UPACC:

Q9NPA0; B2RC00; Q96ED5

Background:

ER membrane protein complex subunit 7 plays a crucial role in the endoplasmic reticulum membrane protein complex (EMC), facilitating the energy-independent insertion of newly synthesized membrane proteins into endoplasmic reticulum membranes. It shows a preference for proteins with transmembrane domains that are weakly hydrophobic or contain destabilizing features. This protein is essential for the cotranslational insertion of multi-pass membrane proteins and the post-translational insertion of tail-anchored proteins, thereby controlling the topology of multi-pass membrane proteins like G protein-coupled receptors.

Therapeutic significance:

Understanding the role of ER membrane protein complex subunit 7 could open doors to potential therapeutic strategies.