Focused On-demand Library for StAR-related lipid transfer protein 3

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.

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.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q14849

UPID:

STAR3_HUMAN

Alternative names:

Metastatic lymph node gene 64 protein; Protein CAB1; START domain-containing protein 3

Alternative UPACC:

Q14849; A8MXA4; B4DUY1; F5H0G2; Q53Y53; Q96HM9

Background:

StAR-related lipid transfer protein 3, also known as Metastatic lymph node gene 64 protein, Protein CAB1, and START domain-containing protein 3, plays a pivotal role in cholesterol transport from the endoplasmic reticulum to endosomes. It functions as a sterol-binding protein, facilitating membrane formation inside endosomes and potentially mediating cholesterol transport between various membranes, including mitochondria and cell membrane. This protein's activity is enhanced by phosphorylation, promoting membrane tethering through interaction with VAPA and VAPB.

Therapeutic significance:

Understanding the role of StAR-related lipid transfer protein 3 could open doors to potential therapeutic strategies.