Focused On-demand Library for Lipid transferase CIDEC

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.

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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q96AQ7

UPID:

CIDEC_HUMAN

Alternative names:

Cell death activator CIDE-3; Cell death-inducing DFFA-like effector protein C; Fat-specific protein FSP27 homolog

Alternative UPACC:

Q96AQ7; C9JMN7; Q67DW9; Q9GZY9

Background:

Lipid transferase CIDEC, also known as Cell death activator CIDE-3, plays a pivotal role in lipid metabolism within white adipose tissue. It facilitates the formation of unilocular lipid droplets by mediating their fusion, thus promoting lipid storage over lipolysis. This process is crucial for maintaining energy balance and metabolic health. CIDEC localizes on the lipid droplet surface, engaging in atypical lipid droplet fusion through liquid-liquid phase separation and directional net neutral lipid transfer.

Therapeutic significance:

CIDEC's involvement in Lipodystrophy, familial partial, 5, a condition characterized by abnormal fat distribution and metabolic complications, underscores its therapeutic potential. Targeting CIDEC's pathway could offer novel interventions for managing lipodystrophy and related metabolic disorders, providing a promising avenue for drug discovery aimed at restoring lipid homeostasis and improving insulin sensitivity.