Focused On-demand Library for Calcium-binding and coiled-coil domain-containing protein 2

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Q13137

UPID:

CACO2_HUMAN

Alternative names:

Antigen nuclear dot 52 kDa protein; Nuclear domain 10 protein NDP52; Nuclear dot protein 52

Alternative UPACC:

Q13137; B2RBT0; B4DDC4; B4DDT4; B4DP36; B4E0C0; E7ENK0; E7ETP5; E9PBE5; Q53FQ5; Q53HB5; Q6IBN9; Q9BTF7

Background:

Calcium-binding and coiled-coil domain-containing protein 2, also known as Nuclear domain 10 protein NDP52, plays a pivotal role in autophagy, specifically targeting intracellular bacteria like Salmonella typhimurium for degradation. It acts as an effector in galectin-sensed membrane damage, orchestrating the targeting of bacteria to autophagosomes and ensuring their degradation by regulating autophagosome maturation. Its interaction with MAP1LC3A, MAP1LC3B, GABARAPL2, and MAP3LC3C is crucial for these processes. Additionally, NDP52 may influence actin cytoskeleton organization and negatively regulate constitutive secretion.

Therapeutic significance:

Understanding the role of Calcium-binding and coiled-coil domain-containing protein 2 could open doors to potential therapeutic strategies.