Focused On-demand Library for Galectin-3

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 employ our advanced, specialised process to create targeted 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 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

P17931

UPID:

LEG3_HUMAN

Alternative names:

35 kDa lectin; Carbohydrate-binding protein 35; Galactose-specific lectin 3; Galactoside-binding protein; IgE-binding protein; L-31; Laminin-binding protein; Lectin L-29; Mac-2 antigen

Alternative UPACC:

P17931; B2RC38; Q16005; Q6IBA7; Q96J47

Background:

Galectin-3, encoded by the gene with accession number P17931, is a multifunctional protein known by various names including 35 kDa lectin, Carbohydrate-binding protein 35, and IgE-binding protein. It plays a pivotal role in biological processes such as endothelial cells migration, early embryogenesis, pre-mRNA splicing, and acute inflammatory responses. Its ability to interact with integrins, coordinate neutrophil activation, and facilitate autophagy underscores its significance in cellular functioning.

Therapeutic significance:

Understanding the role of Galectin-3 could open doors to potential therapeutic strategies. Its involvement in critical cellular processes and inflammatory responses highlights its potential as a target for therapeutic intervention in diseases characterized by inflammation and abnormal cellular migration.