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.

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.

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 utilise our cutting-edge, exclusive workflow to develop 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 distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages 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.