AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Laminin subunit beta-2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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

P55268

UPID:

LAMB2_HUMAN

Alternative names:

Laminin B1s chain; Laminin-11 subunit beta; Laminin-14 subunit beta; Laminin-15 subunit beta; Laminin-3 subunit beta; Laminin-4 subunit beta; Laminin-7 subunit beta; Laminin-9 subunit beta; S-laminin subunit beta

Alternative UPACC:

P55268; Q16321

Background:

Laminin subunit beta-2, known by alternative names such as Laminin B1s chain and Laminin-11 subunit beta, plays a crucial role in the architecture of basement membranes. It is pivotal in mediating cell attachment, migration, and organization during embryonic development by interacting with other extracellular matrix components.

Therapeutic significance:

Laminin subunit beta-2 is implicated in severe disorders like Pierson syndrome and Nephrotic syndrome 5, characterized by early-onset nephrotic syndrome and potential neurodevelopmental delay. Understanding the role of Laminin subunit beta-2 could open doors to potential therapeutic strategies for these life-threatening conditions.

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