AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Laminin subunit alpha-4

Available from Reaxense
Predicted by Alphafold

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 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.

Our high-tech, dedicated method is applied to construct targeted 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q16363

UPID:

LAMA4_HUMAN

Alternative names:

Laminin-14 subunit alpha; Laminin-8 subunit alpha; Laminin-9 subunit alpha

Alternative UPACC:

Q16363; Q14731; Q14735; Q15335; Q4LE44; Q5SZG8; Q9BTB8; Q9UE18; Q9UJN9

Background:

Laminin subunit alpha-4, known by alternative names such as Laminin-14 subunit alpha, Laminin-8 subunit alpha, and Laminin-9 subunit alpha, plays a crucial role in the attachment, migration, and organization of cells into tissues during embryonic development. It achieves this by binding to cells via a high-affinity receptor and interacting with other extracellular matrix components.

Therapeutic significance:

The protein's involvement in Cardiomyopathy, dilated, 1JJ, a disorder characterized by ventricular dilation and impaired systolic function leading to congestive heart failure and arrhythmia, highlights its potential as a target for therapeutic intervention. Understanding the role of Laminin subunit alpha-4 could open doors to potential therapeutic strategies.

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