AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Immunoglobulin lambda-like polypeptide 1

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised 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 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

P15814

UPID:

IGLL1_HUMAN

Alternative names:

CD179 antigen-like family member B; Ig lambda-5; Immunoglobulin omega polypeptide; Immunoglobulin-related protein 14.1

Alternative UPACC:

P15814; Q0P681

Background:

Immunoglobulin lambda-like polypeptide 1, also known as CD179 antigen-like family member B, Ig lambda-5, Immunoglobulin omega polypeptide, and Immunoglobulin-related protein 14.1, plays a pivotal role in B-cell development. This protein's critical function underscores its importance in the immune system's ability to produce antibodies.

Therapeutic significance:

Agammaglobulinemia 2, an autosomal recessive condition, is directly linked to mutations affecting this protein, leading to severe infections early in life due to low or absent serum antibodies and B cells. Understanding the role of Immunoglobulin lambda-like polypeptide 1 could open doors to potential therapeutic strategies for this primary immunodeficiency.

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