Focused On-demand Library for Mucosa-associated lymphoid tissue lymphoma translocation protein 1

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Q9UDY8

UPID:

MALT1_HUMAN

Alternative names:

MALT lymphoma-associated translocation; Paracaspase

Alternative UPACC:

Q9UDY8; Q9NTB7; Q9ULX4

Background:

Mucosa-associated lymphoid tissue lymphoma translocation protein 1, also known as MALT1, plays a pivotal role in immune response. It enhances BCL10-induced activation, crucial for NF-kappa-B and MAP kinase p38 pathways, leading to pro-inflammatory cytokines and chemokines expression. MALT1's protease activity is vital for T-cell antigen receptor-induced integrin adhesion and T helper 17 cells differentiation, marking its significance in adaptive and innate immunity.

Therapeutic significance:

MALT1's involvement in Immunodeficiency 12, characterized by recurrent infections and impaired T-cell responses, underscores its therapeutic potential. Targeting MALT1 could offer new avenues for treating primary immunodeficiencies and related immune disorders, highlighting the importance of understanding its biological mechanisms.