AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cytotoxic T-lymphocyte protein 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 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

P16410

UPID:

CTLA4_HUMAN

Alternative names:

Cytotoxic T-lymphocyte-associated antigen 4

Alternative UPACC:

P16410; A0N1S0; E9PDH0; O95653; Q0PP65; Q52MC1; Q53TD5; Q5S005; Q8WXJ1; Q96P43; Q9UKN9

Background:

Cytotoxic T-lymphocyte protein 4 (CTLA-4), also known as Cytotoxic T-lymphocyte-associated antigen 4, plays a pivotal role in the immune system as a major negative regulator of T-cell responses. Its interaction with natural B7 family ligands, CD80 and CD86, showcases a stronger affinity compared to the stimulatory coreceptor CD28, highlighting its critical function in modulating immune responses.

Therapeutic significance:

CTLA-4's involvement in diseases such as Systemic lupus erythematosus, Type 1 diabetes mellitus 12, Celiac disease 3, and Immune dysregulation with autoimmunity, immunodeficiency, and lymphoproliferation underscores its potential as a therapeutic target. Understanding the role of CTLA-4 could open doors to potential therapeutic strategies, offering hope for patients suffering from these autoimmune disorders.

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