AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Mothers against decapentaplegic homolog 2

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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

Q15796

UPID:

SMAD2_HUMAN

Alternative names:

JV18-1; Mad-related protein 2; SMAD family member 2

Alternative UPACC:

Q15796

Background:

Mothers against decapentaplegic homolog 2 (SMAD2), also known as JV18-1 and Mad-related protein 2, plays a pivotal role in the TGF-beta signaling pathway. This pathway is crucial for cellular processes such as proliferation, differentiation, and apoptosis. SMAD2 functions as a receptor-regulated SMAD (R-SMAD), acting as an intracellular signal transducer and transcriptional modulator activated by TGF-beta and activin type 1 receptor kinases.

Therapeutic significance:

SMAD2's involvement in congenital heart defects and Loeys-Dietz syndrome 6 highlights its potential as a therapeutic target. Understanding the role of SMAD2 could open doors to potential therapeutic strategies for these cardiovascular disorders, offering hope for patients with these challenging conditions.

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