Focused On-demand Library for Serine dehydratase-like

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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

Q96GA7

UPID:

SDSL_HUMAN

Alternative names:

L-serine deaminase; L-serine dehydratase/L-threonine deaminase; L-threonine dehydratase; Serine dehydratase 2

Alternative UPACC:

Q96GA7

Background:

Serine dehydratase-like, encoded by the gene with accession number Q96GA7, exhibits enzymatic activities crucial for amino acid metabolism, specifically in the deamination of serine and threonine. Known by alternative names such as L-serine deaminase and L-threonine dehydratase, this protein plays a pivotal role in the catabolic pathway of these amino acids, converting them into pyruvate and alpha-ketobutyrate, respectively.

Therapeutic significance:

Understanding the role of Serine dehydratase-like could open doors to potential therapeutic strategies. Its involvement in amino acid metabolism suggests its potential impact on metabolic disorders, offering a promising avenue for the development of novel treatments.