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.
The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.
We employ our advanced, specialised process to create targeted libraries.
Fig. 1. The sreening workflow of Receptor.AI
Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.
Our library distinguishes itself through several key aspects:
partner
Reaxense
upacc
P04271
UPID:
S100B_HUMAN
Alternative names:
S-100 protein beta chain; S-100 protein subunit beta; S100 calcium-binding protein B
Alternative UPACC:
P04271; D3DSN6
Background:
Protein S100-B, also known as S-100 protein beta chain, plays a pivotal role in the brain as one of the most abundant soluble proteins. It binds zinc and calcium with high affinity, influencing various cellular processes. Notably, it acts as a neurotrophic factor, enhancing astrocytosis and axonal proliferation, and is crucial in the innervation of thermogenic adipose tissue. Additionally, S100-B is involved in the activation of STK38 kinase and may influence myocyte apoptosis post-myocardial infarction through interaction with AGER.
Therapeutic significance:
Understanding the role of Protein S100-B could open doors to potential therapeutic strategies.