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 utilise our cutting-edge, exclusive workflow to develop focused libraries.
Fig. 1. The sreening workflow of Receptor.AI
Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.
Our library stands out due to several important features:
partner
Reaxense
upacc
P14136
UPID:
GFAP_HUMAN
Alternative names:
-
Alternative UPACC:
P14136; A7REI1; B2RD44; D3DX59; E9PAX3; Q53H98; Q5D055; Q6ZQS3; Q7Z5J6; Q7Z5J7; Q96KS4; Q96P18; Q9UFD0
Background:
The Glial fibrillary acidic protein (GFAP), a class-III intermediate filament, serves as a cell-specific marker distinguishing astrocytes from other glial cells in the central nervous system's development. Its unique structure and function are pivotal in maintaining the integrity and performance of neural networks.
Therapeutic significance:
Alexander disease, a rare central nervous system disorder, is directly linked to mutations affecting GFAP. This connection underscores the protein's critical role in neural health and disease, highlighting the importance of GFAP-targeted research in uncovering novel therapeutic strategies for managing and potentially curing Alexander disease.