Explore the Potential with AI-Driven Innovation
This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.
Our top-notch dedicated system is used to design specialised libraries for protein-protein interfaces.
Fig. 1. The sreening workflow of Receptor.AI
The method includes extensive molecular simulations of the target protein alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that considers conformational mobility in both free and complex states. Potential binding pockets are examined on the protein-protein interaction interface and in distant allosteric sites to cover all possible mechanisms of action.
Key features that set our library apart include:
partner
Reaxense
upacc
P50539
UPID:
MXI1_HUMAN
Alternative names:
Class C basic helix-loop-helix protein 11
Alternative UPACC:
P50539; B1ANN7; D3DR25; D3DRA9; Q15887; Q6FHW2; Q96E53
Background:
Max-interacting protein 1, also known as Class C basic helix-loop-helix protein 11, plays a crucial role in cellular processes by acting as a transcriptional repressor. It forms a complex with MAX, recognizing the core sequence 5'-CAC[GA]TG-3', thereby antagonizing MYC transcriptional activity. This interaction is pivotal in regulating gene expression and maintaining cellular homeostasis.
Therapeutic significance:
Given its involvement in prostate cancer, where disease susceptibility is linked to gene variants, Max-interacting protein 1 represents a promising target for therapeutic intervention. Understanding its role in cancer biology could lead to the development of novel strategies aimed at modulating its activity, potentially offering new avenues for treatment of prostate cancer and enhancing patient outcomes.