Focused On-demand Library for Transcription factor MafA

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q8NHW3

UPID:

MAFA_HUMAN

Alternative names:

Pancreatic beta-cell-specific transcriptional activator; RIPE3b1 factor; V-maf musculoaponeurotic fibrosarcoma oncogene homolog A

Alternative UPACC:

Q8NHW3

Background:

Transcription factor MafA, also known as Pancreatic beta-cell-specific transcriptional activator, RIPE3b1 factor, and V-maf musculoaponeurotic fibrosarcoma oncogene homolog A, is pivotal in insulin gene expression. It synergizes with NEUROD1/BETA2 and PDX1, binding to the insulin enhancer C1/RIPE3b element and TRE-type MARE DNA sequences, crucial for glucose regulation.

Therapeutic significance:

MafA's malfunction is linked to Insulinomatosis and diabetes mellitus, diseases characterized by multicentric insulinomas, hyperinsulinemic hypoglycemia, and varying degrees of glucose intolerance. Understanding MafA's role could unveil new therapeutic strategies for these conditions.