Focused On-demand Library for Forkhead box protein E3

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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 distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q13461

UPID:

FOXE3_HUMAN

Alternative names:

Forkhead-related protein FKHL12; Forkhead-related transcription factor 8

Alternative UPACC:

Q13461; Q5SVY9; Q9NQV9

Background:

Forkhead box protein E3, also known as Forkhead-related protein FKHL12 and Forkhead-related transcription factor 8, plays a pivotal role in lens epithelial cell growth by regulating proliferation, apoptosis, and cell cycle. It is crucial for lens development, ensuring the proper ratio of lens fiber cells to anterior lens epithelium cells through its influence on cell proliferation and differentiation. Additionally, it is instrumental in lens vesicle closure and separation from the ectoderm, and controls DNAJB1 expression, vital for anterior segment eye development.

Therapeutic significance:

Given its involvement in anterior segment dysgenesis 2, cataract 34, multiple types, and familial thoracic aortic aneurysm 11, Forkhead box protein E3 represents a significant target for therapeutic intervention. Understanding its role could open doors to potential therapeutic strategies for these conditions.