Focused On-demand Library for Dihydrofolate reductase 2, mitochondrial

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 utilise our cutting-edge, exclusive workflow to develop focused 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:

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

Q86XF0

UPID:

DYR2_HUMAN

Alternative names:

Dihydrofolate reductase, mitochondrial; Dihydrofolate reductase-like protein 1

Alternative UPACC:

Q86XF0; D3DN30; Q6P4I9

Background:

Dihydrofolate reductase 2, mitochondrial, also known as Dihydrofolate reductase-like protein 1, plays a pivotal role in folate metabolism. It is essential for the de novo mitochondrial thymidylate biosynthesis pathway, crucial for DNA replication and repair. This enzyme's unique function includes preventing uracil accumulation in mitochondrial DNA (mtDNA) and regulating its own mRNA along with that of DHFR.

Therapeutic significance:

Understanding the role of Dihydrofolate reductase 2, mitochondrial could open doors to potential therapeutic strategies. Its critical function in folate metabolism and DNA synthesis positions it as a key target for developing treatments aimed at mitochondrial diseases and disorders related to folate metabolism dysregulation.