AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA mismatch repair protein Mlh3

Available from Reaxense
Predicted by Alphafold

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

Q9UHC1

UPID:

MLH3_HUMAN

Alternative names:

MutL protein homolog 3

Alternative UPACC:

Q9UHC1; P49751; Q56DK9; Q9P292; Q9UHC0

Background:

DNA mismatch repair protein Mlh3, also known as MutL protein homolog 3, plays a crucial role in the repair of mismatches in DNA, ensuring genomic stability and fidelity. Its involvement in the cellular mechanisms that correct DNA replication errors is fundamental for preventing mutations that could lead to cancer.

Therapeutic significance:

The protein is directly associated with Hereditary non-polyposis colorectal cancer 7 (HNPCC) and Colorectal cancer, highlighting its critical role in cancer susceptibility. Understanding the role of DNA mismatch repair protein Mlh3 could open doors to potential therapeutic strategies, especially in targeting the genetic underpinnings of colorectal cancer and improving early detection and treatment options.

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