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

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

Our top-notch dedicated system is used to design specialised 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the 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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