Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P40692

UPID:
MLH1_HUMAN

ALTERNATIVE NAMES:
MutL protein homolog 1

ALTERNATIVE UPACC:
P40692; B4DI13; B4DQ11; E9PCU2

BACKGROUND:
The DNA mismatch repair protein Mlh1, or MutL protein homolog 1, is integral to the body's ability to correct DNA replication errors. By forming complexes such as MutL alpha with PMS2, it ensures the fidelity of DNA replication, playing a critical role in preventing the accumulation of mutations that could lead to cancer. Its interaction with DNA polymerase III highlights its importance in the DNA repair process.

THERAPEUTIC SIGNIFICANCE:
Given its crucial role in preventing mutations that lead to cancer, Mlh1 is associated with a range of hereditary cancer syndromes, including Lynch syndrome and colorectal cancer. The exploration of Mlh1's functions and mechanisms offers promising avenues for the development of novel cancer therapies, particularly for those with a genetic predisposition to these conditions.

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