AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Lethal(3)malignant brain tumor-like protein 1

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.

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

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused 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

Q9Y468

UPID:

LMBL1_HUMAN

Alternative names:

L(3)mbt protein homolog; L3MBTL1

Alternative UPACC:

Q9Y468; B4DRC9; E1P5W7; Q5H8Y8; Q5H8Y9; Q8IUV7; Q9H1E6; Q9H1G5; Q9UG06; Q9UJB9; Q9Y4C9

Background:

Lethal(3)malignant brain tumor-like protein 1 (L3MBTL1), also known as L(3)mbt protein homolog, plays a pivotal role in chromatin compaction and transcription repression. It functions as a 'reader' of post-translational modifications, binding to mono- and dimethyllysine residues on histones and other proteins, such as p53/TP53 and RB1/RB. This activity contributes to maintaining genes in a transcriptionally repressive state, crucial for normal cell proliferation and mitosis.

Therapeutic significance:

Understanding the role of Lethal(3)malignant brain tumor-like protein 1 could open doors to potential therapeutic strategies.

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