AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Mortality factor 4-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.

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.

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 employ our advanced, specialised process to create targeted 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.

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

Reaxense

upacc

Q9UBU8

UPID:

MO4L1_HUMAN

Alternative names:

MORF-related gene 15 protein; Protein MSL3-1; Transcription factor-like protein MRG15

Alternative UPACC:

Q9UBU8; B4DKN6; B7Z6R1; D3DW88; O95899; Q5QTS1; Q6NVX8; Q86YT7; Q9HBP6; Q9NSW5

Background:

Mortality factor 4-like protein 1, also known as MORF-related gene 15 protein, Protein MSL3-1, and Transcription factor-like protein MRG15, plays a pivotal role in transcriptional activation through its involvement in the NuA4 histone acetyltransferase complex. This complex is crucial for acetylation of histones H4 and H2A, altering nucleosome-DNA interactions and facilitating transcription regulation. Additionally, it contributes to DNA repair, apoptosis, and DNA damage response through its association with the mSin3A complex and involvement in homologous recombination repair.

Therapeutic significance:

Understanding the role of Mortality factor 4-like protein 1 could open doors to potential therapeutic strategies.

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