AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable guanine nucleotide exchange factor MCF2L2

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

We utilise our cutting-edge, exclusive workflow to develop focused 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q86YR7

UPID:

MF2L2_HUMAN

Alternative names:

Dbs-related Rho family guanine nucleotide exchange factor; MCF2-transforming sequence-like protein 2

Alternative UPACC:

Q86YR7; O94942; Q6P2B8; Q6ZVJ5; Q8N318

Background:

The Probable guanine nucleotide exchange factor MCF2L2, also known as Dbs-related Rho family guanine nucleotide exchange factor and MCF2-transforming sequence-like protein 2, plays a pivotal role in cellular processes. Its primary function is likely as a guanine nucleotide exchange factor, crucial for intracellular signaling pathways.

Therapeutic significance:

Given its involvement in Type 2 diabetes mellitus, a disorder marked by insulin resistance and metabolic syndrome, MCF2L2 presents a promising target for therapeutic intervention. Understanding the role of MCF2L2 could open doors to potential therapeutic strategies aimed at mitigating the disease's progression and its associated complications.

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