Focused On-demand Library for Leiomodin-1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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 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

P29536

UPID:

LMOD1_HUMAN

Alternative names:

64 kDa autoantigen 1D; 64 kDa autoantigen 1D3; 64 kDa autoantigen D1; Leiomodin, muscle form; Smooth muscle leiomodin; Thyroid-associated ophthalmopathy autoantigen

Alternative UPACC:

P29536; B1APV6; C4AMB1; Q68EN2

Background:

Leiomodin-1, also known as Smooth muscle leiomodin, plays a pivotal role in the contractility of visceral smooth muscle cells. It achieves this by mediating the nucleation of actin filaments, a process critical for muscle contraction. This protein is encoded by the gene with the accession number P29536 and is recognized by several alternative names, including 64 kDa autoantigen 1D and Thyroid-associated ophthalmopathy autoantigen.

Therapeutic significance:

Leiomodin-1 is implicated in Megacystis-microcolon-intestinal hypoperistalsis syndrome 3 (MMIHS3), a severe congenital disorder affecting smooth muscle function in the bladder and intestine. Understanding the role of Leiomodin-1 could open doors to potential therapeutic strategies for MMIHS3, a condition with a high mortality rate due to malnutrition, sepsis, and multiorgan failure.