Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


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.


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


 

Fig. 1. The screening 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
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:
The protein Leiomodin-1, with alternative names such as 64 kDa autoantigen D1 and Smooth muscle leiomodin, is essential for the proper function of visceral smooth muscle cells. It facilitates the formation of actin filaments, crucial for muscle cell contractility. Identified by the unique identifier P29536, Leiomodin-1's significance extends beyond its primary function.

THERAPEUTIC SIGNIFICANCE:
Involvement of Leiomodin-1 in Megacystis-microcolon-intestinal hypoperistalsis syndrome 3 highlights its clinical importance. This genetic disorder, characterized by severe visceral myopathy, underscores the therapeutic potential of targeting Leiomodin-1. Exploring its function and mechanisms could lead to innovative treatments for affected individuals, offering hope for a condition currently associated with significant morbidity and mortality.

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