Focused On-demand Library for Pulmonary surfactant-associated protein C

Focused On-demand Libraries - Receptor.AI 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. Reaxense helps in synthesizing and delivering these compounds.


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 screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
P11686

UPID:
PSPC_HUMAN

ALTERNATIVE NAMES:
Pulmonary surfactant-associated proteolipid SPL(Val); SP5

ALTERNATIVE UPACC:
P11686; A6XNE4; B2RE00; E9PGX3; P11687; Q12793; Q7Z5D0

BACKGROUND:
The protein known as Pulmonary surfactant-associated protein C, with alternative names SP5 and Pulmonary surfactant-associated proteolipid SPL(Val), is essential for maintaining lung function. It significantly contributes to lowering the surface tension within the lungs, facilitating proper gas exchange and preventing alveolar collapse.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Pulmonary surfactant-associated protein C could open doors to potential therapeutic strategies for treating Pulmonary surfactant metabolism dysfunction 2 and Respiratory distress syndrome in premature infants. These insights offer a promising avenue for developing interventions that could significantly improve outcomes for affected individuals.

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