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

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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.

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

P11686

UPID:

PSPC_HUMAN

Alternative names:

Pulmonary surfactant-associated proteolipid SPL(Val); SP5

Alternative UPACC:

P11686; A6XNE4; B2RE00; E9PGX3; P11687; Q12793; Q7Z5D0

Background:

Pulmonary surfactant-associated protein C, also known as SP5 or Pulmonary surfactant-associated proteolipid SPL(Val), plays a crucial role in respiratory function. It is instrumental in promoting alveolar stability by reducing the surface tension at the air-liquid interface in the lungs' peripheral air spaces. This protein's action is vital for efficient gas exchange and lung compliance.

Therapeutic significance:

Mutations in the gene encoding Pulmonary surfactant-associated protein C are linked to Pulmonary surfactant metabolism dysfunction 2 and Respiratory distress syndrome in premature infants. These conditions underscore the protein's critical role in lung health, suggesting that targeted therapies could ameliorate or prevent the progression of related diseases.