Focused On-demand Library for Pulmonary surfactant-associated protein A1

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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.







Alternative names:

35 kDa pulmonary surfactant-associated protein; Alveolar proteinosis protein; Collectin-4

Alternative UPACC:

Q8IWL2; A8K3T8; B7ZW50; E3VLD8; E3VLD9; E3VLE0; E3VLE1; G5E9J3; P07714; Q14DV4; Q5RIR5; Q5RIR7; Q6PIT0; Q8TC19


Pulmonary surfactant-associated protein A1 (SFTPA1) plays a crucial role in respiratory function by reducing surface tension in the alveoli and facilitating normal breathing. It binds to surfactant phospholipids in the presence of calcium ions and enhances the expression of MYO18A/SP-R210 on alveolar macrophages. Additionally, SFTPA1 is involved in the immune response, recognizing and opsonizing pathogens to aid their elimination.

Therapeutic significance:

SFTPA1 is linked to interstitial lung disease 1 and respiratory distress syndrome in premature infants, diseases characterized by impaired gas exchange and lung function. Understanding the role of SFTPA1 could lead to novel therapeutic strategies for these conditions, emphasizing its importance in drug discovery for respiratory diseases.

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