AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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

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

Reaxense

upacc

P07988

UPID:

PSPB_HUMAN

Alternative names:

18 kDa pulmonary-surfactant protein; 6 kDa protein; Pulmonary surfactant-associated proteolipid SPL(Phe)

Alternative UPACC:

P07988; Q96R04

Background:

Pulmonary surfactant-associated protein B, known as SP-B, is crucial for lung function, promoting alveolar stability by reducing surface tension in the air spaces. This protein, with alternative names such as 18 kDa pulmonary-surfactant protein and Pulmonary surfactant-associated proteolipid SPL(Phe), plays a pivotal role in respiratory physiology.

Therapeutic significance:

SP-B is linked to Pulmonary surfactant metabolism dysfunction 1, a rare lung disorder, and Respiratory distress syndrome in premature infants, highlighting its therapeutic potential. Understanding SP-B's role could lead to novel treatments for these life-threatening conditions.

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