Specific mode of interaction between components of model pulmonary surfactants using computer simulations

Yiannis N. Kaznessis, Sangtae Kim, Ronald G. Larson

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


Atomistic molecular dynamics simulations and structural bioinformatics tools enable the identification of the exact mode of interaction between model pulmonary surfactant components. Two nanosecondlong simulations of the N-terminal region of human surfactant protein-B (SP-B1 - 25) in dipalmitoylphosphatidylcholine (DPPC) and dipalmitoylphosphatidylglycerol (DPPG) monolayers of different lipid surface densities reveal the preferential affinity of SP-B1 - 25 for anionic phospholipids. In particular, arginine 12 and lysine 24 interact strongly and with high specificity with the phosphate group of the DPPG lipids, stabilizing the position, the orientation, and the secondary structure of the peptide in the monolayer. The peptide lies at an oblique angle to the interfacial plane, ranging between 47° and 62°, increasing with decreasing lipid surface density. In DPPC monolayers the interaction is largely determined by hydrophobic interactions. The non-specific nature of DPPC-SP-B1 - 25 interactions allows for significant flexibility in the topology of the peptide in the lipid matrix. Bioinformatics tools are employed to generalize the simulation results to the sequences of SP-B1 - 25 in other organisms. The importance of specific residues, and the role of the largely helical and amphiphilic nature of the peptide in the functionality of SP-B1 - 25 are established. The synergy of classical mechanics tools with bioinformatics methods greatly enhances the molecular-level interpretation of pulmonary surfactant action and facilitates the development of design rules for synthetic surfactant analogues.

Original languageEnglish (US)
Pages (from-to)569-582
Number of pages14
JournalJournal of Molecular Biology
Issue number3
StatePublished - 2002

Bibliographical note

Funding Information:
Y.N.K. thanks Pfizer Global Research and Development, Ann Arbor Laboratories, for funding of his postdoctoral fellowship. We thank Ka Yee Lee, Alan Waring, and Eric Fauman for useful suggestions. We also gratefully acknowledge support by the National Computational Science Alliance under grant number MCB000007N at the NCSA Origin2000.

Copyright 2020 Elsevier B.V., All rights reserved.


  • Computer simulations
  • Protein-lipid interactions
  • Surfactant monolayers
  • Synthetic lung surfactants


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