title: Computer-aided design, structural dynamics analysis, and in vitro susceptibility test of antibacterial peptides incorporating unnatural amino acids against microbial infections.
abstract: OBJECTIVE
  Antibacterial peptides (ABPs) are essential components of host defense against microbial infections present in all domains of life. The AMPs incorporating unnatural amino acids (uABPs) exhibit several advantages over naturally occurring AMPs based on factors such as bioavailability, metabolic stability and overall toxicity.
  
  
  METHODS
  Computer-aided modeling and in vitro susceptibility test were combined to rationally design short uABPs with potent antimicrobial activity. In the procedure, peptide characterization and machine learning modeling were used to develop statistical regression predictors, which were then employed to guide the molecular design and structural optimization of uABPs, to which a number of commercially available unnatural amino acids were introduced.
  
  
  RESULTS
  An improved uABP population was obtained, from which several promising candidates were successfully prepared and their antibacterial potencies against three bacterial strains Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli were measured using broth microdilution assay. Consequently, four uABPs with hybrid structure property were determined to have high potency against the tested strains with minimum inhibitory concentration (MIC) of <50 µg/ml.
  
  
  CONCLUSIONS
  Molecular dynamics (MD) simulations revealed that the designed uABPs are amphipathic helix in solution but they would largely unfold when spontaneously embedding into an artificial lipid bilayer that mimics microbial membrane.
authors.affiliation: Department of Hematology, The First People's Hospital of Jining, Jining 272011, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Anesthesiology, The Central Hospital of Jinan, Shandong University, Jinan 250013, China.
authors.forename: Yong-Jian
authors.initials: YJ
authors.lastname: Yang
authors.affiliation: Department of Obstetrics, The Central Hospital of Jinan, Shandong University, Jinan 250013, China.
authors.forename: Ya-Na
authors.initials: YN
authors.lastname: Chen
authors.affiliation: Department of Hematology, The Central Hospital of Jinan, Shandong University, Jinan 250013, China.
authors.forename: Hong-Yu
authors.initials: HY
authors.lastname: Zhao
authors.affiliation: Department of Orthopedics, Qilu Hospital, Shandong University, Jinan 250011, China. Electronic address: shuaizzhang@sina.cn.
authors.forename: Shuai
authors.initials: S
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D017076:Computer-Aided Design; D000069550:Machine Learning; D008826:Microbial Sensitivity Tests; D010455:Peptides / Q000494:pharmacology*
chemical_list: D000900:Anti-Bacterial Agents; D010455:Peptides
keywords: Antibacterial peptide; Bioinformatics; Infectious disease; Machine learning; Rational peptide design