QSAR modeling of the antimicrobial activity of peptides as a mathematical function of a sequence of amino acids

Antimicrobial peptides have emerged as new therapeutic agents for fighting multi-drug-resistant bacteria. However, the process of optimizing peptide antimicrobial activity and specificity using large peptide libraries is both tedious and expensive. Therefore, computational techniques had to be applied for process optimization. In this work, the representation of the molecular structure of peptides (mastoparan analogs) by a sequence of amino acids has been used to establish quantitative structure-activity relationships (QSARs) for their antibacterial activity. The data for the studied peptides were split three times into the training, calibration and test sets. The Monte Carlo method was used as a computational technique for QSAR models calculation. The statistical quality of QSAR for the antibacterial activity of peptides for the external validation set was: n=7, r(2)=0.8067, s=0.248 (split 1); n=6, r(2)=0.8319, s=0.169 (split 2); and n=6, r(2)=0.6996, s=0.297 (split 3). The stated statistical parameters favor the presented QSAR models in comparison to 2D and 3D descriptor based ones. The Monte Carlo method gave a reasonably good prediction for the antibacterial activity of peptides. The statistical quality of the prediction is different for three random splits. However, the predictive potential is reasonably well for all cases. The presented QSAR modeling approach can be an attractive alternative of 3D QSAR at least for the described peptides.

[1]  L. Birnbaumer,et al.  Heterotrimeric Gα(i) proteins are regulated by lipopolysaccharide and are anti-inflammatory in endotoxemia and polymicrobial sepsis. , 2011, Biochimica et biophysica acta.

[2]  E. Ross,et al.  A Gs-selective analog of the receptor-mimetic peptide mastoparan binds to Gs alpha in a kinked helical conformation. , 1997, Biochemistry.

[3]  A. Pokorny,et al.  Wasp mastoparans follow the same mechanism as the cell-penetrating peptide transportan 10. , 2009, Biochemistry.

[4]  A. Milac,et al.  More effective antimicrobial mastoparan derivatives, generated by 3D-QSAR-Almond and computational mutagenesis. , 2012, Molecular bioSystems.

[5]  Andrey A Toropov,et al.  SMILES-based QSAR model for arylpiperazines as high-affinity 5-HT(1A) receptor ligands using CORAL. , 2013, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[6]  D. Devine,et al.  In vitro susceptibility of the Streptococcus milleri group to antimicrobial peptides. , 2008, International endodontic journal.

[7]  E. Krause,et al.  Peptide helicity and membrane surface charge modulate the balance of electrostatic and hydrophobic interactions with lipid bilayers and biological membranes. , 1996, Biochemistry.

[8]  Eduardo A. Castro,et al.  QSAR treatment on a new class of triphenylmethyl-containing compounds as potent anticancer agents , 2011 .

[9]  Kuo-Chen Chou,et al.  Peptide reagent design based on physical and chemical properties of amino acid residues , 2007, J. Comput. Chem..

[10]  Artem Cherkasov,et al.  Application of 'inductive' QSAR descriptors for quantification of antibacterial activity of cationic polypeptides. , 2004, Molecules.

[11]  S. Avram,et al.  Evaluation of Antimicrobial Activity of New Mastoparan Derivatives Using QSAR and Computational Mutagenesis , 2011, International Journal of Peptide Research and Therapeutics.

[12]  Pablo R Duchowicz,et al.  A comparative QSAR on 1,2,5-thiadiazolidin-3-one 1,1-dioxide compounds as selective inhibitors of human serine proteinases. , 2011, Journal of molecular graphics & modelling.

[13]  Y. Ohizumi,et al.  Identification of a 97-kDa mastoparan-binding protein involving in Ca(2+) release from skeletal muscle sarcoplasmic reticulum. , 2000, Molecular pharmacology.

[14]  Hiroshi Nikaido,et al.  The Challenge of Efflux-Mediated Antibiotic Resistance in Gram-Negative Bacteria , 2015, Clinical Microbiology Reviews.

[15]  T. Niidome,et al.  Interaction of mastoparan with membranes studied by 1H-NMR spectroscopy in detergent micelles and by solid-state 2H-NMR and 15N-NMR spectroscopy in oriented lipid bilayers. , 2001, European journal of biochemistry.

[16]  M. Radu,et al.  Mechanisms of Ceftazidime and Ciprofloxacin Transport through Porins in Multidrug-Resistance Developed by Extended-Spectrum Beta-Lactamase E.coli Strains , 2011, Journal of Fluorescence.

[17]  Zong Dai,et al.  QSAR modeling of peptide biological activity by coupling support vector machine with particle swarm optimization algorithm and genetic algorithm. , 2010, Journal of molecular graphics & modelling.

[18]  M. Palma,et al.  Investigating the effect of different positioning of lysine residues along the peptide chain of mastoparans for their secondary structures and biological activities , 2010, Amino Acids.

[19]  M. Palma,et al.  The effect of acidic residues and amphipathicity on the lytic activities of mastoparan peptides studied by fluorescence and CD spectroscopy , 2010, Amino Acids.

[20]  R. Hancock,et al.  Anti-endotoxin properties of cationic host defence peptides and proteins , 2005, Journal of endotoxin research.

[21]  K. Brandenburg,et al.  Endotoxins: relationship between structure, function, and activity. , 2010, Sub-cellular biochemistry.

[22]  M. Palma,et al.  Selectivity in the mechanism of action of antimicrobial mastoparan peptide Polybia-MP1 , 2008, European Biophysics Journal.

[23]  H. Neu,et al.  The Crisis in Antibiotic Resistance , 1992, Science.

[24]  J. Barrett,et al.  Antibiotics: where did we go wrong? , 2005, Drug discovery today.

[25]  Andrey A Toropov,et al.  CORAL software: prediction of carcinogenicity of drugs by means of the Monte Carlo method. , 2014, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[26]  S. Levy,et al.  Antibacterial resistance worldwide: causes, challenges and responses , 2004, Nature Medicine.

[27]  P. Achary,et al.  QSPR modelling of dielectric constants of π-conjugated organic compounds by means of the CORAL software , 2014, SAR and QSAR in environmental research.

[28]  V. Čeřovský,et al.  New potent antimicrobial peptides from the venom of Polistinae wasps and their analogs , 2008, Peptides.

[29]  A. Kowluru,et al.  Mastoparan-induced insulin secretion from insulin-secreting betaTC3 and INS-1 cells: evidence for its regulation by Rho subfamily of G proteins. , 2003, Endocrinology.

[30]  Victor I Band,et al.  Mechanisms of Antimicrobial Peptide Resistance in Gram-Negative Bacteria , 2014, Antibiotics.

[31]  Emilio Benfenati,et al.  QSAR modeling of endpoints for peptides which is based on representation of the molecular structure by a sequence of amino acids , 2012, Structural Chemistry.