Protonation states in molecular dynamics simulations of peptide folding and binding

Current Pharmaceutical Design

Volumn 19, Issue 23, 2013, Pages 4173-4181

  Ben Shimon, Avraham ^a   Shalev, Deborah E ^a   Niv, Masha Y ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

Computational; Docking; Drug design; Flexibility; Molecular dynamics; Peptidomimetics; Protein protein interactions

Indexed keywords

PEPTIDE;

CHEMICAL STRUCTURE; CONFORMATIONAL TRANSITION; DRUG DESIGN; GENETIC ALGORITHM; HYDROGEN BOND; MOLECULAR DYNAMICS; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN FOLDING; PROTEIN PROTEIN INTERACTION; PROTEIN STRUCTURE; PROTON TRANSPORT; REVIEW; SOLVATION; STATIC ELECTRICITY;

MOLECULAR DYNAMICS SIMULATION; PEPTIDES; PEPTIDOMIMETICS; PROTEIN BINDING; PROTEIN FOLDING; PROTEINS; PROTONS;

EID: 84878666357     PISSN: 13816128     EISSN: 18734286     Source Type: Journal    
DOI: 10.2174/1381612811319230003     Document Type: Review

References (126)

1. Ruiz-Gomez G, Tyndall JDA, Pfeiffer B, Abbenante G, Fairlie DP. Update 1 of: Over One Hundred Petide-Activated G Protein-Coupled Receptors Recognized Ligands with Turn Structure. Chem Rev 2010; 110(4): Pr1-Pr41.
2. Stein A, Mosca R, Aloy P. Three-dimensional modeling of protein interactions and complexes is going omics. Current Opinion in Structural Biology 2011; 21(2): 200-8.
3. Rubinstein M, Niv MY. Peptidic modulators of protein-protein interactions: progress and challenges in computational design. Biopolymers 2009; 91(7): 505-13.
4. Arora PS, Ansari AZ. Chemical biology: A Notch above other inhibitors. Nature 2009; 462(7270): 171-3.
5. Kritzer JA. Stapled peptides: Magic bullets in nature's arsenal. Nat Chem Biol 2010; 6(8): 566-7.
6. Niv MY, Rubin H, Cohen J, et al. Sequence-based design of kinase inhibitors applicable for therapeutics and target identification. J Biological Chem 2004; 279(2): 1242-55.
7. Vlieghe P, Lisowski V, Martinez J, Khrestchatisky M. Synthetic therapeutic peptides: science and market. Drug Discovery Today 2010; 15(1-2): 40-56.
8. Webb BA, Chimenti M, Jacobson MP, Barber DL. Dysregulated pH: a perfect storm for cancer progression. Nat Rev Cancer 2011; 11(9): 671-7.
9. Fendos J, Engelman D. pHLIP and Acidity as a Universal Biomarker for Cancer. Yale J Biol Med 2012; 85(1): 29-35.
10. Lowik DWPM, Leunissen EHP, van den Heuvel M, Hansen MB, van Hest JCM. Stimulus responsive peptide based materials. Chem Soc Rev 2010; 39(9): 3394-412.
11. Ben-Shimon A, Niv MY. Deciphering the Arginine-binding preferences at the substrate-binding groove of Ser/Thr kinases by computational surface mapping. PLoS Comput Biol 2011; 7(11): e1002288.
12. Licht-Murava A, Plotkin B, Eisenstein M, Eldar-Finkelman H. Elucidating Substrate and Inhibitor Binding Sites on the Surface of GSK-3 beta and the Refinement of a Competitive Inhibitor. J Mol Biol 2011; 408(2): 366-78.
13. London N, Lamphear CL, Hougland JL, Fierke CA, Schueler-Furman O. Identification of a Novel Class of Farnesylation Targets by Structure-Based Modeling of Binding Specificity. PLoS Comput Biol 2011; 7(10): e1002170.
14. Madsen KL, Beuming T, Niv MY, et al. Molecular determinants for the complex binding specificity of the PDZ domain in PICK1. J Biol Chem 2005; 280(21): 20539-48.
15. Tal-Gan Y, Hurevich M, Klein S, et al. Backbone cyclic peptide inhibitors of protein kinase B (PKB/Akt). J Med Chem 2011; 54(14): 5154-64.
16. Herce HD, Garcia AE. Molecular dynamics simulations suggest a mechanism for translocation of the HIV-1 TAT peptide across lipid membranes. Proc Natl Acad Sci USA 2007; 104(52): 20805-10.
17. Meli M, Morra G, Colombo G. Investigating the mechanism of peptide aggregation: insights from mixed monte carlo-molecular dynamics simulations. Biophys J 2008; 94(11): 4414-26.
18. Kiran MD, Adikesavan NV, Cirioni O, et al. Discovery of a quorum-sensing inhibitor of drug-resistant staphylococcal infections by structure-based virtual screening. Mol Pharmacol 2008; 73(5): 1578-86.
19. Floris M, Moro S. Mimicking Peptides. In Silico. Molecular Informatics 2011; 31(1): 12-20.
20. Ben-Shimon A, Eisenstein M. Computational Mapping of Anchoring Spots on Protein Surfaces. J Mol Biol 2010; 402(1): 259-77.
21. Niv MY, Weinstein H. A flexible docking procedure for the exploration of peptide binding selectivity to known structures and homology models of PDZ domains. J Am Chem Soc 2005; 127(40): 14072-9.
22. Raveh B, London N, Zimmerman L, Schueler-Furman O. Rosetta FlexPepDockab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors. Plos One 2011; 6(4): 11.
23. Donsky E, Wolfson HJ. PepCrawler: a fast RRT-based algorithm for high-resolution refinement and binding affinity estimation of peptide inhibitors. Bioinformatics 2011; 27(20): 2836-42.
24. Staneva I, Wallin S. Binding Free Energy Landscape of Domain-Peptide Interactions. Plos Computational Biol 2011; 7(8): 9.
25. Alexov E, Mehler EL, Baker N, et al. Progress in the prediction of pK(a) values in proteins. Proteins-Structure Function Bioinformatics 2011; 79(12): 3260-75.
26. Nielsen JE, Gunner MR, Garcia-Moreno EB. The pK(a) Cooperative: A collaborative effort to advance structure-based calculations of pK(a) values and electrostatic effects in proteins. Proteins-Structure Function Bioinformatics 2011; 79(12): 3249-59.
27. Kryshtafovych A, Fidelis K, Moult J. CASP9 results compared to those of previous CASP experiments. Proteins.79 Suppl 10: 196-207.
28. Wodak SJ. From the Mediterranean coast to the shores of Lake Ontario: CAPRI's premiere on the American continent. Proteins 2007; 69(4): 697-8.
29. Michino M, Abola E, Brooks CL, 3rd, Dixon JS, Moult J, Stevens RC. Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008. Nat Rev Drug Discov 2009; 8(6): 455-63.
30. Alexov EG, Gunner MR. Incorporating protein conformational flexibility into the calculation of pH-dependent protein properties. Biophys J 1997; 72(5): 2075-93.
31. Antosiewicz J, McCammon JA, Gilson MK. The determinants of pKas in proteins. Biochemistry 1996; 35(24): 7819-33.
32. Nielsen JE, Andersen KV, Honig B, et al. Improving macromolecular electrostatics calculations. Protein Eng 1999; 12(8): 657-62.
33. Nielsen JE, Vriend G. Optimizing the hydrogen-bond network in Poisson-Boltzmann equation-based pK(a) calculations. Proteins 2001; 43(4): 403-12.
34. Castaneda CA, Fitch CA, Majumdar A, Khangulov V, Schlessman JL, Garcia-Moreno BE. Molecular determinants of the pKa values of Asp and Glu residues in staphylococcal nuclease. Proteins 2009; 77(3): 570-88.
35. Simonson T. Dielectric relaxation in proteins: the computational perspective. Photosynth Res 2008; 97(1): 21-32.
36. Whitten ST, Garcia-Moreno EB, Hilser VJ. Local conformational fluctuations can modulate the coupling between proton binding and global structural transitions in proteins. Proc Natl Acad Sci USA 2005; 102(12): 4282-7.
37. Macdermaid CM, Kaminski GA. Electrostatic polarization is crucial for reproducing pKa shifts of carboxylic residues in Turkey ovomucoid third domain. J Phys Chem B 2007; 111(30): 9036-44.
38. Warshel A, Dryga A. Simulating electrostatic energies in proteins: Perspectives and some recent studies of pK(a)s, redox, and other crucial functional properties. Proteins-Structure Function and Bioinformatics 2011; 79(12): 3469-84.
39. Antosiewicz J, McCammon JA, Gilson MK. Prediction of pHdependent properties of proteins. J Mol Biol 1994; 238(3) 415-36.
40. Bashford D, Karplus M. pKa's of ionizable groups in proteins: atomic detail from a continuum electrostatic model. Biochemistry 1990; 29(44): 10219-25.
41. Yang AS, Gunner MR, Sampogna R, Sharp K, Honig B. On the calculation of pKas in proteins. Proteins 1993; 15(3): 252-65.
42. Baker NA. Poisson-Boltzmann methods for biomolecular electrostatics. Methods Enzymol 2004; 383: 94-118.
43. Bashford D. Macroscopic electrostatic models for protonation states in proteins. Front Biosci 2004; 9: 1082-99.
44. Nicholls A, Honig B. A rapid finite difference algorithm, utilizing successive over-relaxation to solve the Poisson-Boltzmann equation. J Comput Chem 1991; 12(4): 435-45.
45. Rocchia W, Sridharan S, Nicholls A, Alexov E, Chiabrera A, Honig B. Rapid grid-based construction of the molecular surface and the use of induced surface charge to calculate reaction field energies: applications to the molecular systems and geometric objects. J Comput Chem 2002; 23(1): 128-37.
46. Li L, Li C, Sarkar S, et al. DelPhi: a comprehensive suite for DelPhi software and associated resources. BMC Biophys 2012; 5(1): 9.
47. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA. Electrostatics of nanosystems: Application to microtubules and the ribosome. Proc Natl Acad Sci USA 2001; 98(18): 10037-41.
48. Lu BZ, Zhou YC, Holst MJ, McCammon JA. Recent progress in numerical methods for the Poisson-Boltzmann equation in biophysical applications. Communications in Computational Physics 2008; 3(5): 973-1009.
49. Bashford D, Case DA. Generalized born models of macromolecular solvation effects. Annu Rev Phys Chem 2000; 51: 129-52.
50. Chen J, Brooks CL, 3rd, Khandogin J. Recent advances in implicit solvent-based methods for biomolecular simulations. Curr Opin Struct Biol 2008; 18(2): 140-8.
51. Onufriev A. Continuum Electrostatics Solvent Modeling with the Generalized Born Model. Modeling Solvent Environments, Wiley-VCH Verlag GmbH & Co KGaA 2010: 127-65.
52. Still WC, Tempczyk A, Hawley RC, Hendrickson T. Semianalytical Treatment of Solvation for Molecular Mechanics and Dynamics. J Am Chem Soc 1990; 112(16): 6127-9.
53. Shell MS, Ritterson R, Dill KA. A test on peptide stability of AMBER force fields with implicit solvation. J Phys Chem B 2008; 112(22): 6878-86.
54. Geney R, Layten M, Gomperts R, Hornak V, Simmerling C. Investigation of salt bridge stability in a generalized born solvent model. J Chemical Theory and Computation 2006; 2(1): 115-27.
55. Godoy-Ruiz R, Perez-Jimenez R, Garcia-Mira MM, Plaza del Pino IM, Sanchez-Ruiz JM. Empirical parametrization of pK values for carboxylic acids in proteins using a genetic algorithm. Biophys Chem 2005; 115(2-3): 263-6.
56. Krieger E, Nielsen JE, Spronk CA, Vriend G. Fast empirical pKa prediction by Ewald summation. J Mol Graph Model 2006; 25(4): 481-6.
57. Milletti F, Storchi L, Cruciani G. Predicting protein pK(a) by environment similarity. Proteins 2009; 76(2): 484-95.
58. Li H, Robertson AD, Jensen JH. Very fast empirical prediction and rationalization of protein pK(a) values. Proteins-Structure Function and Bioinformatics 2005; 61(4): 704-21.
59. Bas DC, Rogers DM, Jensen JH. Very fast prediction and rationalization of pKa values for protein-ligand complexes. Proteins 2008; 73(3): 765-83.
60. Kieseritzky G, Knapp EW. Optimizing pKa computation in proteins with pH adapted conformations. Proteins 2008; 71(3): 1335-48.
61. Spassov VZ, Yan L. A fast and accurate computational approach to protein ionization. Protein Science 2008; 17(11): 1955-70.
62. Stanton CL, Houk KN. Benchmarking pK(a) prediction methods for residues in proteins. J Chemical Theory and Computation 2008; 4(6): 951-66.
63. Sondergaard CR, Olsson MHM, Rostkowski M, Jensen JH. Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pK(a) Values. J Chemical Theory and Computation 2011; 7(7): 2284-95.
64. Warwicker J. Improved pKa calculations through flexibility based sampling of a water-dominated interaction scheme. Protein Sci 2004; 13(10): 2793-805.
65. Warwicker J. pKa predictions with a coupled finite difference Poisson-Boltzmann and Debye-Huckel method. Proteins 2011; 79(12): 3374-80.
66. Georgescu RE, Alexov EG, Gunner MR. Combining conformational flexibility and continuum electrostatics for calculating pK(a)s in proteins. Biophys J 2002; 83(4): 1731-48.
67. Song Y, Mao J, Gunner MR. MCCE2: improving protein pKa calculations with extensive side chain rotamer sampling. J Comput Chem 2009; 30(14): 2231-47.
68. Alexov E. Role of the protein side-chain fluctuations on the strength of pair-wise electrostatic interactions: comparing experimental with computed pK(a)s. Proteins 2003; 50(1): 94-103.
69. Koumanov A, Karshikoff A, Friis EP, Borchert TV. Conformational averaging in pK calculations: Improvement and limitations in prediction of ionization properties of proteins. J Physical Chemistry B 2001; 105(38): 9339-44.
70. Kuhn B, Kollman PA, Stahl M. Prediction of pKa shifts in proteins using a combination of molecular mechanical and continuum solvent calculations. J Comput Chem 2004; 25(15): 1865-72.
71. Sham YY, Chu ZT, Warshel A. Consistent calculations of pK(a)'s of ionizable residues in proteins: Semi-microscopic and microscopic approaches. J Physical Chemistry B 1997; 101(22): 4458-72.
72. van Vlijmen HW, Schaefer M, Karplus M. Improving the accuracy of protein pKa calculations: conformational averaging versus the average structure. Proteins 1998; 33(2): 145-58.
73. Witham S, Talley K, Wang L, et al. Developing hybrid approaches to predict pKa values of ionizable groups. Proteins: Structure, Function, and Bioinformatics 2011; 79(12): 3389-99.
74. Mongan J, Case DA. Biomolecular simulations at constant pH. Curr Opin Struct Biol 2005; 15(2): 157-63.
75. Niv MY, Krylov AI, Gerber RB. Photodissociation, electronic relaxation and recombination of HCl in Ar-n(HCl) clusters-Nonadiabatic molecular dynamics simulations. Faraday Discussions 1997; 108: 243-54.
76. Niv MY, Krylov AI, Gerber RB, Buck U. Photodissociation of HCl adsorbed on the surface of an Ar-12 cluster: Nonadiabatic molecular dynamics simulations. J Chemical Phys 1999; 110(22): 11047-53.
77. Niv MY, Bargheer M, Gerber RB. Photodissociation and recombination of F-2 molecule in Ar-54 cluster: Nonadiabatic molecular dynamics simulations. J Chemical Physics 2000; 113(16): 6660-72.
78. Baptista AM, Teixeira VH, Soares CM. Constant-pH molecular dynamics using stochastic titration. J Chemical Physics 2002; 117(9): 4184-200.
79. Dlugosz M, Antosiewicz JM, Robertson AD. Constant-pH molecular dynamics study of protonation-structure relationship in a heptapeptide derived from ovomucoid third domain. Phys Rev E Stat Nonlin Soft Matter Phys 2004; 69(2 Pt 1): 021915.
80. Mongan J, Case DA, McCammon JA. Constant pH molecular dynamics in generalized Born implicit solvent. J Comput Chem 2004; 25(16): 2038-48.
81. Mertz JE, Pettitt BM. Molecular-Dynamics at a Constant Ph. International J Supercomputer Applications and High Performance Computing 1994; 8(1): 47-53.
82. Baptista AM, Martel PJ, Petersen SB. Simulation of protein conformational freedom as a function of pH: constant-pH molecular dynamics using implicit titration. Proteins 1997; 27(4): 523-44.
83. Lee MS, Salsbury FR, Jr., Brooks CL, 3rd. Constant-pH molecular dynamics using continuous titration coordinates. Proteins 2004; 56(4): 738-52.
84. Khandogin J, Brooks CL, 3rd. Constant pH molecular dynamics with proton tautomerism. Biophys J 2005; 89(1): 141-57.
85. Donnini S, Tegeler F, Groenhof G, Grubmuller H. Constant pH Molecular Dynamics in Explicit Solvent with lambda-Dynamics. J Chem Theory Comput 2011; 7(6): 1962-78.
86. Borjesson U, Hunenberger PH. Explicit-solvent molecular dynamics simulation at constant pH: Methodology and application to small amines. J Chemical Physics 2001; 114(22): 9706-19.
87. Berendsen HJC, Postma JPM, Vangunsteren WF, Dinola A, Haak JR. Molecular-Dynamics with Coupling to an External Bath. J Chemical Physics 1984; 81(8): 3684-90.
88. Baptista AM. Comment on "Explicit-solvent molecular dynamics simulation at constant pH: Methodology and application to small amines". J Chem Phys 2002; 116(17): 7766-8.
89. Khandogin J, Brooks CL, 3rd. Toward the accurate first-principles prediction of ionization equilibria in proteins. Biochemistry 2006; 45(31): 9363-73.
90. Meng Y, Roitberg AE. Constant pH replica exchange molecular dynamics in biomolecules using a discrete protonation model. J Chem Theory Comput 2010; 6(4): 1401-12.
91. Williams SL, de Oliveira CA, McCammon JA. Coupling Constant pH Molecular Dynamics with Accelerated Molecular Dynamics. J Chem Theory Comput 2010; 6(2): 560-8.
92. Itoh SG, Damjanovic A, Brooks BR. pH replica-exchange method based on discrete protonation states. Proteins-Structure Function and Bioinformatics 2011; 79(12): 3420-36.
93. Levitt M, Warshel A. Computer simulation of protein folding. Nature 1975; 253(5494): 694-8.
94. Rossky PJ, Karplus M. Solvation-Molecular-Dynamics Study of a Dipeptide in Water. J the Am Chem Soc 1979; 101(8): 1913-37.
95. Lindorff-Larsen K, Piana S, Dror RO, Shaw DE. How fast-folding proteins fold. Science 334(6055): 517-20.
96. Dyson HJ, Wright PE. Defining Solution Conformations of Small Linear Peptides. Ann Rev Biophys Biophys Chem 1991; 20: 519-38.
97. Stein A, Aloy P. Novel Peptide-Mediated Interactions Derived from High-Resolution 3-Dimensional Structures. PLoS Comput Biol 2010; 6(5): e1000789.
98. Vanhee P, Reumers J, Stricher F, et al. PepX: a structural database of non-redundant protein-peptide complexes. Nucleic Acids Res 2010; 38(Database issue): D545-51.
99. Alexov E. Calculating proton uptake/release and binding free energy taking into account ionization and conformation changes induced by protein-inhibitor association: application to plasmepsin, cathepsin D and endothiapepsin-pepstatin complexes. Proteins 2004; 56(3): 572-84.
100. de Mol NJ, Gillies MB, Fischer MJ. Experimental and calculated shift in pK(a) upon binding of phosphotyrosine peptide to the SH2 domain of p56(lck). Bioorg Med Chem 2002; 10(5): 1477-82.
101. Kirshenbaum K, Daggett V. pH-dependent conformations of the amyloid beta(1-28) peptide fragment explored using molecular dynamics. Biochemistry 1995; 34(23): 7629-39.
102. Talafous J, Marcinowski KJ, Klopman G, Zagorski MG. Solution structure of residues 1-28 of the amyloid beta-peptide. Biochemistry 1994; 33(25): 7788-96.
103. Zagorski MG, Barrow CJ. NMR studies of amyloid beta-peptides: proton assignments, secondary structure, and mechanism of an alpha-helix----beta-sheet conversion for a homologous, 28-residue, N-terminal fragment. Biochemistry 1992; 31(24): 5621-31.
104. Barrow CJ, Yasuda A, Kenny PT, Zagorski MG. Solution conformations and aggregational properties of synthetic amyloid beta-peptides of Alzheimer's disease. Analysis of circular dichroism spectra. J Mol Biol 1992; 225(4): 1075-93.
105. Shalev DE, Rotem S, Fish A, Mor A. Consequences of N-acylation on structure and membrane binding properties of dermaseptin derivative K(4)-S4-(1-13). J Biological Chem 2006; 281(14): 9432-8.
106. Jimenez-Cruz CA, Makhatadze GI, Garcia AE. Protonation/ deprotonation effects on the stability of the Trp-cage miniprotein. Phys Chem Chemical Phys 2011; 13(38): 17056-63.
107. Cheng S, Niv MY. Molecular Dynamics Simulations and Elastic Network Analysis of Protein Kinase B (Akt/PKB) Inactivation. J Chem Information Modeling 2010; 50(9): 1602-10.
108. Yaneva R, Springer S, Zacharias M. Flexibility of the MHC class II peptide binding cleft in the bound, partially filled, and empty states: a molecular dynamics simulation study. Biopolymers 2009; 91(1): 14-27.
109. Gomez J, Freire E. Thermodynamic Mapping of the Inhibitor Site of the Aspartic Protease Endothiapepsin. J Molecular Biology 1995; 252(3): 337-50.
110. Xie D, Gulnik S, Collins L, Gustchina E, Suvorov L, Erickson JW. Dissection of the pH dependence of inhibitor binding energetics for an aspartic protease: Direct measurement of the protonation states of the catalytic aspartic acid residues. Biochemistry 1997; 36(51): 16166-72.
111. Singer AU, Forman-Kay JD. pH titration studies of an SH2 domainphosphopeptide complex: unusual histidine and phosphate pKa values. Protein Sci 1997; 6(9): 1910-9.
112. Bradshaw JM, Grucza RA, Ladbury JE, Waksman G. Probing the "two-pronged plug two-holed socket" model for the mechanism of binding of the Src SH2 domain to phosphotyrosyl peptides: a thermodynamic study. Biochemistry 1998; 37(25): 9083-90.
113. Tong L, Warren TC, Lukas S, et al. Carboxymethyl-phenylalanine as a replacement for phosphotyrosine in SH2 domain binding. J Biol Chem 1998; 273(32): 20238-42.
114. Hussain A, Shaw PE, Hirst JD. Molecular dynamics simulations and in silico peptide ligand screening of the Elk-1 ETS domain. J Cheminformatics 2011 Nov 1; 3.
115. Woolf TB, Roux B. Molecular Dynamics Simulation of the Gramicidin Channel in a Phospholipid Bilayer. Proc Natl Acad Sci USA 1994; 91(24): 11631-5.
116. Lindahl E, Sansom MSP. Membrane proteins: molecular dynamics simulations. Current Opinion in Structural Biology 2008; 18(4): 425-31.
117. Jang H, Michaud-Agrawal N, Johnston JM, Woolf TB. How to lose a kink and gain a helix: pH independent conformational changes of the fusion domains from influenza hemagglutinin in heterogeneous lipid bilayers. Proteins-Structure Function and Bioinformatics 2008; 72(1): 299-312.
118. Mihajlovic M, Lazaridis T. Calculations of pH-dependent binding of proteins to biological membranes. J Physical Chemistry B 2006; 110(7): 3375-84.
119. Panahi A, Feig M. Conformational Sampling of Influenza Fusion Peptide in Membrane Bilayers as a Function of Termini and Protonation States. J Phys Chem B 2010; 114(3): 1407-16.
120. Tanizaki S, Feig M. A generalized Born formalism for heterogeneous dielectric environments: Application to the implicit modeling of biological membranes. J Chemical Phys 2005; 122(12).
121. Sun Y, Weliky DP. 13C-13C correlation spectroscopy of membrane-associated influenza virus fusion peptide strongly supports a helix-turn-helix motif and two turn conformations. J Am Chem Soc 2009; 131(37): 13228-9.
122. Borjesson U, Hunenberger PH. pH-dependent stability of a decalysine alpha-helix studied by explicit-solvent molecular dynamics simulations at constant pH. J Physical Chemistry B 2004; 108(35): 13551-9.
123. Khandogin J, Chen J, Brooks CL, 3rd. Exploring atomistic details of pH-dependent peptide folding. Proc Natl Acad Sci USA 2006; 103(49): 18546-50.
124. Khandogin J, Brooks CL, 3rd. Linking folding with aggregation in Alzheimer's beta-amyloid peptides. Proc Natl Acad Sci USA 2007; 104(43): 16880-5.
125. Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham TE, Debolt S, et al. Amber, a Package of Computer-Programs for Applying Molecular Mechanics, Normal-Mode Analysis, Molecular-Dynamics and Free-Energy Calculations to Simulate the Structural and Energetic Properties of Molecules. Computer Physics Communications 1995; 91(1-3): 1-41.
126. Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M. Charmm-a Program for Macromolecular Energy, Minimization, and Dynamics Calculations. J Computational Chemistry 1983; 4(2): 187-217.