Show simple item record

Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism

dc.contributor.authorGoh, Garrett B.en_US
dc.contributor.authorHulbert, Benjamin S.en_US
dc.contributor.authorZhou, Huiqingen_US
dc.contributor.authorBrooks, Charles L.en_US
dc.date.accessioned2014-07-03T14:41:23Z
dc.date.availableWITHHELD_13_MONTHSen_US
dc.date.available2014-07-03T14:41:23Z
dc.date.issued2014-07en_US
dc.identifier.citationGoh, Garrett B.; Hulbert, Benjamin S.; Zhou, Huiqing; Brooks, Charles L. (2014). "Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism." Proteins: Structure, Function, and Bioinformatics 82(7): 1319-1331.en_US
dc.identifier.issn0887-3585en_US
dc.identifier.issn1097-0134en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/107513
dc.description.abstractpH is a ubiquitous regulator of biological activity, including protein‐folding, protein‐protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH‐dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi‐site λ‐dynamics (CPHMD MSλD ). In the CPHMD MSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi‐site λ‐dynamics, and designed novel biasing potentials to ensure that the physical end‐states are predominantly sampled. We show that explicit solvent CPHMD MSλD simulations model realistic pH‐dependent properties of proteins such as the Hen‐Egg White Lysozyme (HEWL), binding domain of 2‐oxoglutarate dehydrogenase (BBL) and N‐terminal domain of ribosomal protein L9 (NTL9), and the p K a predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 p K a units. With the recent development of the explicit solvent CPHMD MSλD framework for nucleic acids, accurate modeling of pH‐dependent properties of both major class of biomolecules—proteins and nucleic acids is now possible. Proteins 2014; 82:1319–1331. © 2013 Wiley Periodicals, Inc.en_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherProtein Electrostaticsen_US
dc.subject.otherλ‐Dynamicsen_US
dc.subject.otherPHen_US
dc.subject.otherCPHMDen_US
dc.subject.otherProtein Dynamicsen_US
dc.subject.otherExplicit Solventen_US
dc.subject.otherP K a Valuesen_US
dc.subject.otherMolecular Dynamicsen_US
dc.titleConstant pH molecular dynamics of proteins in explicit solvent with proton tautomerismen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelBiological Chemistryen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/1/prot24499-sup-0002-suppinfo02.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/2/prot24499-sup-0001-suppinfo01.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/3/prot24499.pdf
dc.identifier.doi10.1002/prot.24499en_US
dc.identifier.sourceProteins: Structure, Function, and Bioinformaticsen_US
dc.identifier.citedreferenceBerdiev BK, Mapstone TB, Markert JM, Gillespie GY, Lockhart J, Fuller CM, Benos DJ. pH alterations “reset” Ca2+ sensitivity of brain Na+ channel 2, a degenerin/epithelial Na+ ion channel, in planar lipid bilayers. J Biol Chem 2001; 276: 38755 – 38761.en_US
dc.identifier.citedreferenceZheng L, Chen M, Yang W. Random walk in orthogonal space to achieve efficient free‐energy simulation of complex systems. Proc Natl Acad Sci USA 2008; 105: 20227 – 20232.en_US
dc.identifier.citedreferenceShi CY, Wallace JA, Shen JK. Thermodynamic coupling of protonation and conformational equilibria in proteins: theory and simulation. Biophys J 2012; 102: 1590 – 1597.en_US
dc.identifier.citedreferenceBrooks BR, Brooks CL, III, Mackerell AD, Jr., Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M. CHARMM: the biomolecular simulation program. J Comput Chem 2009; 30: 1545 – 1614.en_US
dc.identifier.citedreferenceJorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. J Chem Phys 1983; 79: 926 – 935.en_US
dc.identifier.citedreferenceFeig M, Karanicolas J, Brooks CL, III. MMTSB tool set: enhanced sampling and multiscale modeling methods for applications in structural biology. J Mol Graphics Modell 2004; 22: 377 – 395.en_US
dc.identifier.citedreferenceMacKerell AD, Bashford D, Bellott M, Dunbrack RL, Evanseck JD, Field MJ, Fischer S, Gao J, Guo H, Ha S, Joseph‐McCarthy D, Kuchnir L, Kuczera K, Lau FTK, Mattos C, Michnick S, Ngo T, Nguyen DT, Prodhom B, Reiher WE, Roux B, Schlenkrich M, Smith JC, Stote R, Straub J, Watanabe M, Wiorkiewicz‐Kuczera J, Yin D, Karplus M. All‐atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 1998; 102: 3586 – 3616.en_US
dc.identifier.citedreferenceRyckaert JP, Ciccotti G, Berendsen HJC. Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n‐alkanes. J Comput Phys 1977; 23: 327 – 341.en_US
dc.identifier.citedreferenceCheatham TE, Miller JL, Fox T, Darden TA, Kollman PA. Molecular‐dynamics simulations on solvated biomolecular systems—the particle mesh ewald method leads to stable trajectories of DNA, RNA, and Proteins. J Am Chem Soc 1995; 117: 4193 – 4194.en_US
dc.identifier.citedreferenceSchreiber H, Steinhauser O. Cutoff size does strongly influence molecular‐dynamics results on solvated polypeptides. Biochemistry 1992; 31: 5856 – 5860.en_US
dc.identifier.citedreferenceSteinbach PJ, Brooks BR. New spherical‐cutoff methods for long‐range forces in macromolecular simulation. J Comput Chem 1994; 15: 667 – 683.en_US
dc.identifier.citedreferenceBeck DAC, Armen RS, Daggett V. Cutoff size need not strongly influence molecular dynamics results for solvated polypeptides. Biochemistry 2005; 44: 609 – 616.en_US
dc.identifier.citedreferenceNorberg J, Nilsson L. On the truncation of long‐range electrostatic interactions in DNA. Biophys J 2000; 79: 1537 – 1553.en_US
dc.identifier.citedreferenceOnufriev A, Case DA, Ullmann GM. A novel view of pH titration in biomolecules. Biochemistry 2001; 40: 3413 – 3419.en_US
dc.identifier.citedreferenceNozaki Y, Tanford C. Examination of titration behavior. Methods Enzymol 1967; 11: 715 – 734.en_US
dc.identifier.citedreferenceBashford D, Case DA, Dalvit C, Tennant L, Wright PE. Electrostatic calculations of side‐chain pK(a) values in myoglobin and comparison with NMR data for histidines. Biochemistry 1993; 32: 8045 – 8056.en_US
dc.identifier.citedreferenceParsons SM, Raftery MA. Ionization behavior of the catalytic carboxyls of lysozyme. Effects of ionic strength. Biochemistry 1972; 11: 1623 – 1629.en_US
dc.identifier.citedreferenceKuramitsu S, Ikeda K, Hamaguchi K, Fujio H, Amano T. Ionization constants of Glu 35 and Asp 52 in hen, turkey, and human lysozymes. J Biochem 1974; 76: 671 – 683.en_US
dc.identifier.citedreferenceKuramitsu S, Ikeda K, Hamaguchi K. Participation of the catalytic carboxyls, Asp 52 and Glu 35, and Asp 101 in the binding of substrate analogues to hen lysozyme. J Biochem 1975; 77: 291 – 301.en_US
dc.identifier.citedreferenceTakahashi T, Nakamura H, Wada A. Electrostatic forces in two lysozymes: calculations and measurements of histidine pKa values. Biopolymers 1992; 32: 897 – 909.en_US
dc.identifier.citedreferenceBartik K, Redfield C, Dobson CM. Measurement of the individual Pk(a) values of acidic residues of hen and turkey lysozymes by 2‐dimensional H‐1‐Nmr. Biophys J 1994; 66: 1180 – 1184.en_US
dc.identifier.citedreferenceWebb H, Tynan‐Connolly BM, Lee GM, Farrell D, O'Meara F, Søndergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. Proteins 2011; 79: 685 – 702.en_US
dc.identifier.citedreferenceMachuqueiro M, Baptista AM. Is the prediction of pKa values by constant‐pH molecular dynamics being hindered by inherited problems? Proteins 2011; 79: 3437 – 3447.en_US
dc.identifier.citedreferenceWallace JA, Shen JK. Charge‐leveling and proper treatment of long‐range electrostatics in all‐atom molecular dynamics at constant pH. J Chem Phys 2012; 137: 184105.en_US
dc.identifier.citedreferenceArbely E, Rutherford TJ, Sharpe TD, Ferguson N, Fersht AR. Downhill versus barrier‐limited folding of BBL 1: energetic and structural perturbation effects upon protonation of a histidine of unusually low pK(a). J Mol Biol 2009; 387: 986 – 992.en_US
dc.identifier.citedreferenceKuhlman B, Luisi DL, Young P, Raleigh DP. pK(a) values and the pH dependent stability of the N‐terminal domain of L9 as probes of electrostatic interactions in the denatured state. Differentiation between local and nonlocal interactions. Biochemistry 1999; 38: 4896 – 4903.en_US
dc.identifier.citedreferenceWarshel A. Calculations of enzymatic‐reactions—calculations of pKa, proton‐transfer reactions, and general acid catalysis reactions in enzymes. Biochemistry 1981; 20: 3167 – 3177.en_US
dc.identifier.citedreferenceHarris TK, Turner GJ. Structural basis of perturbed pKa values of catalytic groups in enzyme active sites. IUBMB Life 2002; 53: 85 – 98.en_US
dc.identifier.citedreferenceNielsen JE, Mccammon JA. Calculating pKa values in enzyme active sites. Protein Sci 2003; 12: 1894 – 1901.en_US
dc.identifier.citedreferenceDemchuk E, Genick UK, Woo TT, Getzoff ED, Bashford D. Protonation states and pH titration in the photocycle of photoactive yellow protein. Biochemistry 2000; 39: 1100 – 1113.en_US
dc.identifier.citedreferenceDillet V, Dyson HJ, Bashford D. Calculations of electrostatic interactions and pKas in the active site of Escherichia coli thioredoxin. Biochemistry 1998; 37: 10298 – 10306.en_US
dc.identifier.citedreferenceWilcox JL, Ahluwalia AK, Bevilacqua PC. Charged nucleobases and their potential for RNA catalysis. Acc Chem Res 2011; 44: 1270 – 1279.en_US
dc.identifier.citedreferenceKrishnamurthy R. Role of pK(a) of nucleobases in the origins of chemical evolution. Acc Chem Res 2012; 45: 2035 – 2044.en_US
dc.identifier.citedreferenceShih IH, Been MD. Involvement of a cytosine side chain in proton transfer in the rate‐determining step of ribozyme self‐cleavage. Proc Natl Acad Sci USA 2001; 98: 1489 – 1494.en_US
dc.identifier.citedreferenceKe A, Zhou K, Ding F, Cate JH, Doudna JA. A conformational switch controls hepatitis delta virus ribozyme catalysis. Nature 2004; 429: 201 – 205.en_US
dc.identifier.citedreferenceRavindranathan S, Butcher SE, Feigon J. Adenine protonation in domain B of the hairpin ribozyme. Biochemistry 2000; 39: 16026 – 16032.en_US
dc.identifier.citedreferenceRyder SP, Oyelere AK, Padilla JL, Klostermeier D, Millar DP, Strobel SA. Investigation of adenosine base ionization in the hairpin ribozyme by nucleotide analog interference mapping. RNA 2001; 7: 1454 – 1463.en_US
dc.identifier.citedreferenceBierzynski A, Kim PS, Baldwin RL. A salt bridge stabilizes the helix formed by isolated C‐peptide of Rnase‐A. Proc Natl Acad Sci USA 1982; 79: 2470 – 2474.en_US
dc.identifier.citedreferenceShoemaker KR, Kim PS, Brems DN, Marqusee S, York EJ, Chaiken IM, Stewart JM, Baldwin RL. Nature of the charged‐group effect on the stability of the C‐peptide helix. Proc Natl Acad Sci USA 1985; 82: 2349 – 2353.en_US
dc.identifier.citedreferenceSchaefer M, Van Vlijmen HWT, Karplus M. Electrostatic contributions to molecular free energies in solution. Adv Protein Chem 1998; 51: 1 – 57.en_US
dc.identifier.citedreferenceKelly JW. Alternative conformations of amyloidogenic proteins govern their behavior. Curr Opin Struct Biol 1996; 6: 11 – 17.en_US
dc.identifier.citedreferenceSheinerman FB, Norel R, Honig B. Electrostatic aspects of protein‐protein interactions. Curr Opin Struct Biol 2000; 10: 153 – 159.en_US
dc.identifier.citedreferenceWarshel A. Electrostatic basis of structure‐function correlation in proteins. Acc Chem Res 1981; 14: 284 – 290.en_US
dc.identifier.citedreferenceHunenberger PH, Helms V, Narayana N, Taylor SS, McCammon JA. Determinants of ligand binding to cAMP‐dependent protein kinase. Biochemistry 1999; 38: 2358 – 2366.en_US
dc.identifier.citedreferenceHouck‐Loomis B, Durney MA, Salguero C, Shankar N, Nagle JM, Goff SP, D'Souza VM. An equilibrium‐dependent retroviral mRNA switch regulates translational recoding. Nature 2011; 480: 561 – U193.en_US
dc.identifier.citedreferenceWebb BA, Chimenti M, Jacobson MP, Barber DL. Dysregulated pH: a perfect storm for cancer progression. Nat Rev Cancer 2011; 11: 671 – 677.en_US
dc.identifier.citedreferenceHowell EE, Villafranca JE, Warren MS, Oatley SJ, Kraut J. Functional‐role of aspartic acid‐27 in dihydrofolate‐reductase revealed by mutagenesis. Science 1986; 231: 1123 – 1128.en_US
dc.identifier.citedreferenceRastogi VK, Girvin ME. Structural changes linked to proton translocation by subunit c of the ATP synthase. Nature 1999; 402: 263 – 268.en_US
dc.identifier.citedreferenceReiter NJ, Blad H, Abildgaard F, Butcher SE. Dynamics in the U6 RNA intramolecular stem‐loop: a base flipping conformational change. Biochemistry 2004; 43: 13739 – 13747.en_US
dc.identifier.citedreferenceBullough PA, Hughson FM, Skehel JJ, Wiley DC. Structure of influenza hemagglutinin at the pH of membrane‐fusion. Nature 1994; 371: 37 – 43.en_US
dc.identifier.citedreferenceHarms MJ, Schlessman JL, Sue GR, Garcia‐Moreno B. Arginine residues at internal positions in a protein are always charged. Proc Natl Acad Sci USA 2011; 108: 18954 – 18959.en_US
dc.identifier.citedreferenceIsom DG, Castaneda CA, Cannon BR, Garcia‐Moreno B. Large shifts in pKa values of lysine residues buried inside a protein. Proc Natl Acad Sci USA 2011; 108: 5260 – 5265.en_US
dc.identifier.citedreferencePey AL, Rodriguez‐Larrea D, Gavira JA, Garcia‐Moreno B, Sanchez‐Ruiz JM. Modulation of buried ionizable groups in proteins with engineered surface charge. J Am Chem Soc 2010; 132: 1218 – 1219.en_US
dc.identifier.citedreferenceIsom DG, Cannon BR, Castaneda CA, Robinson A, Garcia‐Moreno B. High tolerance for ionizable residues in the hydrophobic interior of proteins. Proc Natl Acad Sci USA 2008; 105: 17784 – 17788.en_US
dc.identifier.citedreferenceNielsen JE, Gunner MR, Garcia‐Moreno BE. The pKa Cooperative: a collaborative effort to advance structure‐based calculations of pKa values and electrostatic effects in proteins. Proteins 2011; 79: 3249 – 3259.en_US
dc.identifier.citedreferenceAlexov E, Mehler EL, Baker N, Baptista AM, Huang Y, Milletti F, Nielsen JE, Farrell D, Carstensen T, Olsson MH, Shen JK, Warwicker J, Williams S, Word JM. Progress in the prediction of pKa values in proteins. Proteins 2011; 79: 3260 – 3275.en_US
dc.identifier.citedreferenceBashford D. Macroscopic electrostatic models for protonation states in proteins. Front Biosci 2004; 9: 1082 – 1099.en_US
dc.identifier.citedreferenceAntosiewicz J, McCammon JA, Gilson MK. Prediction of pH‐dependent properties of proteins. J Mol Biol 1994; 238: 415 – 436.en_US
dc.identifier.citedreferenceYou TJ, Bashford D. Conformation and hydrogen ion titration of proteins: a continuum electrostatic model with conformational flexibility. Biophys J 1995; 69: 1721 – 1733.en_US
dc.identifier.citedreferenceGeorgescu RE, Alexov EG, Gunner MR. Combining conformational flexibility and continuum electrostatics for calculating pK(a)s in proteins. Biophys J 2002; 83: 1731 – 1748.en_US
dc.identifier.citedreferenceRussell ST, Warshel A. Calculations of electrostatic energies in proteins. The energetics of ionized groups in bovine pancreatic trypsin inhibitor. J Mol Biol 1985; 185: 389 – 404.en_US
dc.identifier.citedreferenceLee FS, Chu ZT, Warshel A. Microscopic and semimicroscopic calculations of electrostatic energies in proteins by the polaris and enzymix programs. J Comput Chem 1993; 14: 161 – 185.en_US
dc.identifier.citedreferenceWarshel A, Sussman F, King G. Free‐energy of charges in solvated proteins—microscopic calculations using a reversible charging process. Biochemistry 1986; 25: 8368 – 8372.en_US
dc.identifier.citedreferenceSham YY, Chu ZT, Warshel A. Consistent calculations of pKa's of ionizable residues in proteins: semi‐microscopic and microscopic approaches. J Phys Chem B 1997; 101: 4458 – 4472.en_US
dc.identifier.citedreferenceMongan J, Case DA. Biomolecular simulations at constant pH. Curr Opin Struct Biol 2005; 15: 157 – 163.en_US
dc.identifier.citedreferenceBurgi R, Kollman PA, van Gunsteren WF. Simulating proteins at constant pH: an approach combining molecular dynamics and Monte Carlo simulation. Proteins 2002; 47: 469 – 480.en_US
dc.identifier.citedreferenceBaptista AM, Teixeira VH, Soares CM. Constant‐pH molecular dynamics using stochastic titration. J Chem Phys 2002; 117: 4184 – 4200.en_US
dc.identifier.citedreferenceMachuqueiro M, Baptista AM. Constant‐pH molecular dynamics with ionic strength effects: protonation‐conformation coupling in decalysine. J Phys Chem B 2006; 110: 2927 – 2933.en_US
dc.identifier.citedreferenceBaptista AM, Machuqueiro M. Acidic range titration of HEWL using a constant‐pH molecular dynamics method. Proteins 2008; 72: 289 – 298.en_US
dc.identifier.citedreferenceIm WP, Lee MS, Brooks CL, III. Generalized born model with a simple smoothing function. J Comput Chem 2003; 24: 1691 – 1702.en_US
dc.identifier.citedreferenceChen JH, Im WP, Brooks CL, III. Balancing solvation and intramolecular interactions: Toward a consistent generalized born force field. J Am Chem Soc 2006; 128: 3728 – 3736.en_US
dc.identifier.citedreference. Dlugosz M, Antosiewicz JM. Constant‐pH molecular dynamics simulations: a test case of succinic acid. Chem Phys 2004; 302: 161 – 170.en_US
dc.identifier.citedreferenceDlugosz 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 2004; 69: 021915.en_US
dc.identifier.citedreferenceMongan J, Case DA, McCammon JA. Constant pH molecular dynamics in generalized born implicit solvent. J Comput Chem 2004; 25: 2038 – 2048.en_US
dc.identifier.citedreferenceWilliams SL, de Oliveira CA, McCammon JA. Coupling constant pH molecular dynamics with accelerated molecular dynamics. J Chem Theory Comput 2010; 6: 560 – 568.en_US
dc.identifier.citedreferenceMeng Y, Roitberg AE. Constant pH replica exchange molecular dynamics in biomolecules using a discrete protonation model. J Chem Theory Comput 2010; 6: 1401 – 1412.en_US
dc.identifier.citedreferenceSwails JM, Roitberg AE. Enhancing conformation and protonation state sampling of hen egg white lysozyme using pH replica exchange molecular dynamics. J Chem Theory Comput 2012; 8: 4393 – 4404.en_US
dc.identifier.citedreferenceSabri Dashti D, Meng Y, Roitberg AE. pH‐replica exchange molecular dynamics in proteins using a discrete protonation method. J Phys Chem B 2012; 116: 8805 – 8811.en_US
dc.identifier.citedreferenceMesser BM, Roca M, Chu ZT, Vicatos S, Kilshtain AV, Warshel A. Multiscale simulations of protein landscapes: using coarse‐grained models as reference potentials to full explicit models. Proteins 2010; 78: 1212 – 1227.en_US
dc.identifier.citedreferenceOlsson MHM, Warshel A. Monte Carlo simulations of proton pumps: on the working principles of the biological valve that controls proton pumping in cytochrome c oxidase. Proc Natl Acad Sci USA 2006; 103: 6500 – 6505.en_US
dc.identifier.citedreferenceAaqvist J, Warshel A. Simulation of enzyme reactions using valence bond force fields and other hybrid quantum/classical approaches. Chem Rev 1993; 93: 2523 – 2544.en_US
dc.identifier.citedreferenceBaptista 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: 523.en_US
dc.identifier.citedreferenceBorjesson U, Hunenberger PH. Explicit‐solvent molecular dynamics simulation at constant pH: Methodology and application to small amines. J Chem Phys 2001; 114: 9706 – 9719.en_US
dc.identifier.citedreferenceKong X, Brooks CL, III. Lambda‐dynamics‐a new approach to free‐energy calculations. J Chem Phys 1996; 105: 2414 – 2423.en_US
dc.identifier.citedreferenceKnight JL, Brooks CL, III. Lambda‐dynamics free energy simulation methods. J Comput Chem 2009; 30: 1692 – 1700.en_US
dc.identifier.citedreferenceGuo Z, Brooks CL, III, Kong X. Efficient and flexible algorithm for free energy calculations using the λ‐dynamics approach. J Phys Chem B 1998; 102: 2032 – 2036.en_US
dc.identifier.citedreferenceLee MS, Salsbury FR, Brooks CL, III. Constant‐pH molecular dynamics using continuous titration coordinates. Proteins 2004; 56: 738 – 752.en_US
dc.identifier.citedreferenceKhandogin J, Brooks CL, III. Constant pH molecular dynamics with proton tautomerism. Biophys J 2005; 89: 141 – 157.en_US
dc.identifier.citedreferenceKhandogin J, Brooks CL, III. Toward the accurate first‐principles prediction of ionization equilibria in proteins. Biochemistry 2006; 45: 9363 – 9373.en_US
dc.identifier.citedreferenceKhandogin J, Chen J, Brooks CL, III. Exploring atomistic details of pH‐dependent peptide folding. Proc Natl Acad Sci USA 2006; 103: 18546 – 18550.en_US
dc.identifier.citedreferenceKhandogin J, Raleigh DP, Brooks CL, III. Folding intermediate in the villin headpiece domain arises from disruption of a N‐terminal hydrogen‐bonded network. J Am Chem Soc 2007; 129: 3056 – 3057.en_US
dc.identifier.citedreferenceKhandogin J, Brooks CL, III. Linking folding with aggregation in Alzheimer's beta‐amyloid peptides. Proc Natl Acad Sci USA 2007; 104: 16880 – 16885.en_US
dc.identifier.citedreferenceZhang BW, Brunetti L, Brooks CL, III. Probing pH‐dependent dissociation of HdeA dimers. J Am Chem Soc 2011; 133: 19393 – 19398.en_US
dc.identifier.citedreferenceShen JK. Uncovering specific electrostatic interactions in the denatured states of proteins. Biophys J 2010; 99: 924 – 932.en_US
dc.identifier.citedreferenceWallace JA, Shen JK. Unraveling a trap‐and‐trigger mechanism in the pH‐sensitive self‐assembly of spider silk proteins. J Phys Chem Lett 2012; 3: 658 – 662.en_US
dc.identifier.citedreferenceLaw SM, Zhang BW, Brooks CL, III. pH‐sensitive residues in the p19 RNA silencing suppressor protein from carnation Italian ringspot virus affect siRNA binding stability. Protein Sci 2013; 22: 595 – 604.en_US
dc.identifier.citedreferenceDlugosz M, Antosiewicz JM. Effects of solute‐solvent proton exchange on polypeptide chain dynamics: a constant‐pH molecular dynamics study. J Phys Chem B 2005; 109: 13777 – 13784.en_US
dc.identifier.citedreferenceMachuqueiro M, Baptista AM. The pH‐dependent conformational states of kyotorphin: a constant‐pH molecular dynamics study. Biophys J 2007; 92: 1836 – 1845.en_US
dc.identifier.citedreferenceCampos SR, Machuqueiro M, Baptista AM. Constant‐pH molecular dynamics simulations reveal a beta‐rich form of the human prion protein. J Phys Chem B 2010; 114: 12692 – 12700.en_US
dc.identifier.citedreferenceArthur EJ, Yesselman JD, Brooks CL, III. Predicting extreme pK(a) shifts in staphylococcal nuclease mutants with constant pH molecular dynamics. Proteins 2011; 79: 3276 – 3286.en_US
dc.identifier.citedreferenceWallace JA, Shen JK. Continuous constant pH molecular dynamics in explicit solvent with pH‐based replica exchange. J Chem Theory Comput 2011; 7: 2617 – 2629.en_US
dc.identifier.citedreferenceWang WZ, Chu XP, Li MH, Seeds J, Simon RP, Xiong ZG. Modulation of acid‐sensing ion channel currents, acid‐induced increase of intracellular Ca2+, and acidosis‐mediated neuronal injury by intracellular pH. J Biol Chem 2006; 281: 29369 – 29378.en_US
dc.identifier.citedreferenceHesselager M, Timmermann DB, Ahring PK. pH dependency and desensitization kinetics of heterologously expressed combinations of acid‐sensing ion channel subunits. J Biol Chem 2004; 279: 11006 – 11015.en_US
dc.identifier.citedreferenceDamaghi M, Bippes C, Koster S, Yildiz O, Mari SA, Kuhlbrandt W, Muller DJ. pH‐dependent interactions guide the folding and gate the transmembrane pore of the beta‐barrel membrane protein OmpG. J Mol Biol 2010; 397: 878 – 882.en_US
dc.identifier.citedreferenceDonnini S, Tegeler F, Groenhof G, Grubmuller H. Constant pH molecular dynamics in explicit solvent with lambda‐dynamics. J Chem Theory Comput 2011; 7: 1962 – 1978.en_US
dc.identifier.citedreferenceKnight JL, Brooks CL, III. Applying efficient implicit non‐geometric constraints in alchemical free energy simulations. J Comput Chem 2011; 32: 3423 – 3432.en_US
dc.identifier.citedreferenceKnight JL, Brooks CL, III. Multisite λ dynamics for simulated structure–activity relationship studies. J Chem Theory Comput 2011; 7: 2728 – 2739.en_US
dc.identifier.citedreferenceGoh GB, Knight JL, Brooks CL, III. Constant pH molecular dynamics simulations of nucleic acids in explicit solvent. J Chem Theory Comput 2012; 8: 36 – 46.en_US
dc.identifier.citedreferenceGoh GB, Knight JL, Brooks CL, III. pH‐dependent dynamics of complex RNA macromolecules. J Chem Theory Comput 2013; 9: 935 – 943.en_US
dc.identifier.citedreferenceGoh GB, Knight JL, Brooks CL, III. Toward accurate prediction of the protonation equilibrium of nucleic acids. J Phys Chem Lett 2013; 4: 760 – 766.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.