Publications

129. Li, Z. & Hirst, J.D., Vibrational structure in the near-ultraviolet electronic circular dichroism spectra of proteins. Chem. Sci., 8, 4318–4333 (2017).
DOI: http://dx.doi.org/10.1039/C7SC00586E
128. Husseini, F.S., Robinson, D., Hunt, N.T., Parker, A.W. & Hirst, J.D. , Computing infrared spectra of proteins using the exciton model. J. Comput. Chem., 38, 1362–1375 (2017).
DOI: http://dx.doi.org/10.1002/jcc.24674
127. Solé-Daura, A., Goovaerts, V., Stroobants, K., Absillis, G., Jiménez-Lozano, P., Poblet, J.M., Hirst, J.D., Parac-Vogt, T.N. & Carbó, J.J., Probing polyoxometalate-protein interactions using molecular dynamics simulations. Chem. Eur. J., 22, 15280–15289 (2016).
DOI: http://dx.doi.org/10.1002/chem.201602263
126. Mulholland, S., Turpin, E.R., Bonev, B.B. & Hirst, J.D. , Docking and molecular dynamics simulations of the ternary complex nisin2:lipid II. Sci. Rep, 6, 21185 (2016).
DOI: http://dx.doi.org/10.1038/srep21185
125. Hanson-Heine, M.W.D., Husseini, F., Hirst, J.D. & Besley, N.A., Simulation of the two-dimensional infrared spectroscopy of peptides using localized normal modes. J. Chem. Theor. Comput., 12, 1905–1918 (2016).
DOI: http://dx.doi.org/10.1021/acs.jctc.5b01198
124. Li, Z., Robinson, D. & Hirst, J.D., Vibronic structure in the far-UV electronic circular dichroism spectra of proteins. Faraday Discussion, 177, 329–344 (2015).
DOI: http://dx.doi.org/10.1039/C4FD00163J
123. Turpin, E.R., Mulholland, S., Bonev, B. & Hirst, J.D., New CHARMM force field parameters for dehydrated amino acid residues, the key to lantibiotic molecular dynamics simulations. RSC Advances., 4, 48621–48631 (2014).
DOI: http://dx.doi.org/10.1039/c4ra09897h
122. Baker, J.A. & Hirst, J.D., Accelerating electrostatic pair methods on graphical processing units to study molecules in supercritical carbon dioxide. Faraday Discussion, 169, 343–357 (2014).
DOI: http://dx.doi.org/10.1039/c4fd00012a
121. Hirst, J.D., Glowacki, D., Baaden, M., Molecular simulations and visualization: introduction and overview. Faraday Discussion, 169, 922 (2014).
DOI: http://dx.doi.org/10.1039/c4fd90024c
120. Aguado-Ullate, S., Baker, J.A., Gonzálezez-González, V., MÜller, C., Hirst, J.D. & Carbó, J.J., A theoretical study of the activity in Rh-catalysed hydroformylation: the origin of the enhanced activity of the p-acceptor phosphinine ligand. Catal. Sci. Technol., 4, 979–987 (2014).
DOI: http://dx.doi.org/10.1039/c3cy00956d
119. Hill R.E., Hunt N.T. & Hirst J.D., Studying biomacromolecules with two-dimensional infrared spectroscopy. Adv. Prot. Chem. Str. Biol., 93, 13150 (2013).
DOI: http://dx.doi.org/10.1016/B978-0-12-416596-0.00001-4
118. Turpin, E.R., Fang, H.-J., Thomas, N.R. & Hirst, J.D., Cooperativity and site selectivity in the ileal lipid binding protein. Biochemistry, 52, 4723–4733 (2013).
DOI: http://dx.doi.org/10.1021/bi400192w
117. Turpin, E.R. & Hirst, J.D., Transformation of the dihedral corrective map for D-amino residues using the CHARMM force field. Chem. Phys. Lett., 543, 142–147 (2012).
DOI: http://dx.doi.org/10.1016/j.cplett.2012.06.041
116. Do, H., Hirst, J.D. & Wheatley, R.J., Calculation of partition functions and free energies of a binary mixture using the energy partitioning method: application to CO2 + CH4. J. Phys. Chem. B, 116, 4535–4542 (2012).
DOI: http://dx.doi.org/10.1021/jp212168f
115. Hussain, A., Shaw, P.E. & Hirst, J.D., Molecular dynamics simulations and in silico peptide ligand screening of the Elk-1 ETS domain. J. Cheminf., 3, 49 (2011).
DOI: http://dx.doi.org/10.1186/1758-2946-3-49
114. Do, H., Hirst, J.D. & Wheatley, R.J., Rapid calculation of the partition function of fluids. J. Chem. Phys., 135, 174105 (2011).
DOI: http://dx.doi.org/10.1063/1.3656296
113. Pu, M., Garrahan, J.P. & Hirst, J.D., Influence of solvent model on protein dynamics. Chem. Phys. Lett., 515, 283–289 (2011).
DOI: http://dx.doi.org/10.1016/j.cplett.2011.09.026
112. Do, H., Wheatley, R.J. & Hirst, J.D., Molecular simulation of the binary mixture of 1-1-1-2-tetrafluoroethane and carbon dioxide. Phys. Chem. Chem. Phys, 13, 15708–15713 (2011).
DOI: http://dx.doi.org/10.1039/c1cp21419e
111. Baker, J.A., Hirst, J.D., Molecular Dynamics Simulations Using Graphics Processing Units. Mol. Inf., 30, 498–504 (2011).
DOI: http://dx.doi.org/10.1002/minf.201100042
110. Robinson, D., Besley, N.A., O'Shea, P. & Hirst, J.D., Water order profiles on phospholipid / cholesterol membrane bilayer surfaces. J. Comput. Chem., 32, 2613 (2011).
DOI: http://dx.doi.org/10.1002/jcc.21840
109. Gaigeot, M.-P., Besley, N.A. & Hirst, J.D, Modelling the infrared and circular dichroism spectroscopy of linear and cyclic diamides. J. Phys. Chem. B, 115, 5562–5535 (2011).
DOI: http://dx.doi.org/10.1021/jp111140f
108. Robinson, D., Besley, N.A., O'Shea, P. & Hirst, J.D., Di-8-ANEPPS Emission Spectra in Phospholipid / Cholesterol Membranes: A Theoretical Study. J. Phys. Chem. B, 115, 4160–4167 (2011).
DOI: http://dx.doi.org/10.1021/jp1111372
107. Oakley, M.T., Do, H., Hirst, J.D. & Wheatley, R.J., First principles predictions of thermophysical properties of refrigerant mixtures. J. Chem. Phys, 134, 114518 (2011).
DOI: http://dx.doi.org/10.1063/1.3567308
106. Chen, P., Evans, C.-L., Hirst, J.D., Searle, M.S., Structural insights into the two sequential folding transition states of the PB1 domain of NBR1 from Φ value analysis and biased molecular dynamics simulations. Biochemistry, 50, 125–135 (2011).
DOI: http://dx.doi.org/10.1021/bi1016793
105. Turpin, E.R., Bonev, B.B., Hirst, J.D., Stereoselective disulfide formation stabilizes the local peptide conformation in Nisin mimics. Biochemistry, 49, 9594–9603 (2010).
DOI: http://dx.doi.org/10.1021/bi101214t
104. Do, H., Wheatley, R.J. & Hirst, J.D., Microscopic structure of liquid 1-1-1-2-tetrafluoroethane (R134a) from Monte Carlo simulation. Phys. Chem. Chem. Phys., 12, 13266–13272 (2010).
DOI: http://dx.doi.org/10.1039/C0CP00620C
103. Jiang, J., Abramavicius, D., Falvo, C., Bulheller, B.M., Hirst, J.D. & Mukamel, S., Simulation of two-dimensional ultraviolet spectroscopy of amyloid fibrils. J. Phys. Chem. B., 114, 12150–12156 (2010).
DOI: http://dx.doi.org/10.1021/jp1046968
102. Kountouris, P. & Hirst, J.D., Predicting β-turns and their types using predicted backbone dihedral angles and secondary structures. BMC Bioinformatics, 11, 407 (2010).
DOI: http://dx.doi.org/10.1186/1471-2105-11-407
101. Jain, P. & Hirst, J.D., Automatic structure classification of small proteins using random forest. BMC Bioinformatics, 11, 364 (2010).
DOI: http://dx.doi.org/10.1186/1471-2105-11-364
100. Jiang, J., Abramavicius, D., Bulheller, B.M., Hirst, J.D. & Mukamel, S., Ultraviolet spectroscopy of protein backbone transitions in aqueous solution: QM/MM simulations. J. Phys. Chem. B, 114, 8270–8277 (2010).
DOI: http://dx.doi.org/10.1021/jp101980a
99. Abramavicius, D., Jiang, J., Bulheller, B.M., Hirst, J.D. & Mukamel, S., Simulation Study of Chiral Two-Dimensional Ultraviolet Spectroscopy of the Protein Backbone. J. Am. Chem. Soc., 132, 7769–7775 (2010).
DOI: http://dx.doi.org/10.1021/ja101968g
98. Bromley, E.H.C., Channon, K.J., King, P.J.S., Mahmoud, Z.N., Banwell, E.F., Butler, M.F., Crump, M.P., Dafforn, T.R., Hicks, M.R., Hirst, J.D., Rodger, A. & Woolfson, D.N., The assembly pathway of a designed α-helical protein fiber. Biophys. J., 98, 1668–1676 (2010).
DOI: http://dx.doi.org/10.1016/j.bpj.2009.12.4309
97. Smith, R.E., Liang, M., Bacardit, J., Stout, M., Krasnogor, N. & Hirst, J.D., A Learning Classifier System with Mutual-Information-Based Fitness. Evolutionary Intelligence, 3, 31–50 (2010).
DOI: http://dx.doi.org/10.1007/s12065-010-0037-9
96. Do, H., Wheatley, R.J. & Hirst, J.D., Gibbs ensemble Monte Carlo simulations of binary mixtures of methane, difluoromethane and carbon dioxide. J. Phys. Chem. B, 114, 3879–3886 (2010).
DOI: http://dx.doi.org/10.1021/jp909769c
95. Hussain, A., Melville, J.L. & Hirst, J.D., Molecular docking and QSAR of aplyronine A and analogues: potent inhibitors of actin. J. Comput.-Aided Mol. Des., 24, 42005 (2010).
DOI: http://dx.doi.org/10.1007/s10822-009-9307-y
94. Spowage, B.M., Bruce, C.L. & Hirst, J.D., Interpretable correlation descriptors for quantitative structure-activity relationships. J. Cheminf, 1, 22 (2009).
DOI: http://dx.doi.org/10.1186/1758-2946-1-22

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93. Kountouris, P. & Hirst, J.D., Prediction of backbone dihedral angles and protein secondary structure using support vector machines. BMC Bioinformatics, 10, 437 (2009).
DOI: http://dx.doi.org/10.1186/1471-2105-10-437
92. Robinson, D., Besley, N.A., O'Shea, P. & Hirst, J.D., Calculating the fluorescence of 5-hydroxytryptophan in proteins. J. Phys. Chem. B, 113, 14521–14528 (2009).
DOI: http://dx.doi.org/10.1021/jp9071108
91. Jain, P. & Hirst, J.D., Exploring protein structural dissimilarity to facilitate structure classification. BMC Structural Biology, 9, 60 (2009).
DOI: http://dx.doi.org/10.1186/1472-6807-9-60
90. Bulheller, B.M., Rodger, A., Hicks, M.R., Dafforn, T.R., Serpell, L.C., Marshall, K.E., Bromley, E.H.C., King, P.J.S., Channon, K.J., Woolfson, D.N. & Hirst, J.D., Flow linear dichroism of some prototypical proteins. J. Am. Chem. Soc., 131, 13305–13314 (2009).
DOI: http://dx.doi.org/10.1021/ja902662e

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89. Bulheller, B.M., Pantoş G.D., Sanders, J.K.M. & Hirst, J.D., Electronic structure and circular dichroism spectroscopy of naphthalenediimide nanotubes. Phys. Chem. Chem. Phys., 11, 6060–6065 (2009).
DOI: http://dx.doi.org/10.1039/b905187b

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88. Jain, P., Garibaldi, J.M. & Hirst, J.D., Supervised machine learning algorithms for protein structure classification. Comp. Biol. Chem., 33, 216–223 (2009).
DOI: http://dx.doi.org/10.1016/j.compbiolchem.2009.04.004
87. Melville, J.L., Burke, E.K. & Hirst, J.D., Machine Learning in Virtual Screening. Comb. Chem. & High Thr. Scr., 12, 332–343 (2009).
86. Robinson, D., Besley, N.A., Lunt, E.A.M., O'Shea, P. & Hirst, J.D., Electronic structure of 5-hydroxyindole: from gas-phase to explicit solvation. J. Phys. Chem. B, 113, 2535–2541 (2009).
DOI: http://dx.doi.org/10.1021/jp808943d
85. Bulheller, B.M. & Hirst, J.D., DichroCalc–circular and linear dichroism online. Bioinformatics, 25, 539–540 (2009).
DOI: http://dx.doi.org/10.1093/bioinformatics/btp016
84. Bacardit, J., Stout, M., Hirst, J.D., Valencia, A., Smith R.E., & Krasnogor, N., Automated alphabet reduction for protein datasets. BMC Bioinformatics, 10, 6 (2009).
DOI: http://dx.doi.org/10.1186/1471-2105-10-6
83. Stout, M., Bacardit, J., Hirst, J.D., Smith, R.E. & Krasnogor, N., Prediction of Topological Contacts in Proteins Using Learning Classifier Systems. Soft Comput., 13, 245–258 (2009).
DOI: http://dx.doi.org/10.1007/s00500-008-0318-8
82. Hamby, S.E. & Hirst, J.D., Prediction of Glycosylation Sites Using Random Forests. BMC Bioinformatics, 9, 500 (2008).
DOI: http://dx.doi.org/10.1186/1471-2105-9-500
81. Oakley, M.T., Barthel, D., Bykov, Y., Garibaldi, J.M., Burke, E.K., Krasnogor, N. & Hirst, J.D., Search Strategies in Structural Bioinformatics. Curr. Prot. Peptide. Sci., 9, 260–274 (2008).
DOI: http://dx.doi.org/10.2174/138920308784534032
80. Stout, M., Bacardit, J., Hirst, J.D. & Krasnogor, N., Prediction of Recursive Convex Hull Class Assignments for Protein Residues Using Learning Classifier Systems. Bioinformatics, 24, 916–923 (2008).
DOI: http://dx.doi.org/10.1093/bioinformatics/btn050
79. Evans, C.-L., Long, J.E., Gallagher, T.R.A., Hirst, J.D. & Searle, M.S., Conformation and dynamics of the three-helix bundle UBA domain of p62 from experiment and simulation. Proteins: Structure, Function & Bioinformatics, 71, 227–240 (2008).
DOI: http://dx.doi.org/10.1002/prot.21692
78. Bulheller, B.M., Miles, A.J., Wallace, B.A. & Hirst, J.D., Charge-Transfer Transitions in the Vacuum-Ultraviolet of Protein Circular Dichroism Spectra. J. Phys. Chem. B, 112, 1866–1874 (2008).
DOI: http://dx.doi.org/10.1021/jp077462k
77. Barthel, D., Hirst, J.D., Blazewicz, J., Burke, E.K. & Krasnogor, N., ProCKSI: a decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information. BMC Bioinformatics, 8, 416 (2007).
DOI: http://dx.doi.org/10.1186/1471-2105-8-416
76. Bacardit, J., Stout, M., Hirst, J.D., Sastry, K. Llora, X. & Krasnogor, N., Automated alphabet reduction method with evolutionary algorithms for protein structure prediction. GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, London, England, (ISBN 978-1-59593-697-4), 346–353 (2007).
DOI: http://dx.doi.org/10.1145/1276958.1277033
75. Melville, J.L., Moal, I.H., Baker-Glenn, C., Shaw, P.E, Pattenden, G. & Hirst, J.D., The Structural Determinants of Macrolide-Actin Binding: In Silico Insights. Biophys. J., 92, 3862–3867 (2007).
DOI: http://dx.doi.org/10.1529/biophysj.106.103580
74. Bulheller, B.M., Rodger, A. & Hirst, J.D., Circular and Linear Dichroism of Proteins. Phys. Chem. Chem. Phys., 9, 2020–2035 (2007).
DOI: http://dx.doi.org/10.1039/b615870f

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73. Oakley, M.T., Guichard, G. & Hirst, J.D., Calculations on the Electronic Excited States of Ureas and Oligoureas. J. Phys. Chem. B, 111, 3274–3279 (2007).
DOI: http://dx.doi.org/10.1021/jp067890a
72. Melville, J.L. & Hirst, J.D., TMACC: Interpretable Correlation Descriptors for Quantitative Structure-Activity Relationships. J. Chem. Inf. Mod., 47, 626–634 (2007).
DOI: http://dx.doi.org/10.1021/ci6004178

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71. Vincent, E., Saxton, J., Baker-Glenn, C., Moal, I., Hirst, J.D., Pattenden, G. & Shaw, P.E., Disruption of actin dynamics and SRF-dependent gene regulation by the marine macrolide ulapualide A and its synthetic analogues. Cell. Mol. Life Sci., 64, 487–497 (2007).
DOI: http://dx.doi.org/10.1007/s00018-007-6427-1
70. Dryden, I.L., Hirst, J.D. & Melville, J.L., Statistical analysis of unlabelled points: comparing molecules in cheminformatics. Biometrics, 63, 237–251 (2007).
DOI: http://dx.doi.org/10.1111/j.1541-0420.2006.00622.x
69. Bruce, C.L., Melville, J.L., Pickett, S.D & Hirst, J.D., Contemporary QSAR Classifiers Compared. J. Chem. Inf. Mod., 47, 219–227 (2007).
DOI: http://dx.doi.org/10.1021/ci600332j

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68. Melville, J.L., Riley, J.F. & Hirst, J.D., Similarity by Compression. J. Chem. Inf. Mod., 47, 25–33 (2007).
DOI: http://dx.doi.org/10.1021/ci600384z

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67. Oakley, M.T. & Hirst, J.D., Charge-Transfer Transitions in Protein Circular Dichroism Calculations. J. Am. Chem. Soc., 128, 12414–12415 (2006).
DOI: http://dx.doi.org/10.1021/ja0644125

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66. Bacardit, J., Stout, M., Krasnogor, N., Hirst, J.D., & Blazewicz, J., Coordination number prediction using learning classifier systems: performance and interpretability. In: Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (Seattle, Washington, USA, July 08 - 12, 2006). GECCO '06, ACM Press, New York, NY, 247–254 (2006).
DOI: http://dx.doi.org/10.1145/1143997.1144041
65. Rogers, D.M., Hirst, J.D., Lee, E.P.F. & Wright, T.G., Ab Initio Study of the Toluene Dimer. Chem. Phys. Lett., 427, 410–413 (2006).
DOI: http://dx.doi.org/10.1016/j.cplett.2006.07.022

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64. Jansen, T.L.C., Dijkstra, A.G., Watson, T.M., Hirst, J.D. & Knoester, J., Modeling the amide I bands of small peptides. J. Chem. Phys., 125, 44312/1 – 44312/9 (2006).
DOI: http://dx.doi.org/10.1063/1.2218516
63. Stout, M., Bacardit, J., Hirst, J.D., Krasnogor, N., & Blazewicz, J., From HP Lattice Models to Real Proteins: coordination number prediction using Learning Classifier Systems. Lectures Notes in Computer Science, 3907, 208–220 (2006).
DOI: http://dx.doi.org/10.1007/11732242_19
62. Oakley, M.T., Bulheller, B.M. & Hirst, J.D., First Principles Calculations of Protein Circular Dichroism in the Far-Ultraviolet and Beyond. Chirality, 18, 340–347 (2006).
DOI: http://dx.doi.org/10.1002/chir.20264
61. Rogers, D.M., Besley, N.A., O'Shea, P. & Hirst, J.D., Modeling the Absorption Spectrum of Tryptophan in Proteins. J. Phys. Chem. B, 109, 23061–23069 (2005).
DOI: http://dx.doi.org/10.1021/jp053309j
60. Blackburne, B.P. & Hirst, J.D., Population Dynamics Simulations of Functional Model Proteins. J. Chem. Phys., 123, 154907/1–154907/9 (2005).
DOI: http://dx.doi.org/10.1063/1.2056545
59. Oakley, M.T., Garibaldi, J.M. & Hirst, J.D., Lattice models of peptide aggregation: Evaluation of conformational search algorithms. J. Comp. Chem., 26, 1638–1646 (2005).
DOI: http://dx.doi.org/10.1002/jcc.20306
58. Melville, J.L., Lovelock, K.J.R., Wilson, C., Allbutt, B., Burke, E.K., Lygo, B. & Hirst, J.D., Exploring Phase-Transfer Catalysis with Molecular Dynamics and 3D/4D Quantitative Structure-Selectivity Relationships. J. Chem. Inf. Mod., 45, 971–981 (2005).
DOI: http://dx.doi.org/10.1021/ci050051l
57. Watson, T.M. & Hirst, J.D., Theoretical Studies of the Amide I Vibrational Frequencies of [Leu]-enkephalin. Mol. Phys., 103, 1531–1546 (2005).
DOI: http://dx.doi.org/10.1080/00268970500052387
56. McNeany, T.J. & Hirst, J.D., Inhibition of the Tyrosine Kinase, Syk, Analyzed by Stepwise Non-Parametric Regression. J. Chem. Inf. Mod., 45, 768–776 (2005).
DOI: http://dx.doi.org/10.1021/ci049631t
55. Wood, M.J. & Hirst, J.D., Protein Secondary Structure Prediction with Dihedral Angles. Proteins: Structure, Function & Bioinformatics, 59, 476–481 (2005).
DOI: http://dx.doi.org/10.1002/prot.20435
54. Pelta, D.A., Krasnogor, N., Bousono-Calzon, C., Verdegay, J.L., Hirst, J.D., Burke, E.K., A Fuzzy Sets based Generalization of Contact Maps for the Overlap of Protein Structures. Fuzzy Sets and Systems, 152, 103–121 (2005).
DOI: http://dx.doi.org/10.1016/j.fss.2004.10.017
53. Besley, N.A, Oakley, M.T., Cowan, A.J. & Hirst, J.D., A Sequential Molecular Mechanics/Quantum Mechanics Study of the Electronic Spectra of Amides. J. Am. Chem. Soc., 126, 13502–13511 (2004).
DOI: http://dx.doi.org/10.1021/ja047603l

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52. Lygo, B., Andrews, B.I., Hirst, J.D., Melville, J.L., Peterson, J.A. & Slack, D., Rapid screening of cinchona alkaloid derived phase-transfer catalysts. Application in the optimization of a glycine imine alkylation. Chim Oggi, 22(9), 41920 (2004).
DOI: http://dx.doi.org/10.1002/chin.200549258
51. Rogers, D.M. & Hirst, J.D., First Principles Calculations of Protein Circular Dichroism in the Near-Ultraviolet. Biochemistry, 43, 11092–11102 (2004).
DOI: http://dx.doi.org/10.1021/bi049031n

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50. Melville, J.L. & Hirst, J.D., On the stability of CoMFA models. J. Chem. Inf. Comput. Sci., 44, 1294–1300 (2004).
DOI: http://dx.doi.org/10.1021/ci049944o
49. Melville, J.L., Andrews, B.I., Lygo, B. & Hirst, J.D., Computational screening of combinatorial catalyst libraries. Chem. Comm., 12, 1410–1411 (2004).
DOI: http://dx.doi.org/10.1039/b402378a

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48. Watson, T.M. & Hirst, J.D., Vibrational Analysis of Capped [Leu]Enkephalin. Phys. Chem. Chem. Phys., 6, 2580–2587 (2004).
DOI: http://dx.doi.org/10.1039/b315501c
47. Gilbert, A.T.B. & Hirst, J.D., Charge-Transfer Transitions in Protein Circular Dichroism Spectra. J. Mol. Struct. (THEOCHEM), 675, 53–60 (2004).
DOI: http://dx.doi.org/10.1016/j.theochem.2003.12.038
46. Rogers, D.M. & Hirst, J.D., Calculations of Protein Circular Dichroism from First Principles. Chirality, 16, 234–243 (2004).
DOI: http://dx.doi.org/10.1002/chir.20018
45. Watson, T.M. & Hirst, J.D., Calculating Vibrational Frequencies of Amides: from Formamide to Concanavalin A. Phys. Chem. Chem. Phys., 6, 998–1005 (2004).
DOI: http://dx.doi.org/10.1039/b312181j
44. Wood, M.J. & Hirst, J.D., Predicting Protein Secondary Structure by Cascade- Correlating Neural Networks. Bioinformatics, 20, 419–420 (2004).
DOI: http://dx.doi.org/10.1093/bioinformatics/btg423
43. Rogers, D.M. & Hirst, J.D., Ab Initio Studies of Aromatic Side-Chains in Gas Phase and Solution. J. Phys. Chem. A, 107, 11191–11200 (2003).
DOI: http://dx.doi.org/10.1021/jp036081d
42. Hirst, J.D., Colella, K. & Gilbert, A.T.B., Electronic Circular Dichroism Spectra of Proteins from First Principles Calculations. J. Phys. Chem. B, 107, 11813–11819 (2003).
DOI: http://dx.doi.org/10.1021/jp035775j
41. Watson, T.M. & Hirst, J.D., Influence of Electrostatic Environment on the Vibrational Frequencies of Proteins. J. Phys. Chem. A, 107, 6843–6849 (2003).
DOI: http://dx.doi.org/10.1021/jp0344500
40. Bhattacharjee, S., Tóth, G., Lovas, S. & Hirst, J.D., Influence of Tyrosine on the Electronic Circular Dichroism of Helical Peptides. J. Phys. Chem. B, 107, 8682–8688 (2003).
DOI: http://dx.doi.org/10.1021/jp034517j
39. Blackburne, B.P. & Hirst, J.D., Three Dimensional Functional Model Proteins: Structure, Function and Evolution. J. Chem. Phys., 119, 3453–3460 (2003).
DOI: http://dx.doi.org/10.1063/1.1590310
38. Cox, K., Watson, T., Soultanas, P. & Hirst, J.D., Molecular Dynamics Simulations of a Helicase. Proteins: Structure, Function & Genetics, 52, 254–262 (2003).
DOI: http://dx.doi.org/10.1002/prot.10400
37. Hirst, J.D., Bhattacharjee, S. & Onufriev, A.V., Theoretical Studies of Time-Resolved Protein Folding. Faraday Discussions, 122, 253–267 (2003).
DOI: http://dx.doi.org/10.1039/b200714b
36. Andrew, C.D., Bhattacharjee, S., Kokkoni, N., Hirst, J.D., Jones, G.R. & Doig, A.J., Stabilizing Interactions between Aromatic and Basic Side Chains in α-Helical Peptides. Tyrosine Effects on Helix Circular Dichroism. J. Am. Chem. Soc., 124, 12706–12714 (2002).
DOI: http://dx.doi.org/10.1021/ja027629h

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35. Krasnogor, N., Blackburne, B.P., Burke, E.K. & Hirst, J.D., Multimeme Algorithms for Protein Structure Prediction. Proceedings of the 7th International Conference on Parallel Problem Solving from Nature, Granada, Spain, Publishers: Springer, pp 769–778 (2002).
34. Carr, B., Hart, W.E., Hirst, J.D., Krasnogor, N., Burke, E.K & Smith, J., Alignment of Protein Structures with a Memetic Evolutionary Algorithm. Proceedings of the Genetic and Evolutionary Computation Conference 2002, NewYork, USA, Publishers: Morgan Kaufmann, pp 1027–1034 (2002).
33. Watson, T.M. & Hirst, J.D., DFT Vibrational Frequencies of Amides and Amide Dimers. J. Phys. Chem. A, 106, 7858–7867 (2002).
DOI: http://dx.doi.org/10.1021/jp025551l
32. Rodger, A., Rajendra, J., Mortimer, R., Andrews, T., Hirst, J.D., Gilbert, A.T.B., Marrington, R., Dafforn, T.R., Hasall, D.J., Ardhammar, M., Nordén, B., Woolhead, C.A., Robinson, C., Pinheiro, T., Kazlauskaite, J., Seymour, M., Perez, N. & Hannon, M.J., Flow Oriented Linear Dichroism to Probe Protein Orientation in Membrane Environments. Phys. Chem. Chem. Phys., 4, 4051–4057 (2002).
DOI: http://dx.doi.org/10.1039/b205080n
31. Hirst, J.D., McNeany, T.J., Howe, T. & Whitehead, L., Application of Non- Parametric Regression to Quantitative Structure-Activity Relationships. Bioorg. Med. Chem., 10, 1037–1041 (2002).
DOI: http://dx.doi.org/10.1016/S0968-0896(01)00359-5

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30. Dang, Z. & Hirst, J.D., Short Hydrogen Bonds, Circular Dichroism and Over- Estimates of Peptide Helicity. Angew. Chemie Intl. Ed., 40, 3619–3621 (2001).
DOI: http://dx.doi.org/10.1002/1521-3773(20011001)40:19<3619::AID-ANIE3619>3.0.CO;2-4
29. Blackburne, B.P. & Hirst, J.D., Evolution of Functional Model Proteins. J. Chem. Phys., 115, 1935–1942 (2001).
DOI: http://dx.doi.org/10.1063/1.1383051
28. Besley, N.A., Brienne, M.-J. & Hirst, J.D., Electronic Structure of a Rigid Cyclic Diamide. J. Phys. Chem. B, 104, 12371–12377 (2000).
DOI: http://dx.doi.org/10.1021/jp0024524
27. Besley, N.A. & Hirst, J.D., Hydrogen Bonding in Protein Circular Dichroism Calculations. J. Mol. Struct. (THEOCHEM), 506, 161–167 (2000).
DOI: http://dx.doi.org/10.1016/S0166-1280(00)00409-7
26. Constans, P & Hirst, J.D., Non-Parametric Regressors Applied to Quantitative Structure-Activity Relationships. J. Chem. Inf. Comput. Sci., 40, 452–459 (2000).
DOI: http://dx.doi.org/10.1021/ci990082e
25. Besley, N.A. & Hirst, J.D., Theoretical Studies toward Quantitative Protein Circular Dichroism Calculations. J. Am. Chem. Soc., 121, 9636–9644 (1999).
DOI: http://dx.doi.org/10.1021/ja990627l
24. Besley, N.A. & Hirst, J.D., Ab Initio Study of the Electronic Spectrum of Formamide with Explicit Solvent. J. Am. Chem. Soc., 121, 8559–8566 (1999).
DOI: http://dx.doi.org/10.1021/ja990064d
23. Hirst, J.D., The Evolutionary Landscapes of Functional Model Proteins. Protein Engineering, 12, 721–726 (1999).
22. Hirst, J.D. & Besley, N.A., Response to »Comment on 'Improving Protein Circular Dichroism Calculations in the Far-Ultraviolet through Reparametrizing the Amide Chromophore'«. J. Chem. Phys. [J. Chem. Phys. 109, 782-788 (1998)], 111, 2846–2847 (1999).
DOI: http://dx.doi.org/10.1063/1.479563
21. Hirst, J.D., Dominy, B., Guo, Z., Vieth, M. & Brooks III, C.L., Conformational and Energetic Aspects of Receptor-Ligand Recognition. Am. Chem. Soc. Symp. Series, 719, 13485 (1999).
20. Besley, N.A. & Hirst, J.D., Ab Initio Study of the Effect of Solvation on the Electronic Spectra of Formamide and N-Methylacetamide. J. Phys. Chem. A, 102, 10791–10797 (1998).
DOI: http://dx.doi.org/10.1021/jp982645f
19. Hirst, J.D., Predicting Ligand Binding Energies. Curr. Opin. Drug Discovery & Development, 1, 28–33 (1998).
18. Hirst, J.D., Improving Protein Circular Dichroism Calculations through Better Ab Initio Models of the Amide Chromophore. Enantiomer, 3, 215–220 (1998).
17. Vieth, M., Hirst, J.D., Dominy, B.N., Daigler, H. & Brooks III, C.L., Assessing Search Strategies for Flexible Docking. J. Comp. Chem., 19, 1623–1631 (1998).
DOI: http://dx.doi.org/10.1002/(SICI)1096-987X(19981115)19:14<1623::AID-JCC8>3.0.CO;2-L
16. Vieth, M., Hirst, J.D., Kolinski, A. & Brooks III, C.L., Assessing Energy Functions for Flexible Docking. J. Comp. Chem., 19, 1612–1622 (1998).
DOI: http://dx.doi.org/10.1002/(SICI)1096-987X(19981115)19:14<1612::AID-JCC7>3.0.CO;2-M
15. Hirst, J.D., Improving Protein Circular Dichroism Calculations in the Far-Ultraviolet through Reparametrizing the Amide Chromophore. J. Chem. Phys., 109, 782–788 (1998).
DOI: http://dx.doi.org/10.1063/1.476617
14. Vieth, M., Hirst, J.D. & Brooks III, C.L., Do Active Site Conformations of Small Ligands Correspond to Low Free Energy Structures? J. Comput.-Aided Mol. Des., 12, 563–572 (1998).
DOI: http://dx.doi.org/10.1023/A:1008055202136
13. Hirst, J.D. & Persson, B.J., Ab Initio Calculations of the Vibrational and Electronic Spectra of Diketopiperazine. J. Phys. Chem. A, 102, 7519–7524 (1998).
DOI: http://dx.doi.org/10.1021/jp982423h
12. Hirst, J.D., Hirst, D.M. & Brooks III, C.L., Multireference Configuration Interaction Calculations of Electronic States of N-Methylformamide, Acetamide, and N-Methylacetamide. J. Phys. Chem. A, 101, 4821–4827 (1997).
DOI: http://dx.doi.org/10.1021/jp970675x
11. Hirst, J.D., Nonlinear Quantitative Structure-Activity Relationship for the Inhibition of Dihydrofolate Reductase by Pyrimidines. J. Med. Chem., 39, 3526–3532 (1996).
DOI: http://dx.doi.org/10.1021/jm960197z
10. Hirst, J.D., Hirst, D.M. & Brooks III, C.L., Ab Initio Calculations of the Excited States of Formamide. J. Phys. Chem., 100, 13487–13491 (1996).
DOI: http://dx.doi.org/10.1021/jp960597y
9. Hirst, J.D., Vieth, M., Skolnick, J. & Brooks III, C.L., Predicting Leucine Zipper Structures from Sequence. Protein Engineering, 9, 657–662 (1996).
DOI: http://dx.doi.org/10.1093/protein/9.8.657
8. Hirst, J.D. & Brooks III, C.L., Molecular Dynamics Simulations of Isolated Helices of Myoglobin. Biochemistry, 34, 7614–7621 (1995).
DOI: http://dx.doi.org/10.1021/bi00023a007
7. King, R.D., Hirst, J.D. & Sternberg, M.J.E., Drug Design by Machine Learning: A Comparative Study. Applications in Artificial Intelligence, 9, 213–233 (1995).
6. Hirst, J.D. & Brooks III, C.L., Helicity, Circular Dichroism and Molecular Dynamics of Proteins. J. Mol. Biol., 243, 173–178 (1994).
DOI: http://dx.doi.org/10.1006/jmbi.1994.1644
5. Hirst, J.D., King, R.D. & Sternberg, M.J.E., Quantitative Structure-Activity Relationships by Neural Networks and Inductive Logic Programming II. The Inhibition of Dihydrofolate Reductase by Triazines. J. Comput.-Aided Mol. Des., 8, 421–432 (1994).
DOI: http://dx.doi.org/10.1007/BF00125376
4. Hirst, J.D., King, R.D. & Sternberg, M.J.E., Quantitative Structure-Activity Relationships by Neural Networks and Inductive Logic Programming I. The Inhibition of Dihydrofolate Reductase by Pyrimidines. J. Comput.-Aided Mol. Des., 8, 405–420 (1994).
DOI: http://dx.doi.org/10.1007/BF00125375
3. King, R.D., Hirst, J.D. & Sternberg, M.J.E., New Approaches to QSAR: Neural Networks and Machine Learning. Perspectives in Drug Discovery and Design, 1, 279–290 (1993).
DOI: http://dx.doi.org/10.1007/BF02174529
2. Hirst, J.D. & Sternberg, M.J.E., Prediction of Structural and Functional Features of Protein and Nucleic Acid Sequences by Artificial Neural Networks. Biochemistry, 31, 7211–7218 (1992).
DOI: http://dx.doi.org/10.1021/bi00147a001
1. Hirst, J.D. & Sternberg, M.J.E., Prediction of ATP-Binding Motifs: A Comparison of a Perceptron-Type Neural Network and a Consensus Sequence Method. Protein Engineering, 4, 615–623 (1991).
DOI: http://dx.doi.org/10.1093/protein/4.6.615