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DOCKING
Huang, X. et al. Elucidating the Inhibiting Mode of AHPBA Derivatives against
HIV-1 Protease and Building Predictive 3D-QSAR Models. J. Med. Chem. 2002
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Thormann, M. and Pons, M. Massive Docking of Flexible Ligands Using
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Gardiner, E.J., Willett, P. and Artymiuk, P.J. Protein Docking Using a
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Del Carpio, M., Adriel, C. and Yoshimori, A. MIAX: A System for Assessment of
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Taylor, J.S. and Burnett, R.M. DARWIN: A Program for Docking Flexible
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Yang, J.-M. and Kao, C.-Y. Flexible ligand docking using a robust
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Hou, T., Wang, J.M. and Xu, X.J. A Comparison of Three Heuristic Algorithms
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Hou, T., Wang, J., Chen, L. and Xu, X. Automated Docking of Peptides and
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Gehlhaar, D.K., Bouzida, D. and Rejto, P.A. Reduced Dimensionality in
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Design of Site-Directed Combinatorial Libraries. In Rational Drug Design:
Novel Methodology and Practical Applications, ACS Symposium Series Vol. 719,
Parrill, A.L., Reddy, M.R., Eds.; American Chemical Society: Washington DC;
1999, pp. 292-311.
Jones, G., Willett, P., Glen, R.C., Leach, A.R. and Taylor, R. Further
Development of a Genetic Algorithm for Ligand Docking and its Application to
Screening Combinatorial Libraries. In Rational Drug Design: Novel Methodology
and Practical Applications, ACS Symposium Series Vol. 719, Parrill, A.L.,
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Chen, J. and Chi, H. Fast Docking of Drug Molecules to their Receptor.
Chin. Sci. Bull. 1999, 44, 904-908.
Wang, J., Hou, T., Chen, L. and Xu, X.J. Automated Docking of Peptides and
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Vieth, V.D., Hirst, J.D., Dominy, B.N., Daigler, H., Brooks, C.L. Assessing
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Morris, G.M., Goodsell, D.S., Halliday, R.S., Huey, R., Hart, W.E., Belew,
R.K. and Olson, A.J. Automated Docking using a Lamarckian Genetic Algorithm and
an Empirical Binding Free Energy Function. Journal of Computational
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Levine, D., Facello, M., Hallstrom, P., Reeder, G., Walenz, B. and Stevens,
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Shah, N.K., Rejto, P.A. and Verkhivker, G.M. Structural Consensus in
Ligand-Protein Docking Identifies Recognition Peptide Motifs that Bind
Streptavidin. Proteins: Structure, Function and Genetics 1997, 28,
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Rejto, P.A. and Verkhivker, G.M. Mean Field Analysis of FKBP-12 Complexes
with FK506 and Rapamycin: Implications for a Role of Crystallographic Water
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Westhead, D.R., Clark, D.E. and Murray, C.W. A Comparison of Heuristic Search
Algorithms for Molecular Docking. Journal of Computer-Aided Molecular
Design 1997, 11, 209-228.
Jones, G., Willett, P., Glen, R.C., Leach, A.R. and Taylor, R. Development
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Sansom, C. Evolution Goes for GOLD in silico. Nature Biotechnology
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Gehlhaar, D.K. and Fogel, D.B. Tuning Evolutionary Programming for
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Verkhivker, G.M., Rejto, P.A., Gehlhaar, D.K. and Freer, S.T. Exploring the
Energy Landscapes of Molecular Recognition by a Genetic Algorithm: Analysis of
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Meadows, R.P. and Hajduk, P.J. A Genetic Algorithm-based Protocol for Docking
Ensembles of Small Ligands using Experimental Results. Journal of
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Jones, G., Willett, P. and Glen, R.C. Molecular Recognition of Receptor Sites
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Molecular Biology 1995, 245, 43-53.
Clark, K.P. and Ajay Flexible Ligand Docking without Parameter Adjustment
across Four Ligand-Receptor Complexes. Journal of Computational Chemistry
1995, 16, 1210-1226.
Gehlhaar, D.K., Verkhivker, G.M., Rejto, P.A., Sherman, C.J. Fogel, D.B.,
Fogel, L.J. and Freer, S.T. Molecular Recognition of the Inhibitor AG-1343 by
HIV-1 Protease: Conformationally Flexible Docking by Evolutionary Programming.
Chemistry and Biology 1995, 2, 317-324.
Gehlhaar, D.K., Verkhivker, G.M., Rejto, P.A., Fogel, D.B., Fogel, L.J. and
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Judson, R.S., Tan, Y.T., Mori, E., Melius, C., Jaeger, E.P., Treasurywala,
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Proteins. Journal of Computational Chemistry 1995, 16, 1405-1419.
Oshiro, C.M., Kuntz, I.D. and Dixon, J.S. Flexible Ligand Docking Using a
Genetic Algorithm. Journal of Computer-Aided Molecular Design 1995, 9,
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Xiao, Y.L. and Williams, D.E. GAME: Genetic Algorithm for Minimisation of
Energy: An Interactive Program for 3-Dimensional Intermolecular Interactions.
Computers and Chemistry 1994, 18, 199-201.
Xiao, Y.L. and Williams, D.E. Genetic Algorithms for Docking of Actinomycin D
and Deoxyguanosine Molecules with Comparison to the Crystal Structure of
Actinomycin D - Deoxyguanosine Complex. Journal of Physical Chemistry
1994, 98, 7191-7200.
Judson, R.S., Jaeger, E.P. and Treasurywala, A.M. A Genetic Algorithm Based
Method for Docking Flexible Molecules. Journal of Molecular Structure
1994, 308, 191-206.
Duncan, B.S. Predicting Protein-Protein Interaction Using Parametric
Surfaces. Paper presented at the 13th Annual Conference of the Molecular
Graphics Society: Molecular Graphics at the Frontier, Evanston (IL), U.S.A.,
July 1994. (An abstract of this paper was published in Chemical Design
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Dixon, J.S. Flexible Docking of Ligands to Receptor Sites using Genetic
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DE NOVO DESIGN
Ibarra-Molero, B. et al. Genetic Algorithm to Design Stabilising Surface
Charge Distributions in Proteins. J. Phys. Chem. B 2002, 106, 6609-6613.
Campbell, W. et al. A Novel Genetic Algorithm for Designing Mimetic Peptides
that Interfere with the Function of a Target Molecule. Microbiology and
Immunology 2002, 46, 211-215.
Pegg, S.C.-H., Haresco, J.J. and Kuntz, I.D. A Genetic Algorithm for
Structure-based De Novo Design. JCAMD 2001, 15, 911-933.
Budin, N., Majeux, N., Tenette-Souaille, C. and Caflisch, A. Structure-based
Ligand Design by a Build-up Approach and Genetic Algorithm Search in
Conformational Space. J. Comput. Chem. 2001, 22, 1956-1970.
Budin, N., Ahmed, S., Majeux, N. and Caflisch, A. An Evolutionary Approach
for Structure-based Design of Natural and Non-natural Peptidic Ligands. Comb.
Chem. HTS 2001, 4, 661-673.
Schneider, G., Clement-Chomienne, O., Hilfiger, L., Schneider, P., Kirsch,
S., Boehm, H.-J. and Neidhart, W. Virtual Screening for Bioactive Molecules by
Evolutionary De Novo Design. Angew. Chem. Int. Ed. Engl. 2000, 39,
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Wang, R., Gao, Y. and Lai, L. LigBuilder: A Multi-Purpose Program for
Structure-based Drug Design. J. Mol. Modell. 2000, 6, 498-516.
Jagla, B. and Schuchhardt, J. Adaptive Encoding Neural Networks for the
Recognition of Human Signal Peptide Cleavage Sites. Bioinformatics 2000,
16, 245-250.
Schneider, G., Lee, M.-L., Stahl, M. and Scheider, P. De novo design of
molecular architectures by evolutionary assembly of drug-derived building
blocks. J. Comput.-Aided Mol. Design 2000, 14, 487-494.
Douguet, D., Thoreau, E. and Grassy, G. A genetic algorithm for the automated
generation of small organic molecules: Drug design using an evolutionary
algorithm. J. Comput.-Aided Mol. Design 2000, 14, 449-466.
Desjarlais, J.R. and Handel, T.M. Side-Chain and Backbone Flexibility in
Protein Core Design. Journal of Molecular Biology 1999, 290, 305-318.
Sullivan, M. Taking Drug Discovery to New Heights. Today's Chemist at
Work 1999, January, 44-46. (This mentions briefly a EA-based de novo design
package called EAinventor developed by Bob Pearlman's group).
Nachbar, R. Molecular Evolution: a Hierarchical Representation for Chemical
Topology and its Automated Manipulation. In Proceedings of the Third Annual
Genetic Programming Conference, University of Wisconsin, Madison, Wisconsin,
22-25 July 1998, pages 246-253.
Patel, S., Stott, I.P., Bhakoo, M. and Elliott, P. Patenting
Computer-Designed Peptides. Journal of Computer-Aided Molecular Design
1998, 12, 543-556.
Sundaram, A. and Venkatasubramanian, V. Parametric Sensitivity and
Search-Space Characterization Studies of Genetic Algorithms for Computer-Aided
Polymer Design. Journal of Chemical Information and Computer Sciences
1998, 38, 1177-1191.
Globus, A., Lawton, J. and Wipke, T. Automatic Molecular Design Using
Evolutionary Techniques. Nanotechnology 1999, 10, 290-299. Click here
to see fulltext of paper.
Schnieder, G., Schroedl, W., Wallukat, G., Mueller, J., Nissen, E., Roenspek,
W., Wrede, P. and Kunze, R. Peptide Design by Artificial Neural Networks and
Computer-based Evolutionary Search. Proceedings of the National Academy of
Sciences of the USA 1998, 95, 12179-12184.
Desjarlais, J.R. and Clarke, N.D. Computer Search Algorithms in Protein
Modification and Design. Current Opinion in Structural Biology 1998, 8,
471-476.
Ghirlanda, G., Lear, J.D., Lombardi, A. and DeGrado, W.F. >From Synthetic
Coiled Coils to Functional Proteins: Automated Design of a Receptor for the
Calmodulin-binding Domain of Calcineurin. Journal of Molecular Biology
1998, 281, 379-391.
Kel, A., Ptitsyn, A., Babenko, V., Meier-Ewert, S. and Lehrach, H. A Genetic
Algorithm for Designing Gene Family-specific Oligonucleotide Sets Used for
Hybridization: the G Protein-coupled Receptor Protein Superfamily.
Bioinformatics 1998, 14, 259-270.
Brusic, V., Rudy, G., Honeyman, M., Hammer, J., and Harrison, L. Prediction
of MHC Class II-binding Peptides Using an Evolutionary Algorithm and Artificial
Neural Network. Bioinformatics 1998, 14, 121-130.
Wrede, P., Landt, O., Klages, S., Fatemi, A., Hahn, U. and Schneider, G.
Peptide Design Aided by Neural Networks: Biological Activity of Artificial
Signal Peptidase I Cleavage Sites. Biochemistry 1998, 37, 3588-3593.
Lazar, G.A., Desjarlais, J.R. and Handel, T.M. De Novo Design of the
Hydrophobic Core of Ubiquitin. Protein Science 1997, 6, 1167-1178.
Jansen, J.M., Koehler, K.F., Hedberg, M.H., Johanssen, A.M., Hacksell, U.,
Nordvall, G. and Snyder, J.P. Molecular Design using the Minireceptor Concept.
Journal of Chemical Information and Computer Sciences, 1997, 37, 812-818.
(Application of LeapFrog).
Devillers, J. Designing Molecules with Specific Properties from
Intercommunicating Hybrid Systems. Journal of Chemical Information and
Computer Sciences 1996, 36, 1061-1066.
Jones, D.T., Moody, C.M., Uppenbrink, J., Viles, J.H., Doyle, P.M., Harris,
C.J., Pearl, L.H., Sadler, P.J. and Thornton, J.M. Towards Meeting the
Paracelsus Challenge: The Design, Synthesis, and Characterization of
Paracelsin-43, an Alpha-Helical Protein with Over 50-Percent Sequence Identity
to an All-Beta Protein. Proteins: Structure, Function and Genetics 1996,
24, 502-513.
Venkatasubramanian, V., Chan, J., Sundaram, A. and Caruthers, J.M. Designing
Molecules with Genetic Algorithms. AIChe Symp. Ser. 1995, 304, 270-275.
Glen, R.C. and Payne, A.W.R. A Genetic Algorithm for the Automated Generation
of Molecules within Constraints. Journal of Computer-Aided Molecular
Design 1995, 9, 181-202.
Westhead, D.R., Clark, D.E., Frenkel, D., Li, J., Murray, C.W., Robson, B.
and Waszkowycz, B. PRO_LIGAND: An Approach to De Novo Molecular Design. 3. A
Genetic Algorithm for Structure Refinement. Journal of Computer-Aided
Molecular Design 1995, 9, 139-148.
Schneider, G., Schuchhardt, J. and Wrede, P. Development of Simple Fitness
Landscapes for Peptides by Artificial Neural Filter Systems. Biological
Cybernetics 1995, 73, 245-254.
Schneider, G., Schuchhardt, J. and Wrede, P. Peptide Design in Machina:
Development of Artificial Mitochondrial Protein Precursor Cleavage Sites by
Simulated Molecular Evolution. Biophysical Journal 1995, 68, 434-447.
Venkatasubramanian, V., Chan, K. and Caruthers, J.M. Evolutionary Design of
Molecules with Desired Properties Using the Genetic Algorithm. Journal of
Chemical Information and Computer Sciences 1995, 35, 188-195.
Venkatasubramanian, V., Chan, K. and Caruthers, J.M. Genetic Algorithmic
Approach for Computer-Aided Molecular Design. In Computer-Aided Molecular
Design: Applications in Agrochemicals, Materials and Pharmaceuticals,
Reynolds, C.H., Holloway, M.K. and Cox, H.K. (Eds). ACS Symposium Series 589,
ACS, Washington DC, 1995. pp. 396-414.
Desjarlais, J.R. and Handel, T.M. De Novo Design of the Hydrophobic Cores of
Proteins. Protein Science 1995, 4, 2006-2018.
Ebeling, M. and Nadler, W. On Constructing Folding Heteropolymers.
Proceedings of the National Academy of Sciences (USA) 1995, 92,
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Venkatasubramanian, V. and Caruthers, J.M. Computer-Aided Molecular Design
Using Genetic Algorithms. Comput. Chem. Eng 1994, 18, 833-844.
Schneider, G., Schuchhardt, J. and Wrede, P. Artificial Neural Networks and
Simulated Molecular Evolution Are Potential Tools for Sequence-Oriented Protein
Design. Computer Applications in the Biosciences 1994, 10, 635-645.
Schneider, G. and Wrede, P. The Rational Design of Amino Acid Sequences by
Artificial Neural Networks and Simulated Molecular Evolution: De Novo Design of
an Idealised Leader Peptidase Cleavage-Site. Biophysical Journal 1994,
66, 335-344.
Jones, D.T. De Novo Protein Design using Pairwise Potentials and a Genetic
Algorithm. Protein Science 1994, 3, 567-574.
Hellinga, H.W. and Richards, F.M. Optimal Sequence Selection in Proteins of
Known Structure by Simulated Evolution. Proceedings of the National Academy
of Sciences (USA) 1994, 91, 5803-5807.
Blaney, J.M., Dixon, J.S. and Weininger, D. Evolution of Molecules to Fit a
Binding Site of Known Structure. Paper presented at the Molecular Graphics
Society Meeting on Binding Sites: Characterising and Satisfying Steric and
Chemical Restraints, York, U.K., March 1993. (Abstracts of this and other papers
presented at this meeting are available from Prof. R.E. Hubbard, Department of
Chemistry, University of York, York, YO1 5DD, United Kingdom. Email:
rod@yorvic.york.ac.uk).
Glen, R.C. Chemical Genesis: A Genetic Algorithm for Automated Drug Design.
Paper presented at the Molecular Graphics Society Meeting on Binding Sites:
Characterising and Satisfying Steric and Chemical Restraints, York, U.K., March
1993.
Cramer, R.D. POSIT: A Second Generation De Novo Drug Discovery Tool. Paper
presented at the Molecular Graphics Society Meeting on Binding Sites:
Characterising and Satisfying Steric and Chemical Restraints, York, U.K., March
1993.
PSEUDORECEPTOR MODELING
Vedani, A., Briem, H., Dobler, M., Dollinger, H. and McMasters, D.R. Multiple
Conformation and Protonation State Representation in 4D-QSAR: The Neurokinin-1
Receptor System. J. Med. Chem. 2000, 43, in press.
Schulze-Alexandru, M., Kova, K.A., Vedani, A. Quasi-Atomistic Receptor
Surrogates for the 5-HT2A Receptor: A 3D-QSAR Study oon Hallucinogenic
Substances. Quant. Struct.-Act. Relat. 1999, 18, 548-560.
Vedani, A. and Zbinden, P. Quasi-Atomistic Receptor Modeling: A Bridge
Between 3-D QSAR and Receptor Modeling. Pharm. Acta Helv. 1998, 73,
11-18.
Walters, D.E. and Muhammad, T.D. Genetically Evolved Receptor Models (GERM):
A Comparison of Evolved Models with Crystallographically Determined Binding
Sites. Alfred Benzon Symposium 1998, 42 (Rational Molecular Design in
Drug Research), 101-114.
Vedani, A., Dobler, M. and Zbinden, P. Quasi-Atomistic Receptor Surface
Models: A Bridge Between 3-D QSAR and Receptor Modeling. Journal of the
American Chemical Society 1998, 120, 4471-4477.
Chen, H., Zhou, J. and Xie, G. PARM: A Genetic Evolved Algorithm to Predict
Bioactivity. Journal of Chemical Information and Computer Sciences 1998,
38, 243-250.
Chen, H., Ren, T. and Zhou, J. Receptor Mapping used for Predicting
Bioactivity. J. Chin. Pharm. Sci. 1997, 6, 149-153.
Chen, H.M., Zhou, J.J., Ren, T.R. and Xie, G.R. PARM: A New QSAR Research
Method Based on Genetic Algorithm. Chinese Chem. Letters 1997, 8,
975-978.
Walters, D.E. and Muhammad, T.D. Genetically Evolved Receptor Models (GERM):
A Procedure for Construction of Atomic-Level Receptor Site Models in the Absence
of a Receptor Crystal Structure. In: Devillers, J. (Ed.) Genetic Algorithms
in Molecular Modelling, Academic Press, 1996, pp. 193-210.
Walters, D.E. and Hinds, R.M. Genetically Evolved Receptor Models: A
Computational Approach to Construction of Receptor Models. Journal of
Medicinal Chemistry 1994, 37, 2527-2536.
PHARMACOPHORE MAPPING
Jones, G. and Willett, P. GASP: Genetic Algorithm Superimposition Program.
IUL Biotechnology Series 2 (Pharmacophore), 2000, 85-106.
Handschuh, S. and Gasteiger, J. Pharmacophores Derived from the 3D
Substructure Perception. IUL Biotechnology Series 2 (Pharmacophore),
2000, 431-453.
McFadyen, I.J. et al. The Steroid SC17599 is a Selective mu-Opioid Agonist:
Implications for the mu-Opioid Pharmacophore. Mol. Pharmacol. 2000, 58,
669-676.
Handschuh, S. and Gasteiger, J. The Search for the Spatial and Electronic
Requirements of a Drug. J. Mol. Modell. 2000, 6, 358-378.
Leherte, L., Meurice, N. and Vercauteren, D.P. Critical Point Representations
of Electron Density Maps for the Comparison of Benzodiazepine-Type Ligands.
J. Chem. Inf. Comput. Sci. 2000, 40, 816-832.
Miller, M.D., Fluder, E.M., Castonguay, L.A., Culberson, J.C., Mosley, R.T.,
Prendergast, K., Kearsley, S.K. and Sheridan, R.P. MEGA-SQ: A Method using the
SQuEAL Function to Find the Optimal Superposition of Several Quasi-Flexible
Molecules. Med. Chem. Res. 1999, 9, 513-534.
Dolata, D.P., Parrill, A.L. and Walters, W.P. CLEW: the Generation of
Pharmacophore Hypotheses through Machine Learning. SAR and QSAR in
Environmental Research 1998, 9, 53-81.
Handschuh, S., Wagener, M. and Gasteiger, J. Superposition of
Three-Dimensional Chemical Structures Allowing for Conformational Flexibility by
a Hybrid Method. Journal of Chemical Information and Computer Sciences
1998, 38, 220-232.
Holliday, J.D. and Willett, P. Identification of Common Structural Features
in Sets of Ligands Using a Genetic Algorithm. Journal of Molecular Graphics
and Modelling 1997, 15, 221-232.
Meurice, N., Leherte, L., Vercauteren, D.P., Bourguignon, J.-J. and Wermuth,
C.G. Development of a Genetic Algorithm Method Especially Designed for the
Comparison of Molecular Models: Application to the Elucidation of the
Benzodiazepine Receptor Pharmacophore. In, H. van de Waterbeemd, B. Testa and G.
Folkers, Eds., Computer-Assisted Lead Finding and Optimization: Current Tools
for Medicinal Chemistry, Wiley-VCH, Weinheim, 1997; pp. 497-509.
Jones, G., Willett, P. and Glen, R.C. A Genetic Algorithm for Flexible
Molecular Overlay and Pharmacophore Elucidation. Journal of Computer-Aided
Molecular Design 1995, 9, 532-549.
CHEMICAL STRUCTURE HANDLING
Gobbi, A., Poppinger, D. and Rohde, B. Finding Biological Active Compounds in
Large Databases. Proc. ECSOC-1/2 1999, 708-722.
Le Bret, C. Exhaustive Isomer Generation Using the Genetic Algorithm.
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PROTEIN STRUCTURE AND SEQUENCE COMPARISON AND
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May, A.C.W. and Johnson, M.S. Improved Genetic Algorithm-Based Protein
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May, A.C.W. and Johnson, M.S. Protein Structure Comparisons Using a
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NMR SPECTROSCOPY
Meiler, J. and Will, M. Genius: A Genetic Algorithm for Automated Structure
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Lunati, E., Cofrancesco, P., Villa, M., Marzola, P. and Sbarbati, A.
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Pearlman, D.A. Automated Detection of Problem Restraints in NMR Data Sets
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Lunati, E.,, Cofrancesco, P., Villa, M., Marzola, P. and Osculati, F.
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Chen, Z., Blandl, T., Prorok, M., Warder, S.E., Li, L., Zhu, Y., Pedersen,
L.G., Ni, F. and Castellino, F.J. Conformational Changes in Conantokin-G Induced
upon Binding of Calcium and Magnesium as Revealed by NMR Structural Analysis.
Journal of Biological Chemistry 1998, 273, 16248-16258.
Choy, W.Y. and Sanctuary, B.C. Using Genetic Algorithms with a Priori
Knowledge for Quantitative NMR Signal Analysis. Journal of Chemical
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Weber, O.M., Duc, C.O., Meier, D. and Boesiger, P. Heuristic Optimization
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Warder, S.E., Prorok, M., Chen, Z., Li, L., Zhu, Y., Pedersen, L.G., Ni, F.
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Journal of Biological Chemistry 1998, 273, 7512-7522.
Baylay, M.J., Jones, G., Willett, P. and Williamson, M.P. GENFOLD: A Genetic
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van Kampen, A.H.C., Beckers, M.L.M. and Buydens, L.M.C. A Comparative Study
of the DG_OMEGA, DGII, and GAT Method for the Structure Elucidation of a
Methylene-Acetal Linked Thymine Dinucleotide. Computers and Chemistry
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Bartels, C., Guentert, P., Billeter, M. and Wuethrich, K. GARANT: A General
Algorithm for Resonance Assignment of Multidimensional Nuclear Magnetic
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Beckers, M.L.M., Buydens, L.M.C., Pikkemaat, J.A. and Altona, C. Application
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Journal of Biomolecular NMR 1997, 9, 25-34.
Rigby, A.C., Baleja, J.D., Li, L., Pedersen, L.G., Furie, B.C. and Furie, B.
Role of Gamma-Carboxyglutamic Acid in the Calcium-induced Structural Transition
of Conantokin G, a Conotoxin from the Marine Snail Conus Geographus.
Biochemistry 1997, 36, 15677-15684.
Li, L., Darden, T.A., Freedman, S.J., Furie, B.C., Furie, B., Baleja, J.D.,
Smith, H., Hiskey, R.G. and Pedersen, L.G. Refinement of the NMR Solution
Structure of the Gamma-Carboxyglutamic Acid Domain of Coagulation Factor IX
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van Kampen, A.H.C. and Buydens, L.M.C. The Ineffectiveness of Recombination
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Intelligent Laboratory Systems 1997, 36, 141-152.
Pearlman, D.A. FINGAR: A New Genetic Algorithm-Based Method for Fitting NMR
Data. Journal of Biomolecular NMR 1996, 8, 49-66.
van Kampen, A.H., Buydens, L.M., Lucasius, C.B. and Blommers, M.J.
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Biomolecular NMR 1996, 8, 214-224.
Bartels, C., Billeter, M., Guentert, P. and Wuethrich, K. Automated
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Zimmerman, D.E. and Montelione, G.T. Automated Assignment of Nuclear Magnetic
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Wehrens, R., Lucasius, C., Buydens, L. and Kateman, G. Sequential Assignment
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Wehrens, R., Lucasius, C., Buydens, L. and Kateman, G. HIPS, a Hybrid
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X-RAY CRYSTALLOGRAPHY
Guimeraes, F.F. et al. Global Optimization of Water Clusters (H20)n (11< n
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Bazterra, V.E., Ferraro, M.B. and Facelli, J.C. Modified Genetic Algorithm to
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Harris, K.D.M. Structure Determination of Molecular Crystals Directly from
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Harris, K.D.M. et al. Structure Solution of Molecular Crystals from Powder
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Tedesco, E. et al. Structure Determination of 4,4'-trimethylenedipyridine
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X-ray Diffraction Data. Chem. Commun. 2001, 16, 1460-1461.
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Miller, S.T., Hogle, J.M. and Filman, D.J. Ab Initio Phasing of High-Symmetry
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Ulyanenkov, A., Omote, K. and Harada, J. The Evaluation of Structure
Parameters of a Mo/Si Superlattice Using X-ray Scattering Data and a Genetic
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Chacon, P., Moran, F., Diaz, J.F., Pantos, E. and Andreu, J.M. A Genetic
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Chacon, P., Diaz, J.F., Moran, F. and Andreu, J.M. Reconstruction of Protein
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Mukoyama, T. Analysis of X-ray Spectra by Genetic Algorithm. Int. J.
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Turner, G.W., Tedesco, E., Harris, K.D.M., Johnston, R.L. and Kariuki, B.M.
Implementation of Lamarckian Concepts in a Genetic Algorithm for Structure
Solution from Powder Diffraction Data. Chem. Phys. Lett. 2000, 321,
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Ulyanenkov, A., Omote, K. and Harada, J. The Genetic Algorithm: Refinement of
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Wormington, M. Panaccione, C., Matney, K.M. and Bowen, K.D. Characterization
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Harris, K.D.M., Johnston, R.L. and Kariuki, B.M. An Evolving Technique for
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Kariuki, B.M., Psallidas, K., Harris, K.D.M., Johnston, R.L., Lancaster,
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Motherwell, S.W.D. Crystal Structure Prediction and the Cambridge Structural
Database. Nova Acta Leopold. 1999, 79, 89-98.
Woodley, S.M., Battle, P.D., Gale, J.D. and Catlow, C.R.A. The Prediction of
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Phys. Chem. Chem. Phys. 1999, 1, 2535-2542.
Kariuki, B.M., Belmonte, S.A., McMahon, M.I., Johnston, R.L., Harris, K.D.M.
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Whole Profile Fitting and Global Optimization Using a Genetic Algorithm. J.
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Kariuki, B., Calcagno, P., Harris, K.D.M., Philp, D. and Johnston, R.L.
Evolving Opportunities in Structure Solution from Powder Diffraction Data -
Crystal Structure Determination of a Molecular System with Twelve Variable
Torsion Angles. Angew. Chemie Int. Ed. Engl. 1999, 36, 831-835.
Harris, K.D.M. New Approaches for Solving Crystal Structures from Powder
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Kariuki, B.M., Johnston, R.L., Harris, K.D.M., Psallidas, K., Ahn, S. and
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Harris, K.D.M., Johnston, R.L. and Kariuki, B.M. The Genetic Algorithm:
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Acta Crystallographica Section A: Foundation of Crystallography 1998,
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Chacon, P., Moran, F., Diaz, J.F., Pantos, E. and Andreu, J.M. Low-resolution
Structures of Proteins in Solution Retrieved from X-ray Scattering with a
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Shankland, K., David, W.I.F., Csoka, T. and McBride, L. Structure Solution of
Ibuprofen from Powder Diffraction Data by the Application of a Genetic Algorithm
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Landree, E., Collazo-Davila, C. and Marks, L.D. Multi-solution Genetic
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Acta Crystallographica Section B: Structural Science 1997, 53, 916-922.
Kariuki, B.M., Serrano-Gonzalez, H., Johnston, R.L. and Harris, K.D.M. The
Application of a Genetic Algorithm for Solving Crystal Structures from Powder
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Shankland, K., David, W.I.F. and Csoka, T. Crystal Structure Determination
from Powder Diffraction Data by the Application of a Genetic Algorithm. Z.
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Chang, G. and Lewis, M. Molecular Replacement Using Genetic Algorithms.
Acta Crystallographica Section D: Biological Crystallography 1997, 53,
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Miller, S.T., Hogel, J.M. and Filman, D.J. A Genetic Algorithm for the Ab
Initio Phasing of Icosahedral Viruses. Acta Crystallographica Section D:
Biological Crystallography 1996, 52, 235-251.
Tam, K.Y. and Compton, R.G. GAMATCH: A Genetic Algorithm-Based Program for
Indexing Crystal Faces. Journal of Applied Crystallography 1995, 28,
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Bush, T.S., Catlow, C.R.A. and Battle, P.D. Evolutionary Programming
Techniques for Predicting Inorganic Crystal Structures. Journal of Materials
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Chang, G. and Lewis, M. Using Genetic Algorithms for Solving Heavy Atom
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de Haan, V.-O. and Drijkoningen, G.G. Genetic Algorithms Used in Model
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WATER SITE PREDICTION
Raymer, M.L., Punch, W.F., Goodman, E.D., Sanschagrin, P.C. and Kuhn, L.A.
Simultaneous Feature Scaling and Selection using a Genetic Algorithm. In Baeck,
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Algorithms, Morgan Kaufmann, San Francisco, 1997; pp. 561-567.
Raymer, M.L., Sanschagrin, P.C, Punch, W.F., Venkataraman, S., Goodman, E.D.
and Kuhn, L.A. Predicting Conserved Water-Mediated and Polar Ligand Interactions
in Proteins Using a K-nearest-neighbors Genetic Algorithm. Journal of
Molecular Biology 1997, 265, 445-464.
PARAMETER DEVELOPMENT AND POTENTIAL ENERGY
SURFACE OPTIMIZATION FOR MM, SEMI-EMPIRICAL AND QM CALCULATIONS
Brothers, E.N. and Merz, K.M. Sodium Parameters for AM1 and PM3 Optimised
using a Genetic Algorithm. J. Phys. Chem. 2002, in press.
Strassner, T., Busold, M. and Radrich, H. FFGenerAtor 2.0: An Automated Tool
for the Generation of MM3 Force Field Parameters. J. Mol. Model. 2001, 7,
374-377.
Strassner, T., Busold, M. and Herrmann, W.A. MM3 Parameterisation of Four-
and Five-coordinated Rhenium Complexes by a Genetic Algorithm - Which Factors
Influence the Optimization Performance? J. Comput. Chem. 2002, 23,
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Wang, J. and Kollman, P.A. Automatic Parameterization of Force Field by
Systematic Search and Genetic Algorithms. J. Comput. Chem. 2001, 22,
1219-1228.
Cundari, T.R. and Fu, W. Genetic Algorithm Optimization of a Molecular
Mechanics Forcefield for Technetium. Inorg. Chim. Acta. 2000, 300-302,
113-124.
Cundari, T., Deng, J. and Fu, W. PM3(tm) Parameterization Using Genetic
Algorithms. Int. J. Quantum Chem. 2000, 77, 421-432.
Chaudhury, P. and Bhattacharyya, S.P. Stochastic Construction of Reaction
Paths: A Genetic Algorithm-based Approach. Int. J. Quantum Chem. 2000,
76, 161-168.
Chaudhury, P. and Bhattacharyya, S.P. Bound States in Screened and Bare
Coulomb Potentials: A Non-orthogonal CI-based Route to Effective Hamiltonians
for Two-electron Systems. Int. J. Quantum Chem. 1999, 74, 153-161.
Horinek, D. and Dick, B. The Potential Energy Surface of the Six Lowest
Singlet States of HOCl: Global Optimization of Parameters for an Extended
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Chem. Phys. 1999, 1, 2667-2674.
Villa, J., Corchado, J.C., Gonzalez-Lafont, A., Lluch, J.M. and Truhlar, D.G.
Variational Transition State Theory with Optimized Orientation of the Dividing
Surface and Semiclassical Tunnelling Calculations for Deuterium and Muonium
Kinetic Isotope Effects in the Free Radical Association Reaction H + C2H4 ->
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Chuang, Y.-Y., Radhakrishnan, M.L., Fast, P.L., Cramer, C.J. and Truhlar,
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Hunger, J. and Huttner, G. Optimization and Analysis of Force Field
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Villa, J., Corchado, J.C., Gonzalez-Lafont, A., Lluch, J.M. and Truhlar, D.G.
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Atom Addition to an Olefin. J. Am. Chem. Soc. 1998, 120, 12141-12142.
Hunger, J., Beyreuther, S., Huttner, G., Allinger, K., Radelof, U. and
Zsolnai, L. How to Derive Force Field Parameters by Genetic Algorithms. Modeling
tripod-Mo(CO)3 Compounds as an Example. European Journal of Inorganic
Chemistry 1998, 6, 693-702.
Hutter, M.C., Reimers, J.R and Hush, M.S. Modeling the Bacterial
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Bash, P.A., Ho, L.L., MacKerell, A.D., Levine, D. and Hallstrom, P. Progress
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Rossi, I. and Truhlar, D.G. Parameterization of NDDO Wavefunctions using
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PROTEIN SECONDARY STRUCTURE PREDICTION
Moereels, H., Lewi, P.J., Daeyart, F., Schenck, E. and Janssen, P.A. The
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Vivarelli, F., Giusti, G., Villani, M., Campanini, R., Fariselli, P.,
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Algorithm and Neural Networks for the Prediction of Secondary Structure of
Proteins. Computer Applications in the Biosciences 1995, 11, 253-260.
DATA MINING
Li, L., Darden, T.A., Weinberg, C.R., Levine, A.J. and Pedersen, L.G. Gene
Assessment and Sample Classification for Gene Expression Data using a Genetic
Algorithm/k-nearest Neighbour Method. Comb. Chem. HTS 2001, 4, 719-725.
Cundari, T. and Russo, M. Database Mining using Soft Computing Techniques. An
Integrated Neural Network-Fuzzy Logic-Genetic Algorithm Approach. J. Chem.
Inf. Comput. Sci. 2001, 41, 281-287.
Laurikkala, J., Juhola, M., Lammi, S. and Viikki, K. Comparison of Genetic
Algorithms and Other Classification Methods in the Diagnosis of Female Urinary
Incontinence. Methods Inf. Med. 1999, 38, 125-131.
Ngan, P.S., Wong, M.L., Lam, W., Leung, K.S. and Cheng, J.C. Medical Data
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GENETIC PROGRAMMING
Gilbert, R.J., Rowland, J.J. and Kell, D. B. (2000). Genomic computing:
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Johnson, H.E., Gilbert, R.J., Winson, M.K., Goodacre, R., Smith, A.R.,
Rowland, J.J., Hall, M.A. & Kell, D.B. (2000). Explanatory analysis of the
metabolome using genetic programming of simple, interpretable rules. Genetic
Programming and Evolvable Machines 1(3), 243-258
Goodacre, R., Shann, B., Gilbert, R.J., Timmins, E.M., McGovern, A.C.,
Alsberg, B.K., Kell, D.B. & Logan, N.A. (2000) The detection of the
dipicolinic acid biomarker in Bacillus spores using Curie-point pyrolysis mass
spectrometry and Fourier-transform infrared spectroscopy. Analytical Chemistry
72, 119-127
Goodacre, R. and Gilbert, R.J. The Detection of Caffeine in a Variety of
Beverages using Curie-point Pyrolysis Mass Spectrometry and Genetic Programming.
Analyst 1999, 124, 1069-1074.
Woodward, A.M., Gilbert, R.J. and Kell, D.B. Genetic Programming as an
Analytical Tool for Non-linear Dielectric Spectroscopy. Bioelectrochem.
Bioenerg. 1999, 48, 389-396.
Hiden, H.G., Willis, M.J., Tharn, M.T. and Montague, G.A. Nonlinear Principal
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