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  • Padhorny, D. (2016). Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds. Proceedings of the National Academy of Sciences. doi: 10.1073/pnas.1603929113
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  • Vajda, S. (2015). Fragments and hot spots in drug discovery. Oncotarget. doi: 0.18632/oncotarget.4968
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  • Kozakov, D. (2015). Ligand deconstruction: Why some fragment binding positions are conserved and others are not. Proceedings of the National Academy of Sciences. doi: 10.1073/pnas.1501567112


  • Villar, E. (2014).  How proteins bind macrocycles. Nature Chemical Biology.  doi: 10.1038/nchembio.1584
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  • Kozakov. (2011). Structural conservation of druggable hot spots in protein-protein interfaces. Proceedings of the National Academy of Sciences, 108(33), 13528–13533. doi:10.1073/pnas.1101835108
  • Hall, D. (2011). Robust Identification of Binding Hot Spots Using Continuum Electrostatics: Application to Hen Egg-White Lysozyme. Journal of the American Chemical Society, 133(51), 20668–20671. doi:10.1021/ja207914y
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  • Kozakov, D. (2010b). Achieving reliability and high accuracy in automated protein docking: Cluspro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19. Proteins: Structure, Function, and Bioinformatics, 78(15), 3124–3130. doi:10.1002/prot.22835
  • Kozakov, D. (2010a). Where does amantadine bind to the influenza virus M2 proton channel? Trends in Biochemical Sciences. doi:10.1016/j.tibs.2010.03.006
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  • Vajda, Sandor, & Kozakov, D. (2009). Convergence and combination of methods in protein–protein docking. Current Opinion in Structural Biology, 19(2), 164–170. doi:10.1016/
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  • Ritchie, D. W., Kozakov, D., & Vajda, S. (2008). Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions. Bioinformatics, 24(17), 1865–1873. doi:10.1093/bioinformatics/btn334
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  • Kozakov, D., Schueler‐Furman, O., & Vajda, S. (2008). Discrimination of near‐native structures in protein–protein docking by testing the stability of local minima. Proteins: Structure, Function, and Bioinformatics, 72(3), 993–1004. doi:10.1002/prot.21997
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  • Silberstein, M., Damborsky, J., & Vajda, S. (2007). Exploring the Binding Sites of the Haloalkane Dehalogenase DhlA from Xanthobacter autotrophicus GJ10. Biochemistry, 46(32), 9239–9249. doi:10.1021/bi700336y
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  • Prasad, J., Goldstone, J., Camacho, C., Vajda, S., & Stegeman, J. (2007). Ensemble Modeling of Substrate Binding to Cytochromes P450:  Analysis of Catalytic Differences between CYP1A Orthologs. Biochemistry, 46(10), 2640–2654. doi:10.1021/bi062320m
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  • Landon, M., David R. Lancia, J., Clodfelter, K., & Vajda, S. (2006). Clustering of domains of functionally related enzymes in the interaction database PRECISE by the generation of primary sequence patterns. Journal of Molecular Graphics and Modelling, 24(6), 426–433. doi:10.1016/j.jmgm.2005.08.004
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  • Kaya, T., Mohr, S., Waxman, D., & Vajda, S. (2006). Computational Screening of Phthalate Monoesters for Binding to PPARγ. Chemical Research in Toxicology, 19(8), 999–1009. doi:10.1021/tx050301s
  • Clodfelter, K., Waxman, D., & Vajda, S. (2006). Computational Solvent Mapping Reveals the Importance of Local Conformational Changes for Broad Substrate Specificity in Mammalian Cytochromes P450. Biochemistry, 45(31), 9393–9407. doi:10.1021/bi060343v


  • Vajda, Sandor. (2005). Classification of protein complexes based on docking difficulty. Proteins: Structure, Function, and Bioinformatics, 60(2), 176–180. doi:10.1002/prot.20554
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  • Vajda, Sandor, & Camacho, C. (2004). Protein–protein docking: is the glass half-full or half-empty? Trends in Biotechnology, 22(3), 110–116. doi:10.1016/j.tibtech.2004.01.006
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  • Silberstein, M., Dennis, S., Brown, L., Kortvelyesi, T., Clodfelter, K., & Vajda, S. (2003). Identification of Substrate Binding Sites in Enzymes by Computational Solvent Mapping. Journal of Molecular Biology, 332(5), 1095–1113. doi:10.1016/j.jmb.2003.08.019
  • Prasad, J., Comeau, S., Vajda, S., & Camacho, C. (2003). Consensus alignment for reliable framework prediction in homology modeling. Bioinformatics, 19(13), 1682–1691. doi:10.1093/bioinformatics/btg211
  • Murphy, J., Gatchell, D., Prasad, J., & Vajda, S. (2003). Combination of scoring functions improves discrimination in protein-protein docking. Proteins: Structure, Function, and Genetics, 53(4), 840–854. doi:10.1002/prot.10473
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  • Valkó, P. (2002). Inversion of Noise-Free Laplace Transforms: Towards a Standardized Set of Test Problems. Inverse Problems in Engineering, 10(5), 467–483. doi:10.1080/10682760290004294
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  • Dennis, S., Kortvelyesi, T., & Vajda, S. (2002). Computational mapping identifies the binding sites of organic solvents on proteins. Proceedings of the National Academy of Sciences, 99(7), 4290–4295. doi:10.1073/pnas.062398499
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  • Kimura, R., Brower, R., Vajda, S., & Camacho, C. (2001). Dynamical View of the Positions of Key Side Chains in Protein-Protein Recognition. Biophysical Journal, 80(2), 635–642. doi:10.1016/S0006-3495(01)76044-4
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  • King, B., Vajda, S., & DeLisi, C. (1996). Empirical free energy as a target function in docking and design: application to HIV-1 protease inhibitors. FEBS Letters, 384(1), 87–91. doi:10.1016/0014-5793(96)00276-1
  • Gulukota, K., Vajda, S., & DeLisi, C. (1996). Peptide docking using dynamic programming. Journal of Computational Chemistry, 17(4), 418–428. doi:10.1002/(SICI)1096-987X(199603)17:4<418::AID-JCC4>3.0.CO;2-X
  • Vajda, Sandor. (1995). Extracting hydrophobicity parameters from solute partition and protein mutation/unfolding experiments. “Protein Engineering, Design and Selection”, 8(11), 1081–1092. doi:10.1093/protein/8.11.1081
  • Rosenfeld, R., Vajda, S., & DeLisi, C. (1995). Flexible Docking and Design. Annual Review of Biophysics and Biomolecular Structure, 24(1), 677–700. doi:10.1146/
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  • Vajda, Sandor, Weng, Z., Rosenfeld, R., & DeLisi, C. (1994). Effect of Conformational Flexibility and Solvation on Receptor-Ligand Binding Free Energies. Biochemistry, 33(47), 13977–13988. doi:10.1021/bi00251a004
  • Vajda, Sandor. (1994). Identifiability and Distinguishability of General Reaction Systems. The Journal of Physical Chemistry, 98(20), 5265–5271. doi:10.1021/j100071a016
  • Godfrey, K. (1994). Identifiability and indistinguishability of nonlinear pharmacokinetic models. Journal of Pharmacokinetics and Biopharmaceutics, 22(3), 229–251. doi:10.1007/BF02353330
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  • Zheng, Q. (1993a). Loop closure via bond scaling and relaxation. Journal of Computational Chemistry, 14(5), 556–565. doi:10.1002/jcc.540140508
  • Vajda, Sandor. (1993). Generalized parametric sensitivity: Application to a CSTR. Chemical Engineering Science, 48(13), 2453–2461. doi:10.1016/0009-2509(93)81066-5
  • Sezerman, U. (1993). Toward computational determination of peptide-receptor structure. Protein Science, 2(11), 1827–1843. doi:10.1002/pro.5560021105
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  • Figge, J. (1993). The binding domain structure of retinoblastoma-binding proteins. Protein Science, 2(2), 155–164. doi:10.1002/pro.5560020204
  • Vajda, Sandor. (1992). Parametric sensitivity and self-similarity in thermal explosion theory. Chemical Engineering Science, 47(5), 1063–1078. doi:10.1016/0009-2509(92)80232-2
  • Jafri. (1992). A membrane model for cytosolic calcium oscillations. A study using Xenopus oocytes. Biophysical Journal, 63(1), 235–246. doi:10.1016/S0006-3495(92)81583-7
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  • Vajda, Sandor, Kataoka, R., DeLisi, C., Margalit, H., Berzofsky, J. A., & Cornette, J. L. (1990). Molecular Structure and Vaccine Design. Annual Review of Biophysics and Biophysical Chemistry, 19(1), 69–82. doi:10.1146/
  • Vajda, Sandor. (1990). Determining minimum energy conformations of polypeptides by dynamic programming. Biopolymers, 29(14), 1755–1772. doi:10.1002/bip.360291408
  • Chappell, M. (1990). Global identifiability of the parameters of nonlinear systems with specified inputs: A comparison of methods. Mathematical Biosciences, 102(1), 41–73. doi:10.1016/0025-5564(90)90055-4
  • Vajda, Sandor. (1989b). Parameter space boundaries for unidentifiable compartmental models. Mathematical Biosciences, 97(1), 27–60. doi:10.1016/0025-5564(89)90042-4
  • Vajda, Sandor. (1989a). Similarity transformation approach to identifiability analysis of nonlinear compartmental models. Mathematical Biosciences, 93(2), 217–248. doi:10.1016/0025-5564(89)90024-2
  • Vajda. (1989). State isomorphism approach to global identifiability of nonlinear systems. IEEE Transactions on Automatic Control, 34(2), 220–223. doi:10.1109/9.21105
  • VAJDA. (1989). QUALITATIVE AND QUANTITATIVE IDENTIFIABILITY ANALYSIS OF NONLINEAR CHEMICAL KINETIC MODELS. Chemical Engineering Communications, 83(1), 191–219. doi:10.1080/00986448908940662
  • Turányi. (1989). Reaction rate analysis of complex kinetic systems. International Journal of Chemical Kinetics, 21(2), 83–99. doi:10.1002/kin.550210203
  • Vajda, Sandor. (1988). Numerical deconvolution using system identification methods. Journal of Pharmacokinetics and Biopharmaceutics, 16(1), 85–107. doi:10.1007/BF01061863
  • Vajda. (1988). Identifiability and distinguishability of first-order reaction systems. The Journal of Physical Chemistry, 92(3), 701–707. doi:10.1021/j100314a024
  • Vajda. (1985). Principal component analysis of kinetic models. International Journal of Chemical Kinetics, 17(1), 55–81. doi:10.1002/kin.550170107
  • Vajda, Sàndor. (1984). Structural equivalence and exhaustive compartmental modeling. Mathematical Biosciences, 69(1), 57–75. doi:10.1016/0025-5564(84)90014-2
  • Vajda, Sandor. (1984). Analysis of unique structural identifiability via submodels. Mathematical Biosciences, 71(2), 125–146. doi:10.1016/0025-5564(84)90023-3
  • Vajda. (1982). Further comments on “On parameter and structural identifiability: Nonunique observability/reconstructibility for identifiable systems, other ambiguities, and new definitions” IEEE Transactions on Automatic Control, 27(5), 1136–1137. doi:10.1109/TAC.1982.1103062
  • Vajda, Sándor. (1981). Structural equivalence of linear systems and compartmental models. Mathematical Biosciences, 55(1-2), 39–64. doi:10.1016/0025-5564(81)90012-2
  • Vajda. (1979). Comments on “Structural identifiability in linear time-invariant systems. IEEE Transactions on Automatic Control, 24(3), 495–496. doi:10.1109/TAC.1979.1102029