Publications

2017

  • Kozakov, D. (2017). The ClusPro web server for protein–protein docking.  Nature Protocols. doi:10.1038/nprot.2016.169
  • Yueh, C. (2017). ClusPro-DC: Dimer Classification by the Cluspro Server for Protein–Protein Docking. Journal of Molecular Biology. doi: 10.1016/j.jmb.2016.10.019

2016

  • 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
  • Bohnuud, T. (2016). A benchmark testing ground for integrating homology modeling and protein docking. Proteins: Structure, Function, and Bioinformatics. doi: 10.1002/prot.25063
  • Whitty, A. (2016). Quantifying the chameleonic properties of macrocycles and other high-molecular-weight drugs. Drug Discovery Today. doi: 10.1016/j.drudis.2016.02.005
  • Mamonov, A. (2016). Focused grid-based resampling for protein docking and mapping. Journal of Computational Chemistry. doi: 10.1002/jcc.24273
  • Xia, B. (2016). Accounting for pairwise distance restraints in FFT-based protein–protein docking. Bioinformatics. doi: 10.1093/bioinformatics/btw306

2015

  • Vajda, S. (2015). Fragments and hot spots in drug discovery. Oncotarget. doi: 0.18632/oncotarget.4968
  • Kozakov, D. (2015). The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins. Nature Protocols. doi:10.1038/nprot.2015.043
  • Lukose, V. (2015). Conservation and covariance in small bacterial phosphoglycosyltransferases identify the functional catalytic core. Biochemistry. doi:10.1021/acs.biochem.5b01086
  • Hall, D. (2015). Lessons from hot spot analysis for fragment-based drug discovery. Trends in Pharmacological Sciences. doi: 10.1016/j.tips.2015.08.003
  • Kozakov, D. (2015) New frontiers in druggability. Journal of Medicinal Chemistry. doi: 10.1021/acs.jmedchem.5b00586
  • Xia, B. (2015). Accounting for observed small angle X-ray scattering profile in the protein-protein docking server cluspro. Journal of Computational Chemistry. doi: 10.1002/jcc.23952
  • Mirzaei, H. (2015). Energy Minimization on Manifolds for Docking Flexible Molecules. Journal of Chemical Theory and Computation. doi: 10.1021/ct500155t
  • Moghadasi, M. (2015). The Impact of Side-Chain Packing on Protein Docking Refinement. Journal of Chemical Information and Modeling. doi: 10.1021/ci500380a
  • 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

2014

  • Villar, E. (2014).  How proteins bind macrocycles. Nature Chemical Biology.  doi: 10.1038/nchembio.1584
  • Shin, U. (2014). Stimulators of translation identified during a small molecule screening campaign. Analytical Biochemistry. doi: 10.1016/j.ab.2013.10.026
  • Bohnuud, T. (2014). Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces. doi:10.1371/journal.pcbi.1003872
  • Chowdhury, R. (2014). Efficient maintenance and update of nonbonded lists in macromolecular simulations. Journal of Chemical Theory and Computation. doi: 10.1021/ct400474w
  • Mottarella, S. (2014). Docking server for the identification of heparin binding sites on proteins. Journal of Chemical Information and Modeling. doi: 10.1021/ci500115j
  • Bogorad, A. (2014). Insights into the architecture of the eIF2Bα/β/γ regulatory subcomplex. Biochemistry. doi:10.1021/bi500346u
  • Kozakov, D. (2014). Encounter complexes and dimensionality reduction in protein protein association. eLife. doi: 10.7554/eLife.01370.001
  • Vakili, P. (2014). Optimization on the space of rigid and flexible motions: an alternative manifold optimization approach. 53rd IEEE Conference on Decision and Control.

2013

  • Moretti, R. (2013). Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions. Proteins: Structure, Function, and Bioinformatics. doi:10.1002/prot.24356
  • Lavi, A. (2013). Detection of peptide-binding sites on protein surfaces: The first step toward the modeling and targeting of peptide-mediated interactions. Proteins: Structure, Function, and Bioinformatics. doi:doi/10.1002/prot.24422
  • Kozakov, D. (2013). How good is automated protein docking? Proteins: Structure, Function, and Bioinformatics. doi:10.1002/prot.24403
  • Vajda, S. (2013). Sampling and scoring: A marriage made in heaven. Proteins: Structure, Function, and Bioinformatics. doi:10.1002/prot.24343
  • Grove, L. (2013). FTFlex: Accounting for binding site flexibility to improve fragment-based identification of druggable hot spots. Bioinformatics. doi:10.1093/bioinformatics/btt102
  • Golden, M. (2013). Comprehensive Experimental and Computational Analysis of Binding Energy Hot Spots at the NF-κB Essential Modulator (NEMO)/IKKβ Protein-Protein Interface. Journal of the American Chemical Society, 130318121200001. doi:10.1021/ja400914z

2012

  • Zerbe, B. (2012). Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein-Protein Interfaces. Journal of chemical information and modeling. doi:10.1021/ci300175u
  • Ngan, C. H. (2012). FTSite: high accuracy detection of ligand binding sites on unbound protein structures. Bioinformatics, 28(2), 286–287. doi:10.1093/bioinformatics/btr651
  • Ngan. (2012). FTMAP: extended protein mapping with user-selected probe molecules. Nucleic Acids Research, 40(W1), W271 – W275. doi:10.1093/nar/gks441
  • Mirzaei, H. (2012). Rigid Body Energy Minimization on Manifolds for Molecular Docking. Journal of Chemical Theory and Computation, 120821123549006. doi:10.1021/ct300272j
  • Hingtgen, S. (2012). A First-Generation Multi-Functional Cytokine for Simultaneous Optical Tracking and Tumor Therapy. PLoS ONE, 7(7), e40234. doi:10.1371/journal.pone.0040234.g006
  • Hall, D. (2012b). Hot Spot Analysis for Driving the Development of Hits into Leads in Fragment-Based Drug Discovery. Journal of Chemical Information and Modeling, 52(1), 199–209. doi:10.1021/ci200468p
  • Hall, D. (2012a). Methods in Molecular Biology (Vol. 819). New York, NY: Springer New York.
  • Brenke, R. (2012). Application of asymmetric statistical potentials to antibody-protein docking. Bioinformatics, 28(20), 2608–2614. doi:10.1093/bioinformatics/bts493
  • Bohnuud. (2012). Computational mapping reveals dramatic effect of Hoogsteen breathing on duplex DNA reactivity with formaldehyde. Nucleic Acids Research, 40(16), 7644–7652. doi:10.1093/nar/gks519
  • Beglov, D. (2012). Minimal ensembles of side chain conformers for modeling protein-protein interactions. Proteins: Structure, Function, and Bioinformatics, 80(2), 591–601. doi:10.1002/prot.23222

2011

  • 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
  • Cencic, R. (2011b). Reversing chemoresistance by small molecule inhibition of the translation initiation complex eIF4F. Proceedings of the National Academy of Sciences of the United States of America, 108(3). doi:10.1073/pnas.1011477108
  • Cencic. (2011a). Blocking eIF4E-eIF4G Interaction as a Strategy To Impair Coronavirus Replication. Journal of Virology, 85(13), 6381–6389. doi:10.1128/JVI.00078-11
  • Buhrman, G. (2011). Analysis of Binding Site Hot Spots on the Surface of Ras GTPase. Journal of Molecular Biology, 413(4), 773–789. doi:10.1016/j.jmb.2011.09.011

2010

  • 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
  • Chuang, Gwo-Yu. (2010). Domain motion and inter-domain hot spots in a multi-domain enzyme. Protein Science. doi:10.1002/pro.446

2009

  • 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/j.sbi.2009.02.008
  • Schwede, T., Sali, A., Honig, B., Levitt, M., Berman, H., Jones, D., … Wilson, I. (2009). Outcome of a Workshop on Applications of Protein Models in Biomedical Research. Structure, 17(2), 151–159. doi:10.1016/j.str.2008.12.014
  • Ngan, C.-H. (2009). The Structural Basis of Pregnane X Receptor Binding Promiscuity. Biochemistry, 48(48), 11572–11581. doi:10.1021/bi901578n
  • Landon, M. (2009). Detection of ligand binding hot spots on protein surfaces via fragment-based methods: application to DJ-1 and glucocerebrosidase. Journal of Computer-Aided Molecular Design, 23(8), 491–500. doi:10.1007/s10822-009-9283-2
  • Kozakov, D., Thiel, S., Landon, M., Ngan, C. H., Vajda, S., Beglov, D., … Hall, D. (2009). Identification of Druggable Hot Spots on Proteins and in Protein Protein Interfaces. In Computational Protein-Protein Interactions.
  • Chuang, Gwo-Yu. (2009). Binding Hot Spots and Amantadine Orientation in the Influenza A Virus M2 Proton Channel. Biophysical Journal, 97(10), 2846–2853. doi:10.1016/j.bpj.2009.09.004
  • Brenke, R., Kozakov, D., Chuang, G.-Y., Beglov, D., Hall, D., Landon, M., … Vajda, S. (2009). Fragment-based identification of druggable “hot spots” of proteins using Fourier domain correlation techniques. Bioinformatics, 25(5), 621–627. doi:10.1093/bioinformatics/btp036
  • Beglov, D. (2009). Structural insights into recognition of β2-glycoprotein I by the lipoprotein receptors. Proteins: Structure, Function, and Bioinformatics, 77(4), 940–949. doi:10.1002/prot.22519
  • Shen, Y., Paschalidis, I. C., Vakili, P., & Vajda, S. (2008). Protein Docking by the Underestimation of Free Energy Funnels in the Space of Encounter Complexes. PLoS Computational Biology, 4(10), e1000191. doi:10.1371/journal.pcbi.1000191

2008

  • 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
  • Landon, M., Amaro, R., Baron, R., Ngan, C. H., Ozonoff, D., McCammon, A., & Vajda, S. (2008). Novel Druggable Hot Spots in Avian Influenza Neuraminidase H5N1 Revealed by Computational Solvent Mapping of a Reduced and Representative Receptor Ensemble. Chemical Biology & Drug Design, 71(2), 106–116. doi:10.1111/j.1747-0285.2007.00614.x
  • 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
  • Chuang, G.-Y., Kozakov, D., Brenke, R., Comeau, S., & Vajda, S. (2008). DARS (Decoys As the Reference State) Potentials for Protein-Protein Docking. Biophysical Journal, 95(9), 4217–4227. doi:10.1529/biophysj.108.135814

2007

  • 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
  • Shen, Y., Brenke, R., Kozakov, D., Comeau, S., Beglov, D., & Vajda, S. (2007). Docking with PIPER and refinement with SDU in rounds 6–11 of CAPRI. Proteins: Structure, Function, and Bioinformatics, 69(4), 734–742. doi:10.1002/prot.21754
  • 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
  • Paschalidis, I. C., Shen, Y., Vakili, P., & Vajda, S. (2007). SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking. IEEE Transactions on Automatic Control, 52(4), 664–676. doi:10.1109/TAC.2007.894518
  • Landon, M., David R. Lancia, J., Yu, J., Thiel, S., & Vajda, S. (2007). Identification of Hot Spots within Druggable Binding Regions by Computational Solvent Mapping of Proteins. Journal of Medicinal Chemistry, 50(6), 1231–1240. doi:10.1021/jm061134b
  • Comeau, S., Kozakov, D., Brenke, R., Shen, Y., Beglov, D., & Vajda, S. (2007). ClusPro: Performance in CAPRI rounds 6–11 and the new server. Proteins: Structure, Function, and Bioinformatics, 69(4), 781–785. doi:10.1002/prot.21795
  • Aslan, F., Yu, Y., Vajda, S., Mohr, S., & Cantor, C. (2007). Engineering a novel, stable dimeric streptavidin with lower isoelectric point. Journal of Biotechnology, 128(2), 213–225. doi:10.1016/j.jbiotec.2006.08.014

2006

  • Vajda, Sandor, & Guarnieri, F. (2006). Characterization of protein-ligand interaction sites using experimental and computational methods. Current Opinion in Drug Discovery and Development, 9(3), 363–369.
  • Vajda, Sandor. (2006b). Classification of protein complexes based on the biophysics of association.
  • Vajda, Sandor. (2006a). Computational Mapping of Proteins for Fragment Based Drug Design.
  • Silberstein, M., Landon, M., Wang, Y., Perl, A., & Vajda, S. (2006). Computational methods for functional site identification suggest a substrate access channel in transaldolase. Genome Informatics, 17(1), 13–22.
  • Paschalidis, I., Shen, Y., Vakili, P., & Vajda, S. (2006). Protein Docking by Exploiting Multi-dimensional Energy Funnels.
  • Paschalidis, I. C., Shen, Y., Vakili, P., & Vajda, S. (2006). Protein-protein docking with reduced potentials by exploiting multi-dimensional energy funnels. Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5330–5333. doi:10.1109/IEMBS.2006.260790
  • Landon, M., Yu, J., Thiel, S., David R. Lancia, J., & Vajda, S. (2006). Identification of “Hot Spots” in Druggable Binding Pockets by Computational Solvent Mapping of Proteins.
  • 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
  • Kozakov, D., Brenke, R., Comeau, S., & Vajda, S. (2006). PIPER: An FFT-based protein docking program with pairwise potentials. Proteins: Structure, Function, and Bioinformatics, 65(2), 392–406. doi:10.1002/prot.21117
  • 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

2005

  • 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
  • Sheu, S.-H., Kaya, T., Waxman, D., & Vajda, S. (2005). Exploring the Binding Site Structure of the PPARγ Ligand-Binding Domain by Computational Solvent Mapping. Biochemistry, 44(4), 1193–1209. doi:10.1021/bi048032c
  • Kozakov, D., Clodfelter, K., Vajda, S., & Camacho, C. (2005b). Optimal Clustering for Detecting Near-Native Conformation in Protein Docking.
  • Kozakov, D., Clodfelter, K., Vajda, S., & Camacho, C. (2005a). Optimal Clustering for Detecting Near-Native Conformations in Protein Docking. Biophysical Journal, 89(2), 867–875. doi:10.1529/biophysj.104.058768
  • Comeau, S., Vajda, S., & Camacho, C. (2005). Performance of the first protein docking server ClusPro in CAPRI rounds 3-5. Proteins: Structure, Function, and Bioinformatics, 60(2), 239–244. doi:10.1002/prot.20564
  • Comeau, S., & Camacho, C. (2005). Predicting oligomeric assemblies: N-mers a primer. Journal of Structural Biology, 150(3), 233–244. doi:10.1016/j.jsb.2005.03.006

2004

  • 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
  • Sheu, S.-H., David R. Lancia, J., Clodfelter, K., Landon, M., & Vajda, S. (2004). PRECISE: a Database of Predicted and Consensus Interaction Sites in Enzymes. Nucleic Acids Research, 33(Database), D206 – D211. doi:10.1093/nar/gki091
  • Rajamani, D., Thiel, S., Vajda, S., & Camacho, C. (2004). Anchor residues in protein-protein interactions. Proceedings of the National Academy of Sciences, 101(31), 11287–11292. doi:10.1073/pnas.0401942101
  • Prasad, J., Vajda, S., & Camacho, C. (2004). Consensus alignment server for reliable comparative modeling with distant templates. Nucleic Acids Research, 32(Web Server), W50 – W54. doi:10.1093/nar/gkh456
  • Comeau, S., Gatchell, D., Vajda, S., & Camacho, C. (2004b). ClusPro: a fully automated algorithm for protein-protein docking. Nucleic Acids Research, 32(Web Server), W96 – W99. doi:10.1093/nar/gkh354
  • Comeau, S., Gatchell, D., Vajda, S., & Camacho, C. (2004a). ClusPro: an automated docking and discrimination method for the prediction of protein complexes. Bioinformatics, 20(1), 45–50. doi:10.1093/bioinformatics/btg371

2003

  • 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
  • Kortvelyesi, T., Silberstein, M., Dennis, S., & Vajda, S. (2003). Improved mapping of protein binding sites. Journal of Computer-Aided Molecular Design, 17(2/4), 173–186. doi:10.1023/A:1025369923311
  • Kortvelyesi, T., Dennis, S., Silberstein, M., Brown, L., & Vajda, S. (2003). Algorithms for computational solvent mapping of proteins. Proteins: Structure, Function, and Genetics, 51(3), 340–351. doi:10.1002/prot.10287
  • Janin, J., Henrick, K., Moult, J., Eyck, L. T., Sternberg, M., Vajda, S., … Wodak, S. (2003). CAPRI: A Critical Assessment of PRedicted Interactions. Proteins: Structure, Function, and Genetics, 52(1), 2–9. doi:10.1002/prot.10381
  • Camacho, C., & Gatchell, D. (2003). Successful discrimination of protein interactions. Proteins: Structure, Function, and Genetics, 52(1), 92–97. doi:10.1002/prot.10394

2002

  • 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
  • Vajda, Sandor, Vakser, I., Sternberg, M., & Janin, J. (2002). Modeling of protein interactions in genomes. Proteins: Structure, Function, and Genetics, 47(4), 444–446. doi:10.1002/prot.10112
  • Dennis, S., & Vajda, S. (2002). Semiglobal simplex optimization and its application to determining the preferred solvation sites of proteins. Journal of Computational Chemistry, 23(3), 319–334. doi:10.1002/jcc.10026
  • 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
  • Camacho, C., & Vajda, S. (2002). Protein–protein association kinetics and protein docking. Current Opinion in Structural Biology, 12(1), 36–40. doi:10.1016/S0959-440X(02)00286-5

2001

  • 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
  • Camacho, C., & Vajda, S. (2001b). Protein docking along smooth association pathways. Proceedings of the National Academy of Sciences, 98(19), 10636–10641. doi:10.1073/pnas.181147798
  • Camacho, C., & Vajda, S. (2001a). Thermodynamic maps of receptor-ligand pairs reveal how some proteins bind. In Drug-Receptor Thermodynamics (pp. 581–592). NY: Wiley.

2000-

  • Gatchell, D., Dennis, S., & Vajda, S. (2000). Discrimination of near-native protein structures from misfolded models by empirical free energy functions. Proteins: Structure, Function, and Genetics, 41(4), 518–534. doi:10.1002/1097-0134(20001201)41:4<518::AID-PROT90>3.0.CO;2-6
  • Dennis, S., Camacho, C., & Vajda, S. (2000b). Continuum electrostatic analysis of preferred solvation sites around proteins in solution. Proteins: Structure, Function, and Genetics, 38(2), 176–188. doi:10.1002/(SICI)1097-0134(20000201)38:2<176::AID-PROT6>3.0.CO;2-O
  • Dennis, S., Camacho, C., & Vajda, S. (2000a). Exploring potential solvation sites of proteins by multistart local minimization. In Optimization in Computational Chemistry and Molecular Biology (pp. 243–261). Kluwer Academic.
  • Camacho, C., Kimura, R., DeLisi, C., & Vajda, S. (2000). Kinetics of Desolvation-Mediated Protein–Protein Binding. Biophysical Journal, 78(3), 1094–1105. doi:10.1016/S0006-3495(00)76668-9
  • Camacho, C., Gatchell, D., Kimura, R., & Vajda, S. (2000). Scoring docked conformations generated by rigid-body protein-protein docking. Proteins: Structure, Function, and Genetics, 40(3), 525–537. doi:10.1002/1097-0134(20000815)40:3<525::AID-PROT190>3.0.CO;2-F
  • Esposito, M., Venkatesh, V., Otvos, L., Weng, Z., Vajda, S., Banki, K., & Perl, A. (1999). Human Transaldolase and Cross-Reactive Viral Epitopes Identified by Autoantibodies of Multiple Sclerosis Patients. The Journal of Immunology, 163, 4027–4032.
  • DeLisi, C., & Vajda, S. (1999). Computational problems in cell biology. Computing in Science & Engineering, 1(3), 26–32. doi:10.1109/5992.764213
  • Camacho, C., Weng, Z., Vajda, S., & DeLisi, C. (1999). Free Energy Landscapes of Encounter Complexes in Protein-Protein Association. Biophysical Journal, 76(3), 1166–1178. doi:10.1016/S0006-3495(99)77281-4
  • Zhang, C., Brower, R., Kimura, R., Weng, Z., Vajda, S., & DeLisi, C. (1998). The waters of life. Journal of the Franklin Institute, 335(2), 213–240. doi:10.1016/S0016-0032(97)00020-3
  • Vajda, Sandor. (1998). Conformational Analysis. In Encyclopedia of Computational Chemistry. Chichester: John Wiley & Sons Ltd.
  • Sano, T., Vajda, S., & Cantor, C. (1998). Genetic engineering of streptavidin, a versatile affinity tag. Journal of Chromatography B: Biomedical Sciences and Applications, 715(1), 85–91. doi:10.1016/S0378-4347(98)00316-8
  • Reznik, G., Vajda, S., Sano, T., & Cantor, C. (1998). A streptavidin mutant with altered ligand-binding specificity. Proceedings of the National Academy of Sciences, 95(23), 13525–13530.
  • Janardhan, A., & Vajda, S. (1998). Selecting near-native conformations in homology modeling: The role of molecular mechanics and solvation terms. Protein Science, 7(8), 1772–1780. doi:10.1002/pro.5560070812
  • Weng, Z., DeLisi, C., & Vajda, S. (1997). Empirical free energy calculation: Comparison to calorimetric data. Protein Science, 6(9), 1976–1984. doi:10.1002/pro.5560060918
  • Vajda, Sandor, Sippl, M., & Novotny, J. (1997). Empirical potentials and functions for protein folding and binding. Current Opinion in Structural Biology, 7(2), 222–228. doi:10.1016/S0959-440X(97)80029-2
  • Sano, T., Vajda, S., Smith, C., & Cantor, C. (1997). Engineering subunit association of multisubunit proteins: A dimeric streptavidin. Proceedings of the National Academy of Sciences, 94(12), 6153–6158.
  • Weng, Z., Vajda, S., & DeLisi, C. (1996). Prediction of protein complexes using empirical free energy functions. Protein Science, 5, 614–626. doi:10.1002/pro.5560050406
  • Sezerman, U., Vajda, S., & DeLisi, C. (1996). Free energy mapping of class I MHC molecules and structural determination of bound peptides. Protein Science, 5(7), 1272–1281. doi:10.1002/pro.5560050706
  • Sano, T., Vajda, S., Reznik, G., Smith, C., & Cantor, C. (1996). Molecular Engineering of Streptavidin. Annals of the New York Academy of Sciences, 799(Enzyme Eng), 383–390. doi:10.1111/j.1749-6632.1996.tb33229.x
  • Reznik, G. (1996). Streptavidins with intersubunit crosslinks have enhanced stability. Nature Biotechnology, 14(8), 1007–1011. doi:10.1038/nbt0896-1007
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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/annurev.bb.24.060195.003333
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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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  • 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/annurev.bb.19.060190.000441
  • 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