The Anatomy and Taxonomy of Protein Structure, Adv Protein Chem, vol.34, pp.167-339, 1981. ,
DOI : 10.1016/S0065-3233(08)60520-3
Disulphide bridges in globular proteins, Journal of Molecular Biology, vol.151, issue.2, pp.261-287, 1981. ,
DOI : 10.1016/0022-2836(81)90515-5
Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology, pp.287-295, 2003. ,
Prediction of the bonding states of cysteines Using the support vector machines based on multiple feature vectors and cysteine state sequences, Proteins: Structure, Function, and Bioinformatics, vol.99, issue.4, pp.1036-1042, 2004. ,
DOI : 10.1073/pnas.252633099
Role of evolutionary information in predicting the disulfide-bonding state of cysteine in proteins, Proteins: Structure, Function, and Genetics, vol.55, issue.3, pp.340-346, 1999. ,
DOI : 10.1103/PhysRevE.55.811
Different sequence environments of cysteines and half cystines in proteins Application to predict disulfide forming residues, FEBS Letters, vol.335, issue.2, pp.117-120, 1992. ,
DOI : 10.1038/335045a0
URL : http://onlinelibrary.wiley.com/doi/10.1016/0014-5793(92)80419-H/pdf
Predicting the oxidation state of cysteines by multiple sequence alignment, Bioinformatics, vol.16, issue.3, pp.251-256, 2000. ,
DOI : 10.1093/bioinformatics/16.3.251
URL : https://academic.oup.com/bioinformatics/article-pdf/16/3/251/681766/160251.pdf
Predicting Redox State of Cysteines in Proteins, Methods Enzymol, vol.353, pp.10-21, 2002. ,
DOI : 10.1016/S0076-6879(02)53032-9
A Two-Stage SVM Architecture for Predicting the Disulfide Bonding State of Cysteines. IEEE NNSP International Workshop: special session on signal processing and neural networks for bionformatics, 2002. ,
DOI : 10.1109/nnsp.2002.1030014
URL : http://www-dsi.dsi.unifi.it/~paolo/ps/NNSP-02-cysteines.pdf
Prediction of disulfide-bonded cysteines in proteomes with a hidden neural network, PROTEOMICS, vol.4, issue.6, pp.1665-1671, 2004. ,
DOI : 10.1002/pmic.200300745
Prediction of the disulfide bonding state of cysteines in proteins with hidden neural networks, Protein Engineering, Design and Selection, vol.15, issue.12, pp.951-953, 2002. ,
DOI : 10.1021/bi992922o
Prediction of the disulfide-bonding state of cysteines in proteins at 88% accuracy, Protein Science, vol.98, issue.(Suppl.1), pp.2735-2739, 2002. ,
DOI : 10.1073/pnas.041615798
Predicting the disulfide bonding state of cysteines using protein descriptors, Proteins: Structure, Function, and Bioinformatics, vol.264, issue.3, pp.243-249, 2002. ,
DOI : 10.1006/jmbi.1996.0664
Prediction of the disulfide-bonding state of cysteine in proteins, "Protein Engineering, Design and Selection", vol.3, issue.8, pp.667-672, 1990. ,
DOI : 10.1093/protein/3.8.667
Learning to discriminate between ligand-bound and disulfide-bound cysteines, Protein Engineering Design and Selection, vol.17, issue.4, pp.367-373, 2004. ,
DOI : 10.1093/protein/gzh042
URL : https://academic.oup.com/peds/article-pdf/17/4/367/4694446/gzh042.pdf
Prediction of the disulfide-bonding state of cysteines in proteins based on dipeptide composition, Biochemical and Biophysical Research Communications, vol.318, issue.1, pp.142-147, 2004. ,
DOI : 10.1016/j.bbrc.2004.03.189
13C NMR chemical shifts can predict disulfide bond formation, Journal of Biomolecular NMR, vol.18, issue.2, pp.165-171, 2000. ,
DOI : 10.1023/A:1008398416292
Prediction of disulfide connectivity in proteins, Bioinformatics, vol.17, issue.10, pp.957-964, 2001. ,
DOI : 10.1093/bioinformatics/17.10.957
URL : https://academic.oup.com/bioinformatics/article-pdf/17/10/957/698296/170957.pdf
Disulfide connectivity prediction using secondary structure information and diresidue frequencies, Bioinformatics, vol.9, issue.5, pp.2336-2346, 2005. ,
DOI : 10.1093/bioinformatics/9.5.499
URL : https://academic.oup.com/bioinformatics/article-pdf/21/10/2336/539489/bti328.pdf
DiANNA: a web server for disulfide connectivity prediction, Nucleic Acids Research, vol.33, issue.Web Server, pp.230-232, 2005. ,
DOI : 10.1093/nar/gki412
URL : https://academic.oup.com/nar/article-pdf/33/suppl_2/W230/7622954/gki412.pdf
Improving disulfide connectivity prediction with sequential distance between oxidized cysteines, Bioinformatics, vol.21, issue.8, pp.4416-4419, 2005. ,
DOI : 10.1093/bioinformatics/bti179
URL : https://academic.oup.com/bioinformatics/article-pdf/21/24/4416/432986/bti715.pdf
A recursive connectionist approach for predicting disulfide connectivity in proteins, Proceedings of the 2003 ACM symposium on Applied computing , SAC '03, pp.66-71, 2003. ,
DOI : 10.1145/952532.952550
Disulfide connectivity prediction using recursive neural networks and evolutionary information, Bioinformatics, vol.20, issue.5, pp.653-659, 2004. ,
DOI : 10.1093/bioinformatics/btg463
URL : https://academic.oup.com/bioinformatics/article-pdf/20/5/653/565587/btg463.pdf
Cysteine separations profiles on protein sequences infer disulfide connectivity, Bioinformatics, vol.40, issue.31, pp.1415-1420, 2005. ,
DOI : 10.1021/bi010409g
URL : https://academic.oup.com/bioinformatics/article-pdf/21/8/1415/692448/bti179.pdf
Model building of disulfide bonds in proteins with known three-dimensional structure, "Protein Engineering, Design and Selection", vol.2, issue.2, pp.119-125, 1988. ,
DOI : 10.1093/protein/2.2.119
URL : https://pure.rug.nl/ws/files/3376659/1988ProteinEngHazes.pdf
Stereochemical modeling of disulfide bridges. Criteria for introduction into proteins by site-directed mutagenesis, "Protein Engineering, Design and Selection", vol.3, issue.2, pp.95-103, 1989. ,
DOI : 10.1093/protein/3.2.95
Molecular recognition in protein families: A database of aligned three-dimensional structures of related proteins, Biochemical Society Transactions, vol.21, issue.3, pp.597-604, 1993. ,
DOI : 10.1042/bst0210597
Relationship between protein structures and disulfide-bonding patterns, Proteins: Structure, Function, and Bioinformatics, vol.231, issue.1, pp.1-5, 2003. ,
DOI : 10.1006/jmbi.1993.1334
Protein similarities beyond disulphide bridge topology, Journal of Molecular Biology, vol.284, issue.3, pp.541-548, 1998. ,
DOI : 10.1006/jmbi.1998.2194
What can Disulfide Bonds Tell Us about Protein Energetics, Function and Folding: Simulations and Bioninformatics Analysis, Journal of Molecular Biology, vol.300, issue.4, pp.975-985, 2000. ,
DOI : 10.1006/jmbi.2000.3893
The Nonconsecutive Disulfide Bond of Escherichia coli Phytase (AppA) Renders It Dependent on the Protein-disulfide Isomerase, DsbC, Journal of Biological Chemistry, vol.280, issue.12, pp.11387-11394, 2005. ,
DOI : 10.1074/jbc.M411774200
Disulfide bonds and the stability of globular proteins, Protein Science, vol.32, issue.10, pp.1551-1558, 1993. ,
DOI : 10.1111/j.1399-3011.1990.tb00958.x
URL : http://onlinelibrary.wiley.com/doi/10.1002/pro.5560021002/pdf
The effects of disulfide bonds on the denatured state of barnase, Protein Science, vol.296, issue.12, pp.2394-2404, 2000. ,
DOI : 10.1021/jp964020s
Control of enzyme activity by an engineered disulfide bond, Science, vol.243, issue.4892, pp.792-794, 1989. ,
DOI : 10.1126/science.2916125
[16] Stabilization of functional proteins by introduction of multiple disulfide bonds, Methods Enzymol, vol.202, pp.336-356, 1991. ,
DOI : 10.1016/0076-6879(91)02018-5
Structural Evidence for a Possible Role of Reversible Disulphide Bridge Formation in the Elasticity of the Muscle Protein Titin, Structure, vol.9, issue.4, pp.331-340, 2001. ,
DOI : 10.1016/S0969-2126(01)00591-3
, Biochemistry, vol.39, issue.15, pp.4207-4216, 2000.
DOI : 10.1021/bi992922o
, Biochemistry, vol.40, issue.31, pp.409059-9064, 2001.
DOI : 10.1021/bi010409g
,
Using a Library of Structural Templates to Recognise Catalytic Sites and Explore their Evolution in Homologous Families, Journal of Molecular Biology, vol.347, issue.3, pp.565-581, 2005. ,
DOI : 10.1016/j.jmb.2005.01.044
Intra-A chain disulfide bond (A6-11) of insulin is essential for displaying its activity, Biochem Mol Biol Int, vol.33, issue.6, pp.1049-1053, 1994. ,
Structural effects induced by removal of a disulfide-bridge: the X-ray structure of the C30A/C51A mutant of basic pancreatic trypsin inhibitor at 1.6 ??, "Protein Engineering, Design and Selection", vol.3, issue.7, pp.591-598, 1990. ,
DOI : 10.1093/protein/3.7.591
Effect of the intermolecular disulfide bond on the conformation and stability of glial cell line-derived neurotrophic factor, Protein Engineering, Design and Selection, vol.15, issue.1, pp.59-64, 2002. ,
DOI : 10.1021/bi00391a031
The genealogy of some recently evolved vertebrate proteins, Trends in Biochemical Sciences, vol.10, issue.6, pp.233-237, 1985. ,
DOI : 10.1016/0968-0004(85)90140-9
Genomic evidence that the intracellular proteins of archaeal microbes contain disulfide bonds, Proceedings of the National Academy of Sciences, vol.5, issue.2, pp.999679-9684, 2002. ,
DOI : 10.2741/scan
Reconsideration of an early dogma, saying ???there is no evidence for disulfide bonds in proteins from archaea???, Extremophiles, vol.32, issue.1, pp.29-38, 2008. ,
DOI : 10.1042/bj3151001
Discrimination of Intracellular and Extracellular Proteins Using Amino Acid Composition and Residue-pair Frequencies, Journal of Molecular Biology, vol.238, issue.1, pp.54-61, 1994. ,
DOI : 10.1006/jmbi.1994.1267
Classification of Proteins into Groups Based on Amino Acid Composition and Other Characters. II. Grouping into Four Types, The Journal of Biochemistry, vol.94, issue.3, pp.997-1007, 1983. ,
DOI : 10.1093/oxfordjournals.jbchem.a134443
Analycys: A database for conservation and conformation of disulphide bonds in homologous protein domains, Proteins: Structure, Function, and Bioinformatics, vol.22, issue.90001, pp.255-261, 2007. ,
DOI : 10.1002/prot.21318
URL : https://hal.archives-ouvertes.fr/hal-01198478
The Protein Data Bank, Nucleic Acids Research, vol.28, issue.1, pp.235-242, 2000. ,
DOI : 10.1093/nar/28.1.235
Predicting Subcellular Localization of Proteins Based on their N-terminal Amino Acid Sequence, Journal of Molecular Biology, vol.300, issue.4, pp.1005-1016, 2000. ,
DOI : 10.1006/jmbi.2000.3903
PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization, Trends in Biochemical Sciences, vol.24, issue.1, pp.34-36, 1999. ,
DOI : 10.1016/S0968-0004(98)01336-X
Support vector machine approach for protein subcellular localization prediction, Bioinformatics, vol.17, issue.8, pp.721-728, 2001. ,
DOI : 10.1093/bioinformatics/17.8.721
Multiple protein sequence alignment from tertiary structure comparison: Assignment of global and residue confidence levels, Proteins: Structure, Function, and Genetics, vol.47, issue.2, pp.309-323, 1992. ,
DOI : 10.1107/S0108768191010315
A method to determine heavy-atom positions for virus structures, Acta Crystallographica Section B Structural Crystallography and Crystal Chemistry, vol.32, issue.11, pp.2975-2979, 1976. ,
DOI : 10.1107/S0567740876009394
URL : http://journals.iucr.org/b/issues/1976/11/00/a13751/a13751.pdf
Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features, Biopolymers, vol.33, issue.12, pp.2577-2637, 1983. ,
DOI : 10.1016/0005-2795(73)90350-4
The interpretation of protein structures: Estimation of static accessibility, Journal of Molecular Biology, vol.55, issue.3, pp.379-400, 1971. ,
DOI : 10.1016/0022-2836(71)90324-X
Naccess V2.1.1, Atomic solvent accessible area calculations, 1993. ,
DPX: for the analysis of the protein core, Bioinformatics, vol.19, issue.2, pp.313-314, 2003. ,
DOI : 10.1093/bioinformatics/19.2.313
URL : https://academic.oup.com/bioinformatics/article-pdf/19/2/313/1060165/190313.pdf