Residue Adjacency Matrix Based Feature Engineering for Predicting Cysteine Reactivity in Proteins

Søndergaard, 2011, Improved treatment of ligands and coupling effects in empirical calculation and rationalization of pKa values, J Chem Theory Comput, 7, 2284, 10.1021/ct200133y

Olsson, 2011, PROPKA3: consistent treatment of internal and surface residues in empirical p K a predictions, J Chem Theory Com-putation, 7, 525, 10.1021/ct100578z

Sanchez, 2008, Prediction of reversibly oxidized protein cysteine thiols using protein structure properties, Protein Sci, 17, 473, 10.1110/ps.073252408

Mitternacht, 2016, FreeSASA: An open source C library for solvent accessible surface area calculations, F1000Res, 5, 189, 10.12688/f1000research.7931.1

Altschul, 1990, Basic local alignment search tool, J Mol Biol, 215, 403, 10.1016/S0022-2836(05)80360-2

Sun, 2016, Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features, BMC Bioinform, 17, 316, 10.1186/s12859-016-1185-4

Li, 2005, Very fast empirical prediction and rationalization of protein pKa values, Proteins, 61, 704, 10.1002/prot.20660

Klomsiri, 2011, Cysteine-based redox switches in enzymes, Antioxid Redox Signal, 14, 1065, 10.1089/ars.2010.3376

Murphy, 2012, Mitochondrial thiols in antioxidant protection and redox signaling: distinct roles for glutathionylation and other thiol modifications, Antioxid Redox Signal, 16, 476, 10.1089/ars.2011.4289

Soylu, 2017, Cpipe: a comprehensive computational platform for sequence and structure-based analyses of Cysteine residues, Bioinformatics, 33, 2395, 10.1093/bioinformatics/btx181

Ferrè, 2006, DiANNA 1.1: an extension of the DiANNA web server for ternary cysteine classification, Nucleic Acids Res, 34, W182, 10.1093/nar/gkl189

Ceroni, 2006, DISULFIND: a disulfide bonding state and cysteine connectivity prediction server, Nucleic Acids Res, 34, W177, 10.1093/nar/gkl266

Zhao, 2004, Cysteine separations profiles on protein sequences infer disulfide connectivity, Bioinformatics, 21, 1415, 10.1093/bioinformatics/bti179

Reddie, 2008, Expanding the functional diversity of proteins through cysteine oxidation, Curr Opin Chem Biol, 12, 746, 10.1016/j.cbpa.2008.07.028

Doulias, 2010, Structural profiling of endogenous S-nitrosocysteine residues reveals unique features that accommodate diverse mechanisms for protein S-nitrosylation, Proc Natl Acad Sci, 107, 16958, 10.1073/pnas.1008036107

Roos, 2013, Understanding the pKa of redox cysteines: the key role of hydrogen bonding, Antioxid Redox Signal, 18, 94, 10.1089/ars.2012.4521

Fomenko, 2008, Functional diversity of cysteine residues in proteins and unique features of catalytic redox-active cysteines in thiol oxidoreductases, Mol Cells, 26, 228

Lee, 2010, Prediction of thioredoxin and glutaredoxin target proteins by identifying reversibly oxidized cysteinyl residues, J Integr Bioinform (JIB), 7, 208, 10.1515/jib-2010-130

Zeida, 2014, Thiol redox biochemistry: insights from computer simulations, Biophys Rev, 6, 27, 10.1007/s12551-013-0127-x

Henikoff, 1992, Amino acid substitution matrices from protein blocks, Proc Natl Acad Sci, 89, 10915, 10.1073/pnas.89.22.10915

Smith, 1981, Identification of common molecular subsequences, J Mol Biol, 147, 195, 10.1016/0022-2836(81)90087-5

Stormo, 1982, Use of the Perceptron' algorithm to distinguish translational initiation sites in E. coli, Nucleic Acids Res, 10, 2997, 10.1093/nar/10.9.2997

McGuffin, 2000, The PSIPRED protein structure prediction server, Bioinformatics, 16, 404, 10.1093/bioinformatics/16.4.404

Lin, 2013, iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins, Mol BioSys, 9, 634, 10.1039/c3mb25466f

Luengo, 2012, On the choice of the best imputation methods for missing values considering three groups of classification methods, Knowl Inform Sys, 32, 77, 10.1007/s10115-011-0424-2

Poprac, 2017, Targeting free radicals in oxidative stress-related human diseases, Trends Pharmacol Sci, 38, 592, 10.1016/j.tips.2017.04.005