Computational approaches for predicting mutant protein stability

Tokuriki N, Stricher F, Serrano L, Tawfik DS (2008) How protein stability and new functions trade off. PLoSComput Biol 4:e1000002 Luo P, Hayes RJ, Chan C, Stark DM, Hwang MY, Jacinto JM, Juvvadi P, Chung HS, Kundu A, Ary ML, Bassil I (2002) Dahiyat development of a cytokine analog with enhanced stability using computational ultrahigh throughput screening. Protein Sci 11:1218–1226 Hartl FU, Bracher A, Hayer-Hartl M (2011) Molecular chaperones in protein folding and proteostasis. Nature 475:324–332 Tokuriki N, Tawfik DS (2009) Chaperonin overexpression promotes genetic variation and enzyme evolution. Nature 459:668–673 Yue P, Li Z, Moult J (2005) Loss of protein structure stability as a major causative factor in monogenic disease. J Mol Biol 353:459–473 Lehmann M, Wyss M (2001) Engineering proteins for thermostability: the use of sequence alignments versus rational design and directed evolution. Curr Opin Biotechnol 12:371–375 Yang DF, Wei YT, Huang RB (2007) Computer-aided design of the stability of pyruvate formate-lyase from Escherichia coli by site-directed mutagenesis. Biosci Biotechnol Biochem 71:746–753 Parthiban V, Gromiha MM, Schomburg D (2006) CUPSAT: prediction of protein stability upon point mutations. Nucleic Acids Res 34((Web Server issue)):W239–W242 Foot E, Kleyn D, Foster PE (2010) Pharmacogenetics-pivotal to the future of the biopharmaceutical industry. Drug Discov Today 15:325–327 Dill KA (1990) Dominant forces in protein folding. Biochemistry 29:7133–7155 Pace CN (1990) Conformational stability of globular proteins. Trends Biochem Sci 15:14–17 Ponnuswamy PK, Gromiha MM (1994) On the conformational stability of folded proteins. J Theor Biol 166:63–74 Parthiban V, Gromiha MM, Hoppe C, Schomburg D (2007) Structural analysis and prediction of protein mutant stability using distance and torsion potentials: role of secondary structure and solvent accessibility. Proteins 66:41–52 Bordner AJ, Abagyan RA (2004) Large-scale prediction of protein geometry and stability changes for arbitrary single point mutations. Proteins 57:400–413 Khatun J, Khare SD, Dokholyan NV (2004) Can contact potentials reliably predict stability of proteins? J Mol Biol 336:1223–1238 Capriotti E, Fariselli P, Casadio R (2004) A neural-network-based method for predicting protein stability changes upon single point mutations. Bioinformatics 20:I63–I68 Cheng JL, Randall A, Baldi P (2006) Prediction of protein stability changes for single-site mutations using support vector machines. Proteins 62:1125–1132 Huang LT, Saraboji K, Ho SY, Hwang SF, Ponnuswamy MN, Gromiha MM (2006) Prediction of protein mutant stability using classification and regression tool. Biophys Chem 125:462–470 Saraboji K, Gromiha MM, Ponnuswamy MN (2005) Relative importance of secondary structure and solvent accessibility to the stability of protein mutants: a case study with amino acid properties and energetics on T4 and human lysozymes. Comput Biol Chem 29:25–35 Saraboji K, Gromiha MM, Ponnuswamy MN (2006) Average assignment method for predicting the stability of protein mutants. Biopolymers 82:80–92 Kamath U, De Jong K, Shehu A (2014) Effective automated feature construction and selection for classification of biological sequences. PLoS One 9:e99982 Kawabata T, Ota M, Nishikawa K (1999) The protein mutant database. Nucleic Acids Res 27:355–357 Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 29:308–311 Fredman D, Siegfried M, Yuan YP, Bork P, Lehväslaiho H, Brookes AJ (2002) HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources. Nucleic Acids Res 30:387–391 Kumar MD, Bava KA, Gromiha MM, Parabakaran P, Kitajima K, Uedaira H, Sarai A (2006) ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions. Nuleic Acids Res 34:D204–D206 Lee PH, Shatkay H (2008) F-SNP: computationally predicted functional SNPs for disease association studies. Nucleic Acids Res 36:D820–D824 Cooper DN, Krawczak M, Polychronakos C, Tyler-Smith C, Kehrer-Sawatzki H (2013) Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease. Hum Genet 132:1077–1130 Liu X, Jian X, Boerwinkle E (2013) dbNSFP v2.0: a database of human non-synonymous SNPs and their functional predictions and annotations. Hum Mutat 34:E2393–E2402 Forbes SA, Beare D, Gunasekaran P, Leung K, Bindal N, Boutselakis H, Ding M, Bamford S, Cole C, Ward S, Kok CY, Jia M, De J, Teague JW, Stratton MR, McDermott U, Campbell PJ (2014) COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res 43:D805–D811 UniProt Consortium (2015) UniProt: a hub for protein information. Nucl. Acids Res 43((Database issue)):D204–D212 Shaw CA, Campbell IM (2015) Variant interpretation through Bayesian fusion of frequency and genomic knowledge. Genome Med 7:4 Bava KA, Gromiha MM, Uedaira H, Kitajima K, Sarai A (2004) ProTherm, version 4.0: thermodynamic database for proteins and mutants. Nucleic Acids Res 32:D120–D121 Bao L, Zhou M, Cui Y (2005) nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms. Nucleic Acids Res 33:W480–W482 Mi H, Lazareva-Ulitsky B, Loo R, Kejariwal A, Vandergriff J, Rabkin S, Guo N, Muruganujan A, Doremieux O, Campbell MJ, Kitano H, Thomas PD (2005) The PANTHER database of protein families, subfamilies, functions and pathways. Nucleic Acids Res 33:D284–D288 Capriotti E, Calabrese R, Casadio R (2006) Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics 22:2729–2734 Yue P, Melamud E, Moult J (2006) SNPs3D: candidate gene and SNP selection for association studies. BMC Bioinform 7:166 Mathe E, Olivier M, Kato S, Ishioka C, Hainaut P, Tavtigian SV (2006) Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods. Nucleic Acids Res 34:1317–1325 Huang LT, Gromiha MM, Ho SY, Ho SY (2007) Sequence analysis and rule development of predicting protein stability change upon mutation using decision tree model. J Mol Model 13:879–890 Yin S, Ding F, Dokholyan NV (2007) Eris: an automated estimator of protein stability. Nat Methods 4:466–467 Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4:1073–1081 Venselaar H, te BeekG TAH, Kuipers RKP, Hekkelman ML, Vriend G (2010) Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. BMC Bioinform 11:548 Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR (2010) A method and server for predicting damaging missense mutations. Nat Methods 7:248–249 Masso M, Vaisman II (2011) A structure-based computational mutagenesis elucidates the spectrum of stability-activity relationships in proteins. Conf Proc IEEE Eng Med Biol Soc 2011:3225–3228 Masso M, Vaisman II (2014) AUTO-MUTE 2.0: a portable framework with enhanced capabilities for predicting protein functional consequences upon mutation. Adv Bioinform http://dx.doi.org/10.1155/2014/278385 Reva B, Antipin Y, Sander C (2011) Predicting the functional impact of protein mutations: applications to cancer genomics. Nucleic Acids Res 39:e118 Wainreb G, Wolf L, Ashkenazy H, Dehouck Y, Ben-Tal N (2011) Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site. Bioinformatics 27:3286–3292 González-Pérez A, López-Bigas N (2011) Improving the assessment of the outcome of nonsynonymous SNPs with a consensus deleteriousness score, Condel. Am J Hum Genet 88:440–449 Gonnelli G, Rooman M, Dehouck Y (2012) Structure-based mutant stability predictions on proteins of unknown structure. J Biotechnol 161:287–293 Choi Y, Sims GE, Murphy S, Miller JR, Chan AP (2012) Predicting the functional effect of amino acid substitutions and indels. PLoS One 7:e46688 Chen CW, Lin J, Chu YW (2013) iStable: off-the-shelf predictor integration for predicting protein stability changes. BMC Bioinform 14(Suppl 2):S5 Capriotti E, Altman RB, Bromberg Y (2013) Collective judgment predicts disease-associated single nucleotide variants, mutations in proteins. BMC Genom 14(suppl 3):S2 Pires DEV, Ascher DV, Blundell TL (2014) DUET: a server for predicting effects of mutations on protein stability via an integrated computational approach. Nucleic Acids Res 42(W1):W314–W319 Suplatov D, Shalaeva D, Kirilin E, Arzhanik V, Švedas V (2014) Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity. J Biomol Struct Dyn 32:75–87 Powers ET, Morimoto RI, Dillin A, Kelly JW, Balch WE (2009) Biological and chemical approaches to diseases of proteostasis deficiency. Annu Rev Biochem 78:959–991 Baets GD, Durme JV, Reumers J, Maurer-Stroh S, Vanhee P, Dopazo J, Schymkowitz J, Rousseau F (2012) SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants. Nucleic Acids Res 40((Database issue)):D935–D939 Han JH, Batey S, Nickson AA, Teichmann SA, Clarke J (2007) The folding and evolution of multidomain proteins. Nat Rev Mol Cell Biol 8:319–330 Ng PC, Henikoff S (2006) Predicting the effects of amino acid substitutions on protein function. Annu Rev Genom Hum Genet 7:61–80 Ng PC, Henikoff S (2002) Accounting for human polymorphisms predicted to affect protein function. Genom Res 12:436–446 Flanagan SE, Patch AM, Ellard S (2010) Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet Test Mol Biomark 14:533–537 Tian J, Wu N, Guo X, Guo J, Zhang J, Fan Y (2007) Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines. BMC Bioinform 8:450 Cheng G, Qian B, Samudrala R, Baker D (2005) Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design. Nucleic Acids Res 33:5861–5867 Dehouck Y, Grosfils A, Folch B, Gilis D, Bogaerts P, Rooman M (2009) Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0. Bioinformatics 25:2537–2543 Johnston MA, Sondergaard C, Nielsen JE (2011) Integrated prediction of the effect of mutations on multiple protein characteristics. Proteins 79:165–178 Bromberg Y, Rost B (2007) SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res 35:3823–3835 Dehouck Y, Kwasigroch MJ, Gilis D, Rooman M (2011) PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC Bioinform 12:151 Castellana S, Mazza T (2013) Congruency in the prediction of pathogenic missense mutations: state-of-the-art web-based tools. Brief Bioinform 14:448–459 Kono TJY, Seth K, Poland JA, Morrell PL (2014) SNPMeta: SNP annotation and SNP metadata collection without a reference genome. Mol Ecol Resour 14:419–425 Potapov V, Cohen M, Schreiber G (2009) Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details. Protein Eng Des Sel 22:553–560 Topham CM, Srinivasan N, Blundell TL (1997) Prediction of protein mutants based on structural environment-dependent amino acid substitution and propensity tables. Protein Eng 10:7–21 Folkman L, Stantic B, Sattar A (2013) Sequence-only evolutionary and predicted structural features for the prediction of stability changes in protein mutants. BMC Bioinform 14(Suppl 2):1 Capriotti E, Fariselli P, Casadio R (2005) I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res 33((Web Server issue)):W306–W310 Kumar S, Sanderford M, Gray VE (2012) Evolutionary diagnosis method for variants in personal exomes. Nat Methods 9:855–856 Bendl J, Stourac J, Salanda O, Pavelka A, Wieben ED, Zendulka J, Brezovsky J, Damborsky J (2014) PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations. PLoS Comput Biol 10:e1003440 Dunbrack RL Jr (2006) Sequence comparison and protein structure prediction. Curr Opin Struct Biol 16:374–384 Giollo M, Martin AJM, Walsh I, Ferrari C, Tosatto SCE (2014) NeEMO: a method using residue interaction networks to improve prediction of protein stability upon mutation. BMC Genom 15(Suppl 4):S7