This work is licensed under the Creative Commons Attribution 4.0 International License.
Levy DE, Darnell JE Jr. Stats: transcriptional control and biological impact. Nat Rev Mol Cell Biol. 2002; 3:651–62.LevyDEDarnellJEJrStats: transcriptional control and biological impactNat Rev Mol Cell Biol.2002365162Search in Google Scholar
Villarino AV, Kanno Y, Ferdinand JR, O’Shea JJ. Mechanisms of Jak/STAT signaling in immunity and disease. J Immunol. 2015; 194:21–7.VillarinoAVKannoYFerdinandJRO’SheaJJMechanisms of Jak/STAT signaling in immunity and diseaseJ Immunol.2015194217Search in Google Scholar
Buettner R, Mora LB, Jove R. Activated STAT signaling in human tumors provides novel molecular targets for therapeutic intervention. Clin Cancer Res. 2002; 8:945–54.BuettnerRMoraLBJoveRActivated STAT signaling in human tumors provides novel molecular targets for therapeutic interventionClin Cancer Res.2002894554Search in Google Scholar
Colomiere M, Ward AC, Riley C, Trenerry MK, Cameron-Smith D, Findlay J, et al. Cross talk of signals between EGFR and IL-6R through JAK2/STAT3 mediate epithelial-mesenchymal transition in ovarian carcinomas. Br J Cancer. 2009; 100:134–44.ColomiereMWardACRileyCTrenerryMKCameron-SmithDFindlayJCross talk of signals between EGFR and IL-6R through JAK2/STAT3 mediate epithelial-mesenchymal transition in ovarian carcinomasBr J Cancer.200910013444Search in Google Scholar
Pawlus MR, Wang L, Hu CJ. STAT3 and HIF1α cooperatively activate HIF1 target genes in MDA-MB-231 and RCC4 cells. Oncogene. 2014; 33:1670–9.PawlusMRWangLHuCJSTAT3 and HIF1α cooperatively activate HIF1 target genes in MDA-MB-231 and RCC4 cellsOncogene.20143316709Search in Google Scholar
Kotkowska A, Sewerynek E, Domańska D, Pastuszak-Lewandoska D, Brzeziańska E. Single nucleotide polymorphisms in the STAT3 gene influence AITD susceptibility, thyroid autoantibody levels, and IL6 and IL17 secretion. Cell Mol Biol Lett. 2015; 20:88–101.KotkowskaASewerynekEDomańskaDPastuszak-LewandoskaDBrzeziańskaESingle nucleotide polymorphisms in the STAT3 gene influence AITD susceptibility, thyroid autoantibody levels, and IL6 and IL17 secretionCell Mol Biol Lett.20152088101Search in Google Scholar
Yuan K, Liu H, Huang L, Ren X, Liu J, Dong X, et al. rs744166 polymorphism of the STAT3 gene is associated with risk of gastric cancer in a Chinese population. Biomed Res Int. 2014; 2014:527918. doi: 10.1155/2014/527918YuanKLiuHHuangLRenXLiuJDongXrs744166 polymorphism of the STAT3 gene is associated with risk of gastric cancer in a Chinese populationBiomed Res Int.2014201452791810.1155/2014/527918Open DOISearch in Google Scholar
Collins FS, Brooks LD, Chakravarti A. A DNA polymorphism discovery resource for research on human genetic variation. Genome Res. 1998; 8:1229–31.CollinsFSBrooksLDChakravartiAA DNA polymorphism discovery resource for research on human genetic variationGenome Res.19988122931Search in Google Scholar
Goswami AM. Structural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3β-hydroxysteroid dehydrogenase type 2. Meta Gene. 2015; 5:162–72.GoswamiAMStructural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3β-hydroxysteroid dehydrogenase type 2Meta Gene.2015516272Search in Google Scholar
Sim N-L, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 2012; 40:W452–7.SimN-LKumarPHuJHenikoffSSchneiderGNgPCSIFT web server: predicting effects of amino acid substitutions on proteinsNucleic Acids Res.201240W4527Search in Google Scholar
Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010; 7:248–9.AdzhubeiIASchmidtSPeshkinLRamenskyVEGerasimovaABorkPA method and server for predicting damaging missense mutationsNat Methods.201072489Search in Google Scholar
Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the functional effect of amino acid substitutions and indels. PLoS One. 2012; 7:e46688. doi: 10.1371/journal.pone.0046688ChoiYSimsGEMurphySMillerJRChanAPPredicting the functional effect of amino acid substitutions and indelsPLoS One.20127e4668810.1371/journal.pone.0046688Open DOISearch in Google Scholar
Thomas PD, Kejariwal A, Guo N, Mi H, Campbell MJ, Muruganujan A, Lazareva-Ulitsky B. Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools. Nucleic Acids Res. 2006; 34(Suppl 2):W645–50.ThomasPDKejariwalAGuoNMiHCampbellMJMuruganujanALazareva-UlitskyBApplications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring toolsNucleic Acids Res.200634Suppl 2W64550Search in Google Scholar
Calabrese R, Capriotti E, Fariselli P, Martelli PL, Casadio R. Functional annotations improve the predictive score of human disease-related mutations in proteins. Hum Mutat. 2009; 30:1237–44.CalabreseRCapriottiEFariselliPMartelliPLCasadioRFunctional annotations improve the predictive score of human disease-related mutations in proteinsHum Mutat.200930123744Search in Google Scholar
Capriotti E, Calabrese R, Casadio R. Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics. 2006; 22:2729–34.CapriottiECalabreseRCasadioRPredicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary informationBioinformatics.200622272934Search in Google Scholar
Capriotti E, Fariselli P, Casadio R. I-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005; 33(Suppl 2):W306–10.CapriottiEFariselliPCasadioRI-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structureNucleic Acids Res.200533Suppl 2W30610Search in Google Scholar
Elkhattabi L, Morjane I, Charoute H, Amghar S, Bouafi H, Elkarhat Z, et al. In silico analysis of coding/noncoding SNPs of human RETN gene and characterization of their impact on resistin stability and structure. J Diabetes Res. 2019; 2019:4951627. doi: 10.1155/2019/4951627ElkhattabiLMorjaneICharouteHAmgharSBouafiHElkarhatZIn silico analysis of coding/noncoding SNPs of human RETN gene and characterization of their impact on resistin stability and structureJ Diabetes Res.20192019495162710.1155/2019/4951627Open DOISearch in Google Scholar
Ashkenazy H, Abadi S, Martz E, Chay O, Mayrose I, Pupko T, Ben-Tal N. ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Res. 2016; 44:W344–50.AshkenazyHAbadiSMartzEChayOMayroseIPupkoTBen-TalNConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromoleculesNucleic Acids Res.201644W34450Search in Google Scholar
Petersen B, Petersen TN, Andersen P, Nielsen M, Lundegaard C. A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Struct Biol. 2009; 9:51. doi: 10.1186/1472-6807-9-51PetersenBPetersenTNAndersenPNielsenMLundegaardCA generic method for assignment of reliability scores applied to solvent accessibility predictionsBMC Struct Biol.200995110.1186/1472-6807-9-51Open DOISearch in Google Scholar
Venselaar H, Te Beek TA, Kuipers RK, Hekkelman ML, Vriend G. Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. BMC Bioinformatics. 2010; 11:548. doi: 10.1186/1471-2105-11-548VenselaarHTe BeekTAKuipersRKHekkelmanMLVriendGProtein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfacesBMC Bioinformatics.20101154810.1186/1471-2105-11-548Open DOISearch in Google Scholar
Geourjon C, Deléage G. SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Comput Appl Biosci. 1995; 11:681–4.GeourjonCDeléageGSOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignmentsComput Appl Biosci.1995116814Search in Google Scholar
Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, et al. The gene MANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010; 38(Suppl 2):W214–20.Warde-FarleyDDonaldsonSLComesOZuberiKBadrawiRChaoPThe gene MANIA prediction server: biological network integration for gene prioritization and predicting gene functionNucleic Acids Res.201038Suppl 2W21420Search in Google Scholar
Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021; 596(7873):583–9.JumperJEvansRPritzelAGreenTFigurnovMRonnebergerOHighly accurate protein structure prediction with AlphaFoldNature.202159678735839Search in Google Scholar
Mariani V, Biasini M, Barbato A, Schwede T. lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests. Bioinformatics. 2013; 29:2722–8.MarianiVBiasiniMBarbatoASchwedeTlDDT: a local superposition-free score for comparing protein structures and models using distance difference testsBioinformatics.20132927228Search in Google Scholar
Pires DE, Ascher DB, Blundell TL. mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics. 2014; 30:335–42.PiresDEAscherDBBlundellTLmCSM: predicting the effects of mutations in proteins using graph-based signaturesBioinformatics.20143033542Search in Google Scholar
Worth CL, Preissner R, Blundell TL. SDM—a server for predicting effects of mutations on protein stability and malfunction. Nucleic Acids Res. 2011; 39(Suppl 2):W215–22.WorthCLPreissnerRBlundellTLSDM—a server for predicting effects of mutations on protein stability and malfunctionNucleic Acids Res.201139Suppl 2W21522Search in Google Scholar
Pires DE, Ascher DB, Blundell TL. DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach. Nucleic Acids Res. 2014; 42(W1): W314–9.PiresDEAscherDBBlundellTLDUET: a server for predicting effects of mutations on protein stability using an integrated computational approachNucleic Acids Res.201442W1W3149Search in Google Scholar
Rozario LT, Sharker T, Nila TA. In silico analysis of deleterious SNPs of human MTUS1 gene and their impacts on subsequent protein structure and function. PLoS One. 2021; 16:e0252932. doi: 10.1371/journal.pone.0252932RozarioLTSharkerTNilaTAIn silico analysis of deleterious SNPs of human MTUS1 gene and their impacts on subsequent protein structure and functionPLoS One.202116e025293210.1371/journal.pone.0252932Open DOISearch in Google Scholar
Witham S, Takano K, Schwartz C, Alexov E. A missense mutation in CLIC2 associated with intellectual disability is predicted by in silico modeling to affect protein stability and dynamics. Proteins Struct Funct Bioinforma. 2011; 79:2444–54.WithamSTakanoKSchwartzCAlexovEA missense mutation in CLIC2 associated with intellectual disability is predicted by in silico modeling to affect protein stability and dynamicsProteins Struct Funct Bioinforma.201179244454Search in Google Scholar
Islam MJ, Khan AM, Parves MR, Hossain MN, Halim MA. Prediction of deleterious non-synonymous SNPs of human STK11 gene by combining algorithms, molecular docking, and molecular dynamics simulation. Sci Rep. 2019; 9:16426. doi: 10.1038/s41598-019-52308-0IslamMJKhanAMParvesMRHossainMNHalimMAPrediction of deleterious non-synonymous SNPs of human STK11 gene by combining algorithms, molecular docking, and molecular dynamics simulationSci Rep.201991642610.1038/s41598-019-52308-0Open DOISearch in Google Scholar
Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, et al. STRING 8—a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 2009; 37(Suppl 1):D412–6.JensenLJKuhnMStarkMChaffronSCreeveyCMullerJSTRING 8—a global view on proteins and their functional interactions in 630 organismsNucleic Acids Res.200937Suppl 1D4126Search in Google Scholar
Mohamoud HS, Hussain MR, El-Harouni AA, Shaik NA, Qasmi ZU, Merican AF, et al. First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene. Comput Math Methods Med. 2014; 2014:904052. doi: 10.1155/2014/904052MohamoudHSHussainMREl-HarouniAAShaikNAQasmiZUMericanAFFirst comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 geneComput Math Methods Med.2014201490405210.1155/2014/904052Open DOISearch in Google Scholar
Yeh JE, Frank DA. STAT3-interacting proteins as modulators of transcription factor function: implications to targeted cancer therapy. Chem Med Chem. 2016; 11:795–801.YehJEFrankDASTAT3-interacting proteins as modulators of transcription factor function: implications to targeted cancer therapyChem Med Chem.201611795801Search in Google Scholar
Yan R, Lin F, Hu C, Tong S. Association between STAT3 polymorphisms and cancer risk: a meta-analysis. Mol Genet genomics. 2015; 290:2261–70.YanRLinFHuCTongSAssociation between STAT3 polymorphisms and cancer risk: a meta-analysisMol Genet genomics.2015290226170Search in Google Scholar
Yu H, Lee H, Herrmann A, Buettner R, Jove R. Revisiting STAT3 signalling in cancer: new and unexpected biological functions. Nat Rev Cancer. 2014; 14:736–46.YuHLeeHHerrmannABuettnerRJoveRRevisiting STAT3 signalling in cancer: new and unexpected biological functionsNat Rev Cancer.20141473646Search in Google Scholar
Mustafa MI, Murshed NS, Abdelmoneim AH, Makhawi AM. In silico analysis of the functional and structural consequences of SNPs in human ARX gene associated with EIEE1. Informatics Med Unlocked. 2020; 21:100447. doi: 10.1016/j.imu.2020.100447MustafaMIMurshedNSAbdelmoneimAHMakhawiAMIn silico analysis of the functional and structural consequences of SNPs in human ARX gene associated with EIEE1Informatics Med Unlocked.20202110044710.1016/j.imu.2020.100447Open DOISearch in Google Scholar