Mariño-Ramírez L, Kann MG, Shoemaker BA, Landsman D. Histone structure and nucleosome stability. Expert Rev Proteomics. 2005;2:719–29.
Article
Google Scholar
Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Zhou Z, et al. PubChem’s BioAssay Database. Nucleic Acids Res. 2012;40:D400–12.
Article
CAS
Google Scholar
Chow J, Heard E. X inactivation and the complexities of silencing a sex chromosome. Curr Opin Cell Biol. 2009;21:359–66.
Article
CAS
Google Scholar
Oliver SS, Denu JM. Dynamic interplay between histone H3 modifications and protein interpreters: emerging evidence for a “Histone Language”. ChemBioChem. 2011;12:299–307.
Article
CAS
Google Scholar
Bannister AJ, Kouzarides T. Regulation of chromatin by histone modifications. Cell Res. 2011;21:381–95.
Article
CAS
Google Scholar
Buschbeck M, Hake SB. Variants of core histones and their roles in cell fate decisions, development and cancer. Nat Rev Mol Cell Biol [Internet]. Nature Publishing Group; 2017;18:299–314. http://www.nature.com/articles/nrm.2016.166. Accessed 30 July 2019.
Singh R, Harshman SW, Ruppert AS, Mortazavi A, Lucas DM, Thomas-Ahner JM, et al. Proteomic profiling identifies specific histone species associated with leukemic and cancer cells. Clin Proteomics [Internet]. BioMed Central; 2015;12:22. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4551702&tool=pmcentrez&rendertype=abstract.
Khan SA. Global histone post-translational modifications and cancer: biomarkers for diagnosis, prognosis and treatment? World J Biol Chem. 2015;6:333.
Article
Google Scholar
Schones DE, Leung A, Natarajan R. Chromatin modifications associated with diabetes and obesity. Arterioscler Thromb Vasc Biol. 2015;35:1557–61.
Article
CAS
Google Scholar
Araki Y, Mimura T. The histone modification code in the pathogenesis of autoimmune diseases. Mediators Inflamm. 2017. https://doi.org/10.1155/2017/2608605.
Article
PubMed
PubMed Central
Google Scholar
Sharda A, Amnekar RV, Natu A, Sukanya, Gupta S. Histone posttranslational modifications: potential role in diagnosis, prognosis, and therapeutics of cancer. Progn Epigenetics. Elsevier; 2019. p. 351–73.
Sporn JC, Kustatscher G, Hothorn T, Collado M, Serrano M, Muley T, et al. Histone macroH2A isoforms predict the risk of lung cancer recurrence. Oncogene. 2009;28:3423–8.
Article
CAS
Google Scholar
Pericentric heterochromatin becomes enriched with H2A.Z during early mammalian development [Internet]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC152904/. Accessed 14 July 2020.
Hu G, Cui K, Northrup D, Liu C, Wang C, Tang Q, et al. H2A.Z facilitates access of active and repressive complexes to chromatin in embryonic stem cell self-renewal and differentiation. Cell Stem Cell. 2013;12:180–92.
Article
CAS
Google Scholar
Vardabasso C, Hake SB, Bernstein E. Histone variant H2A.Z.2: A novel driver of melanoma progression. Mol Cell Oncol. 2016;3:1–2. https://doi.org/10.1080/23723556.2015.1073417.
Article
CAS
Google Scholar
Tomonaga T, Matsushita K, Yamaguchi S, Oohashi T, Shimada H, Ochiai T, et al. Overexpression and mistargeting of centromere protein-A in human primary colorectal cancer. Cancer Res. 2003;63:3511–6.
CAS
PubMed
Google Scholar
Marmorstein R, Trievel RC. Histone modifying enzymes: structures, mechanisms, and specificities. Biochim Biophys Acta. 2009;1789:58–68.
Article
CAS
Google Scholar
Zhen L, Gui-Lan L, Ping Y, Jin H, Ya-Li W. The expression of H3K9Ac, H3K14Ac, and H4K20TriMe in epithelial ovarian tumors and the clinical significance. Int J Gynecol Cancer. 2010;20:82–6.
Article
Google Scholar
Bianco-Miotto T, Chiam K, Buchanan G, Jindal S, Day TK, Thomas M, et al. Global levels of specific histone modifications and an epigenetic gene signature predict prostate cancer progression and development. Cancer Epidemiol Biomarkers Prev. 2010;19:2611–22.
Article
CAS
Google Scholar
Gao Y, Geng J, Hong X, Qi J, Teng Y, Yang Y, et al. Expression of p300 and CBP is associated with poor prognosis in small cell lung cancer. Int J Clin Exp Pathol 2014;7:760–7. http://www.ijcep.com/. Accessed 14 July 2020.
Ishihama K, Yamakawa M, Semba S, Takeda H, Kawata S, Kimura S, et al. Expression of HDAC1 and CBP/p300 in human colorectal carcinomas. J Clin Pathol [Internet]. BMJ Publishing Group; 2007;60:1205–10. /pmc/articles/PMC2095491/?report=abstract. Accessed 20 July 2020.
Li Y, Seto E. HDACs and HDAC inhibitors in cancer development and therapy. Cold Spring Harb Perspect Med [Internet]. Cold Spring Harbor Laboratory Press; 2016;6. /pmc/articles/PMC5046688/?report=abstract. Accessed 20 July 2020.
Gan L, Yang Y, Li Q, Feng Y, Liu T, Guo W. Epigenetic regulation of cancer progression by EZH2: From biological insights to therapeutic potential [Internet]. Biomark. Res. BioMed Central Ltd.; 2018. /pmc/articles/PMC5845366/?report=abstract. Accessed 20 July 2020.
Sethi G, Shanmugam MK, Arfuso F, Kumar AP. Role of RNF20 in cancer development and progression—a comprehensive review [Internet]. Biosci. Rep. Portland Press Ltd; 2018. p. 20171287. /pmc/articles/PMC6043722/?report = abstract. Accessed 20 July 2020.
Cicenas J, Zalyte E, Bairoch A, Gaudet P. Kinases and cancer [Internet]. Cancers (Basel). MDPI AG; 2018. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876638/. Accessed 15 July 2020.
Suraweera A, O’Byrne KJ, Richard DJ. Combination therapy with histone deacetylase inhibitors (HDACi) for the treatment of cancer: achieving the full therapeutic potential of HDACi. Front Oncol. 2018;8:92.
Article
Google Scholar
Zhang Y, Lv J, Liu H, Zhu J, Su J, Wu Q, et al. HHMD: the human histone modification database. Nucleic Acids Res. 2010;38:D149–54.
Article
CAS
Google Scholar
Gendler K, Paulsen T, Napoli C. ChromDB: the chromatin database. Nucleic Acids Res. 2008;36:D298–302.
Article
CAS
Google Scholar
Huang H, Maertens AM, Hyland EM, Dai J, Norris A, Boeke JD, et al. HistoneHits: a database for histone mutations and their phenotypes. Genome Res. 2009;19:674–81.
Article
CAS
Google Scholar
Marino-Ramirez L, Levine KM, Morales M, Zhang S, Moreland RT, Baxevanis AD, et al. The histone database: an integrated resource for histones and histone fold-containing proteins. Database [Internet]. 2011;2011:bar048–bar048. http://www.ncbi.nlm.nih.gov/pubmed/22025671. Accessed 31 July 2019.
Qi Y, Wang D, Wang D, Jin T, Yang L, Wu H, et al. HEDD: the human epigenetic drug database. Database [Internet]. Narnia; 2016;2016:baw159. https://academic.oup.com/database/article-lookup/doi/10.1093/database/baw159. Accessed 4 Sept 2019.
Khare SP, Habib F, Sharma R, Gadewal N, Gupta S, Galande S. HIstome—a relational knowledgebase of human histone proteins and histone modifying enzymes. Nucleic Acids Res [Internet]. Narnia; 2012;40:D337–42. https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkr1125. Accessed 31 July 2019.
FireBrowse.org [Internet]. http://firebrowse.org/. Accessed 4 Sept 2019.
Agarwal V, Bell GW, Nam J-W, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife [Internet]. 2015;4. https://elifesciences.org/articles/05005. Accessed 6 Aug 2019.
Weinstein JN, Collisson EA, Mills GB, Shaw KRM, Ozenberger BA, Ellrott K, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet [Internet]. 2013;45:1113–20. http://www.nature.com/articles/ng.2764. Accessed 4 Sept 2019.
Weininger D. SMILES. 3. DEPICT. Graphical depiction of chemical structures. J Chem Inf Model. 1990;30:237–43. https://doi.org/10.1021/ci00067a005.
Article
CAS
Google Scholar
Weininger D, Weininger A, Weininger JL. SMILES. 2. Algorithm for generation of unique SMILES notation. J Chem Inf Model. 1989;29:97–101. https://doi.org/10.1021/ci00062a008.
Article
CAS
Google Scholar
Weininger D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Model. 1988;28:31–6. https://doi.org/10.1021/ci00057a005.
Article
CAS
Google Scholar
Heller SR, McNaught A, Pletnev I, Stein S, Tchekhovskoi D. InChI, the IUPAC international chemical identifier. J Cheminform. 2015;7:23.
Article
Google Scholar
Heller S, McNaught A, Stein S, Tchekhovskoi D, Pletnev I. InChI—the worldwide chemical structure identifier standard. J Cheminform. 2013;5:7.
Article
CAS
Google Scholar
Frey J, De Roure D, Taylor K, Essex J, Mills H, Zaluska E. CombeChem: a case study in provenance and annotation using the semantic web. Springer, Berlin, Heidelberg; 2006. p. 270–7. http://link.springer.com/10.1007/11890850_27. Accessed 4 Sept 2019.
Bento AP, Gaulton A, Hersey A, Bellis LJ, Chambers J, Davies M, et al. The ChEMBL bioactivity database: an update. Nucleic Acids Res. 2014;42:D1083–90.
Article
CAS
Google Scholar
Irwin JJ, Sterling T, Mysinger MM, Bolstad ES, Coleman RG. ZINC: a free tool to discover chemistry for biology. J Chem Inf Model. 2012;52:1757–68.
Article
CAS
Google Scholar
Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vázquez-Fresno R, et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018;46:D608–17.
Article
CAS
Google Scholar
Hoofnagle JH, Serrano J, Knoben JE, Navarro VJ. LiverTox: a website on drug-induced liver injury. Hepatology. 2013;57:873–4.
Article
Google Scholar
Frolkis A, Knox C, Lim E, Jewison T, Law V, Hau DD, et al. SMPDB: the small molecule pathway database. Nucleic Acids Res. 2010;38:D480–7.
Article
CAS
Google Scholar
Jin C, Felsenfeld G. Nucleosome stability mediated by histone variants H3.3 and H2A.Z. Genes Dev. 2007;21:1519–29.
Article
CAS
Google Scholar
Shah S, Verma T, Rashid M, Gadewal N, Gupta S. Histone H2A isoforms : potential implications in epigenome plasticity and diseases in eukaryotes. 2020;0123456789.
Bhattacharya S, Reddy D, Jani V, Gadewal N, Shah S, Reddy R, Bose K, Sonavane U, Joshi R, Smoot D, Ashktorab H, Gupta S. Histone isoform H2A1H promotes attainment of distinct physiological states by altering chromatin dynamics. Epigenetics Chromatin. 2017;10:48.
Article
Google Scholar
Sievers F, Higgins DG. Clustal omega, accurate alignment of very large numbers of sequences. Methods Mol Biol [Internet]. 2014. p. 105–16. http://www.ncbi.nlm.nih.gov/pubmed/24170397. Accessed 8 Aug 2019.
Crooks GE, Hon G, Chandonia J-M, Brenner SE. WebLogo: a sequence logo generator. Genome Res. 2004;14:1188–90.
Article
CAS
Google Scholar
Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, et al. The genecards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinforma [Internet]. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2016. p. 1.30.1–1.30.33. http://doi.wiley.com/10.1002/cpbi.5. Accessed 4 Sept 2019.
Geer LY, Marchler-Bauer A, Geer RC, Han L, He J, He S, et al. The NCBI BioSystems database. Nucleic Acids Res. 2010;38:D492–6.
Article
CAS
Google Scholar
UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res [Internet]. Narnia; 2019;47:D506–15. https://academic.oup.com/nar/article/47/D1/D506/5160987. Accessed 4 Sept 2019.
Draizen EJ, Shaytan AK, Mariño-Ramírez L, Talbert PB, Landsman D, Panchenko AR. HistoneDB 2.0: a histone database with variants—an integrated resource to explore histones and their variants. Database. 2016;2016:1–10.
Article
Google Scholar
Talbert PB, Ahmad K, Almouzni G, Ausiá J, Berger F, Bhalla PL, et al. A unified phylogeny-based nomenclature for histone variants. Epigenetics Chromatin. 2012;5:1–19.
Article
Google Scholar
Bruford EA, Lush MJ, Wright MW, Sneddon TP, Povey S, Birney E. The HGNC Database in 2008: a resource for the human genome. Nucleic Acids Res [Internet]. Narnia; 2007;36:D445–8. https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkm881. Accessed 6 Aug 2019.
Shimoyama M, De Pons J, Hayman GT, Laulederkind SJF, Liu W, Nigam R, et al. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015;43:D743–50.
Article
CAS
Google Scholar
Bult CJ, Blake JA, Smith CL, Kadin JA, Richardson JE, Anagnostopoulos A, et al. Mouse Genome Database (MGD) 2019. Nucleic Acids Res. 2019;47:D801–6.
Article
CAS
Google Scholar
Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res [Internet]. Narnia; 2019;47:D464–74. https://academic.oup.com/nar/article/47/D1/D464/5144139. Accessed 4 Sept 2019.
Dreos R, Ambrosini G, Périer RC, Bucher P. The Eukaryotic Promoter Database: expansion of EPDnew and new promoter analysis tools. Nucleic Acids Res [Internet]. Narnia; 2015;43:D92–6. http://academic.oup.com/nar/article/43/D1/D92/2437610/The-Eukaryotic-Promoter-Database-expansion-of. Accessed 4 Sept 2019.
Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016;44:D1202–13.
Article
CAS
Google Scholar
https://clinicaltrials.gov/ [Internet]. https://clinicaltrials.gov/. Accessed 4 Sept 2019.
Pronk S, Páll S, Schulz R, Larsson P, Bjelkmar P, Apostolov R, et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics [Internet]. Narnia; 2013;29:845–54. https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btt055. Accessed 8 Aug 2019.
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. J Chem Phys. 1983;79:926–35. https://doi.org/10.1063/1.445869.
Article
CAS
Google Scholar
Jorgensen WL, Tirado-Rives J. The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin. J Am Chem Soc. 1988;110:1657–66. https://doi.org/10.1021/ja00214a001.
Article
CAS
PubMed
Google Scholar