{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T07:03:23Z","timestamp":1789369403276,"version":"build-2803163510"},"publisher-location":"New York, NY","reference-count":24,"publisher":"Springer US","isbn-type":[{"value":"9781071654958","type":"print"},{"value":"9781071654965","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-1-0716-5496-5_16","type":"book-chapter","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T06:09:22Z","timestamp":1789366162000},"page":"193-212","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["In Silico Drug Design of Chikungunya Antivirals: Using Consensus Methods for Virtual Screening"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9937-9212","authenticated-orcid":false,"given":"Leandro","family":"Battini","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1006\/jcss.1997.1504","volume":"55","author":"Y Freund","year":"1997","unstructured":"Freund Y, Schapire RE (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 55:119\u2013139","journal-title":"J Comput Syst Sci"},{"key":"16_CR2","doi-asserted-by":"publisher","first-page":"1422","DOI":"10.1021\/ci010025x","volume":"41","author":"R Wang","year":"2001","unstructured":"Wang R, Wang S (2001) How does consensus scoring work for virtual library screening? An idealized computer experiment. J Chem Inf Comput Sci 41:1422\u20131426","journal-title":"J Chem Inf Comput Sci"},{"key":"16_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-41594-3","volume":"9","author":"K Palacio-Rodr\u00edguez","year":"2019","unstructured":"Palacio-Rodr\u00edguez K, Lans I, Cavasotto CN et al (2019) Exponential consensus ranking improves the outcome in docking and receptor ensemble docking. Sci Rep 9: 5142","journal-title":"Sci Rep"},{"key":"16_CR4","doi-asserted-by":"publisher","first-page":"110111","DOI":"10.1016\/j.abb.2024.110111","volume":"759","author":"M Bhutkar","year":"2024","unstructured":"Bhutkar M, Saha A, Tomar S (2024) Viral methyltransferase inhibitors: berbamine, venetoclax, and ponatinib as efficacious antivirals against chikungunya virus. Arch Biochem Biophys 759:110111","journal-title":"Arch Biochem Biophys"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jmgm.2015.01.001","volume":"57","author":"PTV Nguyen","year":"2015","unstructured":"Nguyen PTV, Yu H, Keller PA (2015) Identification of chikungunya virus nsP2 protease inhibitors using structure-base approaches. J Mol Graph Model 57:1\u20138","journal-title":"J Mol Graph Model"},{"key":"16_CR6","doi-asserted-by":"publisher","first-page":"27632","DOI":"10.1021\/acsomega.4c03417","volume":"9","author":"VW Rabelo","year":"2024","unstructured":"Rabelo VW, Sanchez-Nu\u00f1ez ML, Corr\u00eaa-Amorim LS et al (2024) In silico drug repurposing uncovered the antiviral potential of the antiparasitic drug oxibendazole against the chikungunya virus. ACS Omega 9:27632\u201327642","journal-title":"ACS Omega"},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"2216","DOI":"10.1007\/s00894-014-2216-6","volume":"20","author":"PTV Nguyen","year":"2014","unstructured":"Nguyen PTV, Yu H, Keller PA (2014) Discovery of in silico hits targeting the nsP3 macro domain of chikungunya virus. J Mol Model 20:2216","journal-title":"J Mol Model"},{"key":"16_CR8","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.virol.2017.12.020","volume":"515","author":"R Sharma","year":"2018","unstructured":"Sharma R, Kesari P, Kumar P et al (2018) Structure-function insights into chikungunya virus capsid protein: small molecules targeting capsid hydrophobic pocket. Virology 515:223\u2013234","journal-title":"Virology"},{"key":"16_CR9","doi-asserted-by":"publisher","first-page":"1503","DOI":"10.1021\/acsinfecdis.0c00915","volume":"7","author":"L Battini","year":"2021","unstructured":"Battini L, Fidalgo DM, \u00c1lvarez DE et al (2021) Discovery of a potent and selective chikungunya virus envelope protein inhibitor through computer-aided drug design. ACS Infect Dis 7:1503\u20131518","journal-title":"ACS Infect Dis"},{"key":"16_CR10","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1002\/jcc.21334","volume":"31","author":"O Trott","year":"2010","unstructured":"Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455\u2013461","journal-title":"J Comput Chem"},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"2785","DOI":"10.1002\/jcc.21256","volume":"30","author":"GM Morris","year":"2009","unstructured":"Morris GM, Huey R, Lindstrom W et al (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30:2785\u20132791","journal-title":"J Comput Chem"},{"key":"16_CR12","doi-asserted-by":"publisher","first-page":"3594","DOI":"10.1016\/j.bmcl.2016.06.013","volume":"26","author":"N Zhang","year":"2016","unstructured":"Zhang N, Zhao H (2016) Enriching screening libraries with bioactive fragment space. Bioorg Med Chem Lett 26:3594\u20133597","journal-title":"Bioorg Med Chem Lett"},{"key":"16_CR13","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-3-33","volume":"3","author":"NM O\u2019Boyle","year":"2011","unstructured":"O\u2019Boyle NM, Banck M, James CA et al (2011) Open Babel: an open chemical toolbox. J Cheminform 3:33","journal-title":"J Cheminform"},{"key":"16_CR14","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-168","volume":"10","author":"V Le Guilloux","year":"2009","unstructured":"Le Guilloux V, Schmidtke P, Tuffery P (2009) Fpocket: an open source platform for ligand pocket detection. BMC Bioinform 10:168","journal-title":"BMC Bioinform"},{"key":"16_CR15","doi-asserted-by":"publisher","first-page":"W413","DOI":"10.1093\/nar\/gkp281","volume":"37","author":"M Hernandez","year":"2009","unstructured":"Hernandez M, Ghersi D, Sanchez R (2009) SITEHOUND-web: a server for ligand binding site identification in protein structures. Nucleic Acids Res 37:W413\u2013W416","journal-title":"Nucleic Acids Res"},{"key":"16_CR16","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-018-0285-8","volume":"10","author":"R Kriv\u00e1k","year":"2018","unstructured":"Kriv\u00e1k R, Hoksza D (2018) P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure. J Cheminformatics 10:39","journal-title":"J Cheminformatics"},{"key":"16_CR17","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","volume":"596","author":"J Jumper","year":"2021","unstructured":"Jumper J, Evans R, Pritzel A et al (2021) Highly accurate protein structure prediction with AlphaFold. Nature 596:583\u2013589","journal-title":"Nature"},{"key":"16_CR18","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-015-0067-5","volume":"7","author":"WP Feinstein","year":"2015","unstructured":"Feinstein WP, Brylinski M (2015) Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J Cheminform 7:18","journal-title":"J Cheminform"},{"key":"16_CR19","unstructured":"Morris GM, Goodsell DS, Pique ME et al (2014) User Guide AutoDock Version 4.2, Updated for version 4.2.6. La Jolla, CA: The Scripps Research Institute"},{"key":"16_CR20","doi-asserted-by":"publisher","first-page":"2122","DOI":"10.1099\/vir.0.000144","volume":"96","author":"MKS Van Duijl-Richter","year":"2015","unstructured":"Van Duijl-Richter MKS, Blijleven JS, Van Oijen AM et al (2015) Chikungunya virus fusion properties elucidated by single-particle and bulk approaches. J Gen Virol 96:2122\u20132132","journal-title":"J Gen Virol"},{"key":"16_CR21","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1016\/j.celrep.2019.06.022","volume":"28","author":"MG Noval","year":"2019","unstructured":"Noval MG, Rodriguez-Rodriguez BA, Rangel MV et al (2019) Evolution-driven attenuation of alphaviruses highlights key glycoprotein determinants regulating viral infectivity and dissemination. Cell Rep 28:460\u2013471.e5","journal-title":"Cell Rep"},{"key":"16_CR22","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1186\/1423-0127-19-44","volume":"19","author":"S-C Kuo","year":"2012","unstructured":"Kuo S-C, Chen Y-J, Wang Y-M et al (2012) Cell-based analysis of chikungunya virus E1 protein in membrane fusion. J Biomed Sci 19:44","journal-title":"J Biomed Sci"},{"key":"16_CR23","doi-asserted-by":"publisher","unstructured":"Battini L, Thannickal SA, Cibello MT et al (2024) Evolution of antiviral resistance captures a transient interdomain functional interaction between chikungunya virus envelope glycoproteins, http:\/\/biorxiv.org\/lookup\/doi\/;\u2009https:\/\/doi.org\/10.1101\/2024.11.11.623010","DOI":"10.1101\/2024.11.11.623010"},{"key":"16_CR24","doi-asserted-by":"crossref","unstructured":"Passaro S, Corso G, Wohlwend J et al (2025) Boltz2: Towards accurate and efficient binding affinity prediction. BioRxiv.","DOI":"10.1101\/2025.06.14.659707"}],"container-title":["Methods in Molecular Biology","Chikungunya Virus"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-1-0716-5496-5_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T06:09:27Z","timestamp":1789366167000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-1-0716-5496-5_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,15]]},"ISBN":["9781071654958","9781071654965"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-1-0716-5496-5_16","relation":{},"ISSN":["1064-3745","1940-6029"],"issn-type":[{"value":"1064-3745","type":"print"},{"value":"1940-6029","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,15]]},"assertion":[{"value":"15 September 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}