biostudies-otherUnknown11Lucian SmithPloS onee0152104https://www.ebi.ac.uk/biostudies/studies/MODEL1609190000biostudies-other27015094administratorLucian SmithFrancesco PappalardofalsePappalardo2016 - PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer<notes xmlns="http://www.sbml.org/sbml/level2/version4"> <body xmlns="http://www.w3.org/1999/xhtml"> <div class="dc:title">Pappalardo2016 - PI3K/AKT and MAPK SignalingPathways in Melanoma Cancer</div> <div class="dc:bibliographicCitation"> <p>This model is described in the article:</p> <div class="bibo:title"> <a href="http://identifiers.org/pubmed/27015094" title="Access to this publication">Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.</a> </div> <div class="bibo:authorList">Pappalardo F, Russo G, Candido S, Pennisi M, Cavalieri S, Motta S, McCubrey JA, Nicoletti F, Libra M.</div> <div class="bibo:Journal">PLoS ONE 2016; 11(3): e0152104</div> <p>Abstract:</p> <div class="bibo:abstract"> <p>Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease.Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive.</p> </div> </div> <div class="dc:publisher"> <p>This model is hosted on <a href="http://www.ebi.ac.uk/biomodels/">BioModels Database</a> and identified by: <a href="http://identifiers.org/biomodels.db/MODEL1609190000">MODEL1609190000</a>.</p> <p>To cite BioModels Database, please use: <a href="http://identifiers.org/pubmed/20587024" title="Latest BioModels Database publication">BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models</a>.</p> </div> <div class="dc:license"> <p>To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to <a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0 Public Domain Dedication</a> for more information.</p> </div> </body> </notes>2016-09-19T00:00:00Z2025-07-15T09:56:28.657Z2025-03-29T18:23:09.396ZMODEL1609190000BIOMD0000000666R-HSA-2219528R-HSA-5683057PR:000005201PR:000029187PR:000029189C05981CHEBI:75045MAMO_0000046GO:0031932GO:1990565GO:0030971GO:0031931map04151map040100007815

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