Publication:
dentification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies

dc.contributor.coauthorWeako, Jackson
dc.contributor.coauthorUba, Abdullahi İbrahim
dc.contributor.coauthorYelekçi, Kemal
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.departmentCCBB (The Center for Computational Biology and Bioinformatics)
dc.contributor.kuauthorGürsoy, Attila
dc.contributor.kuauthorKeskin, Özlem
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteResearch Center
dc.date.accessioned2024-11-09T22:49:45Z
dc.date.issued2020
dc.description.abstractMethionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava's Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [BIDEB -2235] We thank the Scientific and Technological Research Council of Turkey (TUBITAK) for supporting this project through the Graduates Scholarship for the least Developed Countries (BIDEB -2235).
dc.description.volume86
dc.identifier.doi10.1016/j.compbiolchem.2020.107244
dc.identifier.eissn1476-928X
dc.identifier.issn1476-9271
dc.identifier.quartileQ3
dc.identifier.scopus2-s2.0-85082743357
dc.identifier.urihttps://doi.org/10.1016/j.compbiolchem.2020.107244
dc.identifier.urihttps://hdl.handle.net/20.500.14288/6558
dc.identifier.wos537621900006
dc.keywordsMetAP2 inhibitors
dc.keywordsStructure-based virtual screening
dc.keywordsMolecular docking
dc.keywordsMolecular dynamics simulation
dc.keywordsDocking
dc.language.isoeng
dc.publisherElsevier Sci Ltd
dc.relation.ispartofComputational Biology and Chemistry
dc.subjectBiology
dc.subjectComputer Science
dc.titledentification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorKeskin, Özlem
local.contributor.kuauthorGürsoy, Attila
local.publication.orgunit1College of Engineering
local.publication.orgunit1Research Center
local.publication.orgunit2Department of Chemical and Biological Engineering
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2CCBB (The Center for Computational Biology and Bioinformatics)
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