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Cover Image, Volume 35, Issue 24
Publication year - 2014
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.23709
Subject(s) - cover (algebra) , citation , computer science , volume (thermodynamics) , function (biology) , flexibility (engineering) , ligand (biochemistry) , image (mathematics) , information retrieval , computer graphics (images) , world wide web , artificial intelligence , chemistry , physics , biology , engineering , mathematics , biochemistry , thermodynamics , mechanical engineering , statistics , receptor , evolutionary biology
In proteins with buried active sites, understanding how ligands migrate through the tunnels that connect the exterior of the protein to the active site can shed light on substrate specificity and enzyme function. On page 1748 (DOI: 10.1002/jcc.23680 ), Laura Kingsley and Markus Lill present the new computational method IterTunnel that combines geometric tunnel prediction with steered MD to incorporate ligand migration and protein flexibility into tunnel prediction. It is demonstrated that the ligand itself can reshape tunnels due to its interaction with the protein resulting in the exposure of new, energetically favorable, tunnels.