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The energy profiles of atomic conformational transition intermediates of adenylate kinase
Author(s) -
Feng Yaping,
Yang Lei,
Kloczkowski Andrzej,
Jernigan Robert L.
Publication year - 2009
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.22467
Subject(s) - chemistry , maxima and minima , protein data bank (rcsb pdb) , adenylate kinase , transition state , energy landscape , steric effects , force field (fiction) , computational chemistry , crystallography , stereochemistry , computer science , catalysis , mathematics , enzyme , artificial intelligence , mathematical analysis , biochemistry
Abstract The elastic network interpolation (ENI) (Kim et al., Biophys J 2002;83:1620–1630) is a computationally efficient and physically realistic method to generate conformational transition intermediates between two forms of a given protein. However it can be asked whether these calculated conformations provide good representatives for these intermediates. In this study, we use ENI to generate conformational transition intermediates between the open form and the closed form of adenylate kinase (AK). Based on C α ‐only intermediates, we construct atomic intermediates by grafting all the atoms of known AK structures onto the C α atoms and then perform CHARMM energy minimization to remove steric conflicts and optimize these intermediate structures. We compare the energy profiles for all intermediates from both the CHARMM force‐field and from knowledge‐based energy functions. We find that the CHARMM energies can successfully capture the two energy minima representing the open AK and closed AK forms, while the energies computed from the knowledge‐based energy functions can detect the local energy minimum representing the closed AK form and show some general features of the transition pathway with a somewhat similar energy profile as the CHARMM energies. The combinatorial extension structural alignment (Shindyalov et al., 1998;11:739–747) and the k‐means clustering algorithm are then used to show that known PDB structures closely resemble computed intermediates along the transition pathway. Proteins 2009. © 2009 Wiley‐Liss, Inc.