A principal component analysis of the dynamics of subdomains and binding sites in human serum albumin |
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Authors: | Guillaume Paris Christophe Ramseyer Mironel Enescu |
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Affiliation: | 1. Laboratoire Chrono Environnement UMR CNRS 6249, Faculté des Sciences et Techniques, La Bouloie, Université de Franche‐Comté, France;2. Laboratoire de Nanomédecine, Imagerie et Thérapeutique, Faculté des Sciences et Techniques, La Bouloie, Université de Franche‐Comté, France |
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Abstract: | The conformational dynamics of human serum albumin (HSA) was investigated by principal component analysis (PCA) applied to three molecular dynamics trajectories of 200 ns each. The overlap of the essential subspaces spanned by the first 10 principal components (PC) of different trajectories was about 0.3 showing that the PCA based on a trajectory length of 200 ns is not completely convergent for this protein. The contributions of the relative motion of subdomains and of the subdomains (internal) distortion to the first 10 PCs were found to be comparable. Based on the distribution of the first 3 PC, 10 protein conformers are identified showing relative root mean square deviations (RMSD) between 2.3 and 4.6 Å. The main PCs are found to be delocalized over the whole protein structure indicating that the motions of different protein subdomains are coupled. This coupling is considered as being related to the allosteric effects observed upon ligand binding to HSA. On the other hand, the first PC of one of the three trajectories describes a conformational transition of the protein domain I that is close to that experimentally observed upon myristate binding. This is a theoretical support for the older hypothesis stating that changes of the protein onformation favorable to binding can precede the ligand complexation. A detailed all atoms PCA performed on the primary Sites 1 and 2 confirms the multiconformational character of the HSA binding sites as well as the significant coupling of their motions. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 561–572, 2014. |
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Keywords: | human serum albumin principal component analysis molecular dynamics simulation binding sites |
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