Abstract
This work presents the analysis of the conformation of albumin in the temperature range of 300K – 312K, i.e., in the physiological range. Using molecular dynamics simulations, we calculate values of the backbone and dihedral angles for this molecule. We analyze the global dynamic properties of albumin treated as a chain. In this range of temperature, we study parameters of the molecule and the conformational entropy derived from two angles that reflect global dynamics in the conformational space. A thorough rationalization, based on the scaling theory, for the subdiffusion Flory–De Gennes type exponent of 0.4 unfolds in conjunction with picking up the most appreciable fluctuations of the corresponding statistical-test parameter. These fluctuations coincide adequately with entropy fluctuations, namely the oscillations out of thermodynamic equilibrium. Using Fisher’s test, we investigate the conformational entropy over time and suggest its oscillatory properties in the corresponding time domain. Using the Kruscal–Wallis test, we also analyze differences between the root mean square displacement of a molecule at various temperatures. Here we show that its values in the range of 306K – 309K are different than in another temperature. Using the Kullback–Leibler theory, we investigate differences between the distribution of the root mean square displacement for each temperature and time window.
Citations
-
3
CrossRef
-
0
Web of Science
-
3
Scopus
Authors (5)
Cite as
Full text
- Publication version
- Accepted or Published Version
- License
- open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
ENTROPY
no. 22,
pages 1 - 21,
ISSN: 1099-4300 - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Weber P., Bełdowski P., Domino K., Ledziński D., Gadomski A.: Changes of Conformation in Albumin with Temperature by Molecular Dynamics Simulations// ENTROPY-SWITZ -Vol. 22,iss. 4 (2020), s.1-21
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/e22040405
- Bibliography: test
-
- Grimaldo, M.; Roosen-Runge, F.; Zhang, F.; Schreiber, F.; Seydel, T. Dynamics of proteins in solution. Quarter. Rev. Biophys. 2019, 52, e7. open in new tab
- Rubinstein, M.; Colby, R.H. Polymer Physics; Oxford University Press: Oxford, UK, 2003.
- De Gennes, P.G. Scaling Concepts in Polymer Physics; open in new tab
- Gadomski, A. On (sub) mesoscopic scale peculiarities of diffusion driven growth in an active matter confined space, and related (bio) material realizations. Biosystems 2019, 176, 56-58. open in new tab
- Metzler, R.; Jeon, J.H.; Cherstvy, A.G.; Barkai, E. Anomalous diffusion models and their properties: Non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking. Phys. Chem. Chem. Phys. 2014, 16, 24128. open in new tab
- Weber, P.; Bełdowski, P.; Bier, M.; Gadomski, A. Entropy Production Associated with Aggregation into Granules in a Subdiffusive Environment. Entropy 2018, 20, 651. open in new tab
- Flory, P. Principles of Polymer Chemistry; Cornell University Press: Ithaca, NY, USA, 1953.
- Doi, M.; Edwards, S.F. The Theory of The Polymer Dynamics. In The International Series of Monographs on Physics; Oxford University Press: New York, NY, USA, 1986; pp. 24-32.
- Bhattacharya, A.A.; Curry, S.; Franks, N.P. Binding of the General Anesthetics Propofol and Halothane to Human Serum Albumin. J. Biol. Chem. 2000, 275, 38731-38738. open in new tab
- Oates, K.M.N.; Krause, W.E.; Jones, R.L.; Colby, R.H. Rheopexy of synovial fluid and protein aggregation. J. R. Soc. Interface 2006, 3, 167-174. open in new tab
- Rebenda, D.;Čípek, P.; Nečas, D.; Vrbka, M.; Hartl, M. Effect of hyaluronic acid on friction of articular cartilage. Eng. Mech. 2018, 24, 709-712. open in new tab
- Seror, J.; Zhu, L.; Goldberg, R.; Day, A.J.; Klein, J. Supramolecular synergy in the boundary lubrication of synovial joints. Nat. Commun. 2015, 6, 6497, doi:10.1038/ncomms7497. open in new tab
- Katta, J.; Jin, Z.; Ingham, E.; Fisher, J. Biotribology of articular cartilage-A review of the recent advances. Med. Eng. Phys. 2000, 30, 1349-1363. open in new tab
- Moghadam, M.N.; Abdel-Sayed, P.; Camine, V.M.; Pioletti, D.P. Impact of synovial fluid flow on temperature regulation in knee cartilage. J. Biomech. 2015, 48, 370-374. open in new tab
- Liwo, A.; Ołdziej, S.; Kaźmierkiewicz, R.; Groth, M.; Czaplewski, C. Design of a knowledge-based force field for off-latice simulations of protein structure. Acta Biochim. Pol. 1997 44, 527-548. open in new tab
- Havlin, S.; Ben-Avraham, D. Diffusion in disordered media. Adv. Phys. 2002, 51, 187-292. open in new tab
- Bhattacharjee, S.M.; Giacometti, A.; Maritan, A. Flory theory for polymers. J. Phys. Condens. Matter 2013, 25, 503101. open in new tab
- Baxa, M.C.; Haddadian, E.J.; Jumper, J.M.; Freed, K.F.; Sosnick, T.R. Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations. Proc. Natl. Acad. Sci. USA 2014 111, 15396-15401. open in new tab
- Ahdesmaki, M.; Lahdesmaki, H.; Yli-Harja, O. Robust Fisher's test for periodicity detection in noisy biological time series. In Proceedings of the IEEE International Workshop on Genomic Signal Processing and Statistics, Tuusula, Finland, 10-12 June 2007. open in new tab
- Wichert, S.; Fokianos, K.; Strimmer, K. Identifying periodically expressed transcripts in microarray time series data. Bioinformatics 2004, 20, 5-20. open in new tab
- Kanji, G.K. 100 Statiatical Tests; SAGE Publications Ltd.: Thousand Oaks, CA, USA, 2006.
- Conover, W.J. Practical Nonparametric Statistics, 2nd ed.; John Wiley & Sons: New York, NY, USA, 1980.
- Gupta, A.; Parameswaran, S.; Lee, C.-H. Classification of electroencephalography signals for different mental activities using Kullback-Leibler divergence. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan, 19-24 April 2009. open in new tab
- Domino, K.; Błachowicz, T.; Ciupak, M. The use of copula functions for predictive analysis of correlations between extreme storm tides. Physica A 2014, 413, 489-497. open in new tab
- Tanner, J.J. Empirical power laws for the radii of gyration of protein oligomers. Acta Crystallogr. D Struct. Biol. 2016, 72, 1119-1129. open in new tab
- Korasick, D.A.; Tanner, J.J. Determination of protein oligomeric structure from small-angle X-ray scattering. Protein Sci. 2018, 27, 814-824. open in new tab
- De Bruyn, P.; Hadži, S.; Vandervelde, A.; Konijnenberg, A.; Prolič-Kalinšek, M.; Sterckx, Y.G.J.; Sobott, F.; Lah, J.; Van Melderen L.; Loris, R. Thermodynamic Stability of the Transcription Regulator PaaR2 from Escherichia coli O157:H7. Biophys. J. 2019, 116, 1420-1431. open in new tab
- Durell, S.R.; Ben-Naim, A. Hydrophobic-Hydrophilic Forces in Protein Folding. Biopolymers 2017, 107, e23020. open in new tab
- Rezaei-Tavirani, M.; Moghaddamnia, S.H.; Ranjbar, B.; Amani, M.; Marashi, S.A. Conformational Study of Human Serum Albumin in Pre-denaturation Temperatures by Differential Scanning Calorimetry, Circular Dichroism and UV Spectroscopy. J. Biochem. Mol. Biol. 2006 39, 530-536. open in new tab
- Isaacson, J.; Lubensky, T.C. Flory exponents for generalized polymer problems. J. Phys. Lett. 1980, 41, L-469-L-471. open in new tab
- Krieger, E.; Vriend, G. New ways to boost molecular dynamics simulations. J. Comput. Chem. 2015, 36, 996-1007. open in new tab
- Mark, P.; Nilsson, L. Structure and Dynamics of the TIP3P, SPC, and SPC/E Water Models at 298 K. J. Phys. Chem. A 2001, 105, 9954-9960. open in new tab
- Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M.C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; et al. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 2003, 24, 1999-2012. open in new tab
- Baruah, A.; Rani, P.; Biswas, P. Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads. Sci. Rep. 2015, 5, 11740. open in new tab
- SciLab. Available online: https://www.scilab.org (accessed on 30 April 2017). c 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). open in new tab
- Verified by:
- Gdańsk University of Technology
seen 149 times
Recommended for you
Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
- V. Raul,
- L. Leifsson,
- S. Kozieł
Effect of Ion and Binding Site on the Conformation of Chosen Glycosaminoglycans at the Albumin Surface
- P. Sionkowski,
- P. Bełdowski,
- N. Kruszewska
- + 3 authors