+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: not found

      Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments.

          Related collections

          Most cited references 257

          • Record: found
          • Abstract: not found
          • Article: not found

          Comparison of simple potential functions for simulating liquid water

            • Record: found
            • Abstract: not found
            • Article: not found

            GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

              • Record: found
              • Abstract: found
              • Article: not found

              ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB.

              Molecular mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Average errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple small adjustments of φ and ψ parameters were tested against NMR scalar coupling data and secondary structure content for short peptides. The best results were obtained from a physically motivated adjustment to the φ rotational profile that compensates for lack of ff99SB QM training data in the β-ppII transition region. Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reproduction of NMR χ1 scalar coupling measurements for proteins in solution. We also discuss the Amber ff12SB parameter set, a preliminary version of ff14SB that includes most of its improvements.

                Author and article information

                J Phys Chem B
                J Phys Chem B
                The Journal of Physical Chemistry. B
                American Chemical Society
                30 June 2017
                31 August 2017
                : 121
                : 34
                : 8009-8025
                []Department of Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States
                []Quantitative Biology Center, RIKEN , Kobe, Japan
                [§ ]Theoretical Molecular Science Laboratory, RIKEN , Wako, Japan
                []iTHES Research Group, RIKEN , Wako, Japan
                []Advanced Institute for Computational Science, RIKEN , Kobe, Japan
                Author notes
                [* ]Address: 603 Wilson Road, Room BCH 218, East Lansing, MI, 48824. E-mail: feig@ . Phone: +1 (517) 432-7439. Fax: +1 (517) 353-9334.
                Copyright © 2017 American Chemical Society

                This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.

                Feature Article
                Custom metadata

                Physical chemistry


                Comment on this article