molecular dynamics Dotaz Zobrazit nápovědu
Given by χ torsional angles, rotamers describe the side-chain conformations of amino acid residues in a protein based on the rotational isomers (hence the word rotamer). Constructed rotamer libraries, based on either protein crystal structures or dynamics studies, are the tools for classifying rotamers (torsional angles) in a way that reflect their frequency in nature. Rotamer libraries are routinely used in structure modeling and evaluation. In this perspective article, we would like to encourage researchers to apply rotamer analyses beyond their traditional use. Molecular dynamics (MD) of proteins highlight the in silico behavior of molecules in solution and thus can identify favorable side-chain conformations. In this article, we used simple computational tools to study rotamer dynamics (RD) in MD simulations. First, we isolated each frame in the MD trajectories in separate Protein Data Bank files via the cpptraj module in AMBER. Then, we extracted torsional angles via the Bio3D module in R language. The classification of torsional angles was also done in R according to the penultimate rotamer library. RD analysis is useful for various applications such as protein folding, study of rotamer-rotamer relationship in protein-protein interaction, real-time correlation between secondary structures and rotamers, study of flexibility of side chains in binding site for molecular docking preparations, use of RD as guide in functional analysis and study of structural changes caused by mutations, providing parameters for improving coarse-grained MD accuracy and speed, and many others. Major challenges facing RD to emerge as a new scientific field involve the validation of results via easy, inexpensive wet-lab methods. This realm is yet to be explored.
Abstract Aromatic stacking of nucleic acid bases is one of the key players in determining the structure and dynamics of nucleic acids. The arrangement of nucleic acid bases with extensive overlap of their aromatic rings gave rise to numerous often contradictory suggestions about the physical origins of stacking and the possible role of delocalized electrons in stacked aromatic π systems, leading to some confusion about the issue. The recent advance of computer hardware and software finally allowed the application of state of the art quantum-mechanical approaches with inclusion of electron correlation effects to study aromatic base stacking, now providing an ultimitate qualitative description of the phenomenon. Base stacking is determined by an interplay of the three most commonly encountered molecular interactions: dispersion attraction, electrostatic interaction, and short-range repulsion. Unusual (aromatic- stacking specific) energy contributions were in fact not evidenced and are not necessary to describe stacking. The currently used simple empirical potential form, relying on atom-centered constant point charges and Lennard-Jones van der Waals terms, is entirely able to reproduce the essential features of base stacking. Thus, we can conclude that base stacking is in principle one of the best described interactions in current molecular modeling and it allows to study base stacking in DNA using large-scale classical molecular dynamics simulations. Neglect of cooperativity of stacking appears to be the most serious approximation of the currently used force field form. This review summarizes recent developments in the field. It is written for an audience that is not necessarily expert in computational quantum chemistry and follows up on our previous contribution (Sponer et. al., J. Biomol. Struct. Dyn. 14, 117, (1997)). First, the applied methodology, its accuracy, and the physical nature of base stacking is briefly overviewed, including a comment on the accuracy of other molecular orbital methods and force fields. Then, base stacking is contrasted with hydrogen bonding, the other dominant force in nucleic acid structure. The sequence dependence and cooperativity of base stacking is commented on, and finally a brief introduction into recent progress in large-scale molecular dynamics simulations of nucleic acids is provided. Using four stranded DNA assemblies as an example, we demonstrate the efficacy of current molecular dynamics techniques that utilize refined and verified force fields in the study of stacking in nucleic acid molecules.
We report the first complete description of the molecular mechanisms behind the transition of the N-methyl-d-aspartate (NMDA) receptor from the state where the transmembrane domain (TMD) and the ion channel are in the open configuration to the relaxed unliganded state where the channel is closed. Using an aggregate of nearly 1 µs of unbiased all-atom implicit membrane and solvent molecular dynamics (MD) simulations we identified distinct structural states of the NMDA receptor and revealed functionally important residues (GluN1/Glu522, GluN1/Arg695, and GluN2B/Asp786). The role of the "clamshell" motion of the ligand binding domain (LBD) lobes in the structural transition is supplemented by the observed structural similarity at the level of protein domains during the structural transition, combined with the overall large rearrangement necessary for the opening and closing of the receptor. The activated and open states of the receptor are structurally similar to the liganded crystal structure, while in the unliganded receptor the extracellular domains perform rearrangements leading to a clockwise rotation of up to 45 degrees around the longitudinal axis of the receptor, which closes the ion channel. The ligand-induced rotation of extracellular domains transferred by LBD-TMD linkers to the membrane-anchored ion channel is responsible for the opening and closing of the transmembrane ion channel, revealing the properties of NMDA receptor as a finely tuned molecular machine.
Molecular dynamics simulations of complexes between Norwalk virus RNA dependent RNA polymerase and its natural CTP and 2dCTP (both containing the O5'-C5'-C4'-O4' sequence of atoms bridging the triphosphate and sugar moiety) or modified coCTP (C5'-O5'-C4'-O4'), cocCTP (C5'-O5'-C4'-C4'') substrates were produced by means of CUDA programmable graphical processing units and the ACEMD software package. It enabled us to gain microsecond MD trajectories clearly showing that similar nucleoside triphosphates can bind surprisingly differently into the active site of the Norwalk virus RNA dependent RNA polymerase. It corresponds to their different modes of action (CTP-substrate, 2dCTP-poor substrate, coCTP-chain terminator, cocCTP-inhibitor). Moreover, extremely rare events-as repetitive pervasion of Arg182 into a potentially reaction promoting arrangement-were captured.
- MeSH
- cytidintrifosfát analogy a deriváty metabolismus MeSH
- infekce viry z čeledi Caliciviridae virologie MeSH
- lidé MeSH
- Norovirus enzymologie metabolismus MeSH
- RNA-dependentní RNA-polymerasa metabolismus MeSH
- simulace molekulární dynamiky MeSH
- simulace molekulového dockingu MeSH
- substrátová specifita MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
In this study, quantitative structure-activity relationship studies which make use of molecular dynamics trajectories were performed on a set of 54 glucokinase protein activators. The conformations obtained by molecular dynamics simulation were superimposed according to the twelve alignments tested in a virtual three-dimensional box comprised of 2 Å cells. The models were generated by the technique that combines genetic algorithms and partial least squares. The best alignment models generated with a determination coefficient (r(2)) between 0.674 and 0.743 and cross-validation (q(2)) between 0.509 and 0.610, indicating good predictive capacity. The 4D-QSAR models developed in this study suggest novel molecular regions to be explored in the search for better glucokinase activators.
Highly Ca2+ selective channels trigger a large variety of cellular signaling processes in both excitable and non-excitable cells. Among these channels, the Orai channel is unique in its activation mechanism and its structure. It mediates Ca2+ influx into the cytosol with an extremely small unitary conductance over longer time-scales, ranging from minutes up to several hours. Its activation is regulated by the Ca2+ content of the endoplasmic reticulum (ER). Depletion of luminal [Ca2+]ER is sensed by the STIM1 single transmembrane protein that directly binds and gates the Orai1 channel. Orai mediated Ca2+ influx increases cytosolic Ca2+ from 100 nM up to low micromolar range close to the pore and thereby forms Ca2+ microdomains. Hence, these features of the Orai channel can trigger long-term signaling processes without affecting the overall Ca2+ content of a single living cell. Here we focus on the architecture and dynamic conformational changes within the Orai channel. This review summarizes current achievements of molecular dynamics simulations in combination with live cell recordings to address gating and permeation of the Orai channel with molecular precision.
A recent study described an allosteric effect in which the binding of a protein to DNA is influenced by another protein bound nearby. The effect shows a periodicity of ∼10 basepairs and decays with increasing protein-protein distance. As a mechanistic explanation, the authors reported a similar periodic, decaying pattern of the correlation coefficient between major groove widths inferred from a shorter molecular dynamics simulation. Here we show that in a state-of-the-art, microsecond-long simulation of the same DNA sequence, the periodicity of the correlation coefficient is not observed. To study the problem further, we extend an earlier mechanical model of DNA allostery based on constrained minimization of effective quadratic deformation energy of the DNA. We demonstrate that, if the constraints mimicking the bound proteins are properly applied, the periodicity in the binding energy is indeed recovered.
With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.
Ricin is a potent cytotoxin with no available antidote. Its catalytic subunit, RTA, damages the ribosomal RNA (rRNA) of eukaryotic cells, preventing protein synthesis and eventually leading to cell death. The combination between easiness of obtention and high toxicity turns ricin into a potential weapon for terrorist attacks, urging the need of discovering effective antidotes. On this context, we used computational techniques, in order to identify potential ricin inhibitors among approved drugs. Two libraries were screened by two different docking algorithms, followed by molecular dynamics simulations and MM-PBSA calculations in order to corroborate the docking results. Three drugs were identified as potential ricin inhibitors: deferoxamine, leucovorin and plazomicin. Our calculations showed that these compounds were able to, simultaneously, form hydrogen bonds with residues of the catalytic site and the secondary binding site of RTA, qualifying as potential antidotes against intoxication by ricin.Communicated by Ramaswamy H. Sarma.
