Theoretical Methods for the Description of the Solvent Effect in Biomolecular Systems.

Nanosecond length simulations applying the particle mesh Ewald method within AMBER 4.1 on canonical A-form and B-form geometries of d[CCAACGTTGG]2, r[CCAACGUUGG]2, and d[CCAACGTTGG]−r[CCAACGUUGG] duplexes in aqueous solution are reported. DNA duplexes only adopt a stable B-DNA geometry, in contrast to RNA duplexes which adopt both a stable A-RNA and “B-RNA” geometry. The observation of a stable “B-RNA” structure is somewhat surprising and suggests significant kinetic barriers to structural conversion in RNA structures on a nanosecond time scale. The “B-RNA” can be converted to A-RNA by forcing a concerted flip in the sugar puckers from C2‘-endo to C3‘-endo. The A-RNA structure displays features similar to A-form crystal structures, specifically interstrand purine stacking at the central pyrimidine−purine step is observed. When started in a canonical A-form geometry, DNA:RNA hybrid duplexes converge to a structure that is characteristic of experimental solution structures; specifically, a minor groove widt...

Molecular dynamics simulations highlight the structural differences among DNA: DNA, RNA:RNA, and DNA:RNA hybrid duplexes

Determining the principal energy-transfer pathways responsible for allosteric communication in biomolecules remains challenging, partially due to the intrinsic complexity of the systems and the lack of effective characterization methods. In this work, we introduce the eigenvector centrality metric based on mutual information to elucidate allosteric mechanisms that regulate enzymatic activity. Moreover, we propose a strategy to characterize the range of correlations that underlie the allosteric processes. We use the V-type allosteric enzyme imidazole glycerol phosphate synthase (IGPS) to test the proposed methodology. The eigenvector centrality method identifies key amino acid residues of IGPS with high susceptibility to effector binding. The findings are validated by solution NMR measurements yielding important biological insights, including direct experimental evidence for interdomain motion, the central role played by helix h[Formula: see text], and the short-range nature of correlations responsible for the allosteric mechanism. Beyond insights on IGPS allosteric pathways and the nature of residues that could be targeted by therapeutic drugs or site-directed mutagenesis, the reported findings demonstrate the eigenvector centrality analysis as a general cost-effective methodology to gain fundamental understanding of allosteric mechanisms at the molecular level.

https://www.pnas.org/content/pnas/115/52/E12201.full.pdf

Eigenvector centrality for characterization of protein allosteric pathways.

Calculations of nucleic acid conformations

Statistical and epidemiological data imply temperature sensitivity of the SARS-CoV-2 coronavirus. However, the molecular level understanding of the virus structure at different temperature is still not clear. Spike protein is the outermost structural protein of the SARS-CoV-2 virus which interacts with the Angiotensin Converting Enzyme 2 (ACE2), a human receptor, and enters the respiratory system. In this study, we performed an all atom molecular dynamics simulation to study the effect of temperature on the structure of the Spike protein. After 200 ns of simulation at different temperatures, we came across some interesting phenomena exhibited by the protein. We found that the solvent exposed domain of Spike protein, namely S1, is more mobile than the transmembrane domain, S2. Structural studies implied the presence of several charged residues on the surface of N-terminal Domain of S1 which are optimally oriented at 10-30°C. Bioinformatics analyses indicated that it is capable of binding to other human receptors and should not be disregarded. Additionally, we found that receptor binding motif (RBM), present on the receptor binding domain (RBD) of S1, begins to close around temperature of 40°C and attains a completely closed conformation at 50°C. We also found that the presence of glycan moieties did not influence the observed protein dynamics. Nevertheless, the closed conformation disables its ability to bind to ACE2, due to the burying of its receptor binding residues. Our results clearly show that there are active and inactive states of the protein at different temperatures. This would not only prove beneficial for understanding the fundamental nature of the virus, but would be also useful in the development of vaccines and therapeutics.

/pdf/investigation-of-the-effect-of-temperature-on-the-structure-4s2wk38kpq.pdf

Investigation of the Effect of Temperature on the Structure of SARS-CoV-2 Spike Protein by Molecular Dynamics Simulations

We present a simple method for compression and management of very large molecular dynamics trajectories. The approach is based on the projection of the Cartesian snapshots collected along the trajectory into an orthogonal space defined by the eigenvectors obtained by diagonalization of the covariance matrix. The transformation is mathematically exact when the number of eigenvectors equals 3N-6 (N being the number of atoms), and in practice very accurate even when the number of eigenvectors is much smaller, permitting a dramatic reduction in the size of trajectory files. In addition, we have examined the ability of the method, when combined with interpolation, to recover dense samplings (snapshots collected at a high frequency) from more sparse (lower frequency) data as a method for further data compression. Finally, we have investigated the possibility of using the approach when extrapolating the behavior of the system to times longer than the original simulation period. Overall our results suggest that the method is an attractive alternative to current approaches for including dynamic information in static structure files such as those deposited in the Protein Data Bank.

Essential Dynamics: A Tool for Efficient Trajectory Compression and Management

Counterion distribution around dna studied by molecular dynamics and quantum mechanical simulations

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Essential Dynamics: A Tool for Efficient Trajectory Compression and Management

Counterion distribution around dna studied by molecular dynamics and quantum mechanical simulations