Development of a “First Principles” Water Potential with Flexible Monomers: Dimer Potential Energy Surface, VRT Spectrum, and Second Virial Coefficient

The development of a “first principles” water potential with flexible monomers (MB-pol) for molecular simulations of water systems from gas to condensed phases is described. MB-pol is built upon the many-body expansion of the intermolecular interactions, and the specific focus of this study is on the two-body term (V_2B) representing the full-dimensional intermolecular part of the water dimer potential energy surface. V_2B is constructed by fitting 40,000 dimer energies calculated at the CCSD­(T)/CBS level of theory and imposing the correct asymptotic behavior at long-range as predicted from “first principles”. The comparison of the calculated vibration–rotation tunneling (VRT) spectrum and second virial coefficient with the corresponding experimental results demonstrates the accuracy of the MB-pol dimer potential energy surface

Theoretical Modeling of Spin Crossover in Metal–Organic Frameworks: [Fe(pz)₂Pt(CN)₄] as a Case Study

Metal–organic frameworks (MOFs) with spin-crossover behavior are promising materials for applications in memory storage and sensing devices. A key parameter that characterizes these materials is the transition temperature <i>T</i>_1/2, defined as the temperature with equal populations of low-spin and high-spin species. In this study, we describe the development, implementation, and application of a novel hybrid Monte Carlo/molecular dynamics method that builds upon the Ligand Field Molecular Mechanics approach and enables the modeling of spin-crossover properties in bulk materials. The new methodology is applied to the study of a spin-crossover MOF with molecular formula [Fe­(pz)₂Pt­(CN)₄] (pz = pyrazine). The total magnetic moment of the material is determined as a function of the temperature from direct calculations of the relative equilibrium populations of both low-spin and high-spin states of each Fe­(II) center of the framework. The <i>T</i>_1/2 value, calculated from the temperature dependence of the magnetization curve, is in good agreement with the available experimental data. A comparison between the spin-crossover behavior of the isolated secondary building block of the framework and the bulk material is presented, which reveals the origin of the different spin-crossover properties of the isolated molecular system and corresponding MOF structure

Erratum: Development of a “First-Principles” Water Potential with Flexible Monomers: Dimer Potential Energy Surface, VRT Spectrum, and Second Virial Coefficient

Erratum: Development of a “First-Principles” Water Potential with Flexible Monomers: Dimer Potential Energy Surface, VRT Spectrum, and Second Virial Coefficien

Development of a “First Principles” Water Potential with Flexible Monomers. II: Trimer Potential Energy Surface, Third Virial Coefficient, and Small Clusters

A full-dimensional potential energy function (MB-pol) for simulations of water from the dimer to bulk phases is developed entirely from “first principles” by building upon the many-body expansion of the interaction energy. Specifically, the MB-pol potential is constructed by combining a highly accurate dimer potential energy surface [<i>J. Chem. Theory Comput.</i> <b>2013</b>, <i>9</i>, 5395] with explicit three-body and many-body polarization terms. The three-body contribution, expressed as a combination of permutationally invariant polynomials and classical polarizability, is derived from a fit to more than 12000 three-body energies calculated at the CCSD­(T)/aug-cc-pVTZ level of theory, imposing the correct asymptotic behavior as predicted from “first principles”. Here, the accuracy of MB-pol is demonstrated through comparison of the calculated third virial coefficient with the corresponding experimental data as well as through analysis of the relative energy differences of small clusters

Toward a Universal Water Model: First Principles Simulations from the Dimer to the Liquid Phase

A full-dimensional model of water, HBB2-pol, derived entirely from “first-principles”, is introduced and employed in computer simulations ranging from the dimer to the liquid. HBB2-pol provides excellent agreement with the measured second and third virial coefficients and, by construction, reproduces the dimer vibration–rotation–tunneling spectrum. The model also predicts the relative energy differences between isomers of small water clusters within the accuracy of highly correlated electronic structure methods. Importantly, when combined with simulation methods that explicitly include zero-point energy and quantum thermal motion, HBB2-pol accurately describes both structural and dynamical properties of the liquid phase

Helix and turn populations of the polyQ peptides.

<p>The helical content is partitioned into - and -helix populations. The structures are also categorized based on the number of their helical segments. The population of each category (0,1,2,) is given if greater than %. The turn content is partitioned based on both the hydrogen-bonding and turn types. For the secondary structure prediction, the DSSP analysis code <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Kabsch1" target="_blank">[58]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Joosten1" target="_blank">[59]</a> was used along with the protocols discussed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#s2" target="_blank"><i>Methods</i></a>.</p

Sample conformations of

<p><b> and </b><b>.</b> Cartoon representation of sample conformations of (a) and (b) . Purple, blue, cyan, and orange represent -helix, -helix, turn, and coil secondary structural motifs, respectively. The licorice-like representation of the proline segment of is given in (b). These structures are plotted by VMD <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Humphrey1" target="_blank">[61]</a> using STRIDE <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Frishman1" target="_blank">[60]</a> for secondary structure prediction.</p

(a) Schematic of amino acid backbone dihedrals

<p><b> and </b><b>, and (b) a corresponding Ramachandran plot.</b> In a typical Ramachandran plot of a glutamine residue, each pixel represents a bin, whose intensity represents its relative population, ranging from 1,2,,9, and 10 or more conformations, sampled in our simulations. Blue, yellow, grey, and pink clusters identify PPII, , , and regions, respectively.</p

Distribution of radius of gyration of polyQ peptides.

<p>(a) The estimated distribution for [red] and [blue]. (b) The estimated distribution for [red] and [blue]. The blue curve can be estimated as the sum [black] of three Gaussian distributions [dotted]. (c) The estimated distribution for , considering only the structures with an all-trans proline segment [green]. Similarly the green curve can be estimated as the sum [black] of four Gaussian distributions [dotted]. Considering only the structures that at least have one cis-proline results in the magenta curve for the distribution. All the histograms are obtained using a window of width . (d) The exponent in relation estimated from select pairs of (x axis) and ( for blue circles and for yellow squares). Inset: The average (in ) of Q peptides for .</p

Helical, turn and coil content of selected polyQ peptides.

<p>Here, given are the contents (as a percentage) of individual glutamine residues found in the following conformations: (a,b) helical (,) (c,d) turn (H-bonded,bend) (e,f) coil. These percentages are plotted against the Glu residue numbers for (a,c,e) [red],[blue] and (b,d,f) [red], [blue]. These percentages are obtained from the DSSP <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Kabsch1" target="_blank">[58]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Joosten1" target="_blank">[59]</a> analysis code.</p