Development of CHARMM-Compatible Force-Field Parameters for Cobalamin and Related Cofactors from Quantum Mechanical Calculations

Corrinoid cofactors such as cobalamin are used by many enzymes and are essential for most living organisms. Therefore, there is broad interest in investigating cobalamin–protein interactions with molecular dynamics simulations. Previously developed parameters for cobalamins are based mainly on crystal structure data. Here, we report CHARMM-compatible force field parameters for several corrinoids developed from quantum mechanical calculations. We provide parameters for corrinoids in three oxidation states, Co³⁺, Co²⁺, and Co¹⁺, and with various axial ligands. Lennard-Jones parameters for the cobalt center in the Co­(II) and Co­(I) states were optimized using a helium atom probe, and partial atomic charges were obtained with a combination of natural population analysis (NPA) and restrained electrostatic potential (RESP) fitting approaches. The Force Field Toolkit was used to optimize all bonded terms. The resulting parameters, determined solely from calculations of cobalamin alone or in water, were then validated by assessing their agreement with density functional theory geometries and by analyzing molecular dynamics simulation trajectories of several corrinoid proteins for which X-ray crystal structures are available. In each case, we obtained excellent agreement with the reference data. In comparison to previous CHARMM-compatible parameters for cobalamin, we observe a better agreement for the fold angle and lower RMSD in the cobalamin binding site. The approach described here is readily adaptable for developing CHARMM-compatible force-field parameters for other corrinoids or large biomolecules

Peptidoglycan under strain.

<p>Shown in all panels is the avg17 cell-wall patch. The black bars in A–D are all 10 nm in length. (A,B) Top view with (A) and (B) . (C) Axial view (glycan strands oriented in the plane of the page). (D) Circumferential view (glycan strains pointing into the page). (E) Normalized mass density for (black), (red), and (green). Thickness was taken as the width at 10% of the maximum for each curve separately. A movie of stretching for  = 0.20 is also provided (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003475#pcbi.1003475.s010" target="_blank">Movie S3</a>).</p

Poisson's ratios () and Young's moduli and for simulated peptidoglycan patches compared with reported values from other studies.

<p>Poisson's ratios () and Young's moduli and for simulated peptidoglycan patches compared with reported values from other studies.</p

Properties of single glycan strands.

<p>(A) Calculation of the persistence length of the polysaccharide. Blue spheres along the strand on the left indicate the oxygen atoms involved in the glycosidic bonds between residues. (B) Average angle between neighboring peptides. On the left are images looking down on a portion of the strand (green) with the initial residues of the peptides shown, colored to indicate depth (red, then white, then blue). The plot on the right shows the average peptide-peptide angle as a function of time for one started at (black) and one started at (red). Light restraints (Ų) in the strand direction were placed on the glycosidic oxygen of every other GlcNAc residue to keep the strand elongated without preventing rotation. Also see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003475#pcbi.1003475.s008" target="_blank">Movie S1</a>.</p

Peptidoglycan constituents.

<p>(A) Chemical composition of the monomeric unit of peptidoglycan, consisting of a disaccharide with a connected five-residue peptide. (B) Transpeptidation reaction between two neighboring peptidoglycan strands. The reacting groups contributed by each peptide are boxed in red and green, respectively, before and after being linked.</p

Peptidoglycan patches simulated.

<p>In all parts, glycan strands are in blue and peptides in green. The dotted red line denotes the unit cell boundaries, with the transparent peptidoglycan being periodic copies. The black scale bars below are all equivalent at 10(A) Initially constructed state for avg17 (other patches appeared similarly at this state). (B–D) Final relaxed states for (B) avg8, (C) avg17, and (D) avg26. Inf1 and Inf2 are shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003475#pcbi.1003475.s006" target="_blank">Fig. S6</a> in Supporting Information. Relaxation of avg17 is shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003475#pcbi.1003475.s009" target="_blank">Movie S2</a>.</p

Extraction of Dielectric Permittivity from Atomistic Molecular Dynamics Simulations and Microwave Measurements

The design of new biotechnology depends on the prediction and measurement of the electrical properties of biomolecules. The dielectric permittivity, in particular, is highly important for the design of microwave systems for diagnostics, yet this property is rarely explicitly targeted during the development of biomolecular force fields for molecular dynamics (MD) simulations. In order to explore the ability of existing force fields to reproduce the frequency-dependent permittivity, we carried out MD simulations of various aqueous solutions, including pure water, isopropyl alcohol, alanine, and the protein ubiquitin. The TIP3P, TIP4P, TIP4P/ε, and SWM4-NDP water models were used along with the CHARMM36m and Drude protein force fields. An experimental setup using a truncated coaxial line was created to measure the permittivity of the same solutions to check for measure-model agreement. We found that one of the nonpolarizable force fields (TIP4P/ε + CHARMM36m) and the polarizable force fields (SWM4-NDP + Drude) closely agree with experimental results. This demonstrates the strength of the tuned TIP4P/ε water model, as well as the physical validity of polarizable force fields in capturing dielectric permittivity. This represents an important step toward the predictive design of biosensors

BFEE: A User-Friendly Graphical Interface Facilitating Absolute Binding Free-Energy Calculations

Quantifying protein–ligand binding has attracted the attention of both theorists and experimentalists for decades. Many methods for estimating binding free energies <i>in silico</i> have been reported in recent years. Proper use of the proposed strategies requires, however, adequate knowledge of the protein–ligand complex, the mathematical background for deriving the underlying theory, and time for setting up the simulations, bookkeeping, and postprocessing. Here, to minimize human intervention, we propose a toolkit aimed at facilitating the accurate estimation of standard binding free energies using a geometrical route, coined the binding free-energy estimator (BFEE), and introduced it as a plug-in of the popular visualization program VMD. Benefitting from recent developments in new collective variables, BFEE can be used to generate the simulation input files, based solely on the structure of the complex. Once the simulations are completed, BFEE can also be utilized to perform the post-treatment of the free-energy calculations, allowing the absolute binding free energy to be estimated directly from the one-dimensional potentials of mean force in simulation outputs. The minimal amount of human intervention required during the whole process combined with the ergonomic graphical interface makes BFEE a very effective and practical tool for the end-user

Transitions of Double-Stranded DNA Between the A- and B‑Forms

The structure of double-stranded DNA (dsDNA) is sensitive to solvent conditions. In solution, B-DNA is the favored conformation under physiological conditions, while A-DNA is the form found under low water activity. The A-form is induced locally in some protein–DNA complexes, and repeated transitions between the B- and A-forms have been proposed to generate the forces used to drive dsDNA into viral capsids during genome packaging. Here, we report analyses on previous molecular dynamics (MD) simulations on B-DNA, along with new MD simulations on the transition from A-DNA to B-DNA in solution. We introduce the A-B Index (ABI), a new metric along the A-B continuum, to quantify our results. When A-DNA is placed in an equilibrated solution at physiological ionic strength, there is no energy barrier to the transition to the B-form, which begins within about 1 ns. The transition is essentially complete within 5 ns, although occasionally a stretch of a few base pairs will remain A-like for up to ∼10 ns. A comparison of four sequences with a range of predicted A-phobicities shows that more A-phobic sequences make the transition more rapidly than less A-phobic sequences. Simulations on dsDNA with a region of roughly one turn locked in the A-form allow us to characterize the A/B junction, which has an average bend angle of 20–30°. Fluctuations in this angle occur with characteristic times of about 10 ns

Biophysics-Guided Lead Discovery of HBV Capsid Assembly Modifiers

Hepatitis B virus (HBV) is the leading cause of chronic liver pathologies worldwide. HBV nucleocapsid, a key structural component, is formed through the self-assembly of the capsid protein units. Therefore, interfering with the self-assembly process is a promising approach for the development of novel antiviral agents. Applied to HBV, this approach has led to several classes of capsid assembly modulators (CAMs). Here, we report structurally novel CAMs with moderate activity and low toxicity, discovered through a biophysics-guided approach combining docking, molecular dynamics simulations, and a series of assays with a particular emphasis on biophysical experiments. Several of the identified compounds induce the formation of aberrant capsids and inhibit HBV DNA replication in vitro, suggesting that they possess modest capsid assembly modulation effects. The synergistic computational and experimental approaches provided key insights that facilitated the identification of compounds with promising activities. The discovery of preclinical CAMs presents opportunities for subsequent optimization efforts, thereby opening new avenues for HBV inhibition