Simulations of HIV capsid protein dimerization reveal the effect of chemistry and topography on the mechanism of hydrophobic protein association

Recent work has shown that the hydrophobic protein surfaces in aqueous solution sit near a drying transition. The tendency for these surfaces to expel water from their vicinity leads to self assembly of macromolecular complexes. In this article we show with a realistic model for a biologically pertinent system how this phenomenon appears at the molecular level. We focus on the association of the C-terminal domain (CA-C) of the human immunodeficiency virus (HIV) capsid protein. By combining all-atom simulations with specialized sampling techniques we measure the water density distribution during the approach of two CA-C proteins as a function of separation and amino acid sequence in the interfacial region. The simulations demonstrate that CA-C protein-protein interactions sit at the edge of a dewetting transition and that this mesoscopic manifestation of the underlying liquid-vapor phase transition can be readily manipulated by biology or protein engineering to significantly affect association behavior. While the wild type protein remains wet until contact, we identify a set of in silico mutations, in which three hydrophilic amino acids are replaced with nonpolar residues, that leads to dewetting prior to association. The existence of dewetting depends on the size and relative locations of substituted residues separated by nm length scales, indicating long range cooperativity and a sensitivity to surface topography. These observations identify important details which are missing from descriptions of protein association based on buried hydrophobic surface area

Confinement Effects on the Kinetics and Thermodynamics of Protein Dimerization

In the cell, protein complexes form relying on specific interactions between their monomers. Excluded volume effects due to molecular crowding would lead to correlations between molecules even without specific interactions. What is the interplay of these effects in the crowded cellular environment? We study dimerization of a model homodimer both when the mondimers are free or tethered to each other. We consider a structured environment: Two monomers first diffuse into a cavity of size $L$ and then fold and bind within the cavity. The folding and binding are simulated using molecular dynamics based on a simplified topology based model. The {\it confinement} in the cell is described by an effective molecular concentration $C \sim L^{-3}$. A two-state coupled folding and binding behavior is found. We show the maximal rate of dimerization occurred at an effective molecular concentration $C^{op}\simeq 1m$M which is a relevant cellular concentration. In contrast, for tethered chains the rate keeps at a plateau when $CC^{op}$. For both the free and tethered cases, the simulated variation of the rate of dimerization and thermodynamic stability with effective molecular concentration agrees well with experimental observations. In addition, a theoretical argument for the effects of confinement on dimerization is also made

A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation

Many important cellular processes are regulated by reaction-diffusion (RD) of molecules that takes place both in the cytoplasm and on the membrane. To model and analyze such multicompartmental processes, we developed a lattice-based Monte Carlo method, Spatiocyte that supports RD in volume and surface compartments at single molecule resolution. Stochasticity in RD and the excluded volume effect brought by intracellular molecular crowding, both of which can significantly affect RD and thus, cellular processes, are also supported. We verified the method by comparing simulation results of diffusion, irreversible and reversible reactions with the predicted analytical and best available numerical solutions. Moreover, to directly compare the localization patterns of molecules in fluorescence microscopy images with simulation, we devised a visualization method that mimics the microphotography process by showing the trajectory of simulated molecules averaged according to the camera exposure time. In the rod-shaped bacterium _Escherichia coli_, the division site is suppressed at the cell poles by periodic pole-to-pole oscillations of the Min proteins (MinC, MinD and MinE) arising from carefully orchestrated RD in both cytoplasm and membrane compartments. Using Spatiocyte we could model and reproduce the _in vivo_ MinDE localization dynamics by accounting for the established properties of MinE. Our results suggest that the MinE ring, which is essential in preventing polar septation, is largely composed of MinE that is transiently attached to the membrane independently after recruited by MinD. Overall, Spatiocyte allows simulation and visualization of complex spatial and reaction-diffusion mediated cellular processes in volumes and surfaces. As we showed, it can potentially provide mechanistic insights otherwise difficult to obtain experimentally

Pitfalls of the Martini Model

R.A. thanks The Netherlands Organisation for Scientific Research NWO (Graduate Programme Advanced Materials, No. 022.005.006) for financial support. S.T. thanks the European Commission for financial support via a Marie Skłodowska-Curie Actions Individual Fellowship (MicroMod-PSII, grant agreement 748895).The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.publishersversionpublishe

Molecular modeling study of β-lactoglobulin dimerization: a first step to hypoallergen design for immunotherapy

"Milk and its derivatives are important worldwide food sources, particularly for infant nutrition, but face a major health complication: some of their proteins are allergens, especially β-lactoglobulin (BLG), a major component of bovine milk. The fate of BLG upon ingestion remains unsettled, being unclear how extensive BLG proteolysis is and how it affects allergenicity. The fact that proteolytic resistance and antigenic response remain related even for non-oral administration suggests that they are not causally related but rather reflect an underlying common feature.(...)

DNA cyclization and looping in the wormlike limit: normal modes and the validity of the harmonic approximation

For much of the last three decades Monte Carlo-simulation methods have been the standard approach for accurately calculating the cyclization probability, $J$, or J factor, for DNA models having sequence-dependent bends or inhomogeneous bending flexibility. Within the last ten years, however, approaches based on harmonic analysis of semi-flexible polymer models have been introduced, which offer much greater computational efficiency than Monte Carlo techniques. These methods consider the ensemble of molecular conformations in terms of harmonic fluctuations about a well-defined elastic-energy minimum. However, the harmonic approximation is only applicable for small systems, because the accessible conformation space of larger systems is increasingly dominated by anharmonic contributions. In the case of computed values of the J factor, deviations of the harmonic approximation from the exact value of $J$ as a function of DNA length have not been characterized. Using a recent, numerically exact method that accounts for both anharmonic and harmonic contributions to $J$ for wormlike chains of arbitrary size, we report here the apparent error that results from neglecting anharmonic behavior. For wormlike chains having contour lengths less than four times the persistence length the error in $J$ arising from the harmonic approximation is generally small, amounting to free energies less than the thermal energy, $k_B T$. For larger systems, however, the deviations between harmonic and exact $J$ values increase approximately linearly with size.Comment: 23 pages, 6 figures. Typos corrected. Manuscript improve

Molecular mechanism of action of tyrocidine antimicrobial peptides using NMR spectroscopy and computational techniques

Includes abstract.Includes bibliographical references.The need to come up with new and novel antibiotics that utilize unique mechanisms, to which bacteria cannot generate resistance, was the main motivation of this study. Tyrocidine peptides are non-selective antibiotics that have such properties. However, very limited information is available about their mechanism of action. The aim of this study was to determine the mechanism of action of tyrocidine peptides, tyrocidine A, tyrocidine B and tyrocidine C

The Poisson-Boltzmann model for implicit solvation of electrolyte solutions: Quantum chemical implementation and assessment via Sechenov coefficients.

We present the theory and implementation of a Poisson-Boltzmann implicit solvation model for electrolyte solutions. This model can be combined with arbitrary electronic structure methods that provide an accurate charge density of the solute. A hierarchy of approximations for this model includes a linear approximation for weak electrostatic potentials, finite size of the mobile electrolyte ions, and a Stern-layer correction. Recasting the Poisson-Boltzmann equations into Euler-Lagrange equations then significantly simplifies the derivation of the free energy of solvation for these approximate models. The parameters of the model are either fit directly to experimental observables-e.g., the finite ion size-or optimized for agreement with experimental results. Experimental data for this optimization are available in the form of Sechenov coefficients that describe the linear dependence of the salting-out effect of solutes with respect to the electrolyte concentration. In the final part, we rationalize the qualitative disagreement of the finite ion size modification to the Poisson-Boltzmann model with experimental observations by taking into account the electrolyte concentration dependence of the Stern layer. A route toward a revised model that captures the experimental observations while including the finite ion size effects is then outlined. This implementation paves the way for the study of electrochemical and electrocatalytic processes of molecules and cluster models with accurate electronic structure methods

Multiscale modeling of organic materials:from the Morphology Up

The field of organic electronics promises a host of thin, lightweight, flexible, and environmentally friendly electronic devices. Such devices are made possible by the use of organic materials, materials constituted by organic molecules which possibly possess interesting electronic properties. To fulfill this promise, scientists need to resolve one fundamental complication which finds its roots in the virtually infinite possibilities offered by organic molecules: master the relations between the molecular structure of the single molecules, their aggregate morphology and the performance of the resulting electronic device. In this context, the aim of this thesis is to demonstrate how information on the molecular organization of organic materials can be obtained by a multiscale modeling approach. The term “multiscale” designates the combined use of various modeling techniques with the aim of covering a large range of length and time scales, from the molecular-scale towards the device-scale. This allows to connect features of the single molecules to their collective structural organization and to understand how this, in turn, affects the electronic properties of the organic material, and thus of the resulting electronic device.This thesis enables multiple developments and extensions, including the possibility of simulating an ever-larger number of organic materials, while systematically connecting the obtained morphologies to the electronic properties which are fundamental to the functioning of the resulting electronic devices. Taken together, the findings of this thesis contribute to the route towards an age where the design of organic materials is based on computational models and simulations