Polarizable Water Model for the Coarse-Grained MARTINI Force Field

Coarse-grained (CG) simulations have become an essential tool to study a large variety of biomolecular processes, exploring temporal and spatial scales inaccessible to traditional models of atomistic resolution. One of the major simplifications of CG models is the representation of the solvent, which is either implicit or modeled explicitly as a van der Waals particle. The effect of polarization, and thus a proper screening of interactions depending on the local environment, is absent. Given the important role of water as a ubiquitous solvent in biological systems, its treatment is crucial to the properties derived from simulation studies. Here, we parameterize a polarizable coarse-grained water model to be used in combination with the CG MARTINI force field. Using a three-bead model to represent four water molecules, we show that the orientational polarizability of real water can be effectively accounted for. This has the consequence that the dielectric screening of bulk water is reproduced. At the same time, we parameterized our new water model such that bulk water density and oil/water partitioning data remain at the same level of accuracy as for the standard MARTINI force field. We apply the new model to two cases for which current CG force fields are inadequate. First, we address the transport of ions across a lipid membrane. The computed potential of mean force shows that the ions now naturally feel the change in dielectric medium when moving from the high dielectric aqueous phase toward the low dielectric membrane interior. In the second application we consider the electroporation process of both an oil slab and a lipid bilayer. The electrostatic field drives the formation of water filled pores in both cases, following a similar mechanism as seen with atomistically detailed models

The power of coarse graining in biomolecular simulations

Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling

Pulmonary Surfactant Lipid Reorganization Induced by the Adsorption of the Oligomeric Surfactant Protein B Complex

Surfactant protein B (SP-B) is essential in transferring surface-active phospholipids from membrane-based surfactant complexes into the alveolar air-liquid interface. This allows maintaining the mechanical stability of the surfactant film under high pressure at the end of expiration; therefore, SP-B is crucial in lung function. Despite its necessity, the structure and the mechanism of lipid transfer by SP-B have remained poorly characterized. Earlier, we proposed higher-order oligomerization of SP-B into ring-like supramolecular assemblies. In the present work, we used coarse-grained molecular dynamics simulations to elucidate how the ring-like oligomeric structure of SP-B determines its membrane binding and lipid transfer. In particular, we explored how SP-B interacts with specific surfactant lipids, and how consequently SP-B reorganizes its lipid environment to modulate the pulmonary surfactant structure and function. Based on these studies, there are specific lipid-protein interactions leading to perturbation and reorganization of pulmonary surfactant layers. Especially, we found compelling evidence that anionic phospholipids and cholesterol are needed or even crucial in the membrane binding and lipid transfer function of SP-B. Also, on the basis of the simulations, larger oligomers of SP-B catalyze lipid transfer between adjacent surfactant layers. Better understanding of the molecular mechanism of SP-B will help in the design of therapeutic SP-B-based preparations and novel treatments for fatal respiratory complications, such as the acute respiratory distress syndrome. (C) 2020 The Author(s). Published by Elsevier Ltd.Peer reviewe

Charge-dependent interactions of monomeric and filamentous actin with lipid bilayers

The cytoskeletal protein actin polymerizes into filaments that are essential for the mechanical stability of mammalian cells. In vitro experiments showed that direct interactions between actin filaments and lipid bilayers are possible and that the net charge of the bilayer as well as the presence of divalent ions in the buffer play an important role. In vivo, colocalization of actin filaments and divalent ions are suppressed, and cells rely on linker proteins to connect the plasma membrane to the actin network. Little is known, however, about why this is the case and what microscopic interactions are important. A deeper understanding is highly beneficial, first, to obtain understanding in the biological design of cells and, second, as a possible basis for the building of artificial cortices for the stabilization of synthetic cells. Here, we report the results of coarse-grained molecular dynamics simulations of monomeric and filamentous actin in the vicinity of differently charged lipid bilayers. We observe that charges on the lipid head groups strongly determine the ability of actin to adsorb to the bilayer. The inclusion of divalent ions leads to a reversal of the binding affinity. Our in silico results are validated experimentally by reconstitution assays with actin on lipid bilayer membranes and provide a molecular-level understanding of the actin-membrane interaction.</p

Coarse-grained modeling for molecular discovery:Applications to cardiolipin-selectivity

The development of novel materials is pivotal for addressing global challenges such as achieving sustainability, technological progress, and advancements in medical technology. Traditionally, developing or designing new molecules was a resource-intensive endeavor, often reliant on serendipity. Given the vast space of chemically feasible drug-like molecules, estimated between 106 - 10100 compounds, traditional in vitro techniques fall short.Consequently, in silico tools such as virtual screening and molecular modeling have gained increasing recognition. However, the computational cost and the limited precision of the utilized molecular models still limit computational molecular design.This thesis aimed to enhance the molecular design process by integrating multiscale modeling and free energy calculations. Employing a coarse-grained model allowed us to efficiently traverse a significant portion of chemical space and reduce the sampling time required by molecular dynamics simulations. The physics-informed nature of the applied Martini force field and its level of retained structural detail make the model a suitable starting point for the focused learning of molecular properties.We applied our proposed approach to a cardiolipin bilayer, posing a relevant and challenging problem and facilitating reasonable comparison to experimental measurements.We identified promising molecules with defined properties within the resolution limit of a coarse-grained representation. Furthermore, we were able to bridge the gap from in silico predictions to in vitro and in vivo experiments, supporting the validity of the theoretical concept. The findings underscore the potential of multiscale modeling and free-energy calculations in enhancing molecular discovery and design and offer a promising direction for future research

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead

Coarse-grained modeling for molecular discovery:Applications to cardiolipin-selectivity

The development of novel materials is pivotal for addressing global challenges such as achieving sustainability, technological progress, and advancements in medical technology. Traditionally, developing or designing new molecules was a resource-intensive endeavor, often reliant on serendipity. Given the vast space of chemically feasible drug-like molecules, estimated between 106 - 10100 compounds, traditional in vitro techniques fall short.Consequently, in silico tools such as virtual screening and molecular modeling have gained increasing recognition. However, the computational cost and the limited precision of the utilized molecular models still limit computational molecular design.This thesis aimed to enhance the molecular design process by integrating multiscale modeling and free energy calculations. Employing a coarse-grained model allowed us to efficiently traverse a significant portion of chemical space and reduce the sampling time required by molecular dynamics simulations. The physics-informed nature of the applied Martini force field and its level of retained structural detail make the model a suitable starting point for the focused learning of molecular properties.We applied our proposed approach to a cardiolipin bilayer, posing a relevant and challenging problem and facilitating reasonable comparison to experimental measurements.We identified promising molecules with defined properties within the resolution limit of a coarse-grained representation. Furthermore, we were able to bridge the gap from in silico predictions to in vitro and in vivo experiments, supporting the validity of the theoretical concept. The findings underscore the potential of multiscale modeling and free-energy calculations in enhancing molecular discovery and design and offer a promising direction for future research

Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models Through Virtual Particles

Coarse-grained (CG) models parameterized using atomistic reference data, i.e., 'bottom up' CG models, have proven useful in the study of biomolecules and other soft matter. However, the construction of highly accurate, low resolution CG models of biomolecules remains challenging. We demonstrate in this work how virtual particles, CG sites with no atomistic correspondence, can be incorporated into CG models within the context of relative entropy minimization (REM) as latent variables. The methodology presented, variational derivative relative entropy minimization (VD-REM), enables optimization of virtual particle interactions through a gradient descent algorithm aided by machine learning. We apply this methodology to the challenging case of a solvent-free CG model of a 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) lipid bilayer and demonstrate that introduction of virtual particles captures solvent-mediated behavior and higher-order correlations which REM alone cannot capture in a more standard CG model based only on the mapping of collections of atoms to the CG sites.Comment: 35 pages, 9 figure

Modeling and Simulation of Membrane Proteins to Understand their Structure, Dynamics and Function

Human cytochrome P450 (CYP) enzymes play an important role in the metabolism of drugs, steroids, fatty acids and xenobiotics. CYPs also catalyze the conversion of some pro-drugs into active drugs. Only about a dozen human CYPs metabolize 70-80% of all drugs. A subset of CYPs is responsible for steroidogenesis, of these CYP17 is a major drug target for prostate cancer therapy. Human CYPs are anchored to the endoplasmic reticulum membrane by their N-terminal transmembrane (TM) helix. However, most crystal structures of CYPs have been resolved after truncating the TM-helix or mutating residues that form contacts with the membrane. Therefore, the structural basis for CYP-membrane interactions and orientation, and the mechanism of substrate entrance into the buried binding pocket and product release is not clearly understood. In order to understand the interactions and orientations of CYPs and their degree of penetration into the membrane, I have optimized a multiscale modeling protocol that involves coarse-grained and all-atom molecular dynamics simulations. The protocol was validated by applying it to several drug-metabolizing CYPs (CYP1A1, 1A2, 2C9, 2C19, 3A4) and CYPs involved in steroidogenesis (CYP17, CYP19) in a lipid bilayer. The simulations revealed that the sequence and structural differences in the protein-membrane interface alter the interactions and orientations of CYPs in the membrane. Furthermore, mutations in the TM-helix of CYP17, particularly W2A and E3L, were seen to disrupt the CYP-membrane interactions and in some cases, obstruct the ligand tunnels between the active site and the membrane, which could lower enzyme turnover. In conclusion, the optimized multiscale simulation protocol has been used to identify different interactions and orientations adopted by the globular domains of CYPs with the membrane that have implications for CYP function. This protocol is also suitable for studying protein-protein-membrane complexes and proteins in membranes with different lipid compositions