Phytochemicals perturb membranes and promiscuously alter protein function

A wide variety of phytochemicals are consumed for their perceived health benefits. Many of these phytochemicals have been found to alter numerous cell functions, but the mechanisms underlying their biological activity tend to be poorly understood. Phenolic phytochemicals are particularly promiscuous modifiers of membrane protein function, suggesting that some of their actions may be due to a common, membrane bilayer-mediated mechanism. To test whether bilayer perturbation may underlie this diversity of actions, we examined five bioactive phenols reported to have medicinal value: capsaicin from chili peppers, curcumin from turmeric, EGCG from green tea, genistein from soybeans, and resveratrol from grapes. We find that each of these widely consumed phytochemicals alters lipid bilayer properties and the function of diverse membrane proteins. Molecular dynamics simulations show that these phytochemicals modify bilayer properties by localizing to the bilayer/solution interface. Bilayer-modifying propensity was verified using a gramicidin-based assay, and indiscriminate modulation of membrane protein function was demonstrated using four proteins: membrane-anchored metalloproteases, mechanosensitive ion channels, and voltage-dependent potassium and sodium channels. Each protein exhibited similar responses to multiple phytochemicals, consistent with a common, bilayer-mediated mechanism. Our results suggest that many effects of amphiphilic phytochemicals are due to cell membrane perturbations, rather than specific protein binding.

The influence of fatty acids on the GpA dimer interface by coarse-grained molecular dynamics simulation

The hydrophobic thickness of membranes, which is manly defined by fatty acids, influences the packing of transmembrane domains of proteins and thus can modulate the activity of these proteins. We analyzed the dynamics of the dimerization of Glycophorin A (GpA) by molecular dynamics simulations to describe the fatty acid dependence of the transmembrane region assembly. GpA represents a well-established model for dimerization of single transmembrane helices containing a GxxxG motif in vitro and in silico. We performed simulations of the dynamics of the NMR-derived dimer as well as self-assembly simulations of monomers in membranes composed of different fatty acid chains and monitored the formed interfaces and their transitions. The observed dimeric interfaces, which also include the one known from NMR, are highly dynamic and converted into each other. The frequency of interface formation and the preferred transitions between interfaces similar to the interface observed by NMR analysis strongly depend on the fatty acid used to build the membrane. Molecular dynamic simulations after adaptation of the helix topology parameters to better represent NMR derived structures of single transmembrane helices yielded an enhanced occurrence of the interface determined by NMR in molecular dynamics simulations. Taken together we give insights into the influence of fatty acids and helix conformation on the dynamics of the transmembrane domain of GpA.

Structural dynamics of the cell wall precursor lipid II in the presence and absence of the lantibiotic nisin

Representing a physiological "Achilles' heel", the cell wall precursor lipid II (LII) is a prime target for various classes of antibiotics. Over the years LII-binding agents have been recognized as promising candidates and templates in the search for new antibacterial compounds to complement or replace existing drugs. To elucidate the molecular structural basis underlying LII functional mechanism and to better understand if and how lantibiotic binding alters the molecular behavior of LII, we performed molecular dynamics (MD) simulations of phospholipid membrane-embedded LII in the absence and presence of the LII-binding lantibiotic nisin. In a series of 2×4 independent, unbiased 100ns MD simulations we sampled the conformational dynamics of nine LII as well as nine LII-nisin complexes embedded in an aqueous 150mM NaCl/POPC phospholipid membrane environment. We found that nisin binding to LII induces a reduction of LII mobility and flexibility, an outward shift of the LII pentapeptide, an inward movement of the LII disaccharide section, and an overall deeper insertion of the LII tail group into the membrane. The latter effect might indicate an initial step in adopting a stabilizing, scaffold-like structure in the process of nisin-induced membrane leakage. At the same time nisin conformation and LII interaction remain similar to the 1WCO LII-nisin NMR solution structure.

MARTINI bead form factors for the analysis of time-resolved X-ray scattering of proteins

Time-resolved small- and wide-angle X-ray scattering (SAXS and WAXS) methods probe the structural dynamics of proteins in solution. Although technologically advanced, these methods are in many cases limited by data interpretation. The calculation of X-ray scattering profiles is computationally demanding and poses a bottleneck for all SAXS/WAXS-assisted structural refinement and, in particular, for the analysis of time-resolved data. A way of speeding up these calculations is to represent biomolecules as collections of coarse-grained scatterers. Here, such coarse-graining schemes are presented and discussed and their accuracies examined. It is demonstrated that scattering factors coincident with the popular MARTINI coarse-graining scheme produce reliable difference scattering in the range 0 < q < 0.75 Å-1. The findings are promising for future attempts at X-ray scattering data analysis, and may help to bridge the gap between time-resolved experiments and their interpretation.

Predicting supramolecular self-assembly on reconstructed metal surfaces

The prediction of supramolecular self-assembly onto solid surfaces is still challenging in many situations of interest for nanoscience. In particular, no previous simulation approach has been capable to simulate large self-assembly patterns of organic molecules over reconstructed surfaces (which have periodicities over large distances) due to the large number of surface atoms and adsorbing molecules involved. Using a novel simulation technique, we report here large scale simulations of the self-assembly patterns of an organic molecule (DIP) over different reconstructions of the Au(111) surface. We show that on particular reconstructions, the molecule-molecule interactions are enhanced in a way that long-range order is promoted. Also, the presence of a distortion in a reconstructed surface pattern not only induces the presence of long-range order but also is able to drive the organization of DIP into two coexisting homochiral domains, in quantitative agreement with STM experiments. On the other hand, only short range order is obtained in other reconstructions of the Au(111) surface. The simulation strategy opens interesting perspectives to tune the supramolecular structure by simulation design and surface engineering if choosing the right molecular building blocks and stabilising the chosen reconstruction pattern.

LipidWrapper: an algorithm for generating large-scale membrane models of arbitrary geometry

As ever larger and more complex biological systems are modeled in silico, approximating physiological lipid bilayers with simple planar models becomes increasingly unrealistic. In order to build accurate large-scale models of subcellular environments, models of lipid membranes with carefully considered, biologically relevant curvature will be essential. In the current work, we present a multi-scale utility called LipidWrapper capable of creating curved membrane models with geometries derived from various sources, both experimental and theoretical. To demonstrate its utility, we use LipidWrapper to examine an important mechanism of influenza virulence. A copy of the program can be downloaded free of charge under the terms of the open-source FreeBSD License from http://nbcr.ucsd.edu/lipidwrapper. LipidWrapper has been tested on all major computer operating systems.

The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems

The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.

Live-cell imaging of phosphatidic acid dynamics in pollen tubes visualized by Spo20p-derived biosensor

Although phosphatidic acid (PA) is structurally the simplest membrane phospholipid, it has been implicated in the regulation of many cellular events, including cytoskeletal dynamics, membrane trafficking and stress responses. Plant PA shows rapid turnover but the information about its spatio-temporal distribution in plant cells is missing. Here we demonstrate the use of a lipid biosensor that enables us to monitor PA dynamics in plant cells. The biosensor consists of a PA-binding domain of yeast SNARE Spo20p fused to fluorescent proteins. Live-cell imaging of PA dynamics in transiently transformed tobacco (Nicotiana tabacum) pollen tubes was performed using confocal laser scanning microscopy. In growing pollen tubes, PA shows distinct annulus-like fluorescence pattern in the plasma membrane behind the extreme tip. Coexpression studies with markers for other plasmalemma signaling lipids phosphatidylinositol 4,5-bisphosphate and diacylglycerol revealed limited colocalization at the shoulders of the apex. PA distribution and concentrations show distinct responses to various lipid signaling inhibitors. Fluorescence recovery after photobleaching (FRAP) analysis suggests high PA turnover in the plasma membrane. Our data show that a biosensor based on the Spo20p-PA binding domain is suitable for live-cell imaging of PA also in plant cells. In tobacco pollen tubes, distinct subapical PA maximum corroborates its involvement in the regulation of endocytosis and actin dynamics.

Methodologies for the analysis of instantaneous lipid diffusion in MD simulations of large membrane systems

Interactions between lipids and membrane proteins play a key role in determining the nanoscale dynamic and structural properties of biological membranes. Molecular dynamics (MD) simulations provide a valuable tool for studying membrane models, complementing experimental approaches. It is now possible to simulate large membrane systems, such as simplified models of bacterial and viral envelope membranes. Consequently, there is a pressing need to develop tools to visualize and quantify the dynamics of these immense systems, which typically comprise millions of particles. To tackle this issue, we have developed visual and quantitative analyses of molecular positions and their velocity field using path line, vector field and streamline techniques. This allows us to highlight large, transient flow-like movements of lipids and to better understand crowding within the lipid bilayer. The current study focuses on visualization and analysis of lipid dynamics. However, the methods are flexible and can be readily applied to e.g. proteins and nanoparticles within large complex membranes. The protocols developed here are readily accessible both as a plugin for the molecular visualization program VMD and as a module for the MDAnalysis library.

Continuum approaches to understanding ion and peptide interactions with the membrane

Experimental and computational studies have shown that cellular membranes deform to stabilize the inclusion of transmembrane (TM) proteins harboring charge. Recent analysis suggests that membrane bending helps to expose charged and polar residues to the aqueous environment and polar head groups. We previously used elasticity theory to identify membrane distortions that minimize the insertion of charged TM peptides into the membrane. Here, we extend our work by showing that it also provides a novel, computationally efficient method for exploring the energetics of ion and small peptide penetration into membranes. First, we show that the continuum method accurately reproduces energy profiles and membrane shapes generated from molecular simulations of bare ion permeation at a fraction of the computational cost. Next, we demonstrate that the dependence of the ion insertion energy on the membrane thickness arises primarily from the elastic properties of the membrane. Moreover, the continuum model readily provides a free energy decomposition into components not easily determined from molecular dynamics. Finally, we show that the energetics of membrane deformation strongly depend on membrane patch size both for ions and peptides. This dependence is particularly strong for peptides based on simulations of a known amphipathic, membrane binding peptide from the human pathogen Toxoplasma gondii. In total, we address shortcomings and advantages that arise from using a variety of computational methods in distinct biological contexts.

A theoretical view of protein dynamics

Proteins are fascinating supramolecular structures, which are able to recognize ligands transforming binding information into chemical signals. They can transfer information across the cell, can catalyse complex chemical reactions, and are able to transform energy into work with much more efficiency than any human engine. The unique abilities of proteins are tightly coupled with their dynamic properties, which are coded in a complex way in the sequence and carefully refined by evolution. Despite its importance, our experimental knowledge of protein dynamics is still rather limited, and mostly derived from theoretical calculations. I will review here, in a systematic way, the current state-of-the-art theoretical approaches to the study of protein dynamics, emphasizing the most recent advances, examples of use and the expected lines of development in the near future.

Perspective: Coarse-grained models for biomolecular systems

By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.

More than the sum of its parts: coarse-grained peptide-lipid interactions from a simple cross-parametrization

Interfacial systems are at the core of fascinating phenomena in many disciplines, such as biochemistry, soft-matter physics, and food science. However, the parametrization of accurate, reliable, and consistent coarse-grained (CG) models for systems at interfaces remains a challenging endeavor. In the present work, we explore to what extent two independently developed solvent-free CG models of peptides and lipids--of different mapping schemes, parametrization methods, target functions, and validation criteria--can be combined by only tuning the cross-interactions. Our results show that the cross-parametrization can reproduce a number of structural properties of membrane peptides (for example, tilt and hydrophobic mismatch), in agreement with existing peptide-lipid CG force fields. We find encouraging results for two challenging biophysical problems: (i) membrane pore formation mediated by the cooperative action of several antimicrobial peptides, and (ii) the insertion and folding of the helix-forming peptide WALP23 in the membrane.

Organization of lipids in the tear film: a molecular-level view

Biophysical properties of the tear film lipid layer are studied at the molecular level employing coarse grain molecular dynamics (MD) simulations with a realistic model of the human tear film. In this model, polar lipids are chosen to reflect the current knowledge on the lipidome of the tear film whereas typical Meibomian-origin lipids are included in the thick non-polar lipids subphase. Simulation conditions mimic those experienced by the real human tear film during blinks. Namely, thermodynamic equilibrium simulations at different lateral compressions are performed to model varying surface pressure, and the dynamics of the system during a blink is studied by non-equilibrium MD simulations. Polar lipids separate their non-polar counterparts from water by forming a monomolecular layer whereas the non-polar molecules establish a thick outermost lipid layer. Under lateral compression, the polar layer undulates and a sorting of polar lipids occurs. Moreover, formation of three-dimensional aggregates of polar lipids in both non-polar and water subphases is observed. We suggest that these three-dimensional structures are abundant under dynamic conditions caused by the action of eye lids and that they act as reservoirs of polar lipids, thus increasing stability of the tear film.

Mesoscopic coarse-grained simulations of lysozyme adsorption

Coarse-grained simulations are adopted to study the adsorption behavior of lysozyme on different (hydrophobic, neutral hydrophilic, zwitterionic, negatively charged, and positively charged) surfaces at the mesoscopic microsecond time scale (1.2 μs). Simulation results indicate the following: (i) the conformation change of lysozyme on the hydrophobic surface is bigger than any other studied surfaces; (ii) the active sites of lysozyme are faced to the hydrophobic surface with a "top end-on" orientation, while they are exposed to the liquid phase on the hydrophilic surface with a "back-on" orientation; (iii) the neutral hydrophilic surface can induce the adsorption of lysozyme, while the nonspecific protein adsorption can be resisted by the zwitterionic surface; (iv) when the solution ionic strength is low, lysozyme can anchor on the negatively charged surface easily but cannot adsorb on the positively charged surface; (v) when the solution ionic strength is high, the positively charged lysozyme can also adsorb on the like-charged surface; (vi) the major positive potential center of lysozyme, especially the residue ARG128, plays a vital role in leading the adsorption of lysozyme on charged surfaces; (vii) when the ionic strength is high, a counterion layer is formed above the positively charged surface, which is the key factor why lysozyme can adsorb on a like-charged surface. The coarse-grained method based on the MARTINI force field for proteins and the BMW water model could provide an efficient way to understand protein interfacial adsorption behavior at a greater length scale and time scale.

Triphenylalanine peptides self-assemble into nanospheres and nanorods that are different from the nanovesicles and nanotubes formed by diphenylalanine peptides

Understanding the nature of the self-assembly of peptide nanostructures at the molecular level is critical for rational design of functional bio-nanomaterials. Recent experimental studies have shown that triphenylalanine(FFF)-based peptides can self-assemble into solid plate-like nanostructures and nanospheres, which are different from the hollow nanovesicles and nanotubes formed by diphenylalanine(FF)-based peptides. In spite of extensive studies, the assembly mechanism and the molecular basis for the structural differences between FFF and FF nanostructures remain poorly understood. In this work, we first investigate the assembly process and the structural features of FFF nanostructures using coarse-grained molecular dynamics simulations, and then compare them with FF nanostructures. We find that FFF peptides spontaneously assemble into solid nanometer-sized nanospheres and nanorods with substantial β-sheet contents, consistent with the structural properties of hundred-nanometer-sized FFF nano-plates characterized by FT-IR spectroscopy. Distinct from the formation mechanism of water-filled FF nanovesicles and nanotubes reported in our previous study, intermediate bilayers are not observed during the self-assembly process of FFF nanospheres and nanorods. The peptides in FFF nanostructures are predominantly anti-parallel-aligned, which can form larger sizes of β-sheet-like structures than the FF counterparts. In contrast, FF peptides exhibit lipid-like assembly behavior and assemble into bilayered nanostructures. Furthermore, although the self-assembly of FF and FFF peptides is mostly driven by side chain-side chain (SC-SC) aromatic stacking interactions, the main chain-main chain (MC-MC) interactions also play an important role in the formation of fine structures of the assemblies. The delicate interplay between MC-MC and SC-SC interactions results in the different nanostructures formed by the two peptides. These findings provide new insights into the structure and self-assembly pathway of di-/tri-phenylalanine peptide assemblies, which might be helpful for the design of bioinspired nanostructures.

Foundations of biomolecular modeling

The 2013 Nobel Prize in Chemistry has been awarded to Martin Karplus, Michael Levitt, and Arieh Warshel for "development of multiscale models for complex chemical systems." The honored work from the 1970s has provided a foundation for the widespread activities today in modeling organic and biomolecular systems.

Interplay between curvature and lateral organization of lipids and peptides/proteins in model membranes

Membrane curvature plays a crucial role in the realization of many cellular membrane functions such as signaling and trafficking. Here, using coarse-grained molecular dynamics (MD) simulation, we present an effective method of producing curved model membranes and systematically investigated the interplay between the curvature and lateral sorting of lipids and transmembrane (TM) peptides/proteins in the model membranes. We first confirmed the experimental results of the lateral organization of lipid domains in curved ternary membranes. Then, we focused on exploring the lateral sorting of TM peptides/proteins with symmetric shape in the curved membranes. The results showed that the lateral inhomogeneous packing of lipids induced by the curvature and/or the component heterogeneity drives the peptides/proteins to accumulate in the curved regions in both the unary and ternary membranes. However, whether the peptides/proteins can stably and compactly reside in the curved regions is determined by their final packing configuration, which may be influenced by the membrane curvature in the curved regions. Additionally, the insertion of peptides/proteins may enhance the membrane curvature. This work provided some theoretical insights into understanding the mechanism of the interplay of membrane curvature and lateral organization (especially the lateral sorting of the peptides/proteins with symmetric shape) in the biomembrane in some biological processes.

Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models

The conversion of coarse-grained to atomistic models is an important step in obtaining insight about atomistic scale processes from coarse-grained simulations. For this process, called backmapping or reverse transformation, several tools are available, but these commonly require libraries of molecule fragments or they are linked to a specific software package. In addition, the methods are usually restricted to specific molecules and to a specific force field. Here, we present an alternative method, consisting of geometric projection and subsequent force-field based relaxation. This method is designed to be simple and flexible, and offers a generic solution for resolution transformation. For simple systems, the conversion only requires a list of particle correspondences on the two levels of resolution. For special cases, such as nondefault protonation states of amino acids and virtual sites, a target particle list can be specified. The mapping uses simple building blocks, which list the particles on the different levels of resolution. For conversion to higher resolution, the initial model is relaxed with several short cycles of energy minimization and position-restrained MD. The reconstruction of an atomistic backbone from a coarse-grained model is done using a new dedicated algorithm. The method is generic and can be used to map between any two particle based representations, provided that a mapping can be written. The focus of this work is on the coarse-grained MARTINI force field, for which mapping definitions are written to allow conversion to and from the higher-resolution force fields GROMOS, CHARMM, and AMBER, and to and from a simplified three-bead lipid model. Together, these offer the possibility to simulate mesoscopic membrane structures, to be transformed to MARTINI and subsequently to an atomistic model for investigation of detailed interactions. The method was tested on a set of systems ranging from a simple, single-component bilayer to a large protein-membrane-solvent complex. The results demonstrate the efficiency and the efficacy of the new approach.

Density based visualization for molecular simulation

Molecular visualization of structural information obtained from computer simulations is an important part of research work flow. A good visualization technique should be capable of eliminating redundant information and highlight important effects clarifying the key phenomena in the system. Current methods of presenting structural data are mostly limited to variants of the traditional ball-and-stick representation. This approach becomes less attractive when very large biological systems are simulated at microsecond timescales, and is less effective when coarse-grained models are used. Real time rendering of such large systems becomes a difficult task; the amount of information in one single frame of a simulation trajectory is enormous given the large number of particles; at the same time, each structure contains information about one configurational point of the system and no information about statistical weight of this specific configuration. In this paper we report a novel visualization technique based on spatial particle densities. The atomic densities are sampled on a high resolution 3-dimensional grid along a relatively short molecular dynamics trajectory using hundreds of configurations. The density information is then analyzed and visualized using the open-source ParaView software. The performance and capability of the method are demonstrated on two large systems simulated with the MARTINI coarse-grained force field: a lipid nanoparticle for delivering siRNA molecules and monolayers with a complex composition under conditions that induce monolayer collapse.

NRas slows the rate at which a model lipid bilayer phase separates

The Ras family of small membrane-associated GTP-ases are important components in many different cell signalling cascades. They are thought to cluster on the cell membrane through association with cholesterol-rich nanodomains. This process remains poorly understood. Here we test the effect of adding multiple copies of NRas, one of the canonical Ras proteins, to a three-component lipid bilayer that rapidly undergoes spinodal decomposition (i.e. unmixing), thereby creating ordered and disordered phases. Coarse-grained molecular dynamics simulations of a large bilayer containing 6000 lipids, with and without protein, are compared. NRas preferentially localises to the interface between the domains and slows the rate at which the domains grow. We infer that this doubly-lipidated cell signalling protein is reducing the line tension between the ordered and disordered regions. This analysis is facilitated by our use of techniques borrowed from image-processing. The conclusions above are contingent upon several assumptions, including the use of a model lipid with doubly unsaturated tails and the limited structural data available for the C-terminus of NRas, which is where the lipid anchors are found.

A Coarse-Grained Molecular Dynamics Simulation Using NAMD Package to Reveal Aggregation Profile of Phospholipids Self-Assembly in Water

The energy profile of self-assembly process of DLPE, DLPS, DOPE, DOPS, DLiPE, and DLiPS in water was investigated by a coarse-grained molecular dynamics simulation using NAMD package. The self-assembly process was initiated from random configurations. The simulation was carried out for 160 ns. This study presented proof that there were three major self-assembled arrangements which became visible for a certain duration when the simulation took place, that is, liposome, deformed liposome, and planar bilayer. The energy profile that shows plateau at the time of these structures emerge confirmed their stability therein. Our findings have highlighted the idea that liposomes and deformed liposomes are metastable phases which eventually will turn into planar bilayer, the stable one.

Influence of different membrane environments on the behavior of cholesterol

Our results show the distribution of cholesterol between stress-free and stressed membranes or between the inner leaflet and the outer leaflet of curved membrane.

Evaluation of reduced point charge models of proteins through Molecular Dynamics simulations: application to the Vps27 UIM-1-Ubiquitin complex

Reduced point charge models of amino acids are designed, (i) from local extrema positions in charge density distribution functions built from the Poisson equation applied to smoothed molecular electrostatic potential (MEP) functions, and (ii) from local maxima positions in promolecular electron density distribution functions. Corresponding charge values are fitted versus all-atom Amber99 MEPs. To easily generate reduced point charge models for protein structures, libraries of amino acid templates are built. The program GROMACS is used to generate stable Molecular Dynamics trajectories of an Ubiquitin-ligand complex (PDB: 1Q0W), under various implementation schemes, solvation, and temperature conditions. Point charges that are not located on atoms are considered as virtual sites with a nul mass and radius. The results illustrate how the intra- and inter-molecular H-bond interactions are affected by the degree of reduction of the point charge models and give directions for their implementation; a special attention to the atoms selected to locate the virtual sites and to the Coulomb-14 interactions is needed. Results obtained at various temperatures suggest that the use of reduced point charge models allows to probe local potential hyper-surface minima that are similar to the all-atom ones, but are characterized by lower energy barriers. It enables to generate various conformations of the protein complex more rapidly than the all-atom point charge representation.

Coarse-grain modelling of protein-protein interactions

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are separately described, but we note the parallel development that is present in both research fields with three important themes: firstly, combining CG modelling with knowledge-based approaches to predict and refine protein-protein complexes; secondly, using physics-based CG models for de novo prediction of protein-protein complexes; and thirdly modelling of large scale protein aggregates.

Computational microscopy of cyclodextrin mediated cholesterol extraction from lipid model membranes

Beta-cyclodextrins (β-CDs) can form inclusion complexes with cholesterol, and are commonly used to manipulate cholesterol levels of biomembranes. In this work, we have used multiscale molecular dynamics simulations to provide a detailed view on the interaction between β-CDs and lipid model membranes. We show that cholesterol can be extracted efficiently upon adsorption of β-CD dimers at the membrane/water interface. However, extraction is only observed to occur spontaneously in membranes with high cholesterol levels. Free energy calculations reveal the presence of a kinetic barrier for cholesterol extraction in the case of low cholesterol content. Cholesterol uptake is facilitated in case of (poly)unsaturated lipid membranes, which increases the free energy of the membrane bound state of cholesterol. Comparing lipid/cholesterol compositions typical of liquid-disordered (L(d)) and liquid-order (L(o)) domains, we furthermore show that cholesterol is preferentially extracted from the disordered regions, in line with recent experimental data.

Embedding Aβ42 in heterogeneous membranes depends on cholesterol asymmetries

Using a coarse-grained lipid and peptide model, we show that the free energy stabilization of amyloid-β in heterogeneous lipid membranes is predicted to have a dependence on asymmetric distributions of cholesterol compositions across the membrane leaflets. We find that a highly asymmetric cholesterol distribution that is depleted on the exofacial leaflet but enhanced on the cytofacial leaflet of the model lipid membrane thermodynamically favors membrane retention of a fully embedded Aβ peptide. However, in the case of cholesterol redistribution that increases concentration of cholesterol on the exofacial layer, typical of aging or Alzheimer's disease, the free energy favors peptide extrusion of the highly reactive N-terminus into the extracellular space that may be vulnerable to aggregation, oligomerization, or deleterious oxidative reactivity.

Lipases immobilization for effective synthesis of biodiesel starting from coffee waste oils

Immobilized lipases were applied to the enzymatic conversion of oils from spent coffee ground into biodiesel. Two lipases were selected for the study because of their conformational behavior analysed by Molecular Dynamics (MD) simulations taking into account that immobilization conditions affect conformational behavior of the lipases and ultimately, their efficiency upon immobilization. The enzymatic synthesis of biodiesel was initially carried out on a model substrate (triolein) in order to select the most promising immobilized biocatalysts. The results indicate that oils can be converted quantitatively within hours. The role of the nature of the immobilization support emerged as a key factor affecting reaction rate, most probably because of partition and mass transfer barriers occurring with hydrophilic solid supports. Finally, oil from spent coffee ground was transformed into biodiesel with yields ranging from 55% to 72%. The synthesis is of particular interest in the perspective of developing sustainable processes for the production of bio-fuels from food wastes and renewable materials. The enzymatic synthesis of biodiesel is carried out under mild conditions, with stoichiometric amounts of substrates (oil and methanol) and the removal of free fatty acids is not required.