Interaction of peptides with cell membranes: insights from molecular modeling.

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Interaction of peptides with cell membranes: insights from molecular modeling

This content has been downloaded from IOPscience. Please scroll down to see the full text. 2016 J. Phys.: Condens. Matter 28 083001 (http://iopscience.iop.org/0953-8984/28/8/083001) View the table of contents for this issue, or go to the journal homepage for more

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Journal of Physics: Condensed Matter J. Phys.: Condens. Matter 28 (2016) 083001 (17pp)

doi:10.1088/0953-8984/28/8/083001

Topical Review

Interaction of peptides with cell membranes: insights from molecular modeling Zhen-lu Li1, Hong-ming Ding2 and Yu-qiang Ma1,2 1

National Laboratory of Solid State Microstructures and Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, People’s Republic of China 2 Center for Soft Condensed Matter Physics and Interdisciplinary Research, Soochow University, Suzhou 215006, People’s Republic of China E-mail: [email protected] and [email protected] Received 8 April 2015, revised 15 December 2015 Accepted for publication 16 December 2015 Published 1 February 2016 Abstract

The investigation of the interaction of peptides with cell membranes is the focus of active research. It can enhance the understanding of basic membrane functions such as membrane transport, fusion, and signaling processes, and it may shed light on potential applications of peptides in biomedicine. In this review, we will present current advances in computational studies on the interaction of different types of peptides with the cell membrane. Depending on the properties of the peptide, membrane, and external environment, the peptide–membrane interaction shows a variety of different forms. Here, on the basis of recent computational progress, we will discuss how different peptides could initiate membrane pores, translocate across the membrane, induce membrane endocytosis, produce membrane curvature, form fibrils on the membrane surface, as well as interact with functional membrane proteins. Finally, we will present a conclusion summarizing recent progress and providing some specific insights into future developments in this field. Keywords: peptide, lipid membrane, channel protein, molecular simulation (Some figures may appear in colour only in the online journal)

1. Introduction

prospects for medicinal applications. For example, antimicrobial peptides (AMPs) can be used as a promising substitute for conventional antibiotics [5] and cell-penetrating peptides (CPPs) may be used as vehicles to deliver membrane impermeable therapeutic macromolecules into the cell interior [6]. Although the peptides are usually short with a sequence length of less than 100 amino acids and an absence of any tertiary structure, the peptide–membrane system still contains a lot of factors influencing the properties of peptides (such as sequence, charge, secondary structure, hydrophobicity, and amphiphilicity), membranes (such as multiple constituents and multiple domain structures), and the environment (such as

The cell membrane, which is mainly composed of lipid molecules and embedded membrane proteins, acts as a border, controlling the materials or signals in and out of the cell. Various types of molecules have to come into contact with the cell membrane to enter or transmit signals into the cell. Of all these foreign molecules, peptides are particularly important, as they are involved in a series of vital membrane-related biological functions, such as antimicrobial defense [1], vesicle traffic [2], virus infection [3], and fibril growth [4]. Currently, peptides are being studied as biocompatible materials with great 0953-8984/16/083001+17$33.00

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© 2016 IOP Publishing Ltd Printed in the UK

Topical Review

J. Phys.: Condens. Matter 28 (2016) 083001

temperature and pH). As a result, the peptide–membrane interaction shows quite a rich and diverse behavior. Figure 1 summarizes the potential mechanisms of peptides interacting with the membrane. One can find that different or even the same kind of peptides could lead to different membrane responses. The membrane may be dissolved by the peptide locally, form a local membrane defect (e.g. membrane disorder, lipid protrusion, or a membrane pore), deform its shape to generate membrane invagination, and act as a template for peptide aggregation or ligand–receptor signaling communication. The varied behavior of the peptide–membrane interaction has attracted a lot of interest from researchers from multiple disciplines. However, the existence of various influencing factors makes the problem complicated and elusive, and sometimes contrary conclusions are even presented in the literature. To better distinguish the different mechanisms and understand the corresponding membrane-associated biological functions, a comprehensive investigation of peptide–membrane interaction at an atomic or molecular level is urgently required. In recent years, the application of computational modeling, including theoretical analysis and computer simulation, has achieved great improvements, resulting in a lot valuable information on the peptide–membrane interaction [7–12]. In fact, the computational method is able to provide multilevel description of the peptide–membrane interaction from a microscopic to a mesoscopic view. Molecular simulations, in particular, may bridge the gap between the molecular structure and biological function of peptides, and can successfully reproduce the elastic structures and dynamic properties of cell membranes. In addition, the partitioning behavior of peptides on the membrane and the corresponding membrane response to peptide binding could be conveniently investigated using computer simulation, where the conditions (such as temper ature, ions, membrane components, and peptide concentration) can also be well controlled. In addition, computational modeling could provide important thermodynamics properties of the peptide–membrane system. Generally, the results acquired from computational modeling can be used to better clarify experimental phenomena, and may sometimes provide distinct insights into experiment design. In this review, we will summarize recent progress in the computational modeling of peptide–membrane interaction. First, the molecular modeling of peptide–membrane interactions will be described. Second, we will present the physical mech anisms of different peptides interacting with the membrane on the basis of the computational results. These peptides include the AMP, the CPP, the membrane remodeling amphiphilic helix (MRAH), the fusion peptide (FP), the amyloid peptide, and a specific peptide that interacts with functional membrane proteins. Finally, we will summarize the recent progress and list some challenging problems waiting to be solved in the future.

Figure 1. Different mechanisms of the peptide interacting with the membrane. (A1) Carpet model, (A2) barrel-stave pore, and (A3) toroidal pore for an AMP interacting with the membrane. (B1) Channel-forming mechanism, (B2) inverted micelle, and (B3) endocytosis mechanism for CPPs interacting with the membrane. (C) The MRAH generates membrane curvature. (D) A FP inserts into the host cell membrane. (E) Amyloid peptides aggregate into fibrils on the membrane surface. (F) A peptide interacts with a functional membrane protein in a direct or an indirect way.

molecular theory and mean field theory could help in acquiring a broad and general understanding of peptide–membrane interactions. But these methods usually need to simplify the model of the membranes and peptides. For example, a continuum elastic membrane model is commonly adopted for the biological membrane [13, 14]. In addition, the peptide is usually resolved beyond the residue level. In the most simple approach, the peptide is just treated as a nano-sized cylinder. Molecular docking is mainly used to predict the preferred orientation of the peptide to the membrane protein targets [15]. Recently, it has become an important tool in the rational design of drugs [16]. By employing this method, one can find the binding site of a peptide to its target, and predict the association affinity of the peptide–membrane protein complex. The predicted structure can be used for comparison with the experimental x-ray crystal structure or nuclear magnetic resonance (NMR) structure of the peptide–membrane protein complex. In addition, the predicted structure may be further applied in molecular simulations. Differing from the theoretical method and molecular docking, molecular simulation could provide multi-level insights into the peptide–membrane interaction. By using molecular simulations, one can investigate both the thermostatic structure and the dynamic evolution of the peptide–membrane system. This makes molecular simulation a very useful tool to explore the physical mechanism of a peptide interacting with a membrane. In the following the molecular simulation method will be discussed in detail.

2. Molecular modeling The molecular modeling used for peptide–membrane systems mainly includes theoretical methods, molecular docking, and molecular simulations. Theoretical methods such as 2

Topical Review


the extent of polarity. The CG water is usually treated as one polar bead, while a polarized CG water model consisted of a central particle and two bound particles with complementary charge is also available in the Martini force field [30, 31]. The elastic network model (ENM), which is a kind of shape-based coarse-graining, has also attracted considerable interest [32, 33]. In the ENM, several lipids are usually combined into one molecule which is connected by several CG sites. Each residue of the peptide is usually represented by one CG site, and to maintain the secondary structures of proteins, a biased harmonic spring potential is applied between Cα atoms within a cutoff distance [32–34]. Recently, there have also been some attempts to investigate the multi-dimensional properties of the peptide–membrane interaction by combining multiscale molecular simulations, such as in the research of AMP magainin-H2 interacting with the membrane [35] and N-BAR protein induced membrane remodeling [36, 37]. 3. A single amino acid

Figure 2. Water defect induced by a positively charged Arg at the center of the DOPC bilayer. Adapted with permission from [38]. Copyright 2008 Elsevier.

Before further reviewing the peptide–membrane interaction, we will briefly present the behavior of a single amino acid partitioning into the membrane. A single amino acid, according to its specific type and properties (hydrophobicity, polarity, charge, and hydrogen bonding ability), could have a different preferred location and orientation when interacting with a membrane with an intrinsic polar surface and hydrophobic interior. For example, by using AA simulation, MacCallum et al [38] showed that hydrophobic residues (Ala, Val, Ile, and Leu) prefer to insert at the center of a DOPC membrane, while Cys, Met, and aromatic amino acids (including Trp, Tyr, and Phe) just locate at the interfacial region (about half of the monolayer thickness). Polar residues (Thr, Ser, Gln, Asn) also distribute between the membrane hydrophobic– polar interface, but the potential of mean force (PMF) shows a high penetrating barrier for their entering into the center of the membrane. For positively charged Arg and Lys, there is a local minimum of the PMF at the membrane interface, then the PMF increases with the decrease of distance, and increases steeply to a very high value at the bilayer center. In contrast, for negatively charged Glu and Asp, the PMF shows a hillside increase from bulk water to the center of the membrane. In addition, if polar or charged amino acids are inserted into the membrane, they will induce water defects connecting the side chains to bulk water (see figure 2). In addition, the amino acids Lys, Glu, and Asp will become uncharged, but Arg can still be protonated when in the membrane interior [39, 40]. Further, we should note that in CG molecular simulation, it is also important to precisely mimic the partitioning behavior of amino acids into the membrane. Currently, the partitioning behavior acquired from the Martini CG simulation is in good agreement with that obtained from the AA one [28, 29]. On the basis of the above discussion, it is easy to see that the peptide, which is connected by the different kinds of amino acids, will have rather complicated interaction behavior with the membrane. Fortunately, peptides with different amino acid sequences commonly present similar properties and functions, which makes them easy to divide into different classes. In the

Molecular simulation includes all-atom (AA) simulation and coarse-grained (CG) simulation. AA simulation considers an explicit representation of all the heavy atoms and hydrogen (the united atom force field model which ignores non-polar hydrogen atoms is a bit different), while CG simulation usually combines several heavy atoms into a single unit to achieve computational efficiency. Force field parameters are applied to describe the non-bonded interaction (the electrostatic and van der Waals interaction) and bonded interaction between the neighboring few atoms. The most popular AA force fields in simulating biomolecules (such as lipids, nucleic acids, amino acids, and peptides) are the CHARMM [17], AMBER [18], GROMOS [19], and OPLS force fields [20]. Both explicit water models such as the SPC, TIP3 or TIP4 representation and an alternative implicit solvation model could be applied [21]. Owing to the great improvements in computational capabilities, molecular simulation can now simulate many different kinds of lipids (such as phospholipids, sphingolipids, glycolipids, cholesterol, and some other special lipids) and large membrane proteins such as membrane transporters and membrane signal proteins [7–9]. AA simulation is usually limited to small systems and short simulation times, however, in many cases there is the need to simulate large systems for long simulation times. To achieve greater computational efficiency, the past decade has witnessed booming development in the CG modeling of biomolecules. Several different CG methods have now been found, such as residue-based coarse-graining (resolving single amino acids and lipid molecules) and shape-based coarsegraining (resolving overall protein and membrane shapes) [10, 12, 22–25]. The Martini CG method [26–29], for example, is a kind of residue-based coarse-graining. It omits the hydrogen atoms and treats four heavy atoms as one bead. These beads are clarified into four different types: hydrophobic, polar, non-polar, and charged. Each type also has subtypes which further distinguish the hydrogen bond abilities or 3

Topical Review


Figure 3. (A) The role of Zn2+ ions in the formation of a dermcidin peptide bundle (left), and an ion leakage pathway through the pore

(right). Adapted with permission from [49]. Copyright 2013 National Academy of Science, USA. (B) A charge zipper formed by several complementary charged residues in a TisB dimer. Adapted with permission from [61]. Copyright 2012 Elsevier. (C) Complementary salt bridge interaction among APHs and DCRs. Adapted with permission from [62]. Copyright 2013 Elsevier.

a fatal depolarization and collapse of the membrane. In the channel-forming model, multiple peptides cooperatively insert into the membrane to form transmembrane peptide bundles, with the hydrophobic region of the peptides contacting the hydrophobic core of the membrane and the hydrophilic region establishing a local polar environment which can guide water and ions through the membrane. The channel-forming model can be further distinguished as a barrel-stave pore (see figure 1(A2)) and a toroidal pore model (see figure 1(A3)). The channel-forming model has been thoroughly investigated in many computational works [46–54]. Using AA simulations, Tieleman et al showed that alamethicin peptides can form a barrel-stave pore [46, 47]. Recently, exper imental results showed that the barrel-stave pores formed by alamethicin even organize themselves into an ordered twodimensional hexagonal lattice structure [55]. CG simulation of the regular amphiphilic peptide LS3 (LSSLLSL)3 and AA investigation of a human host defense peptide, dermcidin, also presented a barrel-stave pore [48, 49]. In recent work by Song et al, dermcidin was found to form a hexameric peptide bundle in a membrane under a transmembrane voltage (see figure 3(A)) [49]. The bundle resembles an ion channel and it displays quite high water permeability and ion conductance activity, which can lead to severe membrane disruption. Zn2+ ions were found to play a particularly important role in this process. They are able to neutralize the negative charges of the dermcidin and help connect three dimers composed of antiparallel dermcidin helices to form the peptide bundle.

following sections, we will review the interaction of the cell membrane with several different types of peptides which have been well studied in recent computational research. 4. The antimicrobial peptide The AMP (or host-defense peptide) exists in various secretions of multicellular organisms [1, 5], such as alamethicin from the Trichoderma viride fungus [41], magainin from an Africa frog [42], and melittin from bee venom [43]. Plants and animals use these agents to defend against microbes such as bacteria, fungi, and viruses. Since the outer leaflet of a microbial membrane is enriched with anionic lipids while that of the mammalian membrane is nearly charge-neutral, the AMP (usually cationic) prefers to associate with the microbial membrane. The association with the membrane will induce leakage of cell contents, resulting in the death of the cell. In addition, the process does not involve specific interaction of the AMP with the membrane receptors, thus the microbes are unlikely to develop efficient multi-drug resistance to the AMP. Hence, the AMP shows broad-spectrum microbial defense, and is being studied as a promising substitute for conventional antibiotics [44, 45]. Different modes for the AMP interacting with the membrane have been proposed theoretically, including the carpet model and the channel-forming model [1, 45]. In the carpet model (see figure 1(A1)), peptides dissolve the bilayer into fragments by forming co-micelles with lipids, leading to 4

Topical Review


region (DCR) [62]. The two domains (in the same or different TAT peptides) can interact with each other through several complementary salt bridge interactions (see the AA simulation results in figure 3(C)). Hence, oligomers formed by TAT peptides will establish multiple zipper-like polar interfaces for water and ion transport across the membrane. Similarly, water transportation through limited polar binding sites in the membrane interior was also found in a CG simulation of a synthetic antimicrobial polymer interacting with the membrane [56].

By inserting the dermcidin bundle with associated Zn2+ into a mixed bilayer of POPE/POPG (3 : 1) in a simulation, the researchers elucidated the vital role of Zn2+ ions in stabilizing peptide bundles—the bundle could not be preserved once Zn2+ ions were absent, resulting in an inactive peptide bundle. In addition to the barrel-stave pore, a toroidal pore structure was also reported for many simulations, such as in the case of magainin, melittin, and the cyclic peptide interacting with the membrane [50–54]. In a barrel-stave pore, three or more peptides are arranged along the pore edge, but for a disordered toroidal pore structure, usually only one or two peptides are distributed along the pore edge [50, 53]. Several factors could have some effect on whether a barrel-stave or a toroidal pore is produced. It is thought that very short peptides cannot span the entire membrane, and thereby are unfavorable to form a barrel-stave pore [56]. Moreover, the AA simulation by Mihajlovic and Lazaridis showed that the difference between the charges of melittin (+5e) and alamethicin (−1e) determines their different tendencies to form a toroidal pore and barrel-stave pore [57]. A barrel-stave pore or a toroidal pore can form spontaneously within several hundred nano seconds or several microseconds in simulations. In addition, a threshold of peptide concentration was needed to induce the membrane pore, namely, only when the ratio of peptide to lipid is large enough can a pore be generated. The concentrationdependent property was well clarified in the theoretical work by Huang et al [58]. They indicated that peptide binding will induce the thinning of the membrane and generate membrane tension, while multiple peptides can cooperatively generate a sufficiently strong membrane tension to initiate a membrane pore. The membrane pore is further stabilized under the balance of pore line tension and membrane tension after several peptides enter into the pore. Recently, computational simulations also indicated the existence of several potential non-pore forming mechanisms [59–62]. The carpet model was reported in a dissipative particle dynamics (DPD) simulation of melittin at a very high concentration interacting with a lipid membrane in the solid phase [59]. The solid state membrane has more compacted lipid-packing than the membrane in the liquid phase. This may make the peptide more favorable to adopt a partial insertion into the membrane with its central axis parallel to the membrane, which could help peptides dissolve the bilayer into fragments [59, 63]. Moreover, in a CG simulation, recruiting of anionic lipids into the microdomain by cationic peptide Ltc1 was found to reduce the stability of the membrane and increase the membrane permeability at phase boundary defects [60]. Another interesting case was found for the peptide TisB, where two anti-parallel TisB helices form a transmembrane TisB dimer connected by complementary charged residues (see figure 3(B)) [61]. The transmembrane dimer does not create a membrane pore, but it can supply a passage for ion leakage and water transport through the zipper-like polar interface established by several salt bridges (see CG simulation results in figure 3(B)). The charge zipper mech anism was further proved in the investigation of twin-arginine translocase (TAT), which has two transmembrane domains— an amphiphilic helix (APH) and a C-terminal densely charged

5. The cell-penetrating peptide The CPP has gained significant attention in recent years, as it possesses a highly efficient membrane penetrating ability [6, 64], which endows it with potential medical value to deliver therapeutic macromolecules such as peptides, proteins, and nucleic acids into the cell interior [65, 66]. The CPPs are usually very short (a sequence length of less than 30 amino acids) and highly cationic in neutral solutions as they are rich in basic amino acids (such as Lys and Arg). The best-known CPPs are penetratin [67], HIV-1 TAT peptide [68], and homopolypeptides of Lys or Arg. The internalization mechanism used by the CPPs can be divided into two types: an energy-independent direct entry mechanism (see figures 1(B1) and (B2)) [64, 65, 69, 70] and an energy-dependent endocytosis mechanism (see figure 1(B3)) [71–73]. The direct entry mechanism is further distinguished into a pore forming mechanism such as in the case of AMP (see figure 1(B1)), and an inverted micelle model which supposes that the CPPs are engulfed into an inverted micelle (see figure 1(B2)). To the best of our knowledge, there are no direct simulations that present an inverted micelle model, except for one DPD simulation where it was asserted that under the condition of very strong attractive interaction between the peptide and lipid head group, there is a possibility to form an inverted micelle [74]. The pore formation mechanism was reported by Herce et al for the TAT peptide and a peptide consisting of multiple arginine residues [75–79]. An AA simulation on Transportan 10 (Tp10) at low density also presented a toroidal pore-like structure, where the membrane showed a significant disorder in the peptide-associated area, with water and phosphate groups penetrating deeply into it [80]. Li and co-workers investigated the direct transport of R9 (connected by nine arginine residues) across an asymmetric membrane using the CG method [81]. In the simulation, more anionic lipids were included into the intracellular leaflet to mimic a eukaryotic cell membrane. It was found that the transmembrane charge asymmetry leads to a free energy difference of peptide binding to the two layers of membranes. The free energy difference promotes the transportation of multiple peptides across the membrane via a transient membrane pore. In addition, they also explored the role of conjugated cargo in the peptide penetrating mechanism (see figure 4(A)) [82, 83]. It was found that peptide conjugated with a hydrophobic particle is easier to transport than a peptide conjugated with a hydrophilic particle. The former shows a decreased free energy barrier across the membrane while the latter has an increased 5

Topical Review


Figure 4. (A) Translocation of a R9-hydrophobic nanoparticle complex across the membrane. Adapted with permission from [81]. Copyright 2013 Royal Society of Chemistry. (B) Peptide induced membrane invagination. Adapted with permission from [84]. Copyright 2009 Elsevier. (C) Comparison between Arg and Lys residues. The guanidimium group of Arg residue forms bidentate hydrogen bonding with the membrane. Adapted with permission from [85]. Copyright 2011 National Academy of Science, USA.

Regardless of the energy-dependent or energy-independent routes, it was proposed that the arginine residues of CPPs have a particular role in generating a saddle-like negative Gaussian curvature structure, which exists in the membrane pore or the neck of the endocytosis vesicle. In an AA simulation, it was shown that arginine rather than lysine containing peptides have a strong tendency to aggregate on the membrane surface [86]. Recently, by using AA simulation, Sun et al found that oligoarginine (rather than oligolysine) could extend the lifetime of a pre-populated membrane pore [87]. Both of the two simulations revealed the importance of arginine residue which is usually enriched in the CPPs. The terminal of the side chain of arginine has a Y-shaped guanidinium group, which could form bidentate hydrogen bonds with more than one lipid phosphate group (see figure 4(C)) [85, 88, 89]. In addition, the guanidinium group is able to force the lipids to align along its Y-shaped contour. This can help produce positive membrane curvature [85], and is essential for generating a saddle-like pore or neck structure.

transport barrier. The complex of R9 and a hydrophilic particle is inclined to form large aggregates, making it unfavorable to translocate across a membrane pore with limited size [81]. Direct computer simulation of the endocytosis pathway is still absent. The endocytosis pathway involves a lot of large membrane proteins. For example, the membrane-associated proteoglycans, such as heparan sulfate proteoglycan, were thought to help increase the concentration of CPPs on the membrane surface through electrostatic attraction. They may serves as a receptor directly or a co-receptor for tyrosine kinase-type growth factor to trigger membrane invagination. Simulating many large membrane proteins could be very time-consuming, so currently it is still difficult to study the internalization of CPP through the endocytosis pathway. However, Yesylevskyy et al indicated a potential micropinocytosis mechanism in an AA simulation, where it was found that multiple penetratin or TAT peptides accumulate on the membrane surface and induce membrane invagination [84] (see figure 4(B)). It is very likely that peptides may use different membrane penetrating mechanisms, depending on the external conditions such as environment temperature and the properties of its conjugated cargoes. For example, it was proposed that as the TAT peptide can interact with the lipid bilayer, membrane receptor, or intracellular actin, respectively, it may accordingly be internalized by the pore-like structure, endocytosis pathways, or macro-pinocytosis process [85].

6. The membrane remodeling amphiphilic helix The MRAH has the ability to generate and stabilize membrane deformation. It usually exists at the N-terminal of traffic proteins such as Epsin [90] and small G proteins such as Sar1p or Arf [91, 92], and functions in producing intracellular transport vehicles [2, 93, 94]. In addition, in vitro experiments showed 6

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Figure 5. (A) Membrane spontaneous curvature as a function of insertion depth of membrane. Adapted with permission from [99]. Copyright 2008 Elsevier. (B) Membrane bud induced by α-synuclein. Adapted with permission from [104]. Copyright 2014 American Chemical Society.

that MRAH could help traffic proteins transform liposomes into small vesicles or membrane tubes tens of nanometers in diameter [90–95]. Apart from inducing membrane curvature, some APHs can also sense high membrane curvature, i.e. they can bind to the membrane in response to high membrane curvature [96, 97]. The so-called local spontaneous curvature mechanism (i.e. the hydrophobic insertion mechanism) was used to describe the mechanism of a MRAH inducing membrane curvature [2, 93, 94, 98]. As the hydrophobic and polar residues of the APH are simply segregated into two opposite faces, the APH is quite well suited for a shallow insertion into the hydrophobic– polar interface of membranes. It is assumed that the insertion of the APH into only one leaflet of membrane acts as a wedge. This changes the local lipid-packing and the stress pressure in the two layers of the membrane. In this way, the insertion of APH could change the spontaneous curvature of membranes (see figure 1(C)). Theoretical research by Campelo et al explored the efficiency of interfacially adsorbed peptide inducing membrane curvature [99]. The peptide was treated as a rod-like cylinder inclusion and the lipid monolayer was considered as an anisotropic elastic material. By analyzing the membrane stress generated by the embedded peptide, they found that the membrane deforms itself to relieve the strain of the two layers. In particular, they indicated that a middle membrane insertion depth (about 40% monolayer thickness) is most suitable for producing membrane curvature (see figure 5(A)) [99]. A similar result was reported in the theoretical research by Zemel et al [100]. By using a molecular-level chain-packing theory, they found that a shallow insertion depth (of the

peptide) induces positive membrane spontaneous curvature, while at insertion depths roughly equal to or larger than the half thickness of the monolayer’s hydrophobic tail, a negative membrane curvature will be generated. Our recent simulation also found that the insertion depth of the MRAH (from Epsin, Sar1p or Arf) is about 1.5 ∼ 2.1 nm from the center of a mixed bilayer of DOPS and DOPC lipids (about 4.2 nm in thickness), which is consistent with the theoretical prediction. Several specific MRAHs such as N-terminal APH from N-BAR protein [101, 102] and α-synuclein protein [103, 104] have attracted a lot of attention during the past few years. The N-BAR protein, for example, usually forms a dimer which contains a charged concave domain and two N-terminal APHs. It was found in one AA simulation that the concave surface plays the main role in bending the membrane, while the membrane-embedded APHs function in maintaining a close association with the bilayer [101]. But if the APHs are inserted into the membrane at sufficiently high concentrations, they could also drive membrane deformation independently [105, 106]. In addition, using AA simulations Cui et al focused on the curvature-sensing ability of N-terminal APH from endophilin [107]. Their results showed that large hydrophobic lipid-packing defects on a convex membrane can recruit APH and promote its folding on the membrane surface, while the APH helps to coalesce small defects into larger ones to decrease membrane surface energy [107]. Braun et al investigated the MRAH from α-synuclein, which is a Parkinson-related protein [103, 104]. After initially positioning 48 CG peptides in a spoke-like shape on the membrane surface, the membrane gradually formed a small bud 7

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due to the asymmetry of the two lipid layers (see figure 5(B)). This work also demonstrated the role of electrostatic attraction between peptide and lipids in inducing membrane curvature. It was found that the amphiphilic peptides can tubulate vesicles composed of pure anionic POPG lipids, but they cannot tubulate vesicles under the condition of 1 : 1 mixed anionic POPG and neutral POPC lipids [103, 104]. In addition, we should note that membrane buckling is not a unique feature of MRAH. For example, in one CG simulation, membrane buckling was also found when the membrane interacted with the AMP magainin 2 at a high concentration [108]. This is because, although segregated into AMP, magainin 2 also presents amphiphilicity. So apart from inducing a membrane pore, it could also initiate membrane bending. Therefore, it is reasonable to speculate that other types of helical peptides with amphiphilicity may also have the capability of deforming membranes.

Each conformation of FP has different proportions of α helix and β strand segments [119]. This indicates a high conformational flexibility of FPs, which is also emphasized in several other computational works [117, 118]. As the FP is involved in different virus fusion processes, it may constantly change its structure or adjust its orientation relative to the membrane. This may make FPs present a high conformational flexibility. The role of FPs in the post-fusion process, including the formation and evolution of the fusion stalk and fusion pore, was recently brought to the fore [3]. For example, experimentally, the N-terminal FP of the paramyxovirus parainfluenza virus 5 fusogenic protein was found to gradually approach and associate with the C-terminal transmembrane helix, driven by thermodynamically favorable interactions [123]. The association could promote the elongation of the hemifusion stalk, and lead to the formation of a fusion pore. Also there have been several computational simulations that revealed the role of the FP in the formation and evolution of fusion intermediates. In one CG simulation, Risselada et al reported that a compacted FP peptide bundle could stabilize the fusion stalk and expand the stalk into the hemifusion diaphragm [124]. Using CG simulations, Fuhrmans et al directly investigated the phase behavior of the lipid membrane in the presence of FPs from influenza hemagglutinin [122, 125]. They found that the system forms an innovative bi-continuous single diamond cubic phase with FD3m10 symmetry (see figure 6). The cubic phase was composed of stalks and pores. The authors suggested that FPs could promote the generation of positive membrane curvature and stabilize the membrane pore. It was proposed that the kinked structure of the FP is well suited to being locates between the bases of two emerging stalks with its helical arms neatly lying on the surface. By this means, FP is favorable to reduce Gaussian curvature elastic energy in forming an intermediate fusion structure [125].

7. The fusion peptide The FP is the N-terminal segment of viral fusion glycoprotein [3, 109]. It is usually hydrophobic with a sequence length of about 20–30 residues. During a virus infection, FPs facilitate the fusion between the virus membrane and the targeting membrane by harpooning themselves into the host cell membrane (see figure 1(D)). In vitro experiments showed that a FP is able to promote the mixture of vesicles [110, 111]. Understanding the viral fusion mechanism could not only help to design an appropriate virus (such as HIV or influenza) infection inhibitor to intervene in the virus fusion process, but also promote engineering membrane FP catalysts to enhance lipid mixing and intracellular transport [112]. The fusion process of the virus membrane and its targeting membrane, such as a mammalian cell membrane, needs to go through several different stages [113], including the initial approach of virus membrane to its targeting membrane, the formation of a hemi-fusion stalk, the fusion pore mediated mixture of aqueous contents, and the final rupture of the fusion pore [114, 115]. The FP is thought to be involved in all of these different fusion stages. Several computational simulations focused on the initial membrane approach and insertion of the FP, as well as its effect on the targeting membrane [116–119]. In particular, for FPs from the influenza virus, the effect of the peptide on the membrane shows a pH-responsive behavior [120]. In a low pH environment, the peptide undergoes conformational change and becomes a little bent at its middle. The kinked helical structure was proved to be required for the fusion activity of the influenza virus [118, 120–122]. By using AA simulation, Li et al compared the FP and its six mutants in a DPPC bilayer [118]. They found that the wild type FP retaining the kinked structure has a more distinct effect on reducing the bilayer thickness in its vicinity. The FP from the HIV-1 virus does not show pH-responsive behavior, but it was found to present a very high conformational flexibility. Within a 300 ns AA simulation of a FP (from the HIV-1 virus) in solution, Venken et al found that the FP can undergo multiple possible conformations.

8. The amyloid peptide Amyloid peptides, such as islet amyloid polypeptide (IAPP) [126], β-amyloid (Aβ) peptide [127], and α-synuclein peptide [128], can form cytotoxic oligomers or fibrils [4]. It is thought that the membrane acts as a template to catalyze the amyloidogenic fibril growth (see figure 1(E)). In the meantime, the amyloid peptide misfolds and the fibril deposit may compromise the structural integrity of the cell membrane, leading to related diseases such as type II diabetes mellitus, Alzheimer’s disease and Parkinsonism diseases [4, 126–129]. Research of this type can aid in the design of specific compounds to alleviate the neuro-degeneration of Alzheimer’s disease and treat other related diseases of the elderly [130, 131]. The membrane promotes the mobility and accumulation of the amyloid peptide on the two-dimensional membrane surface. In this way, the probability of peptides contacting each other increases greatly, which can accelerate the formation of β sheet rich amyloid peptide oligomers. Several membrane constituents (including anionic lipids, cholesterol, and ganglioside) were found to play a particular role in promoting the accumulation of peptides [132–136]. In one CG simulation, 8

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Figure 6. Bi-continuous single diamond cubic phase with FD3m10 symmetry produced by an influenza HA FP (cross section). (A) Domains of the water and headgroup of lipids. (B) Domains of the lipid tail and peptides. The gray is for lipid tails, magenta is for glycerol beads, blue is for water and headgroup beads, brown is for the backbone atoms of the peptide, and yellow is for the side chains of the peptide. The green denotes the surface which separates the lipid tail from the rest of the system. Adapted with permission from [122]. Copyright 2009 American Chemical Society.

Figure 7. (A) A schematic representation of the interaction of the peptide (cartoon) interacting with the membrane cholesterol (sticks). Adapted with permission from [138]. Copyright 2011 American Chemical Society. (B) Formation of an amyloidogenic fibril on the membrane surface. Adapted with permission from [139]. Copyright 2014 American Chemical Society.

it was found that the cholesterol can impose an IAPP positioned at the membrane surface (favorable for peptide aggregation), while in the absence of cholesterol, the IAPP will insert into the membrane and adopt a pore-like assembly structure [132]. Gangliosides were found to be recruited into the membrane microdomain by favorable interaction with the Aβ peptide. Meanwhile, the accumulation of gangliosides could further accelerate the formation of Aβ peptide fibrils on the membrane microdomain [133, 134]. Using AA simulation, Lemkul et al found that ganglioside promotes the conformational conversion of Aβ peptide from an α-helix to a β-strand structure [134]. Ganglioside, cholesterol, and sphingomyelin are the main constituents of the lipid raft. There is evidence that the elevation of cholesterol levels could result in an increased risk of Alzheimer’s disease. These findings highlight the potential effect of the membrane microdomain or lipid raft on amyloidogenic fibril growth. There is a need to know why some lipid constituents (such as anionic lipid and cholesterol) are vital to membrane

catalyzed peptide aggregation. A reason was suggested by several computational studies, which indicated that the existence of several special lipids could bring a subtle balance between peptide–membrane and peptide–peptide interaction [135–138]. For example, a very strong peptide–membrane interaction could be unfavorable for both the association between different amyloid peptides and the eventual release of the mature fibril into solvents. By using a thermodynamic cycle and umbrella sampling molecular dynamics, David and Berkowitz investigated the dimerization of the Aβ peptide on zwitterionic DPPC or anionic DOPS bilayer surfaces [135, 136]. They found that the anionic DOPS lipids promote strong peptide–peptide interaction but weak peptide–lipid interactions, while the role of DPPC is just the reverse. So DOPS could promote aggregation of Aβ peptide into higher-order structures. In the meantime, the weak peptide–lipid interactions could be favorable for the final release of the mature fibril. A similar negative correlation between cholesterol–Aβ peptide interaction and Aβ peptide–Aβ peptide interaction 9

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Figure 8. Encounter complex formed by KTX and the extracellular surface of KcsA-Kv1.3 Left: starting configuration; right: final configuration. Adapted with permission from [153]. Copyright 2008 Elsevier.

with the membrane proteins. In many cases, the peptide acts directly as the ligand of the corresponding membrane protein receptors (see figure 1(F)) [149–151]. The association of peptide to membrane proteins may induce the dysfunction of proteins and lead to some related diseases [152, 153]. In contrast, targeting of peptides to functional membrane protein may be also used in the treatment of some mental or metabolic diseases. For example, the targeting of peptides to the ion channel could block the ion conductance and hence alleviate pain in some diseases. The current computational research of peptides interacting with functional membrane proteins has mainly focused on the peptide binding site of the membrane protein, as well as the structure and conformational flexibility of the peptide– membrane protein complex. The association of a peptide to a membrane receptor could usually shift the conformation of the anchored protein into some more stable conformations. Interaction of a toxin with an ion channel could be one of the most well-known peptide–protein complexes. In one AA simulation, Eriksson and Roux found that the binding of peptide Agitoxin (AgTx2) can induce a conformational change of the Shaker K+ ion channel [152]. Similarly using AA simulation, Zachariae et al studied the tight binding of the peptidic toxin Kaliotoxin (KTX) to the potassium channel (KcsA–Kv1.3) [153]. It was found that the peptide undergoes a locally conformational change after binding to the the ion channel (an orientation change of several residues and a change in the protonation state of Glu71) (see figure 8). In the meantime, the entrance portion of the ion channel is distorted upon peptide binding, which is validated by comparing the chemical shift obtained in the solid state NMR experiments. These conformational changes are sufficient to allow for an efficient KTX blockage of the channel. Several other computational studies focused on the interaction of peptides with GPCRs [154, 155]. In the study of peptide–receptor interaction, it is usually necessary to carefully analyze the electrostatic, hydrophobic, and hydrogen bond interaction between the peptide and membrane protein, as well as the effect of the proximal solvents [152–155]. By using AA simulation, Kirkpatrick et al studied the affinity of peptide Exendin-4 to a glucagon-like peptide 1 receptor

was also reported by Zhao et al through AA simulations (see figure 7(A)), where the cholesterol also promotes strong peptide–peptide interaction on the membrane surface [138]. Computational studies have also revealed a potential membrane disruption mechanism due to amyloid peptide aggregates or amyloid fibrils [139–143]. By using a CG model, Morriss-Andrews et al observed directly the formation of a single-layer amyloid fibril connected by a β-sheet structure (see figure 7(B)). It was found that the amyloid fibril could rigidify the membrane and the bending modulus of the membrane is locally increased by about 50% in the fibril-associated regions in comparison to the unassociated regions [139]. The membrane disruption of amyloid peptide was also reported to show co-operativity, as it was shown in one AA simulation that the membrane perturbation by a membrane-bound IAPP dimer is more pronounced than in the case of two IAPP monomers acting on the membrane [140]. Experimentally, it was proposed that the growing fibril will exert a force to the cell membrane and lead to membrane distortions at the location where the fibril and membrane separate [144, 145]. In addition, the channel hypothesis of Alzheimer’s disease suggests that the Aβ amyloid deposits can directly disrupt membranes through formation of ion conductive channels [146]. In some simulations, the membrane-bound amyloidogenic peptide oligomers was found to enhance water permeation in the vicinity of peptides [141, 143]. For example, using a CG model, Friedman et al showed that during the peptide aggregation process, some peptides will insert into the membrane to form pore-like membrane defects. In particular, they indicated that mature fibrils do not damage the membrane and it is the growing aggregates that induce the water leakage [141]. 9. Specific peptides interacting with functional membrane proteins The cell membrane is embedded with a lot of membrane proteins, which make up about half of the mass of the cell membrane. The membrane proteins are the main target for drugs. In particular, the G protein-coupled receptors (GPCRs) are the target of approximately 40% of modern medicinal drugs [147, 148]. In addition, there is a possibility of peptides interacting 10

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Figure 9. PMFs for the different types of α-helical peptides partitioning into membrane. The helices are described as cylinders and classified into different categories according to the distribution of hydrophobic and polar residues along the α-helix. Blue denotes the hydrophobic face, while white denotes the hydrophilic face of α-helical peptides. Adapted with permission from [159]. Copyright 2010 American Chemical Society.

(GLP1R) [154]. They found that the association of peptide to receptor is enhanced by 14 pairs of strong polar interactions of Exe4 with GLP1R and 10 pairs of hydrophobic interactions. By combining molecular docking and molecular dynamics simulations, Xu et al investigated the binding of neuropeptide Y and peptide YY to the human GPCR Y2, where the role of a hydrogen bond network in peptide binding was emphasized [155]. This work also revealed that several residues (Thr2.61, Gln3.32, and His7.39), which are highly conserved in the neuropeptide Y receptor family, can create a hydrogen bond network to stabilize the peptide binding and receptor structure. Peptides may also interact with the membrane receptors in some indirect (e.g. membrane-mediated) ways (see figure 1(F)). The membrane-catalysis hypothesis [156–158] proposed that the peptide needs to bind to the membrane surface first before association with the membrane receptors. The membrane constrains the diffusion of the peptide on the two-dimensional membrane surface and increases the local concentration of peptides. In this way, the probability of the peptide contacting membrane receptors increases greatly. In addition, by interacting with the membrane, the peptide may adopt more favorable conformations to enhance its further association with the membrane receptor. For example, if the peptide adopts a transmembrane α-helical structure, it may be able to associate with the helical transmembrane domain of many membrane proteins. However, currently only little is known about the docking site of peptide–receptor interaction in the lipid environment.

partitioning into the membrane [159]. The PMF curves for pore formation peptide LS3 ((LSSLLSL)3, type I), amphiphilic non-spanning helix LAP-20 (VSSLLSSLKEYWSSLKESFS, type II), a FP from simian immunodeficiency virus (GVFVLGFLGFLA, type III), and transmembrane helical peptide N-pHLIP (ACEQNPIYWARYANWLFTTPLLL LNLALLVDADEGTG, type IV) were found to differ from each other greatly (see figure 9). The free energy morphology correlates with the corresponding mechanism of the peptide interacting with the membrane. For example, the PMF for an amphiphilic non-spanning helix LAP-20 shows two minima at the membrane interface and a very high energy barrier for penetrating into the membrane. So it is favorable for a partial insertion into the membrane. For the simulated FP, the energy minimum was also at the lipid interface, but only a relatively smaller energy penalty was needed for the peptide locating in the center of the bilayer. This may be favorable for the FP adopting more flexible conformations in the membrane. Although segregated into different classes, the peptides discussed here are not completely independent from each other. Instead, they also share some similarities with each other. For example, a pore-forming mechanism could appear in the cases of AMP, CPP, and amyloid peptides interacting with membrane. The FP is also involved in the formation and stabilization of the fusion pore in the post-fusion process. In addition, membrane catalyzed peptide accumulation on the membrane surface was proposed in the interaction of the amyloid peptide with the membrane, as well as the interaction of the peptide with membrane receptors. Besides, many kinds of peptides within or beyond the scope of this review could present amphiphilicity, thus they may also have some impact on deforming the membrane (such as the MRAH) when inserted into the membrane [103, 108]. The investigation of the differences and similarities between different kinds of peptides may initiate us to design a synthetic peptide which could combine the merits of different peptides. For example, the recently reported pH-responsive peptide pHLIP [160] showed not only a pH-responsive behavior like the FP, but also an efficient membrane transport ability of cell impermeable molecules like the CPP [161, 162]. In a basic pH environment, the pHLIP only binds to the membrane surface, but in a low pH environment, it can fold and insert

10. Differences and similarities between different peptide–membrane interactions As discussed above, different types of peptides may show distinct interaction behaviors when approaching into the cell membranes. Since the binding affinity of the peptide to the membrane as well as its partitioning behavior are closely associated with the free energy morphology of peptide interacting with the membrane, the calculation of PMF could help provide a better understanding of the differences between different peptides interacting with the membrane. Recently, by using CG simulation, Gkeka et al chose several representative α-helical peptides and calculated the PMF of the peptide 11

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into the membrane. So it can target tumor tissue with an extracellular low pH environment. In addition, the decoration of nanoparticles or polymers onto peptides can also affect their interaction with membranes [163–165]. In this way, one can control well the peptide–membrane interactions, which may be beneficial for better use of peptides or peptide-based mat erials in biomedicine.

There is a need to provide a multi-level description of the peptide–membrane interaction. In many cases, the atomicdetail hydrogen bond and hydration interaction are very important for the peptide–membrane interaction. But if a process involves a large morphology change of proteins or membranes, it is better to investigate the system using the CG method. Thus it may be better to combine CG and AA simulations to study these problems from the microscope to mesoscopic view [35–37]. Recently, a hybrid AA and CG model was proposed [168], where different simulation strategies (AA or CG method) are applied for different regions in a simulation box. In addition, it is essential to improve the present force field, especially for the CG force field (e.g. how to improve the description of the hydrogen bond, solvent, and the secondary structure of the peptide/protein in CG modeling). High-performance computing power urgently needs to be improved for large-scale molecular simulations. This could be of crucial importance in simulating a more complicated peptide–membrane system for a longer time, such as the endocytosis of CPP and the interaction of peptides with functional membrane proteins. In addition, this is also very important for several currently unsolved problems, including the folding process of peptides upon hydrophobic insertion into the membrane, as well as the large conformational transition of functional proteins.

11. Summary and perspective Given the significant role of peptides in basic membrane functions and the great opportunities that peptides hold for bio-applications, a comprehensive understanding of peptide– membrane interaction is becoming more and more important. In this review, we have presented the recent theoretical and computational progress on the interaction of peptides with the membrane in different biological processes. Depending on their type, different peptides are able to dissolve the membrane, initiate membrane defects, translocate across the membrane, trigger membrane endocytosis, and produce membrane deformation. Moreover, the membrane can also act as a template for amyloid peptide aggregation or peptide–membrane receptor signaling communication. Although great progress has been achieved in recent years, there are still a lot of challenging problems in this promising field. In the future, from the computational point of view, the following issues should be brought to the fore. Much more attention should be paid to the effect of external environments and macromolecules on the peptide–membrane interaction. For example, if the peptide is enriched by basic amino acids, the charge of the peptide will be dramatically influenced by the external pH, which may in turn affect its interaction with membranes. In addition, considering that the membrane is modified with many glycans at its extracellular region, the peptide may also interact with this sugar coating. Also, if the peptide (such as AMP and CPP) is used for clinical applications, it may need to encounter more biomolecules (in particular charged molecules) in the human body [166, 167]. Currently, there is little research concerning these issues, and more intensive studies are required in the future to consider the role of these external factors. It could be very valuable, although not easy, to better clarify the differences and similarities between the interactions of membranes with different peptides. For example, the CPP, MRAH, and FP could all induce or stabilize positive membrane curvature, but they use completely different mechanisms. For CPP, the Y-shaped contour of the guanidinium of arginine residues contributes to generating positive curvature. For the APH, the reason lies in the (shallow) insertion of the APH. For FP from influenza hemagglutinin, its integrally kinked structure is thought to be responsible for inducing the positive membrane curvature. Although calculation of the PMFs of different peptides partitioning into the membrane could be very useful as discussed in section 10, there is still a long way to go to establish the relationship between the properties of peptides and the potential membrane response, which calls for more detailed information about the peptide–membrane interaction.

Acknowledgments This work is supported by the National Natural Science Foundation of China (Nos. 91427302 and 11474155) and the National Basic Research Program of China (No. 2012CB821500). References [1] Zasloff M 2002 Antimicrobial peptides of multicellular organisms Nature 415 389–95 [2] McMahon H T and Gallop J L 2005 Membrane curvature and mechanisms of dynamic cell membrane remodelling Nature 438 590–6 [3] Harrison S C 2008 Viral membrane fusion Nat. Struct. Mol. Biol. 15 690–8 [4] Butterfield S and Lashuel H 2010 Amyloidogenic protein– membrane interactions: mechanistic insight from model systems Angew. Chem., Int. Ed. Engl. 49 5628–54 [5] Hancock R E W and Sahl H G 2006 Antimicrobial and hostdefense peptides as new anti-infective therapeutic strategies Nat. Biotechnol. 24 1551–7 [6] Gupta B, Levchenko T S and Torchilin V P 2005 Intracellular delivery of large molecules and small particles by cellpenetrating proteins and peptides Adv. Drug Delivery Rev. 57 637–51 [7] Dror R O et al 2013 Structural basis for modulation of a G-protein-coupled receptor by allosteric drugs Nature 503 295–9 [8] Arkhipov A, Shan Y, Das R, Endres N F, Eastwood M P, Wemmer D E, Kuriyan J and Shaw D E 2013 Architecture and membrane interactions of the EGF receptor Cell 152 557–69 12

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17

Interaction of Iron II Complexes with B-DNA. Insights from Molecular Modeling, Spectroscopy, and Cellular Biology.

Insulin receptor: interaction with nonreceptor glycoprotein from liver cell membranes.

Chemokines and their receptors: insights from molecular modeling and crystallography.

Binding characteristics of psoralen with trypsin: Insights from spectroscopic and molecular modeling studies.

Interaction of amyloid inhibitor proteins with amyloid beta peptides: insight from molecular dynamics simulations.

Molecular Interactions of Flavonoids to Hyaluronidase: Insights from Spectroscopic and Molecular Modeling Studies.

Peptide-ligand binding modeling of siRNA with cell-penetrating peptides.

Probing the interaction of anthraquinone with DNA by spectroscopy, molecular modeling and cancer cell imaging technique.

Molecular modeling in dioxane methanol interaction.

Molecular interaction of PCB180 to human serum albumin: insights from spectroscopic and molecular modelling studies.

TFPI2: Structural insights from molecular modeling studies.

The role of spontaneous lipid curvature in the interaction of interfacially active peptides with membranes.

ATP dependent NS3 helicase interaction with RNA: insights from molecular simulations.

Interaction of Vibrio cholerae toxin with sarcoma 180 cell membranes.

Design and synthesis of basic peptides having amphipathic beta-structure and their interaction with phospholipid membranes.

Prediction of linear cationic antimicrobial peptides based on characteristics responsible for their interaction with the membranes.

Interaction of human immunodeficiency virus (HIV-1) fusion peptides with artificial lipid membranes.

Interaction of Alzheimer's β-amyloid peptides with cholesterol: mechanistic insights into amyloid pore formation.

Molecular Modeling of Myrosinase from Brassica oleracea: A Structural Investigation of Sinigrin Interaction.

Interaction of prometryn to human serum albumin: insights from spectroscopic and molecular docking studies.

Platelet interaction with activated endothelium: mechanistic insights from microfluidics.

Insights from molecular modeling, docking and simulation of imidazole nucleus containing chalcones with EGFR kinase domain for improved binding function.

Binding difference of fipronil with GABAARs in fruitfly and zebrafish: insights from homology modeling, docking, and molecular dynamics simulation studies.

Interaction of digitoxigenin with lecithin membranes.