Self-Assembly of Amphiphilic Peptide (AF)6H5K15: Coarse-Grained Molecular Dynamics Simulation

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

A coarse-grained Molecular Dynamics study of phase behavior in Co-assembled lipomimetic oligopeptides

Multicomponent biomolecular aggregates, i.e., systems consisting of more than one type of biomolecular component co-assembling into one aggregate, provide an interesting design space for engineering unique biomaterials. In this study, we examine the co-assembly of two lipomimetic oligopeptide block copolymers selected for their lipid-like amphiphilicity and highly similar architectures into nanofibers via coarse-grained MD simulations. We focus on the behavior of these peptides due to incremental differences in size by selecting two peptides that differ in length by exactly one amino acid residue. We find that the longer peptide sequence displays greater self-association properties.

Development, Validation, and Applications of Nonbonded Interaction Parameters between Coarse-Grained Amino Acid and Water Models

Interactions between amino acids and water play an important role in determining the stability and folding/unfolding, in aqueous solution, of many biological macromolecules, which affects their function. Thus, understanding the molecular-level interactions between water and amino acids is crucial to tune their function in aqueous solutions. Herein, we have developed nonbonded interaction parameters between the coarse-grained (CG) models of 20 amino acids and the one-site CG water model. The nonbonded parameters, represented using the 12-6 Lennard Jones (LJ) potential form, have been optimized using an artificial neural network (ANN)-assisted particle swarm optimization (PSO) (ANN-assisted PSO) method. All-atom (AA) molecular dynamics (MD) simulations of dipeptides in TIP3P water molecules were performed to calculate the Gibbs hydration free energies. The nonbonded force-field (FF) parameters between CG amino acids and the one-site CG water model were developed to accurately reproduce these energies. Furthermore, to test the transferability of these newly developed parameters, we calculated the hydration free energies of the analogues of the amino acid side chains, which showed good agreement with reported experimental data. Additionally, we show the applicability of these models by performing self-assembly simulations of peptide amphiphiles. Overall, these models are transferable and can be used to study the self-assembly of various biomaterials and biomolecules to develop a mechanistic understanding of these processes.

Formulation and Skin Permeation of Active-Loaded Lipid Nanoparticles: Evaluation and Screening by Synergizing Molecular Dynamics Simulations and Experiments

Encapsulation into nanoparticles (NPs) is a potential method to deliver pharmaceutical/cosmetic actives deep into the skin. However, understanding the NP formulations and underlying mechanism of active delivery to skin has scarcely been studied. We report a simulation platform that screens, evaluates, formulates, and provides atomic-resolution interpretation of NP-based formulations, and reveals the active permeation mechanism from NPs to skin. First, three actives, namely, ferulic acid (FA), clotrimazole (CZE), and tretinoin (TTN), and five lipid excipients' (Compritol, Precirol, Geleol, Gelot, Gelucire) combinations were screened by MD simulations for the best pairs. For each suggested pair, the actual active and lipid compositions for the synthesis of stable NP formulations were then obtained by experiments. MD simulations demonstrate that in NP formulations, FA and CZE actives are present at the surface of the NPs, whereas TTN actives are present at both the surface and interior of the NP core. The NP shapes obtained by simulation perfectly match with experiments. For each NP, separate MD simulations illustrate that active-loaded NPs approach the skin surface quickly, and then actives translocate from NP surface to skin surface followed by penetration of NPs through skin. The driving force for the translocation which initiates during the penetration process, is the stronger active-skin interaction compared to active-NP interaction. Permeation free energy indicates spontaneous transfer of actives from solution phase to the surface of the skin bilayer. The free energy barriers are increased in the order of FA < TTN < CZE. Significantly lower diffusions of actives are obtained in the main barrier region compared to bulk, and the average diffusion coefficients of actives are in the same order of magnitude (∼10^-6 cm²/s). The estimated permeability coefficients (log P) of actives are mainly governed by free energy barriers. The study would facilitate the development of novel lipid-based NP formulations for personal-care/pharmaceutical applications.

Computer-Aided Design of Lasso-like Self-Assembling Anticancer Peptides with Multiple Functions for Targeted Self-Delivery and Cancer Treatments

Anticancer peptides are promising drug candidates for cancer treatment, but the short circulation time and low delivery efficiency limit their clinical applications. Herein, we designed several lasso-like self-assembling anticancer peptides (LASAPs) integrated with multiple functions by a computer-aided approach. Among these LASAPs, LASAP1 (CRGDKGPDCGKAFRRFLGALFKALSHLL, 1-9 disulfide bond) was determined to be superior to the others because it can self-assemble into homogeneous nanoparticles and exhibits improved stability in serum. Thus, LASAP1 was chosen for proving the design idea. LASAP1 can self-assemble into nanoparticles displaying iRGD on the surface because of its amphiphilic structure and accumulate to the tumor site after injection because of the EPR effect and iRGD targeting to αVβ3 integrin. The nanoparticles could disassemble in the acidic microenvironment of the solid tumor, and cleaved by the overexpressed hK2, which was secreted by prostate tumor cells, to release the effector peptide PTP-7b (FLGALFKALSHLL), which was further activated by the acidic pH. Therefore, LASAP1 could target the orthotopic prostate tumor in the model mice after intraperitoneal injection and specifically inhibit tumor growth, with low systematic toxicity. Combining the multiple targeting functions, LASAP1 represents a promising design of self-delivery of peptide drugs for targeted cancer treatments.

Computational and Experimental Evaluation of the Stability of a GLP-1-like Peptide in Ethanol–Water Mixtures

Aggregation resulting from the self-association of peptide molecules remains a major challenge during preformulation. Whereas certain organic solvents are known to promote aggregation, ethanol (EtOH) is capable of disrupting interactions between peptide molecules. It is unclear whether it is beneficial or counterproductive to include EtOH in formulations of short peptides. Here, we employed molecular dynamics simulations using the DAFT protocol and MARTINI force field to predict the formation of self-associated dimers and to estimate the stability of a GLP-1-like peptide (G48) in 0–80% aqueous EtOH solutions. Both simulation and experimental data reveal that EtOH leads to a remarkable increase in the conformational stability of the peptide when stored over 15 days at 27 °C. In the absence of EtOH, dimerisation and subsequent loss in conformational stability (α-helix → random coil) were observed. EtOH improved conformational stability by reducing peptide–peptide interactions. The data suggest that a more nuanced approach may be applied in formulation decision making and, if the native state of the peptide is an α-helix organic solvent, such as EtOH, may enhance stability and improve prospects of long-term storage.

Peptide framework for screening the effects of amino acids on assembly

Discovery of peptide domains with unique intermolecular interactions is essential for engineering peptide-based materials. Rather than attempting a brute-force approach, we instead identify a previously unexplored strategy for discovery and study of intermolecular interactions: “co-assembly of oppositely charged peptide” (CoOP), a framework that “encourages” peptide assembly by mixing two oppositely charged hexapeptides. We used an integrated computational and experimental approach, probed the free energy of association and probability of amino acid contacts during co-assembly with atomic-resolution simulations, and correlated them to the physical properties of the aggregates. We introduce CoOP with three examples: dialanine, ditryptophan, and diisoleucine. Our results indicated that the opposite charges initiate the assembly, and the subsequent stability is enhanced by the presence of an undisturbed hydrophobic core. CoOP represents a unique, simple, and elegant framework that can be used to identify the structure-property relationships of self-assembling peptide-based materials.

A hybrid coarse-grained model for structure, solvation and assembly of lipid-like peptides

Reconstituted photosynthetic proteins which are activated upon exposure to solar energy hold enormous potential for powering future solid state devices and solar cells. The functionality and integration of these proteins into such devices has been successfully enabled by lipid-like peptides. Yet, a fundamental understanding of the organization of these peptides with respect to the photosynthetic proteins and themselves remains unknown and is critical for guiding the design of such light-activated devices. This study investigates the relative organization of one such peptide sequence V₆K₂ (V: valine and K: lysine) within assemblies. Given the expansive spatiotemporal scales associated with this study, a hybrid coarse-grained (CG) model which captures the structure, conformation and aggregation of the peptide is adopted. The CG model uses a combination of iterative Boltzmann inversion and force matching to provide insight into the relative organization of V₆K₂ in assemblies. The CG model reproduces the structure of a V₆K₂ peptide sequence along with its all atom (AA) solvation structure. The relative organization of multiple peptides in an assembly, as captured by CG simulations, is in agreement with corresponding results from AA simulations. Also, a backmapping procedure reintroduces the AA details of the peptides within the aggregates captured by the CG model to demonstrate the relative organization of the peptides. Furthermore, a large number of peptides self-assemble into an elongated micelle in the CG simulation, which is consistent with experimental findings. The coarse-graining procedure is tested for transferability to longer peptide sequences, and hence can be extended to other amphiphilic peptide sequences.

Probing mechanical properties and failure mechanisms of fibrils of self-assembling peptides

Self-assembling peptides (SAPs) are a promising class of biomaterials amenable to easy molecular design and functionalization. Despite their increasing usage in regenerative medicine, a detailed analysis of their biomechanics at the nanoscale level is still missing. In this work, we propose and validate, in all-atom dynamics, a coarse-grained model to elucidate strain distribution, failure mechanisms and biomechanical effects of functionalization of two SAPs when subjected to both axial stretching and bending forces. We highlight different failure mechanisms for fibril seeds and fibrils, as well as the negligible contribution of the chosen functional motif to the overall system rupture. This approach could lay the basis for the development of "more" coarse-grained models in the long pathway connecting SAP sequences and hydrogel mechanical properties.

Encapsulation of an endostatin peptide in liposomes: Stability, release, and cytotoxicity study

The endostatin protein is a potent inhibitor of angiogenesis and tumor growth. The anti-angiogenic and antitumor properties of full-length endostatin can be mimicked by its N-terminal segment, including residues 1-27. Therefore, our previous studies have shown that a mutant N-terminal peptide which the Zn-binding loop was replaced by a disulfide loop (referred to as the ES-SS peptide) has preserved antiangiogenic and antitumor properties compared to the native peptide. To increase stability and plasma half-life of the ES-SS peptide, the nano-sized liposomal formulations of the peptide with different ratio of phosphocholine (PC) were synthesized. The liposomal peptide formulations possessed an average size of around 100 nm with (-4 to -36 mv) in zeta potential. The encapsulation efficiency of the ES-SS peptide was in the range of 24-54% with different lipid: peptide molar ratios. In vitro release of the peptide from liposomes indicated a complete peptide release after 7 days. Cytotoxicity assay was evaluated using the human umbilical vein endothelial cells (HUVECs) for various concentrations of the liposomal peptide. The results depicted the gradual release of the peptide through liposomes. By comparing with the free peptide, the liposomal peptide formulations have indicated higher cell viability with IC₅₀ value about 0.1 μM. The peptide-liposome interactions, as well as the peptide effect on the liposome structure, were also investigated through coarse-grained molecular dynamics (CG-MD) simulation. The results revealed that the peptides were assembled in the hydrophilic core of the liposome. The peptide behavior in liposome can stabilize the liposome structure and be a response to the observed low peptide release rate. The investigation is promising for designing a liposome-based anti-angiogenesis peptide delivery system.

Self-Assembly Behavior of Amphiphilic Janus Dendrimers in Water: A Combined Experimental and Coarse-Grained Molecular Dynamics Simulation Approach

Amphiphilic Janus dendrimers (JDs) are repetitively branched molecules with hydrophilic and hydrophobic components that self-assemble in water to form a variety of morphologies, including vesicles analogous to liposomes with potential pharmaceutical and medical application. To date, the self-assembly of JDs has not been fully investigated thus it is important to gain insight into its mechanism and dependence on JDs’ molecular structure. In this study, the aggregation behavior in water of a second-generation bis-MPA JD was evaluated using experimental and computational methods. Dispersions of JDs in water were carried out using the thin-film hydration and ethanol injection methods. Resulting assemblies were characterized by dynamic light scattering, confocal microscopy, and atomic force microscopy. Furthermore, a coarse-grained molecular dynamics (CG-MD) simulation was performed to study the mechanism of JDs aggregation. The obtaining of assemblies in water with no interdigitated bilayers was confirmed by the experimental characterization and CG-MD simulation. Assemblies with dendrimersome characteristics were obtained using the ethanol injection method. The results of this study establish a relationship between the molecular structure of the JD and the properties of its aggregates in water. Thus, our findings could be relevant for the design of novel JDs with tailored assemblies suitable for drug delivery systems.

Molecular simulations of peptide amphiphiles

This review describes recent progress in the area of molecular simulations of peptide assemblies, including peptide-amphiphiles and drug-amphiphiles. The ability to predict the structure and stability of peptide self-assemblies from the molecular level up is vital to the field of nanobiotechnology. Computational methods such as molecular dynamics offer the opportunity to characterize intermolecular forces between peptide-amphiphiles that are critical to the self-assembly process. Furthermore, these computational methods provide the ability to computationally probe the structure of these supramolecular assemblies at the molecular level, which is a challenge experimentally. Herein, we briefly highlight progress in the areas of all-atomistic and coarse-grained simulation studies investigating the self-assembly process of short peptides and peptide amphiphiles. We also discuss recent all-atomistic and coarse-grained simulations of the self-assembly of a drug-amphiphile into elongated filaments. Next, we discuss how these computational methods can provide further insight into the pathway of cylindrical nanofiber formation and predict their biocompatibility by studying the interaction of these peptide-amphiphile nanostructures with model cell membranes.

High-Resolution Insights into the Stepwise Self-Assembly of Nanofiber from Bioactive Peptides

Peptide self-assembly has a profound biological significance since self-assembled bioactive peptides are gifted with improved bioactivity as well as life-span. In this study, peptide self-assembly was investigated using a therapeutic peptide, PTP-7S (EENFLGALFKALSKLL). Combining experiments of atomic force microscopy (AFM), circular dichroism (CD), and 8-anilino-1-naphthalenesulfonic acid (ANS) fluorescence spectra, PTP-7S showed the α-helical structure and was found self-assembling into nanofibers in solution. Relying on the coarse-grained (CG) dynamic simulations, the self-assembling of PTP-7S was revealed as a stepwise process that peptide monomers first clustered into peptide-assembling units (PUs) with charged surface, and then the PUs integrated together to construct nanofibril aggregates. Different roles of the nonbonded driving forces did play in the two phases: the hydrophobic force and electrostatic interaction acted as the predominant motivations in the formation of PUs and nanofiber, respectively. Moreover, the electrostatic interaction helped to guide the longitudinal growth of peptide nanofibers. A sequence principle is proposed for peptide self-assembling in aqueous solution: a balance of the counter charges and sufficient hydrophobicity degree. The self-assembled PTP-7S displayed good anticancer activity, proteases resistance, and sustained drug-release, showing a great potential for clinical application. This study reveals the molecular mechanism in explaining PTP-7S self-assembly and it is beneficial for future innovation of the self-assembled bioactive peptides.

Molecular simulations of self-assembly processes in metal-organic frameworks: Model dependence

Molecular simulation is a powerful tool for investigating microscopic behavior in various chemical systems, where the use of suitable models is critical to successfully reproduce the structural and dynamic properties of the real systems of interest. In this context, molecular dynamics simulation studies of self-assembly processes in metal-organic frameworks (MOFs), a well-known class of porous materials with interesting chemical and physical properties, are relatively challenging, where a reasonably accurate representation of metal-ligand interactions is anticipated to play an important role. In the current study, we both investigate the performance of some existing models and introduce and test new models to help explore the self-assembly in an archetypal Zn-carboxylate MOF system. To this end, the behavior of six different Zn-ion models, three solvent models, and two ligand models was examined and validated against key experimental structural parameters. To explore longer time scale ordering events during MOF self-assembly via explicit solvent simulations, it is necessary to identify a suitable combination of simplified model components representing metal ions, organic ligands, and solvent molecules. It was observed that an extended cationic dummy atom (ECDA) Zn-ion model combined with an all-atom carboxylate ligand model and a simple dipolar solvent model can reproduce characteristic experimental structures for the archetypal MOF system. The successful use of these models in extensive sets of molecular simulations, which provide key insights into the self-assembly mechanism of this archetypal MOF system occurring during the early stages of this process, has been very recently reported.

Elucidating the stability of bolaamphiphilic polypeptide nanosheets using atomistic molecular dynamics

Atomistic molecular dynamics was employed to characterize bolaamphiphilic polypeptides nanosheets.

Computational and experimental approaches for investigating nanoparticle-based drug delivery systems

Most therapeutic agents suffer from poor solubility, rapid clearance from the blood stream, a lack of targeting, and often poor translocation ability across cell membranes. Drug/gene delivery systems (DDSs) are capable of overcoming some of these barriers to enhance delivery of drugs to their right place of action, e.g. inside cancer cells. In this review, we focus on nanoparticles as DDSs. Complementary experimental and computational studies have enhanced our understanding of the mechanism of action of nanocarriers and their underlying interactions with drugs, biomembranes and other biological molecules. We review key biophysical aspects of DDSs and discuss how computer modeling can assist in rational design of DDSs with improved and optimized properties. We summarize commonly used experimental techniques for the study of DDSs. Then we review computational studies for several major categories of nanocarriers, including dendrimers and dendrons, polymer-, peptide-, nucleic acid-, lipid-, and carbon-based DDSs, and gold nanoparticles. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

The self-assembly mechanism of tetra-peptides from the motif of β-amyloid peptides: a combined coarse-grained and all-atom molecular dynamics simulation

Understanding the self-assembly mechanisms of tetra-peptides from Aβ-peptides into different nanostructures.

A computational study of the self-assembly of the RFFFR peptide

The β-amyloid peptide sequence, LVFFA, inspired the investigation of the fiber formation potential of the RFFFR peptide. The self-assembly was studied in silico by coarse grained-, atomistic molecular dynamics simulations and semi-empirical quantum mechanical calculations. The fiber formation was found to occur according to a three step process starting with the emergence of small aggregates that join together and form fiber segments that eventually form one continuous fiber. From a series of simulations the critical fiber concentration was determined to be in the interval between 70 mM and 100 mM. To obtain more structural information of the stable fiber, the final coarse grained configuration was backtransformed to atomistic detail. Based on this structure a 10 ns atomistic simulation was performed, which suggests that the fiber is stabilized by hydrogen bonds and water mediated hydrogen bonds. These stabilizing bonds are, however, reduced by competitive protein-water hydrogen bonds. Hence, π-stacking is suspected to play a larger role in fiber stabilization. The π-stacking of intermolecular Phe residues are found to favor a T-shaped stacking mode, while intramolecular π-stacking interactions assume a broad variety of modes from the parallel displaced mode to the T-shaped stacking mode and modes in between, with equal probability. Selected snapshots from the atomistic simulation were geometry optimized using semi-empirical quantum mechanical methods to validate the fiber stability and π-stacking configuration. An average Cα-RMSD was determined to be 2.68 Å. These findings indicate that the fiber may be used as a novel model system for the study of amyloid fibers or self-assembled conductive biowires, respectively.

Solvent effects on kinetic mechanisms of self-assembly by peptide amphiphiles via molecular dynamics simulations

Peptide amphiphiles are known to form a variety of distinctive self-assembled nanostructures (including cylindrical nanofibers in hydrogels) dependent upon the solvent conditions. Using a novel coarse-grained model, large-scale molecular dynamics simulations are performed on a system of 800 peptide amphiphiles (sequence, palmitoyl-Val3Ala3Glu3) to elucidate kinetic mechanisms of molecular assembly as a function of the solvent conditions. The assembly process is found to occur via a multistep process with transient intermediates that ultimately leads to the stabilized nanostructures including open networks of β-sheets, cylindrical nanofibers, and elongated micelles. Different kinetic mechanisms are compared in terms of peptide secondary structures, solvent-accessible surface area, radius of gyration, relative shape anisotropy, intra/intermolecular interactions, and aggregate size dynamics to provide insightful information for the design of functional biomaterials.

Molecular dynamics simulations of peptides at the air-water interface: influencing factors on peptide-templated mineralization

Biomineralization is the intricate, biomedically highly relevant process by which living organisms deposit minerals on biological matrices to stiffen tissues and build skeletal structures and shells. Rapaport and coworkers ( J. Am. Chem. Soc. 2000 , 122 , 12523 ; Adv. Funct. Mater. 2008 , 18 , 2889 ; Acta Biomater. 2012 , 8 , 2466 ) have designed a class of self-assembling amphiphilic peptides that are capable of forming hydrogels and attracting ions from the environment, generating structures akin to the extracellular matrix and promoting bone regeneration. The air-water interface serves both in experiment and in simulations as a model hydrophobic surface to mimic the cell's organic-aqueous interface and to investigate the organization of the peptide matrix into ordered β-pleated monolayers and the subsequent onset of biomineral formation. To obtain insight into the underlying molecular mechanism, we have used molecular dynamics simulations to study the effect of peptide sequence on aggregate stability and ion-peptide interactions. We find-in excellent agreement with experimental observations-that the nature of the peptide termini (proline vs phenylalanine) affect the aggregate order, while the nature of the acidic side chains (aspartic vs glutamic acid) affect the aggregate's stability in the presence of ions. These simulations provide valuable microscopic insight into the way ions and peptide templates mutually affect each other during the early stages of biomineralization preceding nucleation.

Molecular insights into the self-assembly of short amphiphilic peptides FmDn and FmKn

Molecular dynamics simulation is reported for the self-assembly of short amphiphilic peptides F_mD_n and F_mK_n.