The double cubic lattice method: Efficient approaches to numerical integration of surface area and volume and to dot surface contouring of molecular assemblies

Development of protease resistant and non-cytotoxic Jelleine analogs with enhanced broad spectrum antimicrobial efficacy

Short systemic half- life of Antimicrobial Peptides (AMP) is one of the major bottlenecks that limits their successful commercialization as therapeutics. In this work, we have designed analogs of the natural AMP Jelleine, obtained from royal jelly of apis mellifera. Among the designed peptides, J3 and J4 were the most potent with broad spectrum activities against a varied class of ESKAPE pathogens and fungus C. albicans. All the developed peptides were more effective against Gram-negative bacteria in comparison to the Gram-positive pathogens, and were especially effective against P. aeruginosa and C. albicans.J3 and J4 were completely trypsin resistant and serum stable, while retaining the non-cytotoxicity of the parent Jelleine, Jc. The designed peptides were membranolytic in their mode of action. CD and MD simulations in the presence of bilayers, established that J3 and J4 were non-structured even upon membrane binding and suggested that biological properties of the AMPs were innocent of any specific secondary structural requirements. Enhancement of charge to increase the antimicrobial potency, controlling the hydrophobic-hydrophilic balance to maintain non-cytotoxicity and induction of unnatural amino acid residues to impart protease resistance, remains some of the fundamental principles in the design of more effective antimicrobial therapeutics of the future, which may help combat the quickly rising menace of antimicrobial resistance in the microbes.

Structural Adaptation of Secondary p53 Binding Sites on MDM2 and MDMX

The thermodynamics of secondary p53 binding sites on MDM2 and MDMX were evaluated using p53 peptides containing residues 16-29, 17-35, and 1-73. All the peptides had large, negative heat capacity (ΔCp), consistent with the burial of p53 residues F19, W23, and L26 in the primary binding sites of MDM2 and MDMX. MDMX has a higher affinity and more negative ΔCp than MDM2 for p5317-35, which is due to MDMX stabilization and not additional interactions with the secondary binding site. ΔCp measurements show binding to the secondary site is inhibited by the disordered tails of MDM2 for WT p53 but not a more helical mutant where proline 27 is changed to alanine. This result is supported by all-atom molecular dynamics simulations showing that p53 residues 30-35 turn away from the disordered tails of MDM2 in P27A17-35 and make direct contact with this region in p5317-35. Molecular dynamics simulations also suggest that an intramolecular methionine-aromatic motif found in both MDM2 and MDMX structurally adapts to support multiple p53 binding modes with the secondary site. ΔCp measurements also show that tighter binding of the P27A mutant to MDM2 and MDMX is due to increased helicity, which reduces the energetic penalty associated with coupled folding and binding. Our results will facilitate the design of selective p53 inhibitors for MDM2 and MDMX.

Data on molecular docking and molecular dynamics targeting Mycobacterium tuberculosis shikimic acid kinase

We have previously performed a hierarchical in silico screening of a Mycobacterium tuberculosis shikimic acid kinase [1]. Specifically, 11 compounds were screened from a library of 154,118 compounds provided by ChemBridge [2] using UCSF DOCK [3] and the GOLD [4] program in the first and second steps, respectively. Molecular dynamic simulations were further performed on compound 2 (2-[(5Z)-5-(1-benzyl-5bromo-2-oxoindol-3-(5Z)-5-(1-benzyl-5-bromo-2-oxoindol-3-(5Z)-4-oxo-2 ylidene)-4oxo-2-sulfanylidene-1,3-thiazolidin-3-yl] acetic acid), which showed antimicrobial efficacy. These processes yielded ligand docking scores and trajectories. In this data article, we have added solvent-accessible surface area and PCA analyses, which were calculated from the raw docking scores and trajectories. Data obtained from molecular docking and molecular dynamic simulations are useful in two ways: (1) Further support for previous work (2) Provides a stepping stone for experimental scientists to conduct in silico studies and research ideas for other drug discovery researchers and computational biologists. We believe that this article will provide an opportunity to develop new Mycobacterium tuberculosis therapeutics through searching for analogs and inhibitors against new targets.

Structure of the human KMN complex and implications for regulation of its assembly

Biorientation of chromosomes during cell division is necessary for precise dispatching of a mother cell's chromosomes into its two daughters. Kinetochores, large layered structures built on specialized chromosome loci named centromeres, promote biorientation by binding and sensing spindle microtubules. One of the outer layer main components is a ten-subunit assembly comprising Knl1C, Mis12C and Ndc80C (KMN) subcomplexes. The KMN is highly elongated and docks on kinetochores and microtubules through interfaces at its opposite extremes. Here, we combine cryogenic electron microscopy reconstructions and AlphaFold2 predictions to generate a model of the human KMN that reveals all intra-KMN interfaces. We identify and functionally validate two interaction interfaces that link Mis12C to Ndc80C and Knl1C. Through targeted interference experiments, we demonstrate that this mutual organization strongly stabilizes the KMN assembly. Our work thus reports a comprehensive structural and functional analysis of this part of the kinetochore microtubule-binding machinery and elucidates the path of connections from the chromatin-bound components to the force-generating components.

Effect of Pressure on the Conformational Landscape of Human γD-Crystallin from Replica Exchange Molecular Dynamics Simulations

Human γD-crystallin belongs to a crucial family of proteins known as crystallins located in the fiber cells of the human lens. Since crystallins do not undergo any turnover after birth, they need to possess remarkable thermodynamic stability. However, their sporadic misfolding and aggregation, triggered by environmental perturbations or genetic mutations, constitute the molecular basis of cataracts, which is the primary cause of blindness in the globe according to the World Health Organization. Here, we investigate the impact of high pressure on the conformational landscape of wild-type HγD-crystallin using replica exchange molecular dynamics simulations augmented with principal component analysis. We find pressure to have a modest impact on global measures of protein stability, such as root-mean-square displacement and radius of gyration. Upon projecting our trajectories along the first two principal components from principal component analysis, however, we observe the emergence of distinct free energy basins at high pressures. By screening local order parameters previously shown or hypothesized as markers of HγD-crystallin stability, we establish correlations between a tyrosine-tyrosine aromatic contact within the N-terminal domain and the protein's end-to-end distance with projections along the first and second principal components, respectively. Furthermore, we observe the simultaneous contraction of the hydrophobic core and its intrusion by water molecules. This exploration sheds light on the intricate responses of HγD-crystallin to elevated pressures, offering insights into potential mechanisms underlying its stability and susceptibility to environmental perturbations, crucial for understanding cataract formation.

Structural Rearrangements of Pigeon Cryptochrome 4 Undergoing a Complete Redox Cycle

Cryptochrome is currently the major contender of a protein to underpin magnetoreception, the ability to sense the Earth's magnetic field. Among various types of cryptochromes, cryptochrome 4 has been identified as the likely magnetoreceptor in migratory birds. All-atom molecular dynamics (MD) studies have offered first insights into the structural dynamics of cryptochrome but are limited to a short time scale due to large computational demands. Here, we employ coarse-grained MD simulations to investigate the emergence of long-lived states and conformational changes in pigeon cryptochrome 4. Our coarse-grained simulations complete the picture by permitting observation on a significantly longer time scale. We observe conformational transitions in the phosphate-binding loop of pigeon cryptochrome 4 upon activation and identify prominent motions in residues 440-460, suggesting a possible role as a signaling state of the protein or as a gated interaction site for forming protein complexes that might facilitate downstream processes. The findings highlight the importance of considering longer time scales in studying cryptochrome dynamics and magnetoreception. Coarse-grained MD simulations offer a valuable tool to unravel the complex behavior of cryptochrome proteins and shed new light on the mechanisms underlying their role in magnetoreception. Further exploration of these conformational changes and their functional implications may contribute to a deeper understanding of the molecular mechanisms of magnetoreception in birds.

Effect of ionic groups on the morphology and transport properties in a novel perfluorinated ionomer containing sulfonic and phosphonic acid groups: a molecular dynamics study

Combining the phosphonic acid group with the sulfonic acid group in PEMs has been shown to be an effective strategy for improving the fuel cell performance. However, the interplay of two different ionic groups and the resulting effect on the membrane properties have not been fully elucidated. Here, we used classical molecular dynamics simulation to investigate the morphologies, transport properties and effects of ionic groups in a novel perfluorinated PEM containing two ionic groups (PFSA-PFPA) in comparison to the corresponding homopolymers. Phase separations between hydrophilic and hydrophobic domains are confirmed in these PEMs and result from the evolution of water clusters formed around the ionic groups. The combination of both ionic groups brings a complicated morphological feature in PFSA-PFPA, with near-cylindrical aqueous domains of large length scales interconnected by tortuous domains of small sizes. And we found that the self-diffusion coefficients of water molecules are strongly related to morphologies, with the water transport in PFSA-PFPA lying between two analogous homopolymers. At the molecular level, we found that the sulfonic and phosphonic acid groups have distinct effects on the coordination behaviors and the dynamics of water molecules and hydronium ions. Strong electrostatic interactions lead to compact coordination structures and sluggish dynamics of hydronium ions around phosphonic acid groups, which determine the morphological evolution and transport properties in PFSA-PFPA. Our study affords insights into the relationship between molecular characteristics and transport properties bridged by phase-separated morphologies in a novel PEM containing both sulfonic acid and phosphonic acid groups, which deepens the understanding of the interplay between two ionic groups and may inspire the rational design of high-performance PEMs.

How ATP suppresses the fibrillation of amyloid peptides: analysis of the free-energy contributions

Recent experiments have revealed that adenosine triphosphate (ATP) suppresses the fibrillation of amyloid peptides - a process closely linked to neurodegenerative diseases such as Alzheimer's and Parkinson's. Apart from the adsorption of ATP onto amyloid peptides, the molecular understanding is still limited, leaving the underlying mechanism for the fibrillation suppression by ATP largely unclear, especially in regards to the molecular energetics. Here we provide an explanation at the molecular scale by quantifying the free energies using all-atom molecular dynamics simulations. We found that the changes of the free energies due to the addition of ATP lead to a significant equilibrium shift towards monomeric peptides in agreement with experiments. Despite ATP being a highly charged species, the decomposition of the free energies reveals that the van der Waals interactions with the peptide are decisive in determining the relative stabilization of the monomeric state. While the phosphate moiety exhibits strong electrostatic interactions, the compensation by the water solvent results in a minor, overall Coulomb contribution. Our quantitative analysis of the free energies identifies which intermolecular interactions are responsible for the suppression of the amyloid fibril formation by ATP and offers a promising method to analyze the roles of similarly complex cosolvents in aggregation processes.

Formation of Polyimide Membranes via Non-Solvent Induced Phase Separation: Insight from Molecular Dynamics Simulations

Molecular dynamics simulations were applied to investigate the formation of P84 polyimide membranes through the non-solvent induced phase separation (NIPS) process, considering two scenarios: one using a conventional organic solvent like n-methyl-2-pyrrolidone (NMP) and the other a greener alternative, γ-butyrolactone (GBL), with water serving as the non-solvent. Different compositions of polymer solutions were established along the binodal boundaries of the respective systems, derived from experimental cloud point data on the ternary phase diagram. The resulting polymer membranes were analyzed and compared in terms of their morphology. The wettability of their surfaces was notably affected by the polymer content in the initial casting solution and demonstrated a correlation with the Brunauer-Emmet-Teller (BET) specific surface area of the associated polymer nanostructures. The GBL solvent systems produced porous polymers qualitatively similar to those obtained with NMP, albeit with slightly narrower pore size distributions.

Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers

The pervasive presence of nanoplastics (NPs) in the environment has gained increasing attention due to their accumulation in living organisms. These emerging contaminants inevitably interact with extracellular polymeric substances along respiratory or gastrointestinal tracts, and diverse organic coating on the surface of NPs, known as bio- or eco-corona, is formed. Although its impact on altering the NP properties and potential cell internalization has been extensively examined, studies on its role in NP partitioning in the cell membrane are elusive yet. In this work, molecular dynamics is used to investigate the formation of chitosan (CT) corona centered on a polyvinyl chloride (PVC) nanoparticle and the uptake of the resulting complex onto lipid membranes. Coarse-grained models compatible with the newly developed Martini 3.0 force field are implemented for the two polymers employing the atomistic properties as targets in the parameterization. The reliability of the coarse-grained polymer models is demonstrated by reproducing the structural properties of the PVC melt and of solvated CT strands, as well as by determining the conformation adopted by the latter at the NP surface. Results show that the spontaneous binding of CT chains of high and intermediate protonation degrees led to the formation of soft and hard corona that modulates the interaction of PVC core with model membranes. The structural changes of the corona adsorbed at the lipid-water interface enable a subsequent transfer of the NP to the center of the saturated lipid membranes and a complete or partial transition to a snorkel conformation depending on the hydrophilic/hydrophobic balance in the CT-PVC complex. Overall, the computational investigation of the coarse-grained model system provides implications for understanding how the eco-corona development influences the uptake and implicit toxicology of NPs.

A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore

The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Calculations of Absolute Free Energies, Enthalpies, and Entropies for Drug Binding

Computer simulation methods can aid in the rational design of drugs aimed at a specific target, typically a protein. The affinity of a drug for its target is given by the free energy of binding. Binding can be further characterized by the enthalpy and entropy changes in the process. Methods exist to determine exact free energies, enthalpies, and entropies that are dependent only on the quality of the potential model and adequate sampling of conformational degrees of freedom. Entropy and enthalpy are roughly an order of magnitude more difficult to calculate than the free energy. This project combines a replica exchange method for enhanced sampling, designed to be efficient for protein-sized systems, with free energy calculations. This approach, replica exchange with dynamical scaling (REDS), uses two conventional simulations at different temperatures so that the entropy can be found from the temperature dependence of the free energy. A third replica is placed between them, with a modified Hamiltonian that allows it to span the temperature range of the conventional replicas. REDS provides temperature-dependent data and aids in sampling. It is applied to the bromodomain-containing protein 4 (BRD4) system. We find that for the force fields used, the free energies are accurate but the entropies and enthalpies are not, with the entropic contribution being too positive. Reproducing the entropy and enthalpy of binding appears to be a more stringent test of the force fields than reproducing the free energy.

Computer-assisted discovery and evaluation of potential ribosomal protein S6 kinase beta 2 inhibitors

S6K2 is an important protein in mTOR signaling pathway and cancer. To identify potential S6K2 inhibitors for mTOR pathway treatment, a virtual screening of 1,575,957 active molecules was performed using PLANET, AutoDock GPU, and AutoDock Vina, with their classification abilities compared. The MM/PB(GB)SA method was used to identify four compounds with the strongest binding energies. These compounds were further investigated using molecular dynamics (MD) simulations to understand the properties of the S6K2/ligand complex. Due to a lack of available 3D structures of S6K2, OmegaFold served as a reliable 3D predictive model with higher evaluation scores in SAVES v6.0 than AlphaFold, AlphaFold2, and RoseTTAFold2. The 150 ns MD simulation revealed that the S6K2 structure in aqueous solvation experienced compression during conformational relaxation and encountered potential energy traps of about 19.6 kJ mol-1. The virtual screening results indicated that Lys75 and Lys99 in S6K2 are key binding sites in the binding cavity. Additionally, MD simulations revealed that the ligands remained attached to the activation cavity of S6K2. Among the compounds, compound 1 induced restrictive dissociation of S6K2 in the presence of a flexible region, compound 8 achieved strong stability through hydrogen bonding with Lys99, compound 9 caused S6K2 tightening, and the binding of compound 16 was heavily influenced by hydrophobic interactions. This study suggests that these four potential inhibitors with different mechanisms of action could provide potential therapeutic options.

Microphase Separation Produces Interfacial Environment within Diblock Biomolecular Condensates

The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.

Predicting the Structure of Enzymes with Metal Cofactors: The Example of [FeFe] Hydrogenases

The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron-sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron-sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron-sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron-sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix.

Electric field induced the changes in structure and function of human transforming growth factor beta receptor type I: from molecular dynamics to docking

The transforming growth factor beta (TGF-β) signaling pathway is believed to play essential roles in several physiological activities, including cancer. TGF-β receptor type I (TBR-I) is a key membrane receptor protein in the TGF-β signaling pathway, which relates to many intracellular biological effects. In recent years, cold atmospheric plasma (CAP) has been found to have promising prospects in selective anticancer therapy and has confirmed its essential role in the TGF-β signaling pathway. However, the ambiguous effect of CAP-induced electric field (EF) on TBR-I still limits the application of CAP in clinical therapy. Molecular dynamics is applied to assess the effect of EF on the structure of the extracellular domain of TBR-I using a series of indicators and methods, and then we discuss the ligand binding ability of TBR-I. Results show that moderate EF intensities' structural restraints may contribute to the structural stability and ligand-binding ability of TBR-I, but an EF higher than 0.1 V/nm will be harmful. What's more, EF induces a change in the docking interface of TBR-I, showing the conformation and position of special sequences of residues decide the ligand binding surface. The relevant results suggest that CAP-induced EF plays a crucial role in receptor-receptor interaction and provides significant guidelines for EF-related anticancer therapy.Communicated by Ramaswamy H. Sarma.

Unraveling Partial Coalescence Between Droplet and Oil-Water Interface in Water-in-Oil Emulsions under a Direct-Current Electric Field via Molecular Dynamics Simulation

When the electric field strength (E) surpasses a certain threshold, secondary droplets are generated during the coalescence between water droplets in oil and the oil-water interface (so-called the droplet-interface partial coalescence phenomenon), resulting in a lower efficiency of droplet electrocoalescence. This study employs molecular dynamics (MD) simulations to investigate the droplet-interface partial coalescence phenomenon under direct current (DC) electric fields. The results demonstrate that intermolecular interactions, particularly the formation of hydrogen bonds, play a crucial role in dipole-dipole coalescence. Droplet-interface partial coalescence is categorized into five regimes based on droplet morphology. During the contact and fusion of the droplet with the water layer, the dipole moment of the droplet exhibits alternating increases and decreases along the electric field direction. Electric field forces acting on sodium ions and the internal interactions within droplets promote the process of droplet-interface partial coalescence. High field strengths cause significant elongation of the droplet, leading to its fragmentation into multiple segments. The migration of hydrated ions has a dual impact on the droplet-interface partial coalescence, with both facilitative and suppressive effects. The time required for droplet-interface partial coalescence initially decreases and subsequently increases as the field strength increases, depending on the competitive relationship between the extent of droplet stretching and the electric field force. This work provides molecular insights into the droplet-interface coalescence mechanisms in water-in-oil emulsions under DC electric fields.

Structural studies of catalytic peptides using molecular dynamics simulations

Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.

Mechanistic Insights into the Adsorption of Monoclonal Antibodies at the Water/Vapor Interface

Monoclonal antibodies (mAbs) are active components of therapeutic formulations that interact with the water-vapor interface during manufacturing, storage, and administration. Surface adsorption has been demonstrated to mediate antibody aggregation, which leads to a loss of therapeutic efficacy. Controlling mAb adsorption at interfaces requires a deep understanding of the microscopic processes that lead to adsorption and identification of the protein regions that drive mAb surface activity. Here, we report all-atom molecular dynamics (MD) simulations of the adsorption behavior of a full IgG1-type antibody at the water/vapor interface. We demonstrate that small local changes in the protein structure play a crucial role in promoting adsorption. Also, interfacial adsorption triggers structural changes in the antibody, potentially contributing to the further enhancement of surface activity. Moreover, we identify key amino acid sequences that determine the adsorption of antibodies at the water-air interface and outline strategies to control the surface activity of these important therapeutic proteins.

Effect of ligand and shell densities on the surface structure of core-shell nanoparticles self-assembled from function-spacer-lipid constructs

Biomolecular corona is the major obstacle to the clinical translation of nanomedicines. Since corona formation is governed by molecular interactions at the nano-bio interface, nanoparticle surface properties such as topography, charge and surface chemistry can be tuned to manipulate biomolecular corona formation. To this end, as the first step towards a deep understanding of the processes of corona formation, it is necessary to develop nanoparticles employing various biocompatible materials and characterize their surface structure and dynamics at the molecular level. In this work, we applied molecular dynamics simulation to study the surface structure of organic core-shell nanoparticles formed by the self-assembly of synthetic molecules composed of a DOPE lipid, a carboxymethylglycine spacer and biotin. Lipid moieties form the hydrophobic core, spacer motifs serve as a hydrophilic shell and biotin residues function as a targeting ligand. By mixing such function-spacer-lipid, spacer-lipid and lipid-only constructs at various molar ratios, densities of the ligand and spacer on the nanoparticle surface were modified. For convenient analysis of the structure and dynamics of all regions of the nanoparticle surface, we compiled topography maps based on atomic coordinates. It was shown that an increase in the density of the shell does not reduce exposure of the core, but increases shell average thickness. Biotin, due to its alkyl valeric acid chain and spacer flexibility, is localized primarily near the hydrophobic core and its partial presentation on the surface occurs only in nanoparticles with higher ligand densities. However, an increase in biotin density leads to its clustering. In turn, ligand clustering diminishes the stealth properties of the shell and targeting efficiency. Based on nanoparticle surface structures, we determined the optimal density of biotin. Experimental studies reported in the literature confirm these conclusions. We also suggest design tips to achieve the preferred biotin presentation. Simulation results are consistent with the synchrotron SAXS profile. We believe that such studies will contribute to a better understanding of nano-bio interactions towards the rational design of efficient drug delivery systems.

Identification of apigenin-4'-glucoside as bacterial DNA gyrase inhibitor by QSAR modeling, molecular docking, DFT, molecular dynamics, and in vitro confirmation studies

CONTEXT

It is well known that antibiotic resistance is a major health hazard. To eradicate antibiotic-resistant bacterial infections, it is essential to find a novel antibacterial agent. Hence, in this study, a quantitative structure-activity relationship (QSAR) model was developed using 43 DNA gyrase inhibitors, and 700 natural compounds were screened for their antibacterial properties. Based on molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, the top three leads viz., apigenin-4'-glucoside, 8-deoxygartanin, and cryptodorine were selected and structurally optimized using density functional theory (DFT) studies. The optimized structures were redocked, and molecular dynamic (MD) simulations were performed. Binding energies were calculated by molecular mechanics/Poisson-Boltzmann surface area solvation (MM-PBSA). Based on the above studies, apigenin-4'-glucoside was identified as a potent antibacterial lead. Further in vitro confirmation studies were performed using the plant Lawsonia inermis containing apigenin-4'-glucoside to confirm the antibacterial activity.

METHODS

For QSAR modeling, 2D descriptors were calculated by PaDEL-Descriptors v2.21 software, and the model was developed using the DTClab QSAR tool. Docking was performed using PyRx v0.8 software. ORCA v5.0.1 computational package was used to optimize the structures. The job type used in optimization was equilibrium structure search using the DFT hybrid functional ORCA method B3LYP. The basis set was 6-311G (3df, 3pd) plus four polarization functions for all atoms. Accurate docking was performed for optimized leads using the iGEMDOCK v2.1 tool with a genetic algorithm by 10 solutions each of 80 generations. Molecular dynamic simulations were performed using GROMACS 2020.04 software with CHARMM36 all-atom force field.

Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots

With machine learning now transforming the sciences, successful prediction of biological structure or activity is mainly limited by the extent and quality of data available for training, the astute choice of features for prediction, and thorough assessment of the robustness of prediction on a variety of new cases. In this chapter, we address these issues while developing and sharing protocols to build a robust dataset and rigorously compare several predictive classifiers using the open-source Python machine learning library, scikit-learn. We show how to evaluate whether enough data has been used for training and whether the classifier has been overfit to training data. The most telling experiment is 500-fold repartitioning of the training and test sets, followed by prediction, which gives a good indication of whether a classifier performs consistently well on different datasets. An intuitive method is used to quantify which features are most important for correct prediction.The resulting well-trained classifier, hotspotter, can robustly predict the small subset of amino acid residues on the surface of a protein that are energetically most important for binding a protein partner: the interaction hot spots. Hotspotter has been trained and tested here on a curated dataset assembled from 1046 non-redundant alanine scanning mutation sites with experimentally measured change in binding free energy values from 97 different protein complexes; this dataset is available to download. The accessible surface area of the wild-type residue at a given site and its degree of evolutionary conservation proved the most important features to identify hot spots. A variant classifier was trained and validated for proteins where only the amino acid sequence is available, augmented by secondary structure assignment. This version of hotspotter requiring fewer features is almost as robust as the structure-based classifier. Application to the ACE2 (angiotensin converting enzyme 2) receptor, which mediates COVID-19 virus entry into human cells, identified the critical hot spot triad of ACE2 residues at the center of the small interface with the CoV-2 spike protein. Hotspotter results can be used to guide the strategic design of protein interfaces and ligands and also to identify likely interfacial residues for protein:protein docking.

Solvent-Assisted Graphene Exfoliation from Graphite Using Umbrella Sampling Simulations

We employed molecular dynamics (MD) simulations coupled with umbrella sampling to explore the thermodynamics governing the exfoliation of a single graphene layer from a graphitic substrate in five different solvents such as dimethylacetamide (DMA), N-methyl-2-pyrrolidone (NMP), dimethyl sulfoxide (DMSO), cyclohexane (CHX), and water. The substrate was modeled as a stack of three identical graphene layers with the graphene sheet undergoing exfoliation positioned on top of this stack. The initial configurations for each umbrella simulation were generated through steered MD simulations carried out along two distinct coordinates: one parallel and the other perpendicular to the graphene layers. Our analyses revealed a uniform wetting behavior for both the nanosheet and the graphitic substrate in all of the tested solvents. Consistent with experimental observations, the steered simulations confirmed that exfoliation is more favorable along the parallel direction than along the perpendicular one. All non-water solvents exhibit comparable effectiveness in the exfoliation of graphene. The calculated free energies of these solvents in parallel exfoliation consistently fell within the range of 90-100 kJ/mol/nm2. In perpendicular exfoliation, however, the corresponding energies converge to lower values. This difference is attributed to the nonequilibrium nature of the perpendicular exfoliation, primarily caused by the great steering velocity of the graphene sheet immediately after detachment from the substrate. This rapid motion of the nanosheet along the perpendicular coordinate results in an elevated system energy and heating.

Classification of Hemilabile Ligands Using Machine Learning

Hemilabile ligands have the capacity to partially disengage from a metal center, providing a strategy to balance stability and reactivity in catalysis, but they are not straightforward to identify. We identify ligands in the Cambridge Structural Database that have been crystallized with distinct denticities and are thus identifiable as hemilabile ligands. We implement a semi-supervised learning approach using a label-spreading algorithm to augment a small negative set that is supported by heuristic rules of ligand and metal co-occurrence. We show that a heuristic based on coordinating atom identity alone is not sufficient to identify whether a ligand is hemilabile, and our trained machine-learning classification models are instead needed to predict whether a bi-, tri-, or tetradentate ligand is hemilabile with high accuracy and precision. Feature importance analysis of our models shows that the second, third, and fourth coordination spheres all play important roles in ligand hemilability.

Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations

Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.

In silico and structure-based assessment to classify VUS identified in the α-helical domain of BRCA2

Breast cancer type 2 susceptibility (BRCA2) protein plays a crucial role in DNA double-strand breaks repair mechanism by homologous recombination. Pathogenic mutations in the BRCA2 gene confer an increased risk of hereditary breast and ovarian cancer (HBOC). Different missense mutations are identified from a larger cohort of patient populations in the BRCA2. However, most missense mutations are classified as 'Variants of Uncertain Significance' (VUS) due to a lack of data from structural, functional, and clinical assessments. Therefore, this study focused on assessing VUS identified in the α-helical domain of h-BRCA2 using different in silico tools and structure-based molecular dynamics simulation. A total of 286 identified VUS were evaluated using Align-GVGD, PROVEAN and PANTHER servers and 18 variants were predicted to be pathogenic. Further, out of 18 variants analyzed using the ConSurf server, 16 variants were found to be evolutionary conserved. These 16 conserved variants were submitted to PremPS and Dynamut server to assess the effect of the mutation at the protein structure level; 12 mutations were predicted to have a destabilizing effect on the native protein structure. Finally, molecular dynamics simulations revealed 5 variants BRCA2 Cys2646Tyr, Asp2665Val, Trp2619Arg, Trp2619Ser and Tyr2660Cys can alter the folding pattern and need further validation using in vitro, structural and in vivo studies to classify as pathogenic.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation study on Bacillus subtilis EngA: the presence of Mg2+ at the active-sites promotes the functionally important conformation

EngA, a GTPase contains two GTP binding domains [GD1, GD2], and the C-terminal KH domain shown to be involved in the later stages of ribosome maturation. Association of EngA to the ribosomal subunit in the intermediate stage of maturation is essential for complete ribosome maturation. However, this association was shown to be dependent on the nucleotide bound combinations. This nucleotide dependent association tendency is attributed to the conformational changes that occur among different nucleotide bound combinations. Therefore, to explore the conformational changes, all-atom molecular dynamics simulations for Bacillus subtilis EngA in different nucleotide bound combinations along with the presence or absence of Mg2+ in the active-sites were carried out. The presence of Mg2+ along with the bound nucleotide at the GD2 active-site dictates the GD2-Sw-II mobility, but the GD1-Sw-II mobility has not shown any nucleotide or Mg2+ dependent movement. However, the GD1-Sw-II secondary conformations are shown to be influenced by the GD2 nucleotide bound state. This allosteric connection between the GD2 active-site and the GD1-Sw-II is also observed through the dynamic network analysis. Further, the exploration of the GD1-KH interface interactions exhibited a more attractive tendency when GD1 is bound to GTP-Mg2+. In addition, the presence of Mg2+ stabilizes active-site water and also increases the distances between the α- and γ- phosphates of the bound GTP. Curiously, three water molecules in the GD1 active-site and only one water molecule in the GD2 active-site are stabilized. This indicates that the probability of GTP hydrolysis is more in GD1 compared to GD2.Communicated by Ramaswamy H. Sarma.

The C-terminal tail of Rad17, iVERGE, binds the 9‒1‒1 complex independently of AAA+ ATPase domains to provide another clamp-loader interface

The ATR pathway plays a crucial role in maintaining genome integrity as the major DNA damage checkpoint. It also attracts attention as a therapeutic target in cancer treatment. The Rad17-RFC2-5 complex loads the Rad9-Hus1-Rad1 (9-1-1) DNA clamp complex onto damaged chromatin to activate the ATR pathway. We previously reported that phosphorylation of a polyanionic C-terminal tail of human Rad17, iVERGE, is essential for the interaction between Rad17 and the 9-1-1 complex. However, the molecular mechanism has remained unclear. Here, we show that iVERGE directly interacts with the Hus1 subunit of the 9-1-1 complex through Rad17-S667 phosphorylation independently of the AAA+ ATPase domains. An exogenous iVERGE peptide interacted with the 9-1-1 complex in vivo. The binding conformation of the iVERGE peptide was analyzed by de novo modeling with docking simulation, simulated annealing-molecular dynamics simulation, and the fragment molecular orbital method. The in silico analyses predicted the association of the iVERGE peptide with the hydrophobic and basic patches on the Hus1 protein, and the corresponding Hus1 mutants were deficient in the interaction with the iVERGE peptide in vivo. The iVERGE peptide occupied the same position as the C-terminus of Saccharomyces cerevisiae RAD24 on MEC3. The interaction energy calculation suggested that the Rad17 KYxxL motif and the iVERGE peptide are the primary and secondary interaction surfaces between the Rad17-RFC2-5 and 9-1-1 complexes. Our data reveal a novel molecular interface, iVERGE, between the Rad17-RFC2-5 and 9-1-1 complexes in vertebrates and implicate that Rad17 utilizes two distinct molecular interfaces to regulate the 9-1-1 complex.

Computational insights of the molecular recognition between volatile molecules and odorant binding proteins from the red palm weevil Rhynchophorus ferrugineus

The red palm weevil Rhynchophorus ferrugineus (Coleoptera: Curculionidae) is one of the most harmful pests for palm trees, causing serious economic damage worldwide. The present work aims to model and study the 3D structures of highly expressed odorant binding proteins from R. ferrugineus (RferOBPs) and identify possible binding modes and ligand release mechanism by docking and molecular dynamics. Highly confident 3D structures of a total of 11 odorant binding proteins (OBPs) were obtained with AlphaFold2. All 3D RferOBPs modeled structures displayed six characteristic α-helices, except for RfeOBP7 and RfeOBP10, which had an extra terminal α-helix. Among the eleven modeled RferOBPs, RferOBP4 was highly expressed in the antennae and subsequently selected for further analyses. Molecular docking analyses demonstrated that ferruginol, α-pinene, DEET, and picaridin can favorably bind the RferOBP4 cavity with low affinity energies. Molecular dynamic simulations of RferOBP4 bound to ferruginol at different pH values showed that low pH environments dictate a structural change into an apo-state that modifies the number of tunnels where the ligand can coexist, further triggering ligand release by a pH-dependent mechanism. This is the first report concerning the modelling and study of ligand binding modes and release mechanism of R. ferrugineus OBPs.Communicated by Ramaswamy H. Sarma.

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses

Molecular dynamics (MD) simulation is a powerful computational tool used in biomolecular studies to investigate the dynamics, energetics, and interactions of a wide range of biological systems at the atomic level. GROMACS is a widely used free and open-source biomolecular MD simulation software recognized for its efficiency, accuracy, and extensive range of simulation options. However, the complexity of setting up, running, and analyzing MD simulations for diverse systems often poses a significant challenge, requiring considerable time, effort, and expertise. Here, we introduce CHAPERONg, a tool that automates the GROMACS MD simulation pipelines for protein and protein-ligand systems. CHAPERONg also integrates seamlessly with GROMACS modules and third-party tools to provide comprehensive analyses of MD simulation trajectories, offering up to 20 post-simulation processing and trajectory analyses. It also streamlines and automates established pipelines for conducting and analyzing biased MD simulations via the steered MD-umbrella sampling workflow. Thus, CHAPERONg makes MD simulations more accessible to beginner GROMACS users whilst empowering experts to focus on data interpretation and other less programmable aspects of MD simulation workflows. CHAPERONg is written in Bash and Python, and the source code is freely available at https://github.com/abeebyekeen/CHAPERONg. Detailed documentation and tutorials are available online at dedicated web pages accessible via https://abeebyekeen.com/chaperong-online.

Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.

Cysteinyl and methionyl redox switches: Structural prerequisites and consequences

Redox modifications of specific cysteinyl and methionyl residues regulate key enzymes and signal-transducing proteins in various pathways. Here, we analyzed the effect of redox modifications on protein structure screening the RCSB protein data bank for oxidative modifications of proteins, i.e. protein disulfides, mixed disulfides with glutathione, cysteinyl sulfenic acids, cysteinyl S-nitrosylation, and methionyl sulfoxide residues. When available, these structures were compared to the structures of the same proteins in the reduced state with respect to both pre-requirements for the oxidative modifications as well as the structural consequences of the modifications. In general, the conformational changes induced by the redox modification are small, i.e. within the range of normal fluctuations. Some redox modifications, disulfides in particular, induces alterations in the electrostatic properties of the proteins. Solvent accessibility does not seem to be a strict pre-requirement for the redox modification of a particular residue. We identified an enrichment of certain other amino acid residues in the vicinity of the susceptible residues, for disulfide and sulfenic acid modifications, for instance, histidyl and tyrosyl residues. These motifs, as well as the specific features of the susceptible sulfur-containing amino acids, may become helpful for the prediction of redox modifications.

Computational assessment of lipid facilitated membrane permeation of vancomycin using force-probe molecular dynamic simulation

In this study the efficacy of different edible lipids for drug permeation enhancement of vancomycin through biological membrane was investigated using molecular dynamic simulation. In this regard, at first the ability of the lipids for complex formation with the drug was evaluated for number of most common edible lipids including tripalmitin (TPA), trimyristin (TMY), labrafil (LAB), glycerol monostearate (GMS), glycerol monooleate (GMO), Distearoylphosphorylethanolamine (DSPE), dipalmitoylphosphatidylethanolamine (DPPE), Dipalmitoylphosphatidylcholine (DPPC), cholesterol (CL), stearic acid (SA), palmitic acid (PA) and oleic acid (OA). Then the complexes were pulled thorough a bilayer membrane while the changes in force were probed. The results showed that besides the SA, PA and OA the other examined lipids were able to perform a perfect molecular complex with the drug. Also the results of pulling simulation revealed that the least of force was needed for drug transmittance through the membrane when it was covered by LAB, TMY and DSPE. These results indicated that these lipids can be the excellent materials of choice as permeation enhancer for preparing a proper oral formulation of vancomycin.Communicated by Ramaswamy H. Sarma.

Improving the Thermostability of Serine Protease PB92 from Bacillus alcalophilus via Site-Directed Mutagenesis Based on Semi-Rational Design

Proteases have been widely employed in many industrial processes. In this work, we aimed to improve the thermostability of the serine protease PB92 from Bacillus alcalophilus to meet the high-temperature requirements of biotechnological treatments. Eight mutation sites (N18, S97-S101, E110, and R143) were identified, and 21 mutants were constructed from B-factor comparison and multiple sequence alignment and expressed via Bacillus subtilis. Among them, fifteen mutants exhibited increased half-life (t1/2) values at 65 °C (1.13-31.61 times greater than that of the wild type). Based on the composite score of enzyme activity and thermostability, six complex mutants were implemented. The t1/2 values of these six complex mutants were 2.12-10.05 times greater than that of the wild type at 65 °C. In addition, structural analysis revealed that the increased thermal stability of complex mutants may be related to the formation of additional hydrophobic interactions due to increased hydrophobicity and the decreased flexibility of the structure. In brief, the thermal stability of the complex mutants N18L/R143L/S97A, N18L/R143L/S99L, and N18L/R143L/G100A was increased 4-fold, which reveals application potential in industry.

Amyloid-β Tetramers and Divalent Cations at the Membrane/Water Interface: Simple Models Support a Functional Role

Charge polarization at the membrane interface is a fundamental process in biology. Despite the lower concentration compared to the abundant monovalent ions, the relative abundance of divalent cations (Ca2+, Mg2+, Zn2+, Fe2+, Cu2+) in particular spaces, such as the neuron synapse, raised many questions on the possible effects of free multivalent ions and of the required protection of membranes by the eventual defects caused by the free forms of the cations. In this work, we first applied a recent realistic model of divalent cations to a well-investigated model of a polar lipid bilayer, di-myristoyl phosphatidyl choline (DMPC). The full atomistic model allows a fairly good description of changes in the hydration of charged and polar groups upon the association of cations to lipid atoms. The lipid-bound configurations were analyzed in detail. In parallel, amyloid-β 1-42 (Aβ42) peptides assembled into tetramers were modeled at the surface of the same bilayer. Two of the protein tetramers' models were loaded with four Cu2+ ions, the latter bound as in DMPC-free Aβ42 oligomers. The two Cu-bound models differ in the binding topology: one with each Cu ion binding each of the monomers in the tetramer; one with pairs of Cu ions linking two monomers into dimers, forming tetramers as dimers of dimers. The models here described provide hints on the possible role of Cu ions in synaptic plasticity and of Aβ42 oligomers in storing the same ions away from lipids. The release of structurally disordered peptides in the synapse can be a mechanism to recover ion homeostasis and lipid membranes from changes in the divalent cation concentration.

Mechanistic Investigation of tert-Butanol's Impact on Biopharmaceutical Formulations: When Experiments Meet Molecular Dynamics

The use of tert-butyl alcohol for the lyophilization of pharmaceuticals has seen an uptick over the past years. Its advantages include increased solubility of hydrophobic drugs, enhanced product stability, shorter reconstitution time, and decreased processing time. While the mechanisms of protein stabilization exerted by cryo- and lyo-protectants are well known when water is the solvent of choice, little is known for organic solvents. This work investigates the interactions between two model proteins, namely, lactate dehydrogenase and myoglobin, and various excipients (mannitol, sucrose, 2-hydroxypropyl-β-cyclodextrin and Tween 80) in the presence of tert-butyl alcohol. We thermally characterized mixtures of these components by differential scanning calorimetry and freeze-drying microscopy. We also spectroscopically evaluated the protein recovery after freezing and freeze-drying. We additionally performed molecular dynamics simulations to elucidate the interactions in ternary mixtures of the herein-investigated excipients, tert-butyl alcohol and the proteins. Both experiments and simulations revealed that tert-butyl alcohol had a detrimental impact on the recovery of the two investigated proteins, and no combination of excipients yielded a satisfactory recovery when the organic solvent was present within the formulation. Simulations suggested that the denaturing effect of tert-butyl alcohol was related to its propensity to accumulate in the proximity of the peptide surface, especially near positively charged residues.

Dynamic structural analysis-based epitope prediction of Exendin-4 in aqueous solution

The study of epitopes has a broad range of applications in drug discovery, vaccine design, and immunotherapy. In this study, an epitope prediction method was developed based on the dynamic structure of protein antigens. Solvent accessible surface area, charge, and root mean square fluctuation were introduced as the key residue property parameters. The epitope prediction algorithm was established by constructing a three-parameter complex metrics of seven-peptide groups. The method was applied to predict the epitopes of Exendin-4, an effective antidiabetic drug. The epitopes of both the natural and C-terminal amidated forms of Exendin-4 were predicted and compared in their folded and intermediate states. In the folded state, the epitopes of natural Exendin-4 (His1-Phe6 and Asp9-Val19) were found to be nearly identical to the epitopes of C-terminal aminated Exendin-4 (His1-Thr7 and Asp9-Val19). In the intermediate state, however, the epitopes of natural Exendin-4 (His1-Gly4, Phe6 and Lys12-Arg20) covered fewer amino acids than the epitopes of C-terminal aminated Exendin-4 (His1-Gly4, Phe6, Asp9-Val19 and Trp25-Lys27). The comparison with the results from other prediction tools demonstrates the reliability of our predicted epitopes of Exendin-4.

Morphology and Dynamics in Hydrated Graphene Oxide/Branched Poly(ethyleneimine) Nanocomposites: An In Silico Investigation

Graphene oxide (GO)-branched poly(ethyleneimine) (BPEI) hydrated mixtures were studied by means of fully atomistic molecular dynamics simulations to assess the effects of the size of polymers and the composition on the morphology of the complexes, the energetics of the systems and the dynamics of water and ions within composites. The presence of cationic polymers of both generations hindered the formation of stacked GO conformations, leading to a disordered porous structure. The smaller polymer was found to be more efficient at separating the GO flakes due to its more efficient packing. The variation in the relative content of the polymeric and the GO moieties provided indications for the existence of an optimal composition in which interaction between the two components was more favorable, implying more stable structures. The large number of hydrogen-bonding donors afforded by the branched molecules resulted in a preferential association with water and hindered its access to the surface of the GO flakes, particularly in polymer-rich systems. The mapping of water translational dynamics revealed the existence of populations with distinctly different mobilities, depending upon the state of their association. The average rate of water transport was found to depend sensitively on the mobility of the freely to move molecules, which was varied strongly with composition. The rate of ionic transport was found to be very limited below a threshold in terms of polymer content. Both, water diffusivity and ionic transport were enhanced in the systems with the larger branched polymers, particularly with a lower polymer content, due to the higher availability of free volume for the respective moieties. The detail afforded in the present work provides a new insight for the fabrication of BPEI/GO composites with a controlled microstructure, enhanced stability and adjustable water transport and ionic mobility.

N-Acetylation of Biodegradable Supramolecular Peptide Nanofilaments Selectively Enhances Their Proteolytic Stability for Targeted Delivery of Gold-Based Anticancer Agents

Peptide materials are promising for various biomedical applications; however, a significant concern is their lack of stability and rapid degradation in vivo due to non-specific proteolysis. For materials specifically designed to respond to disease-specific proteases, it would be desirable to retain high susceptibility to target proteases while minimizing the impact of non-specific proteolysis. We describe N-terminal acetylation as a simple synthetic modification of amphiphilic self-assembling peptides that contain an MMP-9-cleavable segment and form soluble, nanoscale filaments. We found that the N-terminus capping of these peptides did not significantly impact their self-assembly behavior, critical aggregation concentration, or ability to encapsulate hydrophobic payloads. By contrast, their proteolytic stability in human plasma (especially for anionic peptide sequences) was considerably increased while susceptibility to hydrolysis by MMP-9 was retained when compared to non-acetylated peptides, especially during the first 12 h. We note, however, that due to the longer time scale required for in vitro studies (72 h), non-specific proteolysis of both anionic acetylated peptides leads to similar activity in vitro despite differing MMP-9 kinetics during the early stages. Overall, the enhanced stability against non-specific proteases, combined with the ability of these nanofilaments to enhance the effectiveness of gold-based drugs toward cancerous cells compared to healthy cells, brings these acetylated peptide filaments a step closer toward clinical translation.

In-silico engineering of RNA nanoplatforms to promote the diabetic wound healing

One of the most notable required features of wound healing is the enhancement of angiogenesis, which aids in the acceleration of regeneration. Poor angiogenesis during diabetic wound healing is linked to a shortage of pro-angiogenic or an increase in anti-angiogenic factors. As a result, a potential treatment method is to increase angiogenesis promoters and decrease suppressors. Incorporating microRNAs (miRNAs) and small interfering RNAs (siRNAs), two forms of quite small RNA molecules, is one way to make use of RNA interference. Several different types of antagomirs and siRNAs are now in the works to counteract the negative effects of miRNAs. The purpose of this research is to locate novel antagonists for miRNAs and siRNAs that target multiple genes to promote angiogenesis and wound healing in diabetic ulcers.In this context, we used gene ontology analysis by exploring across several datasets. Following data analysis, it was processed using a systems biology approach. The feasibility of incorporating the proposed siRNAs and miRNA antagomirs into polymeric bioresponsive nanocarriers for wound delivery was further investigated by means of a molecular dynamics (MD) simulation study. Among the three nanocarriers tested (Poly (lactic-co-glycolic acid) (PLGA), Polyethylenimine (PEI), and Chitosan (CTS), MD simulations show that the integration of PLGA/hsa-mir-422a is the most stable (total energy = -1202.62 KJ/mol, Gyration radius = 2.154 nm, and solvent-accessible surface area = 408.416 nm²). With values of -25.437 KJ/mol, 0.047 nm for the Gyration radius, and 204.563 nm² for the SASA, the integration of the second siRNA/ Chitosan took the last place. The results of the systems biology and MD simulations show that the suggested RNA may be delivered through bioresponsive nanocarriers to speed up wound healing by boosting angiogenesis.

Y225A induces long-range conformational changes in human prion protein that are protective in Drosophila

Prion protein (PrP) misfolding is the key trigger in the devastating prion diseases. Yet the sequence and structural determinants of PrP conformation and toxicity are not known in detail. Here, we describe the impact of replacing Y225 in human PrP with A225 from rabbit PrP, an animal highly resistant to prion diseases. We first examined human PrP-Y225A by molecular dynamics (MD) simulations. We next introduced human PrP in Drosophila and compared the toxicity of human PrP-WT and Y225A in the eye and in brain neurons. Y225A stabilizes the β2-α2 loop into a 3₁₀-helix from 6 different conformations identified in WT and lowers hydrophobic exposure. Transgenic flies expressing PrP-Y225A exhibit less toxicity in the eye and in brain neurons and less accumulation of insoluble PrP. Overall, we determined that Y225A lowers toxicity in Drosophila assays by promoting a structured loop conformation that increases the stability of the globular domain. These findings are significant because they shed light on the key role of distal α-helix 3 on the dynamics of the loop and the entire globular domain.

Naphthoquinone-dopamine hybrids disrupt α-synuclein fibrils by their intramolecular synergistic interactions with fibrils and display a better effect on fibril disruption

α-Synuclein (αSyn) is an intrinsically disordered protein and its abnormal aggregation into amyloid fibrils is the main hallmark of Parkinson's disease (PD). The disruption of preformed αSyn fibrils using small molecules is considered as a potential strategy for PD treatment. Recent experiments have reported that naphthoquinone-dopamine hybrids (NQDA), synthesized by naphthoquinone (NQ) and dopamine (DA) molecules, can significantly disrupt αSyn fibrils and cross the blood-brain barrier. To unravel the fibril-disruptive mechanisms at the atomic level, we performed microsecond molecular dynamics simulations of αSyn fibrils in the absence and presence of NQDA, NQ, DA, or NQ+DA molecules. Our simulations showed that NQDA reduces the β-sheet content, disrupts K45-E57 and E46-K80 salt-bridges, weakens the inter-protofibril interaction, and thus destabilizes the αSyn fibril structure. NQDA has the ability to form cation-π and H-bonding interactions with K45/K80, and form π-π stacking interactions with Y39/F94. Those interactions between NQDA and αSyn fibrils play a crucial role in disaggregating αSyn fibrils. Moreover, we found that NQDA has a better fibril destabilization effect than that of NQ, DA, and NQ+DA molecules. This is attributed to the synergistic fibril-binding effect between NQ and DA groups in NQDA molecules. The DA group can form strong π-π stacking interactions with aromatic residues Y39/F94 of the αSyn fibril, while the DA molecule cannot. In addition, NQDA can form stronger cation-π interactions with residues K45/K80 than those of both NQ and DA molecules. Our results provide the molecular mechanism underlying the disaggregation of the αSyn fibril by NQDA and its better performance in fibril disruption than NQ, DA, and NQ+DA molecules, which offers new clues for the screening and development of promising drug candidates to treat PD.

A pH-dependent cluster of charges in a conserved cryptic pocket on flaviviral envelopes

Flaviviruses are enveloped viruses which include human pathogens that are predominantly transmitted by mosquitoes and ticks. Some, such as dengue virus, exhibit the phenomenon of antibody-dependent enhancement (ADE) of disease, making vaccine-based routes of fighting infections problematic. The pH-dependent conformational change of the envelope (E) protein required for fusion between the viral and endosomal membranes is an attractive point of inhibition by antivirals as it has the potential to diminish the effects of ADE. We examined six flaviviruses by employing large-scale molecular dynamics (MD) simulations of raft systems that represent a substantial portion of the flaviviral envelope. We utilised a benzene-mapping approach that led to a discovery of shared hotspots and conserved cryptic sites. A cryptic pocket previously shown to bind a detergent molecule exhibited strain-specific characteristics. An alternative conserved cryptic site at the E protein domain interfaces showed a consistent dynamic behaviour across flaviviruses and contained a conserved cluster of ionisable residues. Constant-pH simulations revealed cluster and domain-interface disruption under low pH conditions. Based on this, we propose a cluster-dependent mechanism that addresses inconsistencies in the histidine-switch hypothesis and highlights the role of cluster protonation in orchestrating the domain dissociation pivotal for the formation of the fusogenic trimer.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.

Investigation of the inhibitory behavior of XFE and mitoxantrone molecules in interaction with AKT1 protein: a molecular dynamics simulation study

The PI3K/Akt/mTOR pathway is one of the important pathways in many cancers. Akt is a serine-threonine kinase protein identified as a drug target for cancer treatment. Therefore, anticancer drugs are essential therapeutic targets for this pathway. In the current study, the inhibitory effect of two anticancer molecules, XFE and mitoxantrone, on AKT1 protein that can impact the activity of the AKT1 protein was investigated by using molecular docking and molecular dynamics (MD) simulations. The molecular docking results presented a relatively higher binding affinity of the mitoxantrone molecule in interaction with AKT1 than the XFE molecule. These results were validated by the MM/PBSA technique that was performed on obtained trajectories of 25 ns MD simulations. The mitoxantrone molecule has an intense binding energy of - 880.536 kcal/mol with AKT1 protein, while the XFE molecule shows a binding energy value of - 83.569 kcal/mol. Our findings from molecular dynamics simulations indicated that both molecules have favorite interactions with AKT1 protein. Other analyses, such as RMSF and hydrogen binding on trajectories obtained from MD simulations, indicated that the mitoxantrone molecule could be a relatively potent inhibitor for AKT1. Based on the results of this study and the structure of mitoxantrone, it is expected to be a good candidate for cancer treatment as a (PI3K)/Akt/mTOR inhibitor.

Molecular Dynamics Study on the Aggregation Behavior of Triton X Micelles with Different PEO Chain Lengths in Aqueous Solution

The aggregation structure of Triton X (TX) amphiphilic molecules in aqueous solution plays an important role in determining the various properties and applications of surfactant solutions. In this paper, the properties of micelles formed by TX-5, TX-114, and TX-100 molecules with different poly(ethylene oxide) (PEO) chain lengths in TX series of nonionic surfactants were studied via molecular dynamics (MD) simulation. The structural characteristics of three micelles were analyzed at the molecular level, including the shape and size of micelles, the solvent accessible surface area, the radial distribution function, the micelle configuration, and the hydration numbers. With the increase of PEO chain length, the micelle size and solvent accessible surface area also increase. The distribution probability of the polar head oxygen atoms on the surface of the TX-100 micelle is higher than that in the TX-5 or TX-114 micelle. In particular, the tail quaternary carbon atoms in the hydrophobic region are mainly located at the micelle exterior. For TX-5, TX-114, and TX-100 micelles, the interactions between micelles and water molecules are also quite different. These structures and comparisons at the molecular level contribute to the further understanding of the aggregation and applications of TX series surfactants.

Molecular Insights on Morphology, Composition, and Stability of Mixed Micelles Formed by Ionic Surfactant and Nonionic Block Copolymer in Water Using Coarse-Grained Molecular Dynamics Simulations

The nanoscale association domains are the ultimate determinants of the macroscopic properties of complex fluids involving amphiphilic polymers and surfactants, and hence, it is foremost important to understand the role of polymer/surfactant concentration on these domains. We have used coarse-grained molecular dynamics simulations to investigate the effect of polymer/surfactant concentration on the morphology of poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO, i.e., pluronics or poloxamers) block copolymer, and ionic surfactants sodium dodecyl sulfate (SDS), mixed micelles in aqueous solution. The proclivity of the surfactant to form the mixed micelles is also probed using umbrella sampling simulations. In this study, we observed that the core of the pluronic + SDS formed mixed micelles consists of PPO, the alkyl tail of SDS, and some water molecules, whereas the PEO, water, and sulfate headgroups of SDS form a shell, consistent with experimental observations. The micelles are spherical at high-pluronic/low-SDS compositions, ellipsoidal at high-SDS/low-pluronic compositions, and wormlike-cylindrical at high-pluronic/high-SDS compositions. The transitions in micelle morphology are governed by the solvent accessible surface area of mixed aggregates, electrostatic repulsion between SDS-headgroups, and dehydration of PEO and PPO segments. The free energy barrier for SDS escape is much higher in mixed micelles than in pure SDS micelles, indicating a stronger tendency for SDS to form pluronic-SDS mixed micelles.

Effects of temperature and microwave on the stability of the blast effector complex APikL2A/sHMA25 as determined by molecular dynamics analyses

Magnaporthe oryzae is the causal agent of rice blast, and understanding how abiotic stress affects the resistance of plants to this disease is useful for designing disease control strategies. In this paper, the effects of temperature and microwave irradiation on the effector complex comprising APikL2A from M. oryzae and sHMA25 from foxtail millet were investigated by molecular dynamics simulations using the GROMACS software package. While the structure of APikL2A/sHMA25 remained relatively stable in a temperature range of 290 K (16.85 °C) to 320 K (46.85 °C), the concave shape of the temperature-dependent binding free energy curve indicated that there was maximum binding affinity between APikL2A and sHMA25 at 300 K-310 K. This coincided with the optimum infectivity temperature, thus suggesting that coupling of the two polypeptides may play a role in the infection process. A strong oscillating electric field destroyed the structure of APikL2A/sHMA25, although it was stable and not susceptible to weak electric fields.

Structural and dynamic insights into α-synuclein dimer conformations

Parkinson disease is associated with the aggregation of the protein α-synuclein. While α-synuclein can exist in multiple oligomeric states, the dimer has been a subject of extensive debates. Here, using an array of biophysical approaches, we demonstrate that α-synuclein in vitro exhibits primarily a monomer-dimer equilibrium in nanomolar concentrations and up to a few micromolars. We then use spatial information from hetero-isotopic cross-linking mass spectrometry experiments as restrains in discrete molecular dynamics simulations to obtain the ensemble structure of dimeric species. Out of eight structural sub-populations of dimers, we identify one that is compact, stable, abundant, and exhibits partially exposed β-sheet structures. This compact dimer is the only one where the hydroxyls of tyrosine 39 are in proximity that may promote dityrosine covalent linkage upon hydroxyl radicalization, which is implicated in α-synuclein amyloid fibrils. We propose that this α-synuclein dimer features etiological relevance to Parkinson disease.