A smooth particle mesh Ewald method

Simulating the Skin Permeation Process of Ionizable Molecules

It is commonly assumed that ionizable molecules, such as drugs, permeate through the skin barrier in their neutral form. By using molecular dynamics simulations of the charged and neutral states separately, we can study the dynamic protonation behavior during the permeation process. We have studied three weak acids and three weak bases and conclude that the acids are ionized to a larger extent than the bases, when passing through the headgroup region of the lipid barrier structure, at pH values close to their pKa. It can also be observed that even if these dynamic protonation simulations are informative, in the cases studied herein they are not necessary for the calculation of permeability coefficients. It is sufficient to base the calculations only on the neutral form, as is commonly done.

In-Depth Understanding of the Effect of the Distribution of Substituents on the Morphology and Physical Properties of Ethylcellulose: Molecular Dynamics Simulations Insights

Ethylcellulose (EC) is a crucial cellulose derivative with widespread applications, particularly in the pharmaceutical industry, where precise property adjustments through chemical modification are imperative. The degree of substitution (DS) and the localization of substituents along the cellulose chains are pivotal factors in this process. However, the impact of the substituent location within the repeating unit of EC remains unexplored. To address this gap, we conducted molecular dynamics simulations on amorphous EC, comparing randomly and uniformly substituted ethyl groups in the repeating units. This comprehensive study of pairwise interactions revealed significant differences in intramolecular and intermolecular hydrogen-bonding capabilities, depending on whether the hydroxyl groups were substituted at C2, C3, or C6. While our simulations demonstrated that substituent localization in the repeating unit influenced the density, number of hydrogen bonds, and conformations, the DS emerged as the dominant determinant. This insight led us to propose and validate a hypothesis: a straightforward linear function using the properties of uniform models and molar fractions can predict the properties of randomly substituted EC with a given DS. This innovative approach is anticipated to contribute to the selection of cellulose derivatives with desirable properties for the pharmaceutical industry and new applications in other fields.

MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.

Current State of Open Source Force Fields in Protein-Ligand Binding Affinity Predictions

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

Force Field X: A computational microscope to study genetic variation and organic crystals using theory and experiment

Force Field X (FFX) is an open-source software package for atomic resolution modeling of genetic variants and organic crystals that leverages advanced potential energy functions and experimental data. FFX currently consists of nine modular packages with novel algorithms that include global optimization via a many-body expansion, acid-base chemistry using polarizable constant-pH molecular dynamics, estimation of free energy differences, generalized Kirkwood implicit solvent models, and many more. Applications of FFX focus on the use and development of a crystal structure prediction pipeline, biomolecular structure refinement against experimental datasets, and estimation of the thermodynamic effects of genetic variants on both proteins and nucleic acids. The use of Parallel Java and OpenMM combines to offer shared memory, message passing, and graphics processing unit parallelization for high performance simulations. Overall, the FFX platform serves as a computational microscope to study systems ranging from organic crystals to solvated biomolecular systems.

Nontrivial effects of geometric and charge defects on one-dimensional confined water

Water confined within nanochannels with specific functionalities serves as the foundation for a variety of emerging nanofluidic applications. However, the structure and dynamics of the confined liquid are susceptibly influenced by practically hard-to-avoid defects, yet knowledge of this fact remains largely unexplored. Here, using extensive molecular dynamics simulations, we elucidate the significant influence of geometric and charge defects on one-dimensional confined water. We show that the two types of defects can both reshape the water density distribution by constraining the translocation of water molecules along the circumferential direction. In addition to structural alterations, collective translocation and rotation of water slabs arise during transportation under external pressure. Below the temperature threshold marking the initiation of liquid-solid transition, the geometric defect retards water diffusion through a pinning effect, while the charge defect induces an anti-freezing effect. The latter is attributed to the electrostatic interaction between the charge defect and water molecules that hinders the formation of a stable hydrogen bond network by disrupting molecular dipole orientation. Consequently, this behavior results in a reduction in the number and lifetime of hydrogen bonds within the phase transition interval. The distinct roles of the two types of defects could be utilized to control the structure and dynamics of confined liquids that may result in distinct functionalities for nanofluidic applications.

Spatial organization of the ions at the free surface of imidazolium-based ionic liquids

HYPOTHESIS

Experimental information on the molecular scale structure of ionic liquid interfaces is controversial, giving rise to two competing scenarios, namely the double layer-like and "chessboard"-like structures. This issue can be resolved by computer simulation methods, at least for the underlying molecular model. Systematically changing the anion type can elucidate the relative roles of electrostatic interactions, hydrophobic (or, strictly speaking, apolar) effects and steric restrictions on the interfacial properties.

SIMULATIONS

Molecular dynamics simulation is combined with intrinsic analysis methods both at the molecular and atomic levels, supplemented by Voronoi analysis of self-association.

FINDINGS

We see no evidence for the existence of a double-layer-type arrangement of the ions, or for their self-association at the surface of the liquid. Instead, our results show that cation chains associate into apolar domains that protrude into the vapour phase, while charged groups form domains that are embedded in this apolar environment at the surface. However, the apolar chains largely obscure the cation groups, to which they are bound, while the smaller and more mobile anions can more easily access the free surface, leading to a somewhat counterintuitive net excess of negative charge at the interface. Importantly, this excess charge could only be identified by applying intrinsic analysis.

Computational discovery of AKT serine/threonine kinase 1 inhibitors through shape screening for rheumatoid arthritis intervention

Rheumatoid Arthritis (RA) is a chronic, symmetrical inflammatory autoimmune disorder characterized by painful, swollen synovitis and joint erosions, which can cause damage to bone and cartilage and be associated with progressive disability. Despite expanded treatment options, some patients still experience inadequate response or intolerable adverse effects. Consequently, the treatment options for RA remain quite limited. The enzyme AKT1 is crucial in designing drugs for various human diseases, supporting cellular functions like proliferation, survival, metabolism, and angiogenesis in both normal and malignant cells. Therefore, AKT serine/threonine kinase 1 is considered crucial for targeting therapeutic strategies aimed at mitigating RA mechanisms. In this context, directing efforts toward AKT1 represents an innovative approach to developing new anti-arthritis medications. The primary objective of this research is to prioritize AKT1 inhibitors using computational techniques such as molecular modeling and dynamics simulation (MDS) and shape-based virtual screening (SBVS). A combined SBVS approach was employed to predict potent inhibitors against AKT1 by screening a pool of compounds sourced from the ChemDiv and IMPPAT databases. From the SBVS results, only the top three compounds, ChemDiv_7266, ChemDiv_2796, and ChemDiv_9468, were subjected to stability analysis based on their high binding affinity and favorable ADME/Tox properties. The SBVS findings have revealed that critical residues, including Glu17, Gly37, Glu85, and Arg273, significantly contribute to the successful binding of the highest-ranked lead compounds at the active site of AKT1. This insight helps to understand the specific binding mechanism of these leads in inhibiting RA, facilitating the rational design of more effective therapeutic agents.

Exploring the influence of pore shape on conductance and permeation

There are increasing numbers of ion channel structures featuring heteromeric subunit assembly, exemplified by synaptic α1βB glycine and α4β2 nicotinic receptors. These structures exhibit inherent pore asymmetry, but the relevance of this to function is unknown. Furthermore, molecular dynamics simulations performed on symmetrical homomeric channels often lead to thermal distortion whereby conformations of the resulting ensemble are also asymmetrical. When functionally annotating ion channels, researchers often rely on minimal constrictions determined via radius-profile calculations performed with computer programs, such as HOLE or CHAP, coupled with an assessment of pore hydrophobicity. However, such tools typically employ spherical probe particles, limiting their ability to accurately capture pore asymmetry. Here, we introduce an algorithm that employs ellipsoidal probe particles, enabling a more comprehensive representation of the pore geometry. Our analysis reveals that the use of nonspherical ellipsoids for pore characterization provides a more accurate and easily interpretable depiction of conductance. To quantify the implications of pore asymmetry on conductance, we systematically investigated carbon nanotubes with varying degrees of pore asymmetry as model systems. The conductance through these channels shows surprising effects that would otherwise not be predicted with spherical probes. The results have broad implications not only for the functional annotation of biological ion channels but also for the design of synthetic channel systems for use in areas such as water filtration. Furthermore, we make use of the more accurate characterization of channel pores to refine a physical conductance model to obtain a heuristic estimate for single-channel conductance. The code is freely available, obtainable as pip-installable python package and provided as a web service.

Stable peptide-assembled nanozyme mimicking dual antifungal actions

Natural antimicrobial peptides (AMPs) and enzymes (AMEs) are promising non-antibiotic candidates against antimicrobial resistance but suffer from low efficiency and poor stability. Here, we develop peptide nanozymes which mimic the mode of action of AMPs and AMEs through de novo design and peptide assembly. Through modelling a minimal building block of IHIHICI is proposed by combining critical amino acids in AMPs and AMEs and hydrophobic isoleucine to conduct assembly. Experimental validations reveal that IHIHICI assemble into helical β-sheet nanotubes with acetate modulation and perform phospholipase C-like and peroxidase-like activities with Ni coordination, demonstrating high thermostability and resistance to enzymatic degradation. The assembled nanotubes demonstrate cascade antifungal actions including outer mannan docking, wall disruption, lipid peroxidation and subsequent ferroptotic death, synergistically killing >90% Candida albicans within 10 min on disinfection pad. These findings demonstrate an effective de novo design strategy for developing materials with multi-antimicrobial mode of actions.

Comparative Linkage of Novel Anti-Tumor Pd(II) Complex with Bio-Macromulecules: Fluorescence, UV-Vis, DFT, Molecular Docking and Molecular Dynamics Simulation Studies

A novel mononuclear palladium complex, [Pd(dach)(SSA)], where dach and SSA are diaminocyclohexane and sulfosalicylic acid ligands, respectively, has been synthesized and identified utilizing analytical and spectral methods. DFT calculations, namely geometry optimization, MEP, HOMO-LUMO and NBO analysis, have been conducted at B3LYP level by aug-ccpVTZ-PP and 6-311G(d, p) basis sets. NBO and HOMO-LUMO analysis exhibited that the palladium compound is stable. MEP showed the potential sites of molecule for the interaction. By employing MTT assay, the cytotoxicity activity of the aforesaid compound was examined on K562 cell line, which revealed a proper activity compared to cisplatin. To ascertain the lipophilicity of the newly made compound, the partition coefficient measurement was accomplished, which follows the order of cisplatin < Pd(II) complex. Next, investigation of binding properties of the studied compound with DNA of calf thymus and BSA were done by spectroscopic (CD, fluorescence emission and electronic adsorption) and non-spectroscopic (viscosity measurements, DNA gel electrophoresis, molecular docking and molecular dynamics simulation) methods. The outcomes of CD and UV-Vis spectroscopy demonstrated that the title compound refolded the protein via increasing the alpha helix percentage. The data obtained from UV-Vis studies indicated the non-intercalative mutual action between Pd(II) complex with DNA. It also revealed that the Kapp magnitude of CT-DNA (7.43 × 104 M- 1) is higher than the BSA (5.17 × 103 M- 1), and L1/2 (midpoint of transition) of CT-DNA (5 µM) is lower than the BSA (5.7 µM), indicating that the complex has a greater binding affinity to CT-DNA than BSA. Fluorescence quenching mechanism of the two biomolecules by the metal complex is static and the calculated thermodynamic parameters (ΔS° < 0 and ΔH° < 0) suggested the hydrogen bonding and/ or van der Waals forces with DNA and BSA. Further, molecular docking indicated that the studied compound fits into the groove of DNA and the site I of BSA. The stability of metal compound-DNA/-BSA in the presence of H2O solvent and over the time were validated via molecular dynamics simulation.

Modeling solvent effects and convergence of 31P-NMR shielding calculations with COBRAMM

Solvent effects on 31P-NMR parameters for triphenylphosphine oxide and triphenylphosphine in chloroform have been extensively investigated by testing different solvation models. The solvent is described implicitly, mixed implicitly/explicitly, and using full explicit models. Polarizable continuum model (PCM), molecular dynamic (MD) simulations, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations are used to disclose the effects of solute/solvent interactions and, more generally, the role of the embedding in NMR simulations. The results show the beneficial effect of carrying out QM/MM optimizations on top of geometries directly extracted from classical MD simulations, used to ensure representative conformational sampling. The nuclear shielding convergence has been tested against a different number of snapshots and with the inclusion of solvent shells into the QM region. An automated MD//QM/MM//GIAO protocol, implemented in the COBRAMM package, is here proposed and tested on trimethyl phosphite showing that our approach boosts the convergence of nuclear shielding satisfactorily. The present work aims to be a stepping-stone to assess proper QM/MM computational strategies in simulating chemical shifts in non-homogeneous systems like supramolecular and biological systems.

Softening in Two-Component Lipid Mixtures by Spontaneous Curvature Variance

The bending modulus of a lipid bilayer quantifies its mechanical resistance to curvature. It is typically understood in terms of thickness; e.g., thicker bilayers are usually stiffer. Here, we describe an additional and powerful molecular determinant of stiffness─the variance in the distribution of curvature sensitivity of lipids and lipid conformations. Zwitterionic choline and ethanolamine headgroups of glycerophospholipids dynamically explore inter- and intraspecies interactions, leading to transient clustering. We demonstrate that these clusters couple strongly to negative curvature, exciting undulatory membrane modes and reducing the apparent bending modulus. Three force fields (Martini 2, Martini 3, and all-atom CHARMM C36) each show the effect to a different extent, with the coarse-grained Martini models showing the most clustering and thus the most softening. The theory is a guide to understanding the stiffness of biological membranes with their complex composition, as well as how choices of force field parameterization are translated into mechanical stiffness.

An Investigation into the Transdermal Behavior of Active Ingredients by Combination of Experiments and Multiscale Simulations

Transdermal behavior is a critical aspect of studying delivery systems and evaluating the efficacy of cosmetics. However, existing methods face challenges such as lengthy experiments, high cost, and limited model accuracy. Therefore, developing accurate transdermal models is essential for formulation development and effectiveness assessment. In this study, we developed a multiscale model to describe the transdermal behavior of active ingredients in the stratum corneum. Molecular dynamics simulations were used to construct lipid bilayers and determine the diffusion coefficients of active ingredients in different regions of these bilayers. These diffusion coefficients were integrated into a multilayer lipid pathway model using finite element simulations. The simulation results were in close agreement with our experimental results for three active ingredients (mandelic acid (MAN), nicotinamide (NIC), and pyruvic acid (PYR)), demonstrating the effectiveness of our multiscale model. This research provides valuable insights for advancing transdermal delivery methods.

A Membrane-Assisted Mechanism for the Release of Ceramide from the CERT START Domain

Ceramide transfer protein CERT is the mediator of nonvesicular transfer of ceramide from the ER to Golgi. In CERT, START is the domain responsible for the binding and transport of ceramide. A wealth of structural data has revealed a helix-grip fold surrounding a large hydrophobic cavity holding the ceramide. Yet, little is known about the mechanisms by which START releases the ceramide through the polar region and into the packed environment of cellular membranes. As such events do not lend themselves easily to experimental investigations, we used multiple unbiased microsecond-long molecular simulations. We propose a membrane-assisted mechanism in which the membrane acts as an allosteric effector initiating the release of ceramide and where the passage of the ceramide acyl chains is facilitated by the intercalation of a single phosphatidylcholine lipid in the cavity, practically greasing the ceramide way out. We verify using free energy calculation and experimental lipidomics data that CERT forms stable complexes with phosphatidylcholine lipids, in addition to ceramide, thus providing validation for the proposed mechanism.

Polyethylene Glycol Impacts Conformation and Dynamics of Escherichia coli Prolyl-tRNA Synthetase Via Crowding and Confinement Effects

Polyethylene glycol (PEG) is a flexible, nontoxic polymer commonly used in biological and medical research, and it is generally regarded as biologically inert. PEG molecules of variable sizes are also used as crowding agents to mimic intracellular environments. A recent study with PEG crowders revealed decreased catalytic activity of Escherichia coli prolyl-tRNA synthetase (Ec ProRS), where the smaller molecular weight PEGs had the maximum impact. The molecular mechanism of the crowding effects of PEGs is not clearly understood. PEG may impact protein conformation and dynamics, thus its function. In the present study, the effects of PEG molecules of various molecular weights and concentrations on the conformation and dynamics of Ec ProRS were investigated using a combined experimental and computational approach including intrinsic tryptophan fluorescence spectroscopy, atomic force microscopy, and atomistic molecular dynamic simulations. Results of the present study suggest that lower molecular weight PEGs in the dilute regime have modest effects on the conformational dynamics of Ec ProRS but impact the catalytic function primarily via the excluded volume effect; they form large clusters blocking the active site pocket. In contrast, the larger molecular weight PEGs in dilute to semidilute regimes have a significant impact on the protein's conformational dynamics; they wrap on the protein surface through noncovalent interactions. Thus, lower-molecular-weight PEG molecules impact protein dynamics and function via crowding effects, whereas larger PEGs induce confinement effects. These results have implications for the development of inhibitors for protein targets in a crowded cellular environment.

Varying the position of phospholipid acyl chain unsaturation modulates hopanoid and sterol ordering

The cell membrane must balance mechanical stability with fluidity to function as both a barrier and an organizational platform. Key to this balance is the ordering of hydrocarbon chains and the packing of lipids. Many eukaryotes synthesize sterols, which are uniquely capable of modulating the lipid order to decouple membrane stability from fluidity. Ancient sterol analogs known as hopanoids are found in many bacteria and proposed as ancestral ordering lipids. The juxtaposition of sterols and hopanoids in extant organisms prompts us to ask why both pathways persist, especially in light of their convergent ability to order lipids. In this work, simulations, monolayer experiments, and cellular assays show that hopanoids and sterols order unsaturated phospholipids differently based on the position of double bonds in the phospholipid acyl chain. We find that cholesterol and diplopterol's methyl group distributions lead to distinct effects on unsaturated lipids. In Mesoplasma florum, diplopterol's constrained ordering capacity reduces membrane resistance to osmotic stress, unlike cholesterol. These findings suggest that cholesterol's broader lipid-ordering ability may have facilitated the exploration of a more diverse lipidomic landscape in eukaryotic membranes.

Impact of Protein Corona Formation and Polystyrene Nanoparticle Functionalisation on the Interaction with Dynamic Biomimetic Membranes Comprising of Integrin

Plastics, omnipresent in the environment, have become a global concern due to their durability and limited biodegradability, especially in the form of microparticles and nanoparticles. Polystyrene (PS), a key plastic type, is susceptible to fragmentation and surface alterations induced by environmental factors or industrial processes. With widespread human exposure through pollution and diverse industrial applications, understanding the physiological impact of PS, particularly in nanoparticle form (PS-NPs), is crucial. This study focuses on the interaction of PS-NPs with model blood proteins, emphasising the formation of a protein corona, and explores the subsequent contact with platelet membrane mimetics using experimental and theoretical approaches. The investigation involves αIIbβ3-expressing cells and biomimetic membranes, enabling real-time and label-free nanoscale precision. By employing quartz-crystal microbalance with dissipation monitoring studies, the concentration-dependent cytotoxic effects of differently functionalised ~210 nm PS-NPs on HEK293 cells overexpressing αIIbβ3 are evaluated in detail. The study unveils insights into the molecular details of PS-NP interaction with supported lipid bilayers, demonstrating that a protein corona formed in the presence of exemplary blood proteins offers protection against membrane damage, mitigating PS-NP cytotoxicity.

Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information

The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.

Computational and experimental examinations of new antitumor palladium(II) complex: CT-DNA-/BSA-binding, in-silico prediction, DFT perspective, docking, molecular dynamics simulation and ONIOM

Since the design of metal complexes with better biological activities is important, herein a new palladium(II) complex bearing en and acac (en and acac stand for ethylenediamine and acetylacetonato, respectively) as its ligands, [Pd(en)(acac)]NO3 complex, was synthesized and fully characterized. Quantum chemical computations of the palladium(II) complex were done via DFT/B3LYP method. Cytotoxicity activity of the new compound on leukemia cell line (K562) was assessed via MTT method. The findings indicated that the metal complex has remarkable cytotoxic effect than cisplatin. OSIRIS DataWarrior software was employed to calculate in-silico physicochemical and toxicity parameters of the synthesized complex which rendered significant results. To comprehend the interaction type of new metal compound with macromolecules, the in depth investigation of interaction of mentioned complex with CT-DNA and BSA was accomplished by fluorescence, UV-Visible absorption spectroscopy, viscosity measurement, gel electrophoresis, FRET analysis and circular dichroism (CD) spectroscopy. On the other hand, computational molecular docking was carried out and the obtained data demonstrated that H-bond and van der Waals forces are the dominant forces for the binding of the compound to the mentioned biomolecules. Molecular dynamics simulation was also done and confirmed the stability of best docked pose of palladium(II) complex inside DNA or BSA over the time and in presence of water solvent. Also, Our own N-layered Integrated molecular Orbital and molecular Mechanics (ONIOM) methodology based on the hybridization of quantum mechanics and molecular mechanics (QM/MM) methodology was accomplished to inquire about binding of Pd(II) complex with DNA or BSA.HIGHLIGHTSNew biologically active Pd(II) complex was synthesized and characterized.The in silico studies of the designed complex and its ligands were accomplished by OSIRIS DataWarrior softwareInteraction with CT-DNA and BSA was assessed by various spectroscopic methods.Molecular docking simulation supported the interaction with both macromolecules.Based on ONIOM analysis, the structures of the complex and biomolecules are altered after binding. Communicated by Ramaswamy H. Sarma.

Exploring the interaction of a potent anti-cancer drug Selumetinib with bovine serum albumin: Spectral and computational attributes

The binding of drugs to plasma proteins determines its fate within the physiological system, hence profound understanding of its interaction within the bloodstream is important to understand its pharmacodynamics and pharmacokinetics and thereby its therapeutic potential. In this regard, our work delineates the mechanism of interaction of Selumetinib (SEL), a potent anti-cancer drug showing excellent effect against multiple solid tumors, with plasma protein bovine serum albumin (BSA), using methods such as absorption, steady-state fluorescence, time-resolved, fluorescence resonance energy transfer, Fourier transform infrared spectra (FTIR), circular dichroism (CD), synchronous and 3D-fluorescence, salt fluorescence, molecular docking and molecular dynamic simulations. The BSA fluorescence intensity was quenched with increasing concentration of SEL which indicates interactions of SEL with BSA. Stern-Volmer quenching analysis and lifetime studies indicate the involvement of dynamic quenching. However, some contributions from the static quenching mechanism could not be ruled out unambiguously. The association constant was found to be 5.34 × 105 M-1 and it has a single binding site. The Förster distance (r) indicated probable energy transmission between the BSA and SEL. The positive entropy changes and enthalpy change indicate that the main interacting forces are hydrophobic forces, also evidenced by the results of molecular modeling studies. Conformation change in protein framework was revealed from FTIR, synchronous and 3D fluorescence and CD studies. Competitive binding experiments as well as docking studies suggest that SEL attaches itself to site I (subdomain IIA) of BSA where warfarin binds. Molecular dynamic simulations indicate the stability of the SEL-BSA complex. The association energy between BSA and SEL is affected in the presence of different metals differently.

A Membrane-Targeting Aggregation-Induced Emission Probe for Monitoring Lipid Droplet Dynamics in Ischemia/Reperfusion-Induced Cardiomyocyte Ferroptosis

Myocardial ischemia/reperfusion injury (MIRI) is the leading cause of irreversible myocardial damage. A pivotal pathogenic factor is ischemia/reperfusion (I/R)-induced cardiomyocyte ferroptosis, marked by iron overload and lipid peroxidation. However, the impact of lipid droplet (LD) changes on I/R-induced cardiomyocyte ferroptosis is unclear. In this study, an aggregation-induced emission probe, TPABTBP is developed that is used for imaging dynamic changes in LD during myocardial I/R-induced ferroptosis. TPABTBP exhibits excellent LD-specificity, superior capability for monitoring lipophagy, and remarkable photostability. Molecular dynamics (MD) simulation and super-resolution fluorescence imaging demonstrate that the TPABTBP is specifically localized to the phospholipid monolayer membrane of LDs. Imaging LDs in cardiomyocytes and myocardial tissue in model mice with MIRI reveals that the LD accumulation level increase in the early reperfusion stage (0-9 h) but decrease in the late reperfusion stage (>24 h) via lipophagy. The inhibition of LD breakdown significantly reduces the lipid peroxidation level in cardiomyocytes. Furthermore, it is demonstrated that chloroquine (CQ), an FDA-approved autophagy modulator, can inhibit ferroptosis, thereby attenuating MIRI in mice. This study describes the dynamic changes in LD during myocardial ischemia injury and suggests a potential therapeutic target for early MIRI intervention.

Graph Theoretical Description of Phase Transitions in Complex Multiscale Phases with Supramolecular Assemblies

Phase transitions are typically quantified using order parameters, such as crystal lattice distances and radial distribution functions, which can identify subtle changes in crystalline materials or high-contrast phases with large structural differences. However, the identification of phases with high complexity, multiscale organization and of complex patterns during the structural fluctuations preceding phase transitions, which are essential for understanding the system pathways between phases, is challenging for those traditional analyses. Here, it is shown that for two model systems- thermotropic liquid crystals and a lyotropic water/surfactant mixtures-graph theoretical (GT) descriptors can successfully identify complex phases combining molecular and nanoscale levels of organization that are hard to characterize with traditional methodologies. Furthermore, the GT descriptors also reveal the pathways between the different phases. Specifically, centrality parameters and node-based fractal dimension quantify the system behavior preceding the transitions, capturing fluctuation-induced breakup of aggregates and their long-range cooperative interactions. GT parameterization can be generalized for a wide range of chemical systems and be instrumental for the growth mechanisms of complex nanostructures.

Structure-based virtual screening, molecular docking, and molecular dynamics simulation approaches for identification of new potential inhibitors of class a β-lactamase enzymes

Bacteria are smart organisms that create drug resistance by decreasing the effect of antibiotics in different ways, such as secretion of the β-lactamase enzymes. Finding the compounds that can act as the inhibitors of these enzymes is a great help in reducing drug resistance and treat all types of infections. In this study, using molecular docking and molecular dynamics simulation techniques, we introduced two Relebactam substructures as new inhibitors of class A β-lactamase enzymes. Results of molecular docking show that the conformation of these two compounds in the active site of class A β-lactamase enzymes has a good match with Relebactam and their binding affinity to enzymes is equal to or better than Relebactam. Results showed a good tendency for binding and the formation of van der Waals and hydrogen interactions between the desired compounds and the β-lactamase enzymes. The results of the analysis of the molecular dynamics simulation trajectories showed that in the presence of the desired compounds, the second structures of the enzymes did not undergo many changes and in none of the systems, the binding of the compounds to the enzyme did not cause much instability, and in most cases made the structure stable. The hydrogen bonds were stable during the simulation time and in most cases, the new compounds formed more hydrogen bonds and had better binding affinity than Relebactam confirms the docking results. The results of this study can be helpful in designing new beta-lactamase inhibitors and new treatment methods to deal with drug resistance.Communicated by Ramaswamy H. Sarma.

A study of hydrophobic domain formation of polymeric drug precipitation inhibitors in aqueous solution

Despite the widespread use of polymers as precipitation inhibitors in supersaturating drug formulations, the current understanding of their mechanisms of action is still incomplete. Specifically, the role of hydrophobic drug interactions with polymers by considering possible supramolecular conformations in aqueous dispersion is an interesting topic. Accordingly, this study investigated the tendency of polymers to create hydrophobic domains, where lipophilic compounds may nest to support drug solubilisation and supersaturation. Fluorescence spectroscopy with the environment-sensitive probe pyrene was compared with atomistic molecular dynamics simulations of the model drug fenofibrate (FENO). Subsequently, kinetic drug supersaturation and thermodynamic solubility experiments were conducted. As a result, the different polymers showed hydrophobic domain formation to a varying degree and the molecular simulations supported interpretation of fluorescence spectroscopy data. Molecular insights were gained into the conformational structure of how the polymers interacted with FENO in solution phase, which apart from nucleation and crystal growth effects, determined drug concentrations in solution. Notable was that even at the lowest polymer concentration of 0.01 %, w/v, there were polymer-specific solubilisation effects of FENO observed and the resulting reduction in apparent drug supersaturation provided relevant knowledge both from a mechanistic and practical perspective.

SEM Electron-Beam-Induced Ultrathin Carbon Deposition Layer on Cu Substrate: Improved Dry Oxidation Protection Performance than CVD Single Layer Graphene

An amorphous carbon deposition layer (CDL) with nanoscale thickness induced by scanning electron microscope (SEM) electron beam is studied as a carbon-based protective layer on copper (Cu). CDL is prepared by inducing the deposition of pollutants or hydrocarbons in the cavity of SEM through electron beam irradiation (EBI). Wrinkles and cracks will not form and the interfacial spacing of CDL/Cu is smaller than Graphene/Cu (Gr/Cu). The thickness and coverage of the interfacial oxide layer of CDL/Cu are all smaller than that of the Gr/Cu after the same oxidation conditions. Characterization of Raman mapping also demonstrates that CDL shows better oxidation inhibition effects than graphene. The structure of CDL is determined to be C = C and C = O, CH3- and C-O can be loaded vertically on CDL. Density functional theory (DFT) is employed for demonstrating the smaller interfacial gap of CDL/Cu, less wrinkles and cracks and larger adsorbing energy of water/oxygen compared with Gr/Cu. Molecular dynamic (MD) simulation also indicates that the diffusion of water or oxygen into CDL/Cu is more difficult and the oxidation of Cu covered by CDL is well suppressed. This work provides a new approach for the study of carbon-based antioxidant materials on Cu.

Mechanistic Insight into how β-Ketoacyl ACP Synthase I (KasA) Recognizes the Fatty Acid Chain Length of its Substrate

β-ketoacyl ACP synthase I (KasA) has been considered as a promising drug target against Tuberculosis because it is known to play a pivotal role in the survival of Mycobacterium Tuberculosis, a causative agent of Tuberculosis. KasA catalyzes the reaction elongating only the acyl chain that is 16 carbon atoms in length or longer, but the molecular details of how KasA selectively recognizes only the substrate longer than a certain length still remain unknown. In the present study, this challenging subject is addressed, and to this end, molecular dynamics (MD) simulations and free energy calculations for actual substrate binding process are carried out. The results illustrate that the substrate specificity of KasA is highly linked to its cooperativity and this cooperativity is realized through the activation of catalytic residues. Through these results, the mechanistic details of how KasA can be selectively activated only by the substrate with a proper length are suggested.

Self-Assembly of Lamellae-in-Lamellae by Double-Tail Cationic Surfactants

The molecular structures of surfactants play a pivotal role in influencing their self-assembly behaviors. In this work, using simulations and experiments, an unconventional hierarchically layered structure in the didodecyldimethylammonium bromide (DDAB)/water binary system: lamellae-in-lamellae is revealed, a new self-assembly structure in surfactant system. This self-assembly structure refers to a lamellar structure with a shorter periodic length (inner lamellae) embedded in a lamellar phase with a longer periodic length (outer lamellae). The normal vectors of these two lamellar regions orient perpendicularly. In addition, it is observed that this lamellar-in-lamellar phase disappears when the two tails of the cationic surfactants become longer. The formation of the lamellar-in-lamellar architecture arises from multiple interacting factors. The key element is that the short tails of the DDAB surfactants enhance hydrophilicity and rigidity, which facilitates the formation of the inner lamellae. Moreover, the lateral monolayer of the inner lamellae provides shielding from the water and prompts the formation of the outer lamellae. These findings indicate that molecular structures and flexibility can profoundly redirect the hierarchical self-assembly behaviors in amphiphilic systems. More broadly, this work presents a new strategy to deliberately program hierarchical nanomaterials by designing specific surfactant molecules to act as tunable scaffolds, reactors, and carriers.

Deafness causing neuroplastin missense variants fail to promote plasma membrane Ca2+-ATPase levels and Ca2+ transient regulation in brain neurons

Hearing, the ability to sense sounds, and the processing of auditory information are important for perception of the world. Mice lacking expression of neuroplastin (Np), a type-1 transmembrane glycoprotein, display deafness, multiple cognitive deficiencies, and reduced expression of plasma membrane calcium (Ca2+) ATPases (PMCAs) in cochlear hair cells and brain neurons. In this study, we transferred the deafness causing missense mutations pitch (C315S) and audio-1 (I122N) into human Np (hNp) constructs and investigated their effects at the molecular and cellular levels. Computational molecular dynamics show that loss of the disulfide bridge in hNppitch causes structural destabilization of immunoglobulin-like domain (Ig) III and that the novel asparagine in hNpaudio-1 results in steric constraints and an additional N-glycosylation site in IgII. Additional N-glycosylation of hNpaudio-1 was confirmed by PNGaseF treatment. In comparison to hNpWT, transfection of hNppitch and hNpaudio-1 into HEK293T cells resulted in normal mRNA levels but reduced the Np protein levels and their cell surface expression due to proteasomal/lysosomal degradation. Furthermore, hNppitch and hNpaudio-1 failed to promote exogenous PMCA levels in HEK293T cells. In hippocampal neurons, expression of additional hNppitch or hNpaudio-1 was less efficient than hNpWT to elevate endogenous PMCA levels and to accelerate the restoration of basal Ca2+ levels after electrically evoked Ca2+ transients. We propose that mutations leading to pathological Np variants, as exemplified here by the deafness causing Np mutants, can affect Np-dependent Ca2+ regulatory mechanisms and may potentially cause intellectual and cognitive deficits in humans.

Molecular dynamics simulations of choline chloride and ascorbic acid deep eutectic solvents: Investigation of structural and dynamics properties

Deep eutectic solvents (DESs) composed of choline chloride (ChCl) and ascorbic acid (AA) were investigated using the molecular dynamics (MD) simulations. The analyses of the configuration, radial distribution function (RDFs), coordination number, spatial distribution function (SDFs), interaction energies, hydrogen bond number, and self-diffusion coefficient of the ChCl/AA binary systems of different concentrations showed that the stability of the hydrogen bond network and the mutual attraction between systems were the strongest at the experimental eutectic concentration (molar ratio of 2:1). In our simulated temperature range from 303.15 to 353.15 K, the hydrogen bonding network of ChCl/AA DES does not undergo considerable alterations, indicating that its stability was insensitive to temperature. In addition, the influence of the water content on the ChCl/AA DES system was further investigated. The simulated results revealed that the water molecules could disrupt the formation of the hydrogen bonding network by occupyin positions that are essential for the formation of hydrogen bonds within the DES system.

Structural bases for stoichiometry-selective calcium potentiation of a neuronal nicotinic receptor

BACKGROUND AND PURPOSE

α4β2 nicotinic acetylcholine (nACh) receptors assemble in two stoichiometric forms, one of which is potentiated by calcium. The sites of calcium binding that underpin potentiation are not known.

EXPERIMENTAL APPROACH

To identify calcium binding sites, we applied cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations to each stoichiometric form of the α4β2 nACh receptor in the presence of calcium ions. To test whether the identified calcium sites are linked to potentiation, we generated mutants of anionic residues at the sites, expressed wild type and mutant receptors in clonal mammalian fibroblasts, and recorded ACh-elicited single-channel currents with or without calcium.

KEY RESULTS

Both cryo-EM and MD simulations show calcium bound to a site between the extracellular and transmembrane domains of each α4 subunit (ECD-TMD site). Substituting alanine for anionic residues at the ECD-TMD site abolishes stoichiometry-selective calcium potentiation, as monitored by single-channel patch clamp electrophysiology. Additionally, MD simulation reveals calcium association at subunit interfaces within the extracellular domain. Substituting alanine for anionic residues at the ECD sites reduces or abolishes stoichiometry-selective calcium potentiation.

CONCLUSIONS AND IMPLICATIONS

Stoichiometry-selective calcium potentiation of the α4β2 nACh receptor is achieved by calcium association with topographically distinct sites framed by anionic residues within the α4 subunit and between the α4 and β2 subunits. Stoichiometry-selective calcium potentiation could result from the greater number of calcium sites in the stoichiometric form with three rather than two α4 subunits. The results are relevant to modulation of signalling via α4β2 nACh receptors in physiological and pathophysiological conditions.

Pyroglutamylation modulates electronic properties and the conformational ensemble of the amyloid β-peptide

Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by the formation of extracellular amyloid-β (Aβ) plaques. The underlying cause of AD is unknown, however, post-translational modifications (PTMs) of Aβ have been found in AD patients and are thought to play a role in protein aggregation. One such PTM is pyroglutamylation, which can occur at two sites in Aβ, Glu3 and Glu11. This modification of Aβ involves the truncation and charge-neutralization of N-terminal glutamate, causing Aβ to become more hydrophobic and prone to aggregation. The molecular mechanism by which the introduction of pyroglutamate (pE) promotes aggregation has not been determined. To gain a greater understanding of the role that charge neutralization and truncation of the N-terminus plays on Aβ conformational sampling, we used the Drude polarizable force field (FF) to perform molecular dynamics simulations on AβpE3-42 and AβpE11-42 and comparing their properties to previous simulations of Aβ1-42. The Drude polarizable FF allows for a more accurate representation of electrostatic interactions, therefore providing novel insights into the role that charge plays in protein dynamics. Here, we report the parametrization of pE in the Drude polarizable FF and the effect of pyroglutamylation on Aβ. We found that AβpE3-42 and AβpE11-42 alter the permanent and induced dipoles of the peptide. Specifically, we found that AβpE3-42 and AβpE11-42 have modification-specific backbone and sidechain polarization response and perturbed solvation properties that shift the Aβ conformational ensemble.

Functional diversity among cardiolipin binding sites on the mitochondrial ADP/ATP carrier

Lipid-protein interactions play a multitude of essential roles in membrane homeostasis. Mitochondrial membranes have a unique lipid-protein environment that ensures bioenergetic efficiency. Cardiolipin (CL), the signature mitochondrial lipid, plays multiple roles in promoting oxidative phosphorylation (OXPHOS). In the inner mitochondrial membrane, the ADP/ATP carrier (AAC in yeast; adenine nucleotide translocator, ANT in mammals) exchanges ADP and ATP, enabling OXPHOS. AAC/ANT contains three tightly bound CLs, and these interactions are evolutionarily conserved. Here, we investigated the role of these buried CLs in AAC/ANT using a combination of biochemical approaches, native mass spectrometry, and molecular dynamics simulations. We introduced negatively charged mutations into each CL-binding site of yeast Aac2 and established experimentally that the mutations disrupted the CL interactions. While all mutations destabilized Aac2 tertiary structure, transport activity was impaired in a binding site-specific manner. Additionally, we determined that a disease-associated missense mutation in one CL-binding site in human ANT1 compromised its structure and transport activity, resulting in OXPHOS defects. Our findings highlight the conserved significance of CL in AAC/ANT structure and function, directly tied to specific lipid-protein interactions.

Elucidating the complex membrane binding of a protein with multiple anchoring domains using extHMMM

Membrane binding is a crucial mechanism for many proteins, but understanding the specific interactions between proteins and membranes remains a challenging endeavor. Coagulation factor Va (FVa) is a large protein whose membrane interactions are complicated due to the presence of multiple anchoring domains that individually can bind to lipid membranes. Using molecular dynamics simulations, we investigate the membrane binding of FVa and identify the key mechanisms that govern its interaction with membranes. Our results reveal that FVa can either adopt an upright or a tilted molecular orientation upon membrane binding. We further find that the domain organization of FVa deviates (sometimes significantly) from its crystallographic reference structure, and that the molecular orientation of the protein matches with domain reorganization to align the C2 domain toward its favored membrane-normal orientation. We identify specific amino acid residues that exhibit contact preference with phosphatidylserine lipids over phosphatidylcholine lipids, and we observe that mostly electrostatic effects contribute to this preference. The observed lipid-binding process and characteristics, specific to FVa or common among other membrane proteins, in concert with domain reorganization and molecular tilt, elucidate the complex membrane binding dynamics of FVa and provide important insights into the molecular mechanisms of protein-membrane interactions. An updated version of the HMMM model, termed extHMMM, is successfully employed for efficiently observing membrane bindings of systems containing the whole FVa molecule.

Voronoi Tessellation as a Tool for Predicting the Formation of Deep Eutectic Solvents

Deep eutectic solvents (DESs) have attracted increasing attention in recent years due to their broad applicability in different fields, but their computer-aided discovery, which avoids a time-consuming trial-and-error investigation, is still lagging. In this paper, a set of nine DESs, composed of choline chloride as a hydrogen-bond acceptor and nine functionalized phenols as hydrogen bond donors, is simulated by using classical molecular dynamics to investigate the possible formation of a DES. The tool of the Voronoi tessellation analysis is employed for producing an intuitive and straightforward representation of the degree of mixing between the different components of the solutions, therefore permitting the definition of a metric quantifying the propensity of the components to produce a uniform solution. The computational findings agree with the experimental results, thus confirming that the Voronoi tessellation analysis can act as a lightweight yet powerful approach for the high-throughput screening of mixtures in the optics of the new DES design.

Structural packing of the non-amyloid component core domain in α-synuclein plays a role in the stability of the fibrils

Parkinson's disease (PD) is one of many neurodegenerative diseases. The protein associated with PD is α-synuclein (AS). Aggregation of AS protein into oligomers, protofilaments, and finally to fibrils yields to the development of PD. The aggregation process of AS leads to the formation of polymorphic AS fibrils. Herein, we compared four polymorphic full-length AS1-140 fibrils, using extensive computational tools. The main conclusion of this study emphasizes the role of the structurally packed non-amyloid component (NAC) core domain in AS fibrils. Polymorphic AS fibrils that presented a packed NAC core domain, exhibited more β-sheets and fewer fluctuations in the NAC domain. Hence, these AS fibrils are more stable and populated than the AS fibrils, by which the NAC domains are more exposed, more fluctuate and less packed in the fibrillary structure. Therefore, this study emphasizes the importance of the NAC domain packing in the morphology of AS fibrils. The results obtained in this study will initiate future studies to develop compounds to prevent and inhibit AS aggregation.

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

A computational study to assess the pathogenicity of single or combinations of missense variants on respiratory complex I

Variants found in the respiratory complex I (CI) subunit genes encoded by mitochondrial DNA can cause severe genetic diseases. However, it is difficult to establish a priori whether a single or a combination of CI variants may impact oxidative phosphorylation. Here we propose a computational approach based on coarse-grained molecular dynamics simulations aimed at investigating new CI variants. One of the primary CI variants associated with the Leber hereditary optic neuropathy (m.14484T>C/MT-ND6) was used as a test case and was investigated alone or in combination with two additional rare CI variants whose role remains uncertain. We found that the primary variant positioned in the E-channel region, which is fundamental for CI function, stiffens the enzyme dynamics. Moreover, a new mechanism for the transition between π- and α-conformation in the helix carrying the primary variant is proposed. This may have implications for the E-channel opening/closing mechanism. Finally, our findings show that one of the rare variants, located next to the primary one, further worsens the stiffening, while the other rare variant does not affect CI function. This approach may be extended to other variants candidate to exert a pathogenic impact on CI dynamics, or to investigate the interaction of multiple variants.

Effect of quercetin on the protein-substrate interactions in SIRT6: Insight from MD simulations

SIRT6 is of interest for its promising effect in the treatment of aging-related diseases. Studies have shown quercetin (QUE) and its derivatives have varying degrees of effect on the catalytic effect of SIRT6. In the research, the effect of QUE on the protein-substrate interaction in the SIRT6-mediated mono-ADP ribosylation system was investigated by conventional molecular dynamics (MD) simulations combined with MM/PBSA binding free energy calculations. The results show that QUE can bind stably to SIRT6 with the binding energy of -22.8 kcal/mol and further affect the atomic interaction between SIRT6 and NAD+ (or H3K9), resulting in an increased affinity between SIRT6-NAD+ and decreased SIRT6-H3K9 binding capacity. At the same time, the binding of QUE can also alter some structural characteristics of the protein, with large shifts occurring in the residue regions involving the N-terminal (residues 1-27), Rossmann fold regions (residues 55-92), and ZBD (residues 164-179). Thus, QUE shows great potential as a scaffold for the design of novel potent SIRT6 modulators.

Complexation Mechanisms of Aqueous Amylose: Molecular Dynamics Study Using 3-Pentadecylphenol

Molecular dynamics (MD) simulations of linear amylose fragments containing 10 to 40 glucose units were used to study the complexation of the prototypical compound, 3-pentadecylphenol (PDP)─a natural product with surfactant-like properties─in aqueous solution. The amylose-PDP binding leverages mainly hydrophobic interactions together with excluded volume effects. It was found that while the most stable complexes contained PDP inside the helical structure of the amylose in the expected guest-host (inclusion) complexation manner, at higher temperatures, the commonly observed PDP-amylose complexes often involved more nonspecific interactions than inclusion complexation. In the case where a stoichiometric excess of PDP was added to the simulation box, self-aggregation of the small molecule precluded its ability to enter the internal helical part of the oligosaccharide, and as a result, inclusion complexation became ineffective. MD simulation trajectories were analyzed preliminarily using cluster analysis (CA), followed by more rigorous solvent accessible surface area (SASA) determination over the temperature range spanning from 277 to 433 K. It was found that using the SASA of PDP corrected for its intrinsic conformational changes, together with a generic hidden Markov model (HMM), an adequate quantification of the different types of PDP-amylose aggregates was obtained to allow further analysis. The enthalpy change associated with the guest-host binding equilibrium constant (Kgh) in aqueous solution was estimated to be -75 kJ/mol, which is about twice as high as one might expect based on experimentally measured values of similar complexes in the solid state where the (unsolvated) helical structure of amylose remains rigid. On the other hand, the nonspecific binding (Kns) enthalpy change associated with PDP-amylose interactions in the same solution environment was found to be about half of the inclusion complexation value.

Identification of pseudobaptigenin as a novel polyphenol-based multi-target antagonist of different hormone receptors for breast cancer therapeutics

Breast cancer (BC) is one of the most prevalent cancers in the world and is one of the major reasons for the death of women worldwide. BC is majorly categorized based on the presence or absence of three cell receptors ER, PR and HER2. The latest treatment for BC involves interfering with the production and action of hormones such as estrogen and progesterone. These hormones bind with receptors such as ER and PR and enhance the growth and proliferation of the BC cells. Although the available are effective, the increasing resistance and side effects related to hormonal imbalance are significant and hence there is a need for designing. On the other hand, plant-derivative products have gained a lot of popularity for their promising anti-cancerous activities. Polyphenols are one such group of plant derivatives that have proven to be useful against cancer. In the present study, an in-silico approach was used to search for a polyphenol that can inhibit ER. In this work, a total of 750 polyphenols were taken into consideration. This number was narrowed down to 55, based on their ADMET properties. These 55 polyphenols were then docked to the receptors, ER, PR and HER2. The molecular docking was followed by Molecular Dynamics (MD) simulations. Based on molecular docking and MD simulation results it was concluded that Pseudobaptigenin has the potential to be an inhibitor of ER, PR and HER2.Communicated by Ramaswamy H. Sarma.

Insights into the mechanism of peptide fibril growth on gold surface

Understanding the formation of β-fibrils over the gold surface is of paramount interest in nano-bio-medicinal Chemistry. The intricate mechanism of self-assembly of neurofibrillogenic peptides and their growth over the gold surface remains elusive, as experiments are limited in unveiling the microscopic dynamic details, in particular, at the early stage of the peptide aggregation. In this work, we carried out equilibrium molecular dynamics and enhanced sampling simulations to elucidate the underlying mechanism of the growth of an amyloid-forming sequence of tau fragments over the gold surface. Our results disclose that the collective intermolecular interactions between the peptide chains and peptides with the gold surface facilitate the peptide adsorption, followed by integration, finally leading to the fibril formation.

The Effects of External Interfaces on Hydrophobic Interactions I: Smooth Surface

External interfaces, such as the air-water and solid-liquid interfaces, are ubiquitous in nature. Hydrophobic interactions are considered the fundamental driving force in many physical and chemical processes occurring in aqueous solutions. It is important to understand the effects of external interfaces on hydrophobic interactions. According to the structural studies on liquid water and the air-water interface, the external interface primarily affects the structure of the topmost water layer (interfacial water). Therefore, an external interface may affect hydrophobic interactions. The effects of interfaces on hydrophobicity are related not only to surface molecular polarity but also to the geometric characteristics of the external interface, such as shape and surface roughness. This study is devoted to understanding the effects of a smooth interface on hydrophobicity. Due to hydrophobic interactions, the solutes tend to accumulate at external interfaces to maximize the hydrogen bonding of water. Additionally, these can be demonstrated by the calculated potential mean forces (PMFs) using molecular dynamic (MD) simulations.

In silico modelling of ciprofloxacin specific aptamer for the development of high-performance biosensor

Ciprofloxacin (CFX), a widely used fluoroquinolone antibiotic, is critical in healthcare settings for treating patients. However, improper treatment of wastewater from these facilities can lead to environmental contamination with CFX. This underscores the need for an efficient, straightforward method for early detection. In this study, a DNA aptamer was selected through a hierarchical docking workflow, and the stability and interactions were assessed by Molecular Dynamics (MD) simulation. The aptamer-CFX complex that showed the most promise had a docking score of -8.596 kcal/mol and was further analyzed using MD simulation and MM/PBSA. Based on the overall results, the identified ssDNA sequence length of 60 nt (CAGCGCTAGGGCTTTTAGCGTAATGGGTAGGGTGGTGCGGTGCAGATATCGGAATTGGTG) was immobilized over a gold transducer surface through the self-assembled monolayer (SAM; Au-S-ssDNA) method. The ssDNA-modified surface has demonstrated a high affinity towards CFX, which is confirmed by cyclic voltammogram (CV) and electrochemical impedance spectroscopy measurements (EIS). The DNA-aptamer modified electrode demonstrated a good linear range (10 × 10-9 - 200 × 10-9 M), detection limit (1.0 × 10-9 M), selectivity, reproducibility, and stability. The optimized DNA-aptamer-based CFX sensor was further utilized for the accurate determination of CFX with good recoveries in real samples.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduced an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β 1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Mode coupling behavior and fragile to strong transition of trehalose in a binary mixture with water upon supercooling

We perform molecular dynamics simulations of a binary mixture of water and trehalose with the TIP4P/Ice water model. We analyze the slow dynamics of trehalose molecules in the mildly supercooled region for concentrations of 3.66 and 18.57 wt. %. We previously studied the dynamics of water in the same mixtures. Supercooled TIP4P/Ice water solvating trehalose molecules was found to follow the Mode Coupling Theory (MCT) and to undergo a transition from a fragile to a strong behavior for both concentrations. Here, we show that also the dynamics of trehalose molecules follows the MCT and displays a fragile to strong crossover (FSC). The results show that trehalose in binary mixtures with water shares with it the dynamical behavior typical of glass forming liquids. Moreover, the FSC for trehalose structural relaxation times is found to occur at temperatures close to those previously obtained for water in the same solutions, showing that the dynamics of the solute is strongly coupled to that of the solvent. We also perform a MCT test showing that the trehalose dynamics obeys the MCT time-temperature superposition principle and that the exponents derived from the theory and the ones obtained from fitting procedure of the relaxation times are comparable, confirming that trehalose molecules in supercooled water solutions follow the MCT of glassy dynamics. Moreover, as predicted by the theory, trehalose particles have MCT parameters comparable to those of water in the same mixtures. This is an important result, given that MCT was originally formulated for monoatomic particles.

Design, synthesis, inhibitory activity, and molecular simulations study for d-glucose-conjugated thioureas containing pyrimidine ring as multitarget inhibitors against α-amylase, α-glucosidase, DDP-4, and PTP1B in Type 2 diabetes mellitus

A series of tetra-O-acetyl-α-d-glucopyranosyl thioureas 8a-l of substituted 2-aminopyrimidines 4a-l have been designed and synthesized. The latter were prepared from corresponding chalcones 3a-l of p-bromoacetophenone and appropriate substituted benzaldehydes by their reaction with guanidine. The target thiourea compounds 8a-l exhibited significant inhibitory activity in vitro against enzymes that were related to type 2 diabetes mellitus, including α-amylase, α-glucosidase, DPP-4, and PTP1B. Amongst these thioureas, compound 8k with an ortho-methoxy group was the most potential enzyme inhibitor against α-amylase with an IC50 value of 9.72 ± 0.34 μM. Its meta-isomer 8j was the strongest inhibitor against α-glucosidase with IC50 = 9.73 ± 0.72 μM. In the inhibition against DPP-4, compound 8f with a para-bromo substituent exhibited the strongest activity with an IC50 value of 2.53 ± 0.03 nM. In the inhibition against PTP1B, compound 8h with a para-isopropyl substituent had the strongest inhibitory activity with an IC50 value of 2.74 ± 0.03 μM. The enzyme kinetics of the most active compounds, including 8j, 8f and 8h against α-glucosidase, DPP-4, and PTP1B, respectively, were studied. The obtained results showed that 8j was a competitive α-glucosidase inhibitor with an inhibitory constant K I value of 9.31 μM. Compound 8f was a non-competitive inhibitor for DDP-4 with an inhibitory constant K I value of 12.57 μM. Compound 8h was also a non-competitive inhibitor for DDP-4 with an inhibitory constant K I value of 12.41 μM. The cytotoxicity of the most active compounds, including 8f and 8k (against α-amylase), 8i and 8j (against α-glucosidase), 8a, 8f, and 8g (against DPP-4), and 8d, 8f, and 8h (against PTP1B) was screened. The obtained cytotoxicity showed that all tested inhibitors were noncytotoxic to human normal cell line 3T3. Induced fit docking simulations of all synthesized compounds 8a-l were performed on four enzymes 4W93 (for α-amylase), 3TOP (for α-glucosidase), 3W2T (for DPP-4), and 1NNY (for PTP1B). Key interactions of each of these ligands with residues in the active pocket of each studied enzyme have been shown.

Exploiting the Fc base of IgG antibodies to create functional nanoparticle conjugates

The structures of the Fc base of various IgG antibodies have been examined with a view to understanding how this region can be used to conjugate IgG to nanoparticles. The base structure is found to be largely consistent across a range of species and subtypes, comprising a hydrophobic region surrounded by hydrophilic residues, some of which are charged at physiological conditions. In addition, atomistic Molecular Dynamics simulations were performed to explore how model nanoparticles interact with the base using neutral and negatively charged gold nanoparticles. Both types of nanoparticle interacted readily with the base, leading to an adaptation of the antibody base surface to enhance the interactions. Furthermore, these interactions left the rest of the domain at the base of the Fc region structurally intact. This implies that coupling nanoparticles to the base of an IgG molecule is both feasible and desirable, since it leaves the antibody free to interact with its surroundings so that antigen-binding functionality can be retained. These results will therefore help guide future attempts to develop new nanotechnologies that exploit the unique properties of both antibodies and nanoparticles.

Binding of steroid substrates reveals the key to the productive transition of the cytochrome P450 OleP

OleP is a bacterial cytochrome P450 involved in oleandomycin biosynthesis as it catalyzes regioselective epoxidation on macrolide intermediates. OleP has recently been reported to convert lithocholic acid (LCA) into murideoxycholic acid through a highly regioselective reaction and to unspecifically hydroxylate testosterone (TES). Since LCA and TES mainly differ by the substituent group at the C17, here we used X-ray crystallography, equilibrium binding assays, and molecular dynamics simulations to investigate the molecular basis of the diverse reactivity observed with the two steroids. We found that the differences in the structure of TES and LCA affect the capability of these molecules to directly form hydrogen bonds with N-terminal residues of OleP internal helix I. The establishment of these contacts, by promoting the bending of helix I, fosters an efficient trigger of the open-to-closed structural transition that occurs upon substrate binding to OleP and contributes to the selectivity of the subsequent monooxygenation reaction.

Applications of the Newly Developed Force-Field Parameters Uncover a Dynamic Nature of Ω-Loop C in the Lys-Ligated Alkaline Form of Cytochrome c

Lys-ligated cytochromes make up an emerging family of heme proteins. Density functional theory calculations on the amine/imidazole-ligated c-type ferric heme were employed to develop force-field parameters for molecular dynamics (MD) simulations of structural and dynamic features of these proteins. The new force-field parameters were applied to the alkaline form of yeast iso-1 cytochrome c to rationalize discrepancies resulting from distinct experimental conditions in prior structural studies and to provide insights into the mechanisms of the alkaline transition. Our simulations have revealed the dynamic nature of Ω-loop C in the Lys-ligated protein and its unfolding in the Lys-ligated conformer having this loop in the same position as in the native Met-ligated protein. The proximity of Tyr67 or Tyr74 to the Lys ligand of ferric heme iron suggests a possible mechanism of the backward alkaline transition where a proton donor Tyr assists in Lys dissociation. The developed force-field parameters will be useful in structural and dynamic characterization of other native or engineered Lys-ligated heme proteins.