Testing of the GROMOS Force-Field Parameter Set 54A8: Structural Properties of Electrolyte Solutions, Lipid Bilayers, and Proteins

Caspase-Based Fusion Protein Technology: Substrate Cleavability Described by Computational Modeling and Simulation

The Caspase-based fusion protein technology (CASPON) allows for universal cleavage of fusion tags from proteins of interest to reconstitute the native N-terminus. While the CASPON enzyme has been optimized to be promiscuous against a diversity of N-terminal peptides, the cleavage efficacy for larger proteins can be surprisingly low. We develop an efficient means to rationalize and predict the cleavage efficiency based on a structural representation of the intrinsically disordered N-terminal peptides and their putative interactions with the CASPON enzyme. The number of favorably interacting N-terminal conformations shows a very good agreement with the experimentally observed cleavage efficiency, in agreement with a conformational selection model. The method relies on computationally cheap molecular dynamics simulations to efficiently generate a diverse collection of N-terminal conformations, followed by a simple fitting procedure into the CASPON enzyme. It can be readily used to assess the CASPON cleavability a priori.

On the Validation of Protein Force Fields Based on Structural Criteria

Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.

The Effect of Microwaves on Protein Structure: Molecular Dynamics Approach

The impact of microwave (MW) irradiation on protein folding, potentially inciting misfolding, was investigated by employing molecular dynamics (MD) simulations. Twenty-nine proteins were subjected to MD simulations under equilibrium (300 K) and MW conditions, where the rotational temperature was elevated to 700 K. The utilized replacement model captures the microwave effects of δ- and γ-relaxation processes (frequency range of ∼300 MHz to ∼20 GHz). The results disclosed that MW heating incited a shift toward more compact protein conformations, as indicated by decreased root-mean-square deviations, root-mean-square fluctuations, head-to-tail distances, and radii of gyration. This compaction was attributed to the intensification of intramolecular electrostatic interactions and hydrogen bonds within the protein caused by MW-destabilized hydrogen bonds between the protein and solvent. The solvent-accessible surface area (SASA), particularly that of polar amino-acid residues, shrank under MW conditions, corresponding to a reduced polarity of the water solvent. However, MW irradiation produced no significant alterations in protein secondary structures; hence, MW heating was observed to primarily affect the protein tertiary structures.

Tyrosine phosphorylation of recombinant hirudin increases affinity to thrombin and antithrombotic activity

Thrombin is one of the key enzymes of the blood coagulation system and a promising target for the development of anticoagulants. One of the most specific natural thrombin inhibitors is hirudin, contained in the salivary glands of medicinal leeches. The medicinal use of recombinant hirudin is limited because of the lack of sulfation on Tyr63, resulting in a 10-fold decrease in activity compared to native (sulfated) hirudin. In the present work, a set of hirudin derivatives was tested for affinity to thrombin: phospho-Tyr63, Tyr63(carboxymethyl)Phe, and Tyr63Glu mutants, which mimic Tyr63 sulfation and Gln65Glu mutant and lysine-succinylated hirudin, which enhance the overall negative charge of hirudin, as well as sulfo-hirudin and desulfo-hirudin as references. Using steered molecular dynamics simulations with subsequent umbrella sampling, phospho-hirudin was shown to exhibit the highest affinity to thrombin among all hirudin analogs, including native sulfo-hirudin; succinylated hirudin was also prospective. Phospho-hirudin exhibited the highest antithrombotic activity in in vitro assay in human plasma. Taking into account the modern methods for obtaining phospho-hirudin and succinylated hirudin, they are prospective as anticoagulants in clinical practice.

Prediction and biological analysis of yeast VDAC1 phosphorylation

The mitochondrial outer membrane protein porin 1 (Por1), the yeast orthologue of mammalian voltage-dependent anion channel (VDAC), is the major permeability pathway for the flux of metabolites and ions between cytosol and mitochondria. In yeast, several Por1 phosphorylation sites have been identified. Protein phosphorylation is a major modification regulating a variety of biological activities, but the potential biological roles of Por1 phosphorylation remains unaddressed. In this work, we analysed 10 experimentally observed phosphorylation sites in yeast Por1 using bioinformatics tools. Two of the residues, T100 and S133, predicted to reduce and increase pore permeability, respectively, were validated using biological assays. In accordance, Por1T100D reduced mitochondrial respiration, while Por1S133E phosphomimetic mutant increased it. Por1T100A expression also improved respiratory growth, while Por1S133A caused defects in all growth conditions tested, notably in fermenting media. In conclusion, we found phosphorylation has the potential to modulate Por1, causing a marked effect on mitochondrial function. It can also impact on cell morphology and growth both in respiratory and, unpredictably, also in fermenting conditions, expanding our knowledge on the role of Por1 in cell physiology.

System-Specific Parameter Optimization for Nonpolarizable and Polarizable Force Fields

The accuracy of classical force fields (FFs) has been shown to be limited for the simulation of cation-protein systems despite their importance in understanding the processes of life. Improvements can result from optimizing the parameters of classical FFs or by extending the FF formulation by terms describing charge transfer (CT) and polarization (POL) effects. In this work, we introduce our implementation of the CTPOL model in OpenMM, which extends the classical additive FF formula by adding CT and POL. Furthermore, we present an open-source parametrization tool, called FFAFFURR, that enables the (system-specific) parametrization of OPLS-AA and CTPOL models. The performance of our workflow was evaluated by its ability to reproduce quantum chemistry energies and by molecular dynamics simulations of a zinc-finger protein.

Development of nano-delivery systems for loaded bioactive compounds: using molecular dynamics simulations

Over the past decade, a remarkable surge in the development of functional nano-delivery systems loaded with bioactive compounds for healthcare has been witnessed. Notably, the demanding requirements of high solubility, prolonged circulation, high tissue penetration capability, and strong targeting ability of nanocarriers have posed interdisciplinary research challenges to the community. While extensive experimental studies have been conducted to understand the construction of nano-delivery systems and their metabolic behavior in vivo, less is known about these molecular mechanisms and kinetic pathways during their metabolic process in vivo, and lacking effective means for high-throughput screening. Molecular dynamics (MD) simulation techniques provide a reliable tool for investigating the design of nano-delivery carriers encapsulating these functional ingredients, elucidating the synthesis, translocation, and delivery of nanocarriers. This review introduces the basic MD principles, discusses how to apply MD simulation to design nanocarriers, evaluates the ability of nanocarriers to adhere to or cross gastrointestinal mucosa, and regulates plasma proteins in vivo. Moreover, we presented the critical role of MD simulation in developing delivery systems for precise nutrition and prospects for the future. This review aims to provide insights into the implications of MD simulation techniques for designing and optimizing nano-delivery systems in the healthcare food industry.

Alchemical Free Energy Calculations on Membrane-Associated Proteins

Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.

Dual role of pulmonary surfactant corona in modulating carbon nanotube toxicity and benzo[a]pyrene bioaccessibility

Inhaled carbon nanotubes (CNTs) can deposit in the deep lung, where they interact with pulmonary surfactant (PS) to form coronas, potentially altering the fate and toxicity profile of CNTs. However, the presence of other contaminants in combination with CNTs may affect these interactions. Here, we used passive dosing and fluorescence-based techniques confirm the partial solubilization of BaPs adsorbed on CNTs by PS in simulated alveolar fluid. MD simulations were performed to elucidate the competition of interactions between BaPs, CNTs, and PS. We found that PS play two opposing roles in altering the toxicity profile of the CNTs. First, the formation of PS coronas reduce CNTs' toxicity by decreasing the hydrophobicity of the CNTs and decreasing their aspect ratio. Second, the interaction with PS increases the bioaccessibility of BaP through interactions with PS, which may exacerbate the inhalation toxicity of CNTs. These findings suggest that the inhalation toxicity of PS-modified CNTs should consider the bioaccessibility of coexisting contaminants, with the CNT size and aggregation state playing an important role.

An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation

Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchmarks. While such benchmarks are rather common in the fields of quantum chemistry, this is not the case for empirical FFs. That is, few benchmarks are reused to evaluate FFs, and development teams rather use their own training and test sets. Here we present an overview of currently available tests and benchmarks for computational chemistry, focusing on organic compounds, including halogens and common ions, as FFs for these are the most common ones. We argue that many of the benchmark data sets from quantum chemistry can in fact be reused for evaluating FFs, but new gas phase data is still needed for compounds containing phosphorus and sulfur in different valence states. In addition, more nonequilibrium interaction energies and forces, as well as molecular properties such as electrostatic potentials around compounds, would be beneficial. For the condensed phases there is a large body of experimental data available, and tools to utilize these data in an automated fashion are under development. If FF developers, as well as researchers in artificial intelligence, would adopt a number of these data sets, it would become easier to compare the relative strengths and weaknesses of different models and to, eventually, restore the balance in the force.

Structural models of viral insulin-like peptides and their analogs

The insulin receptor (IR), the insulin-like growth factor-1 receptor (IGF1R), and the insulin/IGF1 hybrid receptors (hybR) are homologous transmembrane receptors. The peptide ligands, insulin and IGF1, exhibit significant structural homology and can bind to each receptor via site-1 and site-2 residues with distinct affinities. The variants of the Iridoviridae virus family show capability in expressing single-chain insulin/IGF1 like proteins, termed viral insulin-like peptides (VILPs), which can stimulate receptors from the insulin family. The sequences of VILPs lacking the central C-domain (dcVILPs) are known, but their structures in unbound and receptor-bound states have not been resolved to date. We report all-atom structural models of three dcVILPs (dcGIV, dcSGIV, and dcLCDV1) and their complexes with the receptors (μIR, μIGF1R, and μhybR), and probed the peptide/receptor interactions in each system using all-atom molecular dynamics (MD) simulations. Based on the nonbonded interaction energies computed between each residue of peptides (insulin and dcVILPs) and the receptors, we provide details on residues establishing significant interactions. The observed site-1 insulin/μIR interactions are consistent with previous experimental studies, and a residue-level comparison of interactions of peptides (insulin and dcVILPs) with the receptors revealed that, due to sequence differences, dcVILPs also establish some interactions distinct from those between insulin and IR. We also designed insulin analogs and report enhanced interactions between some analogs and the receptors.

Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set

The level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρ_liq and vaporization enthalpies ΔH_vap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κ_T, the isobaric thermal-expansion coefficient α_P, the isobaric heat capacity c_P, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔG_wat, and the free energy of solvation ΔG_che in cyclohexane. For the target properties ρ_liq and ΔH_vap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κ_T, α_P, ϵ, D, and ΔG_che; and less accurate results in terms of c_P and ΔG_wat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.

Effect of Solvent Removal Rate and Annealing on the Interface Properties in a Blend of a Diketopyrrolopyrrole-Based Polymer with Fullerene

We study the effect of solvent-free annealing and explicit solvent evaporation protocols in classical molecular dynamics simulations on the interface properties of a blend of a diketopyrrolopyrrole (DPP) polymer with conjugated substituents (DPP2Py2T) and PCBM[60]. We specifically analyze the intramolecular segmental mobility of the different polymer building blocks as well as intermolecular radial and angular distribution functions between donor and acceptor. The annealing simulations reveal an increase of the glass-transition temperature of 45 K in the polymer–fullerene blend compared to that of pure DPP2Py2T. Our results show that the effective solvent evaporation rates at room temperature only have a minor influence on the segmental mobility and intermolecular orientation, characterized in all cases by a preferential arrangement of PCBM[60] close to the electron-donating substituents in DPP2Py2T. In contrast, solvent-free annealing from a liquid yields clustering of the fullerene close to the electron-withdrawing DPP, generally considered to be detrimental for application in organic solar cells. We find that the difference can be attributed to differences in the behavior of 2-hexyldecyl side-chains, which collapse toward DPP when solvent is explicitly removed, thereby blocking access of PCBM[60].

Structural insights into the pSer/pThr dependent regulation of the SHP2 tyrosine phosphatase in insulin and CD28 signaling

Serine/threonine phosphorylation of insulin receptor substrate (IRS) proteins is well known to modulate insulin signaling. However, the molecular details of this process have mostly been elusive. While exploring the role of phosphoserines, we have detected a direct link between Tyr-flanking Ser/Thr phosphorylation sites and regulation of specific phosphotyrosine phosphatases. Here we present a concise structural study on how the activity of SHP2 phosphatase is controlled by an asymmetric, dual phosphorylation of its substrates. The structure of SHP2 has been determined with three different substrate peptides, unveiling the versatile and highly dynamic nature of substrate recruitment. What is more, the relatively stable pre-catalytic state of SHP2 could potentially be useful for inhibitor design. Our findings not only show an unusual dependence of SHP2 catalytic activity on Ser/Thr phosphorylation sites in IRS1 and CD28, but also suggest a negative regulatory mechanism that may also apply to other tyrosine kinase pathways as well.

SHP2 is an important human tyrosine phosphatase with key roles in cancer, immune responses and insulin signaling. Here, the authors explore its substrate recognition mechanism in molecular detail and uncover a complex regulatory mechanism for this enzyme that marks specific target sites for dephosphorylation.

Using Atomistic Simulations to Explore the Role of Methylation and ATP in Chemotaxis Signal Transduction

A bacterial chemotaxis mechanism is activated when nutrients bind to surface receptors. The sequence of intra- and interprotein events in this signal cascade from the receptors to the eventual molecular motors has been clearly identified. However, the atomistic details remain elusive, as in general may be expected of intraprotein signal transduction pathways, especially when fibrillar proteins are involved. We performed atomistic calculations of the methyl accepting chemoprotein (MCP)-CheA-CheW multidomain complex from Escherichia coli, simulating the methylated and unmethylated conditions in the chemoreceptors and the ATP-bound and apo conditions of the CheA. Our results indicate that these atomistic simulations, especially with one of the two force fields we tried, capture several relevant features of the downstream effects, such as the methylation favoring an intermediate structure that is more toward a dipped state and increases the chance of ATP hydrolysis. The results thus suggest the sensitivity of the model to reflect the nutrient signal response, a nontrivial validation considering the complexity of the system, encouraging even more detailed studies on the thermodynamic quantification of the effects and the identification of the signaling networks.

Structures and interactions of insulin-like peptides from cone snail venom

The venomous insulin-like peptides released by certain cone snails stimulate hypoglycemic shock to immobilize fish and catch the prey. Compared to human insulin (hIns), the cone snail insulins (Con-Ins) are typically monomeric and shorter in sequence, yet they exhibit moderate hIns-like biological activity. We have modeled six variants of Con-Ins (G3, K1, K2, T1A, T1B, and T2) and carried out explicit-solvent molecular dynamics (MD) simulations of eight types of insulins, two with known structures (hIns and Con-Ins-G1) and six Con-Ins with modeled structures, to characterize key residues of each insulin that interact with the truncated human insulin receptor (μIR). We show that each insulin/μIR complex is stable during explicit-solvent MD simulations and hIns interactions indicate the highest affinity for the "site 1" of IR. The residue contact maps reveal that each insulin preferably interacts with the αCT peptide than the L1 domain of IR. Through analysis of the average nonbonded interaction energy contribution of every residue of each insulin for the μIR, we probe the residues establishing favorable interactions with the receptor. We compared the interaction energy of each residue of every Con-Ins to the μIR and observed that γ-carboxylated glutamate (Gla), His, Thr, Tyr, Tyr/His, and Asn in Con-Ins are favorable substitutions for GluA4, AsnA21, ValB12, LeuB15, GlyB20, and ArgB22 in hIns, respectively. The identified insulin analogs, although lacking the last eight residues of the B-chain of hIns, bind strongly to μIR. Our findings are potentially useful in designing potent fast-acting therapeutic insulin.

S-Nitrosation of E3 Ubiquitin Ligase Complex Components Regulates Hormonal Signalings in Arabidopsis

E3 ubiquitin ligases mediate the last step of the ubiquitination pathway in the ubiquitin-proteasome system (UPS). By targeting transcriptional regulators for their turnover, E3s play a crucial role in every aspect of plant biology. In plants, SKP1/CULLIN1/F-BOX PROTEIN (SCF)-type E3 ubiquitin ligases are essential for the perception and signaling of several key hormones including auxins and jasmonates (JAs). F-box proteins, TRANSPORT INHIBITOR RESPONSE 1 (TIR1) and CORONATINE INSENSITIVE 1 (COI1), bind directly transcriptional repressors AUXIN/INDOLE-3-ACETIC ACID (AUX/IAA) and JASMONATE ZIM-DOMAIN (JAZ) in auxin- and JAs-depending manner, respectively, which permits the perception of the hormones and transcriptional activation of signaling pathways. Redox modification of proteins mainly by S-nitrosation of cysteines (Cys) residues via nitric oxide (NO) has emerged as a valued regulatory mechanism in physiological processes requiring its rapid and versatile integration. Previously, we demonstrated that TIR1 and Arabidopsis thaliana SKP1 (ASK1) are targets of S-nitrosation, and these NO-dependent posttranslational modifications enhance protein-protein interactions and positively regulate SCF^TIR1 complex assembly and expression of auxin response genes. In this work, we confirmed S-nitrosation of Cys140 in TIR1, which was associated in planta to auxin-dependent developmental and stress-associated responses. In addition, we provide evidence on the modulation of the SCF^COI1 complex by different S-nitrosation events. We demonstrated that S-nitrosation of ASK1 Cys118 enhanced ASK1-COI1 protein-protein interaction. Overexpression of non-nitrosable ask1 mutant protein impaired the activation of JA-responsive genes mediated by SCF^COI1 illustrating the functional relevance of this redox-mediated regulation in planta. In silico analysis positions COI1 as a promising S-nitrosation target, and demonstrated that plants treated with methyl JA (MeJA) or S-nitrosocysteine (NO-Cys, S-nitrosation agent) develop shared responses at a genome-wide level. The regulation of SCF components involved in hormonal perception by S-nitrosation may represent a key strategy to determine the precise time and site-dependent activation of each hormonal signaling pathway and highlights NO as a pivotal molecular player in these scenarios.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Structure-guided glyco-engineering of ACE2 for improved potency as soluble SARS-CoV-2 decoy receptor

Infection and viral entry of SARS-CoV-2 crucially depends on the binding of its Spike protein to angiotensin converting enzyme 2 (ACE2) presented on host cells. Glycosylation of both proteins is critical for this interaction. Recombinant soluble human ACE2 can neutralize SARS-CoV-2 and is currently undergoing clinical tests for the treatment of COVID-19. We used 3D structural models and molecular dynamics simulations to define the ACE2 N-glycans that critically influence Spike-ACE2 complex formation. Engineering of ACE2 N-glycosylation by site-directed mutagenesis or glycosidase treatment resulted in enhanced binding affinities and improved virus neutralization without notable deleterious effects on the structural stability and catalytic activity of the protein. Importantly, simultaneous removal of all accessible N-glycans from recombinant soluble human ACE2 yields a superior SARS-CoV-2 decoy receptor with promise as effective treatment for COVID-19 patients.

Impact of the dynamics of the catalytic arginine on nitrite and chlorite binding by dimeric chlorite dismutase

Chlorite dismutases (Clds) are heme b containing oxidoreductases able to decompose chlorite to chloride and molecular oxygen. This work analyses the impact of the distal, flexible and catalytic arginine on the binding of anionic angulate ligands like nitrite and the substrate chlorite. Dimeric Cld from Cyanothece sp. PCC7425 was used as a model enzyme. We have investigated wild-type CCld having the distal catalytic R127 hydrogen-bonded to glutamine Q74 and variants with R127 (i) being arrested in a salt-bridge with a glutamate (Q74E), (ii) being fully flexible (Q74V) or (iii) substituted by either alanine (R127A) or lysine (R127K). We present the electronic and spectral signatures of the high-spin ferric proteins and the corresponding low-spin nitrite complexes elucidated by UV-visible, circular dichroism and electron paramagnetic resonance spectroscopies. Furthermore, we demonstrate the impact of the dynamics of R127 on the thermal stability of the respective nitrite adducts and present the X-ray crystal structures of the nitrite complexes of wild-type CCld and the variants Q74V, Q74E and R127A. In addition, the molecular dynamics (MD) and the binding modi of nitrite and chlorite to the ferric wild-type enzyme and the mutant proteins and the interaction of the oxoanions with R127 have been analysed by MD simulations. The findings are discussed with respect to the role(s) of R127 in ligand and chlorite binding and substrate degradation.

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

Preparing and Analyzing Polarizable Molecular Dynamics Simulations with the Classical Drude Oscillator Model

Molecular dynamics (MD) simulations performed with force fields that include explicit electronic polarization are becoming more prevalent in the field. The increasing emergence of these simulations is a result of continual refinement against a range of theoretical and empirical target data, optimization of software algorithms for higher performance, and availability of graphical processing unit hardware to further accelerate the simulations. Polarizable MD simulations are likely to be most impactful in biomolecular systems in which heterogeneous environments or unique microenvironments exist that would lead to inaccuracies in simulations performed with fixed-charge, nonpolarizable force fields. The further adoption of polarizable MD simulations will benefit from tutorial material that specifically addresses preparing and analyzing their unique features. In this chapter, we introduce common protocols for preparing routine biomolecular systems containing proteins, including both a globular protein in aqueous solvent and a transmembrane model peptide in a phospholipid bilayer. Details and example input files are provided for preparation of the simulation system using CHARMM, performing the simulations with OpenMM, and analyzing interesting dipole moment properties in CHARMM.

Nanocapsule designs for antimicrobial resistance

The pressing need of new antimicrobial products is growing stronger, particularly because of widespread antimicrobial resistance, endangering our ability to treat common infections. The recent coronavirus pandemic has dramatically highlighted the necessity of effective antibacterial and antiviral protection. This work explores at the molecular level the mechanism of action of antibacterial nanocapsules assembled in virus-like particles, their stability and their interaction with mammal and antimicrobial model membranes. We use Molecular Dynamics with force-fields of different granularity and protein design strategies to study the stability, self-assembly and membrane poration properties of these nanocapsules.

Molecular dynamics simulation for mechanism revelation of the safety and nutrition of lipids and derivatives in food: State of the art

Molecular dynamics (MD) simulation has proved to be a powerful tool in the study of proteins, nucleic acids, lipids, and carbohydrates et al. in fields of health, nutrition, and food science. In particular, MD simulation has been employed in the investigation of various lipid systems such as triglycerides, phospholipid membranes, etc. Due to the continuous updating of computing resources and the development of new MD simulation methods and force field parameters, the simulation's time and size scale of lipids system has increased by several orders of magnitude. However, MD simulation cannot be used for systems invovle chemical reactions. These greatly limit its further application in the field of lipid research. This paper reviews the progress and development of MD simulation, especially for the application of MD simulation in different lipid systems. In this paper, MD simulation and its general workflow was briefly introduced firstly. Subsequently, the application of MD simulation in various lipid systems was reviewed in-depth. Finally, the limitation and future prospects of MD simulation in lipid research were also discussed. This review provided new insights into the investigation of MD simulation, and a novel thought for lipid study. We believe that MD simulation will exhibit more and more great advantages in the investigation of lipids in the future due to the development of novlel methods.

Molecular Simulations Guidelines for Biological Nanomaterials: From Peptides to Membranes

In studying biological processes and focusing on the molecular mechanisms at the basis of these, molecular dynamics (MD) simulations have demonstrated to be a very useful tool for the past 50 years. This suite of computational methods calculates the time-dependent evolution of a molecular system using physics-based first principles. In this chapter, we give a brief introduction to the theory and practical use of molecular dynamics simulations, highlighting the different models and algorithms that have been developed to tackle specific problems, with a special focus on classical force fields. Some examples of how simulations have been used in the past will help the reader in discerning their power, limitations, and significance.

The transition from salt-in-water to water-in-salt nanostructures in water solutions of organic ionic liquids relevant for biological applications

Computer simulations show how nano-structural motifs in organic salts/water solutions change with salt content increasing from dilute to highly concentrated.

The effect of different cutoff schemes in molecular simulations of proteins

Molecular simulations of nanoscale systems invariably involve assumptions and approximations to describe the electrostatic interactions, which are long‐ranged in nature. One approach is the use of cutoff schemes with a reaction‐field contribution to account for the medium outside the cutoff scheme. Recent reports show that macroscopic properties may depend on the exact choice of cutoff schemes in modern day simulations. In this work, a systematic analysis of the effects of different cutoff schemes was performed using a set of 52 proteins. We find no statistically significant differences between using a twin‐range or a single‐range cutoff scheme. Applying the cutoff based on charge groups or based on atomic positions, does lead to significant differences, which is traced to the cutoff noise for energies and forces. While group‐based cutoff schemes show increased cutoff noise in the potential energy, applying an atomistic cutoff leads to artificial structure in the solvent at the cutoff distance. Carefully setting the temperature control, or using an atomistic cutoff for the solute and a group‐based cutoff for the solvent significantly reduces the effects of the cutoff noise, without introducing structure in the solvent. This study aims to deepen the understanding of the implications different cutoffs have on molecular dynamics simulations.

Nitrogen-containing naringenin derivatives for reversing multidrug resistance in cancer

Naringenin (1), isolated from Euphorbia pedroi, was previously derivatized yielding compounds 2-13. In this study, aiming at expanding the pool of analogues of the flavanone core towards better multidrug resistance (MDR) reversal agents, alkylation reactions and chemical modification of the carbonyl moiety was performed (15-39). Compounds structures were assigned mainly by 1D and 2D NMR experiments. Compounds 1-39 were assessed as MDR reversers, in human ABCB1-transfected mouse T-lymphoma cells, overexpressing P-glycoprotein (P-gp). The results revealed that O-methylation at C-7, together with the introduction of nitrogen atoms and aromatic moieties at C-4 or C-4', significantly improved the activity, being compounds 27 and 37 the strongest P-gp modulators and much more active than verapamil. In combination assays, synergistic interactions of selected compounds with doxorubicin substantiated the results. While molecular docking suggested that flavanone derivatives act as competitive modulators, molecular dynamics showed that dimethylation promotes binding to a modulator-binding site. Moreover, flavanones may also interact with a vicinal ATP-binding site in both nucleotide-binding domains, hypothesizing an allosteric mode of action.

Caught in the Act: Mechanistic Insight into Supramolecular Polymerization-Driven Self-Replication from Real-Time Visualization

Self-assembly features prominently in fields ranging from materials science to biophysical chemistry. Assembly pathways, often passing through transient intermediates, can control the outcome of assembly processes. Yet, the mechanisms of self-assembly remain largely obscure due to a lack of experimental tools for probing these pathways at the molecular level. Here, the self-assembly of self-replicators into fibers is visualized in real-time by high-speed atomic force microscopy (HS-AFM). Fiber growth requires the conversion of precursor molecules into six-membered macrocycles, which constitute the fibers. HS-AFM experiments, supported by molecular dynamics simulations, revealed that aggregates of precursor molecules accumulate at the sides of the fibers, which then diffuse to the fiber ends where growth takes place. This mechanism of precursor reservoir formation, followed by one-dimensional diffusion, which guides the precursor molecules to the sites of growth, reduces the entropic penalty associated with colocalizing precursors and growth sites and constitutes a new mechanism for supramolecular polymerization.

Emulsification of Surfactant on Oil Droplets by Molecular Dynamics Simulation

Heavy oil in crude oil flooding is extremely difficult to extract due to its high viscosity and poor fluidity. In this paper, molecular dynamics simulation was used to study the emulsification behavior of sodium dodecyl sulfonate (SDSn) micelles on heavy oil droplets composed of asphaltenes (ASP) at the molecular level. Some analyzed techniques were used including root mean square displacement, hydrophile-hydrophobic area of an oil droplet, potential of mean force, and the number of hydrogen bonds between oil droplet and water phase. The simulated results showed that the asphaltene with carboxylate groups significantly enhances the hydration layer on the surface of oil droplets, and SDSn molecules can change the strength of the hydration layer around the surface of the oil droplets. The water bridge structure between both polar heads of the surfactant was commonly formed around the hydration layer of the emulsified oil droplet. During the emulsification of heavy oil, the ratio of hydrophilic hydrophobic surface area around an oil droplet is essential. Molecular dynamics method can be considered as a helpful tool for experimental techniques at the molecular level.

Revisiting OPLS-AA Force Field for the Simulation of Anionic Surfactants in Concentrated Electrolyte Solutions

Hereby, we developed a set of nonbonded parameters within all-atom optimized potentials for liquid simulations (OPLS-AA) force field for the simulation of concentrated electrolyte solutions of anionic surfactants. More specifically, the aim of this paper is to assess the performance of five sets of atomic charges calculated using different population analyses (DDEC6, CHelpG, CHelpG-SMD, RESP, and CM5), as well as the original set of charges used in the literature for sodium dodecyl sulfate (SDS) simulation. Recently, Farafonov et al. have revised the SDS OPLS-AA force field; however, we were unable to obtain the experimental rodlike micelles using this parameter set on long time scale. In fact, the initial SDS bilayer micelle adopted a rodlike shape transiently and then broke down into spherical micelles. Updating OPLS-AA force field with DDEC6, CHelpG, and CHelpG-SMD charges resulted in stable rod micelles for a long simulation time (1 μs). The atomic charges of Farafonov (taken from Shelley et al.), RESP, and CM5 could not correctly describe SDS in concentrated electrolyte solutions. Analysis of the interaction of SDS with the counterions and solvent highlights the role of a balance of the intermolecular forces that must be met to describe adequately the anionic surfactant electrolyte solutions. Further, the optimization of the SDS Lennard-Jones parameters enabled the Farafonov set to properly reproduce the experimental rod micelle. In addition, we have examined the performance of different parameters of sodium ions: the first developed based on the Kirkwood-Buff integrals (KBI) and the second developed by Joung et al. The excessive ion pairing caused by KBI parameters screens significantly SDS-water interactions, which stabilize the rod micelle. Further, a tight interaction of the Na⁺-SDS head group resulted in stabilization of the bilayer micelle as observed in the case of Na⁺ parameters developed by Joung et al.

Pairwise-additive and polarizable atomistic force fields for molecular dynamics simulations of proteins

Protein force fields have been undergoing continual development since the first complete parameter sets were introduced nearly four decades ago. The functional forms that underlie these models have many common elements for the treatment of bonded and nonbonded forces, which are reviewed here. The most widely used force fields to date use a fixed-charge convention in which electronic polarization effects are treated via a mean-field approximation during partial charge assignment. Despite success in modeling folded proteins over many years, the fixed-charge assumption has limitations that cannot necessarily be overcome within their potential energy equations. To overcome these limitations, several force fields have recently been derived that explicitly treat electronic polarization effects with straightforward extensions of the potential energy functions used by nonpolarizable force fields. Here, we review the history of the most popular nonpolarizable force fields (AMBER, CHARMM, OPLS, and GROMOS) as well as studies that have validated them and applied them to studies of protein folding and misfolding. Building upon these force fields are more recent polarizable interaction potentials, including fluctuating charge models, POSSIM, AMOEBA, and the classical Drude oscillator. These force fields differ in their implementations but all attempt to model electronic polarization in a computationally tractable manner. Despite their recent emergence in the field of protein folding, several studies have already applied these polarizable models to challenging problems in this domain, including the role of polarization in folding free energies and sequence-specific effects on the stability of α-helical structures.

Hamiltonian Reweighing To Refine Protein Backbone Dihedral Angle Parameters in the GROMOS Force Field

Molecular dynamics simulations of proteins depend critically on the underlying force field, which may be parameterized against experimental data or high-quality quantum calculations. Here, we develop search algorithms based on Monte Carlo and steepest descent calculations to optimize the backbone dihedral angle parameters from a single reference simulation. We apply these tools to improve the agreement between simulations of single, capped amino acids and experimentally determined J values and secondary structure propensities of these molecules. The parameters are further refined based on simulations of a set of seven proteins and finally validated in simulations on a large set of 52 protein structures. Improvements in the dihedral angle distributions are observed, and structural propensities of the proteins are reproduced very well. Overall, the GROMOS 54A8_bb parameter set forms an improvement to previous parameter sets, both for small molecules and for protein simulations.

Molecular Dynamics Simulation of Proteins

Molecular dynamics simulations allow the conformational motion of a molecule such as a protein to be followed over time at atomic-level detail. Several choices need to be made prior to running a simulation, including the software, which molecules to include in the simulation, and the force field used to describe their behavior. Guidance on making these choices and other important aspects of running MD simulations is outlined here.

Peppy: A virtual reality environment for exploring the principles of polypeptide structure

A key learning outcome for undergraduate biochemistry classes is a thorough understanding of the principles of protein structure. Traditional approaches to teaching this material, which include two-dimensional (2D) images on paper, physical molecular modeling kits, and projections of 3D structures into 2D, are unable to fully capture the dynamic 3D nature of proteins. We have built a virtual reality application, Peppy, aimed at facilitating teaching of the principles of protein secondary structure. Rather than attempt to model molecules with the same fidelity to the underlying physical chemistry as existing, research-oriented molecular modelling approaches, we took the more straightforward approach of harnessing the Unity video game physics engine. Indeed, the simplicity and limitations of our model are strengths in a teaching context, provoking questions and thus deeper understanding. Peppy allows exploration of the relative effects of hydrogen bonding (and electrostatic interactions more generally), backbone φ/ψ angles, basic chemical structure, and steric effects on a polypeptide structure in an accessible format that is novel, dynamic, and fun to use. Apart from describing the implementation and use of Peppy, we discuss the outcomes of deploying Peppy in undergraduate biochemistry courses.

Lipid Head Group Parameterization for GROMOS 54A8: A Consistent Approach with Protein Force Field Description

Membranes are a crucial component of both bacterial and mammalian cells, being involved in signaling, transport, and compartmentalization. This versatility requires a variety of lipid species to tailor the membrane’s behavior as needed, increasing the complexity of the system. Molecular dynamics simulations have been successfully applied to study model membranes and their interactions with proteins, elucidating some crucial mechanisms at the atomistic detail and thus complementing experimental techniques. An accurate description of the functional interplay of the diverse membrane components crucially depends on the selected parameters that define the adopted force field. A coherent parameterization for lipids and proteins is therefore needed. In this work, we propose and validate new lipid head group parameters for the GROMOS 54A8 force field, making use of recently published parametrizations for key chemical moieties present in lipids. We make use additionally of a new canonical set of partial charges for lipids, chosen to be consistent with the parameterization of soluble molecules such as proteins. We test the derived parameters on five phosphocholine model bilayers, composed of lipid patches four times larger than the ones used in previous studies, and run 500 ns long simulations of each system. Reproduction of experimental data like area per lipid and deuterium order parameters is good and comparable with previous parameterizations, as well as the description of liquid crystal to gel-phase transition. On the other hand, the orientational behavior of the head groups is more realistic for this new parameter set, and this can be crucial in the description of interactions with other polar molecules. For that reason, we tested the interaction of the antimicrobial peptide lactoferricin with two model membranes showing that the new parameters lead to a weaker peptide–membrane binding and give a more realistic outcome in comparing binding to antimicrobial versus mammal membranes.

Free-Energy Calculations for Bioisosteric Modifications of A3 Adenosine Receptor Antagonists

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A₃ adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

Setting Up All-Atom Molecular Dynamics Simulations to Study the Interactions of Peripheral Membrane Proteins with Model Lipid Bilayers

All-atom molecular dynamics (MD) simulations enable the study of biological systems at atomic detail, complement the understanding gained from experiment, and can also motivate experimental techniques to further examine a given biological process. This method is based on statistical mechanics; it predicts the trajectory of atoms over time by solving Newton's Laws of motion taking into account all forces. Here, we describe the use of this methodology to study the interaction between peripheral membrane proteins and a lipid bilayer. Specifically, we provide step-by-step instructions to set up MD simulations to study the binding and interaction of the amphipathic helix of Osh4, a lipid transport protein, and Thanatin, an antimicrobial peptide (AMP), with model lipid bilayers using both fully detailed lipid tails and the highly mobile membrane-mimetic (HMMM) method to enhance conformational sampling.

The effect of non-thermal atmospheric plasma on the production and activity of recombinant phytase enzyme

Atmospheric pressure cold plasma (ACP) is introduced as a useful tool in a variety of biological applications. Proteins are the most abundant macromolecules in living systems with a central role in all biological processes. These organic molecules are modified by ACP exposure that is responsible for many of ACP's biological effects. This study evaluated the effect of ACP on the production of recombinant phytase in yeast Pichia pastoris (P. pastoris) as well as the structure and function of the phytase enzyme. The results indicated that yeast cells treated with ACP, directly or indirectly, produced higher amounts of recombinant phytase, which was associated with the time of ACP treatment. The exposure of commercial phytase solution with ACP caused a significant increase in the enzyme activity (125%) after 4 hours. Evaluation of the phytase solution by far- and near-UV circular dichroism (CD) and fluorescence analysis indicated that this protein maintained its secondary structure when exposed to ACP while the tertiary structure was slightly unfolded. The effects of heat and H2O2 on the phytase structure and function were compared with the effect of ACP treatment. The modification of Cys, Tyr and Trp amino acids upon reactive oxygen/nitrogen spices was simulated using a molecular dynamics approach. RMSF and RMSD analysis suggested that this structural alteration occurs owing to changes made by reactive species in accessible amino acids.

Biomolecular Simulations of Halogen Bonds with a GROMOS Force Field

Halogen bonds (XBs) are non-covalent interactions in which halogens (X), acting as electrophiles, interact with Lewis bases. XBs are able to mediate protein-ligand recognition and therefore play an important role in rational drug design. In this context, the development of molecular modeling tools that can tackle XBs is paramount. XBs are predominantly explained by the existence of a positive region on the electrostatic potential of X named the σ-hole. Typically, with molecular mechanics force fields, this region is modeled using a charged extra point (EP) linked to X along the R-X covalent bond axis. In this work, we developed the first EP-based strategy for GROMOS force fields (specifically GROMOS 54A7) using bacteriophage T4 lysozyme in complex with both iodobenzene and iodopentafluorobenzene as a prototype system. Several EP parametrization schemes were tested by adding a virtual interaction site to ligand topologies retrieved from the Automated Topology Builder (ATB) and Repository. Contrary to previous approaches using other force fields, our analysis is based on the capability of each parametrization scheme to sample XBs during MD simulations. Our results indicate that the implementation of an EP at a distance from iodine corresponding to R_min provides a good qualitative description of XBs in MD simulations, supporting the compatibility of our approach with the GROMOS 54A7 force field.

Supramolecular Nucleoside-Based Gel: Molecular Dynamics Simulation and Characterization of Its Nanoarchitecture and Self-Assembly Mechanism

Among the diversity of existing supramolecular hydrogels, nucleic acid-based hydrogels are of particular interest for potential drug delivery and tissue engineering applications because of their inherent biocompatibility. Hydrogel performance is directly related to the nanostructure and the self-assembly mechanism of the material, an aspect that is not well-understood for nucleic acid-based hydrogels in general and has not yet been explored for cytosine-based hydrogels in particular. Herein, we use a broad range of experimental characterization techniques along with molecular dynamics (MD) simulation to demonstrate the complementarity and applicability of both approaches for nucleic acid-based gelators in general and propose the self-assembly mechanism for a novel supramolecular gelator, N4-octanoyl-2'-deoxycytidine. The experimental data and the MD simulation are in complete agreement with each other and demonstrate the formation of a hydrophobic core within the fibrillar structures of these mainly water-containing materials. The characterization of the distinct duality of environments in this cytidine-based gel will form the basis for further encapsulation of both small hydrophobic drugs and biopharmaceuticals (proteins and nucleic acids) for drug delivery and tissue engineering applications.

Extension of the GROMOS 56a6CARBO/CARBO_R Force Field for Charged, Protonated, and Esterified Uronates

An extension of the GROMOS 56a6_{CARBO/CARBO_R} force field for hexopyranose-based carbohydrates is presented. The additional parameters describe the conformational properties of uronate residues. The three distinct chemical states of the carboxyl group are considered: deprotonated (negatively charged), protonated (neutral), and esterified (neutral). The parametrization procedure was based on quantum-chemical calculations, and the resulting parameters were tested in the context of (i) flexibility of the pyranose rings under different pH conditions, (ii) conformation of the glycosidic linkage of the (1 → 4)-type for uronates with different chemical states of carboxyl moieties, (iii) conformation of the exocyclic (i.e., carboxylate and lactol) moieties, and (iv) structure of the Ca²⁺-linked chain-chain complexes of uronates. The presently proposed parameters in combination with the 56a6_{CARBO/CARBO_R} set can be used to describe the naturally occurring polyuronates, composed either of homogeneous (e.g., glucuronans) or heterogeneous (e.g., pectins, alginates) segments. The results of simulations relying on the new set of parameters indicate that the conformation of glycosidic linkage is nearly unaffected by the chemical state of the carboxyl group, in contrary to the ring conformational equilibria. The calculations for the poly(α-d-galacturonate)-Ca²⁺ and poly(α-l-guluronate)-Ca²⁺ complexes show that both parallel and anitiparallel arrangements of uronate chains are possible but differ in several structural aspects.

Screening of potential lead molecules against prioritised targets of multi-drug-resistant-Acinetobacter baumannii - insights from molecular docking, molecular dynamic simulations and in vitro assays

Acinetobacter baumannii, an opportunistic pathogen, has become multi-drug resistant (MDR) to major classes of antibacterial and poses grave threat to public health. The current study focused to screen novel phytotherapeutics against prioritised targets of Acinetobacter baumannii by computational investigation. Fourteen potential drug targets were screened based on their functional role in various biosynthetic pathways and the 3D structures of 9 targets were retrieved from Protein Data Bank and others were computationally predicted. By extensive literature survey, 104 molecules from 48 herbal sources were screened and subjected to virtual screening. Ten clinical isolates of A. baumannii were tested for antibiotic susceptibility towards clinafloxacin, imipenem and polymyxin-E. Computational screening suggested that Ajmalicine ((19α)-16, 17-didehydro-19-methyloxayohimban-16-carboxylic acid methyl ester from Rauwolfia serpentina), Strictamin (Akuammilan-17-oic acid methyl ester from Alstonia scholaris) and Limonin (7, 16-dioxo-7, 16-dideoxylimondiol from Citrus sps) exhibited promising binding towards multiple drug targets of A. baumannii in comparison with the binding between standard drugs and their targets. Limonin displayed promising binding potential (binding energy -9.8 kcal/mol) towards diaminopimelate epimerase (DapF) and UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA). Ajmalicine and Strictamin demonstrated good binding potential (-9.5, -8.5 kcal/mol, respectively) towards MurA and shikimate dehydrogenase (-7.8 kcal/mol). Molecular dynamic simulations further validated the docking results. In vitro assay suggested that the tested isolates exhibited resistance to clinafloxacin, imipenem and polymyxin-E and the herbal preparations (crude extract) demonstrated a significant antibacterial potential (p ≤ .05). The study suggests that the aforementioned lead candidates and targets can be used for structure-based drug screening towards MDR A. baumannii.