CHARMM Force Field Research Articles

CHARMM-GUI Implicit Solvent Modeler for Various Generalized Born Models in Different Simulation Programs

Implicit solvent models are widely used because they are advantageous to speed up simulations by drastically decreasing the number of solvent degrees of freedom, which allows one to achieve long simulation time scales for large system sizes. CHARMM-GUI, a web-based platform, has been developed to support the setup of complex multicomponent molecular systems and prepare input files. This study describes an Implicit Solvent Modeler (ISM) in CHARMM-GUI for various generalized Born (GB) implicit solvent simulations in different molecular dynamics programs such as AMBER, CHARMM, GENESIS, NAMD, OpenMM, and Tinker. The GB models available in ISM include GB-HCT, GB-OBC, GB-neck, GBMV, and GBSW with the CHARMM and Amber force fields for protein, DNA, RNA, glycan, and ligand systems. Using the system and input files generated by ISM, implicit solvent simulations of protein, DNA, and RNA systems produce similar results for different simulation packages with the same input information. Protein-ligand systems are also considered to further validate the systems and input files generated by ISM. Simple ligand root-mean-square deviation (RMSD) and molecular mechanics generalized Born surface area (MM/GBSA) calculations show that the performance of implicit simulations is better than docking and can be used for early stage ligand screening. These reasonable results indicate that ISM is a useful and reliable tool to provide various implicit solvent simulation applications.

Parametrization of Force Field Bonded Terms under Structural Inconsistency.

Parametrization of the bonded part of molecular mechanics (MM) force fields (FFs) is typically done by fitting reference quantum mechanical (QM) energies or forces of representative structures. FFs for small molecules are constructed in incremental parametrization procedures, where parameters developed previously are retained for novel molecules, followed by optimization of missing, not previously optimized parameters. Equilibrium QM and MM geometries of molecules can deviate due to parameters transferred from existing molecules in the FF. In this work, we demonstrate that conventional parametrization methods based on fitting QM energies and/or forces to derive parameters for bond and angle terms produce largely suboptimal force constants when MM and QM equilibrium structures deviate. We further developed and tested a new method to derive CHARMM FF parameters based on the potential energy surface scans where a structural deviation between QM and MM optimized geometries is explicitly allowed during parametrization. The test of the new method was performed on a diverse set of 32 molecules. The results show that without any need for additional restraints, the new method produces robust and largely transferable parameters for bond and angle terms. The new method also improves the agreement for the normal modes for all molecules in the test set, reducing the average error in the reproduction of QM normal mode frequencies from 9.5% computed with CGenFF parameters to 6.8% computed with the new parameters. The new method will allow parametrization of molecules under structural deviations, common for force fields for small molecules, producing robust and transferable parameters.

SP-A binding to the SARS-CoV-2 spike protein using hybrid quantum and classical in silico modeling and molecular pruning by Quantum Approximate Optimization Algorithm (QAOA) Based MaxCut with ZDOCK.

The pulmonary surfactant protein A (SP-A) is a constitutively expressed immune-protective collagenous lectin (collectin) in the lung. It binds to the cell membrane of immune cells and opsonizes infectious agents such as bacteria, fungi, and viruses through glycoprotein binding. SARS-CoV-2 enters airway epithelial cells by ligating the Angiotensin Converting Enzyme 2 (ACE2) receptor on the cell surface using its Spike glycoprotein (S protein). We hypothesized that SP-A binds to the SARS-CoV-2 S protein and this binding interferes with ACE2 ligation. To study this hypothesis, we used a hybrid quantum and classical in silico modeling technique that utilized protein graph pruning. This graph pruning technique determines the best binding sites between amino acid chains by utilizing the Quantum Approximate Optimization Algorithm (QAOA)-based MaxCut (QAOA-MaxCut) program on a Near Intermediate Scale Quantum (NISQ) device. In this, the angles between every neighboring three atoms were Fourier-transformed into microwave frequencies and sent to a quantum chip that identified the chemically irrelevant atoms to eliminate based on their chemical topology. We confirmed that the remaining residues contained all the potential binding sites in the molecules by the Universal Protein Resource (UniProt) database. QAOA-MaxCut was compared with GROMACS with T-REMD using AMBER, OPLS, and CHARMM force fields to determine the differences in preparing a protein structure docking, as well as with Goemans-Williamson, the best classical algorithm for MaxCut. The relative binding affinity of potential interactions between the pruned protein chain residues of SP-A and SARS-CoV-2 S proteins was assessed by the ZDOCK program. Our data indicate that SP-A could ligate the S protein with a similar affinity to the ACE2-Spike binding. Interestingly, however, the results suggest that the most tightly-bound SP-A binding site is localized to the S2 chain, in the fusion region of the SARS-CoV-2 S protein, that is responsible for cell entry Based on these findings we speculate that SP-A may not directly compete with ACE2 for the binding site on the S protein, but interferes with viral entry to the cell by hindering necessary conformational changes or the fusion process.

L-DOPA and Droxidopa: From Force Field Development to Molecular Docking into Human β2-Adrenergic Receptor.

The increasing interest in the molecular mechanism of the binding of different agonists and antagonists to 2-adrenergic receptor (2AR) inactive and active states has led us to investigate protein–ligand interactions using molecular docking calculations. To perform this study, the 3.2 Å X-ray crystal structure of the active conformation of human 2AR in the complex with the endogenous agonist adrenaline has been used as a template for investigating the binding of two exogenous catecholamines to this adrenergic receptor. Here, we show the derivation of L-DOPA and Droxidopa OPLS all atom (AA) force field (FF) parameters via quantum mechanical (QM) calculations, molecular dynamics (MD) simulations in aqueous solutions of the two catecholamines and the molecular docking of both ligands into rigid and flexible 2AR models. We observe that both ligands share with adrenaline similar experimentally observed binding anchor sites, which are constituted by Asp113/Asn312 and Ser203/Ser204/Ser207 side chains. Moreover, both L-DOPA and Droxidopa molecules exhibit binding affinities comparable to that predicted for adrenaline, which is in good agreement with previous experimental and computational results. L-DOPA and Droxidopa OPLS AA FFs have also been tested by performing MD simulations of these ligands docked into 2AR proteins embedded in lipid membranes. Both hydrogen bonds and hydrophobic interaction networks observed over the 1 s MD simulation are comparable with those derived from molecular docking calculations and MD simulations performed with the CHARMM FF.

Intermolecular Interactions of Nucleoside Antibiotic Tunicamycin with On-Target MraYCB-TUN and Off-Target DPAGT1-TUN in the Active Sites Delineated by Quantum Mechanics/Molecular Mechanics Calculations.

Tunicamycin (TUN) is a nucleoside antibiotic with a complex structure comprising uracil, tunicamine sugar, N-acetylglucosamine (GlcNAc), and fatty acyl tail moieties. TUN, known as a canonical inhibitor, blocks vital functions of certain transmembrane protein families, for example, the insect enzyme dolichyl phosphate α-N-acetylglucosaminylphosphotransferase (DPAGT1) of Spodoptera frugiperda and the bacterial enzyme phospho-N-acetylmuramoylpentapeptide translocase (MraYCB) of Clostridium bolteae. Accurate description of protein–drug interactions has an immense impact on structure-based drug design, while the main challenge is to create proper topology and parameter entries for TUN in modeling protein–TUN interactions given the structural complexity. Starting from DPAGT1–TUN and MraYCB–TUN crystal structures, we first sketched these structural complexes on the basis of the CHARMM36 force field and optimized each of them using quantum mechanics/molecular mechanics (QM/MM) calculations. By continuing calculations on the active site (QM region) of each optimized structure, we specified the characteristics of intermolecular interactions contributing to the binding of TUN to each active site by quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) analyses at the M06-2X/6-31G** level. The results outlined that TUN insertion into each active site requires multiple weak, moderate, and strong hydrogen bonds accompanying charge–dipole, dipole–dipole, and hydrophobic interactions among different TUN moieties and adjacent residues. The water-mediated interactions also play central roles in situating the uracil and tunicamine moieties of TUN within the DPAGT1 active site as well as in preserving the uracil-binding pocket in the MraYCB active site. The TUN binds more strongly to DPAGT1 than to MraYCB. The information garnered here is valuable particularly for better understanding mode of action at the molecular level, as it is conducive to developing next generations of nucleoside antibiotics.

Force-Field-Dependent DNA Breathing Dynamics: A Case Study of Hoogsteen Base Pairing in A6-DNA.

The Hoogsteen (HG) base pairing conformation, commonly observed in damaged and mutated DNA helices, facilitates DNA repair and DNA recognition. The free energy difference between HG and Watson-Crick (WC) base pairs has been computed in previous studies. However, the mechanism of the conformational transition is not well understood. A detailed understanding of the process of WC to HG base pair transition can provide a deeper understanding of DNA repair and recognition. In an earlier study, we explored the free energy landscape for this process using extensive computer simulation with the CHARMM36 force field. In this work, we study the impact of force field models in describing the WC to HG base pairing transition using meta-eABF enhanced sampling, quasi-harmonic entropy calculation, and nonbonded energy analysis. The secondary structures of both base pairing forms and the topology of the free energy landscapes were consistent over different force field models, although the relative free energy, entropy, and the interaction energies tend to vary. The relative stability of the WC and HG conformations is dictated by a delicate balance between the enthalpic stabilization and the reduced entropy of the structurally rigid HG structure. These findings highlight the impact that subtleties in force field models can have on accurately modeling DNA base pair dynamics and should stimulate further computational investigations into other dynamically important motions in DNA.

Structure of POPC Lipid Bilayers in OPLS3e Force Field.

It is crucial for molecular dynamics simulations of biomembranes that the force field parameters give a realistic model of the membrane behavior. In this study, we examined the OPLS3e force field for the carbon-hydrogen order parameters SCH of POPC (1-palmitoyl-2-oleoylphosphatidylcholine) lipid bilayers at varying hydration conditions and ion concentrations. The results show that OPLS3e behaves similarly to the CHARMM36 force field and relatively accurately follows the experimentally measured SCH for the lipid headgroup, the glycerol backbone, and the acyl tails. Thus, OPLS3e is a good choice for POPC bilayer simulations under many biologically relevant conditions. The exception are systems with an abundancy of ions, as similarly to most other force fields OPLS3e strongly overestimates the membrane-binding of cations, especially Ca2+. This leads to undesirable positive charge of the membrane surface and drastically lowers the concentration of Ca2+ in the surrounding solvent, which might cause issues in systems sensitive to correct charge distribution profiles across the membrane.

Molecular Simulations of Thermomechanical Properties of Epoxy-Amine Resins.

All-atom molecular dynamics (MD) simulations were performed with the CHARMM force field to characterize various epoxy resins, such as aliphatic and bisphenol-based resins. A multistep cross-linking algorithm was established, and key properties such as density, glass temperature, and elastic modulus were calculated. A quantitative comparison was made and was proven to be in good agreement with experimental data, with average absolute deviations between experiments and molecular simulation comprised between 2% and 12%. Additional findings on structure–property relationships were highlighted such as the effect of the cross-linking rate and oligomerization of the resin.

Accurate Description of Solvent-Exposed Salt Bridges with a Non-polarizable Force Field Incorporating Solvent Effects.

The strength of salt bridges resulting from the interaction of cations and anions is modulated by their environment. However, polarization of the solvent molecules by the charged moieties makes the accurate description of cation-anion interactions in an aqueous solution by means of a pairwise additive potential energy function and classical combination rules particularly challenging. In this contribution, aiming at improving the representation of solvent-exposed salt-bridge interactions with an all-atom non-polarizable force field, we put forth here a parametrization strategy. First, the interaction of a cation and an anion is characterized by hybrid quantum mechanical/molecular mechanics (QM/MM) potential of mean force (PMF) calculations, whereby constantly exchanging solvent molecules around the ions are treated at the quantum mechanical level. The Lennard-Jones (LJ) parameters describing the salt-bridge ion pairs are then optimized to match the reference QM/MM PMFs through the so-called nonbonded FIX, or NBFIX, feature of the CHARMM force field. We apply the new set of parameters, coined CHARMM36m-SBFIX, to the calculation of association constants for the ammonium-acetate and guanidinium-acetate complexes, the osmotic pressures for glycine zwitterions, guanidinium, and acetate ions, and to the simulation of both folded and intrinsically disordered proteins. Our findings indicate that CHARMM36m-SBFIX improves the description of solvent-exposed salt-bridge interactions, both structurally and thermodynamically. However, application of this force field to the standard binding free-energy calculation of a protein-ligand complex featuring solvent-excluded salt-bridge interactions leads to a poor reproduction of the experimental value, suggesting that the parameters optimized in an aqueous solution cannot be readily transferred to describe solvent-excluded salt-bridge interactions. Put together, owing to their sensitivity to the environment, modeling salt-bridge interactions by means of a single, universal set of LJ parameters remains a daunting theoretical challenge.

Dynamics of Topology-dependent Water Purification by Siliceous Zeolite Membranes

• Simulated the effect of topology and pore size of zeolites on water purification. • Compared porous LTA, FAU, and MFI zeolites in purification of Cl - , Pb 2+ , and Co 2+ . • Tersoff and Lennard-Jones hybrid force fields, and TIP3P water models were used. • Applying PMF in MD simulation, the efficiency of zeolite membranes was conceptualized. • Applying a long time of 15 ns, heavy metal ions behaved differently in rejection. The efficiency of pollutant rejection (PR, %) and water purification of the zeolite membranes is highly dependent on their topology, i.e., porosity and chemical composition. Nevertheless, mechanisms controlling such a physicochemical phenomenon have been limitedly discussed. Herein, we provide insights into the physics and dynamics of water purification by zeolite nanosheets in terms of topological variables. The molecular dynamics (MD) simulation pictured the molecular-lever water purification having heavy metal ions (Co 2+ and Pb 2+ ) as typical water contaminants. Three siliceous zeolites having different topologies, i.e., LTA, FAU, and MFI zeolites, were positioned in the simulation space. MD simulation was served under pressure and temperature of 24 MPa and 300 K, respectively, applying the Canonical ensemble (NVT) condition. The intermolecular interactions between contaminant ions, zeolite, and graphene were tracked by hybridizing Tersoff and Lenard-Jones potentials, while the TIP3P model of the CHARMM force field was used to simulate water dynamics. The LAMMPS software and Visual Molecular Dynamics (VMD) were used to collect data and graphics over 15 ns, with early 5 ns devoted to reaching equilibrium. Interestingly, we demonstrated by the aid of potential of the mean force (PMF) pollutant ions which encounter the zeolite pores smaller than their kinetic diameter consume more energy for permeation across the membrane, -reason why LTA appeared selective against Pb 2+ , Co 2+ , and Cl - ions, with PR of 40, 60, and 100%, respectively. The absolute water flux values were monitored, and LTA and FAU fluxes were ∼ 50% higher than MFI zeolite, but 5 ns after equilibrium, LTA flux was overtaken sharply by the simulation because of the larger pore size. Overall, the electrostatic forces showed absolute control over the purification but were governed by the zeolite topology.

Benchmarking Adaptive Steered Molecular Dynamics (ASMD) on CHARMM Force Fields.

The potentials of mean force (PMFs) along the end‐to‐end distance of two different helical peptides have been obtained and benchmarked using the adaptive steered molecular dynamics (ASMD) method. The results depend strongly on the choice of force field driving the underlying all‐atom molecular dynamics, and are reported with respect to the three most popular CHARMM force field versions: c22, c27 and c36. Two small peptides, ALA10 and 1PEF, serve as the particular case studies. The comparisons between the versions of the CHARMM force fields provides both a qualitative and quantitative look at their performance in forced unfolding simulations in which peptides undergo large changes in structural conformations. We find that ASMD with the underlying c36 force field provides the most robust results for the selected benchmark peptides.

Protein-Nucleic Acid Interactions for RNA Polymerase II Elongation Factors by Molecular Dynamics Simulations.

RNA polymerase II (Pol II) forms a complex with elongation factors to proceed to the elongation stage of the transcription process. In this work, we studied the elongation factor SPT5 and explored the protein-nucleic acid interactions for the isolated systems of KOW1 and KOW4 domains of SPT5 with DNA and RNA, respectively. We performed molecular dynamics (MD) simulations using three commonly used force fields that are CHARMM c36m, AMBER ff14sb, and ff19sb. Simulations showed strong protein-nucleic acid interactions and low electrostatic binding free energies for all force fields used. RNA was found to be highly dynamic with all force fields, while DNA had relatively more stable conformations with the AMBER force fields compared to that with CHARMM. Furthermore, we performed MD simulations of the complete elongation complex using CHARMM c36m and AMBER ff19sb force fields to compare the dynamics and interactions with the isolated systems. Similarly, strong KOW1 and DNA interactions were observed in the complete elongation complex simulations and DNA was further stabilized by a network of interactions involving SPT5-KOW1, SPT4, and rpb2 of Pol II. Overall, our study showed that the differences between CHARMM and AMBER force fields strongly affect the dynamics of the nucleic acids. CHARMM provides highly flexible DNA, while AMBER largely stabilizes the DNA structure. Although the presence of the entire interaction network stabilized the DNA and decreased the differences in the results from the two force fields, the discrepancies of the force fields for smaller systems may reflect their problems in generating accurate dynamics of nucleic acids.

Multiscale Simulation of Ternary Stratum Corneum Lipid Mixtures: Effects of Cholesterol Composition.

Molecular dynamics simulations of mixtures of the ceramide nonhydroxy-sphingosine (NS), cholesterol, and a free fatty acid are performed to gain molecular-level understanding of the structure of the lipids found in the stratum corneum layer of skin. A new coarse-grained force field for cholesterol was developed using the multistate iterative Boltzmann inversion (MS-IBI) method. The coarse-grained cholesterol force field is compatible with previously developed coarse-grained force fields for ceramide NS, free fatty acids, and water and validated against atomistic simulations of these lipids using the CHARMM force field. Self-assembly simulations of multilayer structures using these coarse-grained force fields are performed, revealing that a large fraction of the ceramides adopt extended conformations, which cannot occur in the single bilayer in water structures typically studied using molecular simulation. Cholesterol fluidizes the membrane by promoting packing defects, and an increase in cholesterol content is found to reduce the bilayer thickness due to an increase in interdigitation of the C24 lipid tails, consistent with experimental observations. Using a reverse-mapping procedure, a self-assembled coarse-grained multilayer system is used to construct an equivalent structure with atomistic resolution. Simulations of this atomistic structure are found to closely agree with experimentally derived neutron scattering length density profiles. Significant interlayer hydrogen bonding is observed in the inner layers of the atomistic multilayer structure that are not found in the outer layers in contact with water or in equivalent bilayer structures. This work highlights the importance of simulating multilayer structures, as compared to the more commonly studied bilayer systems, to enable more appropriate comparisons with multilayer experimental membranes. These results also provide validation of the efficacy of the MS-IBI derived coarse-grained force fields and the framework for multiscale simulation.

A New Variant of Mutational and Polymorphic Signatures in the ERG11 Gene of Fluconazole-Resistant Candida albicans.

BackgroundResistance to antifungal drugs for treating Candida infections remains a major concern globally despite the range of medications available. Most of these drugs target key proteins essential to the life cycle of the organism. An enzyme essential for fungal cell membrane integrity, lanosterol 14–α demethylase (CYP51), is encoded by the ERG11 gene in Candida species. This enzyme is the target of azole–based drugs. The organism has, however, devised molecular adaptations to evade the activity of these drugs.Materials and MethodsClassical methods were employed to characterize clinical isolates sampled from women and dogs of reproductive age. For fluconazole efficacy studies, CLSI guidelines on drug susceptibility testing were used. To understand the susceptibility pattern, various molecular and structural analytic approaches, including sequencing, in silico site-directed mutagenesis, and protein-ligand profiling, were applied to the ERG11 gene and CYP51 protein sequences. Several platforms, comprising Clustal Omega, Pymol plugin manager, Pymol molecular visualizer, Chimera–curated Dynameomics rotamer library, protein–ligand interaction profiler, Charmm36 force field, GROMACS, Geneious, and Mega7, were employed for this analysis.ResultsThe following Candida species distribution was obtained: 37.84% C. albicans, 8.12% C. glabrata, 10.81% C. krusei, 5.41% C. tropicalis, and 37.84% of other unidentified Candida species. Two codons in the nucleotide sequence of the wild-type (CTC and CCA) coding for LEU–370 and PRO–375, respectively, were mutated to L370S and P375H in the resistant strain. The mutation stabilized the protein at the expense of the heme moiety. We found that the susceptible isolate from dogs (Can–iso–029/dog) is closely related to the most resistant isolate from humans.ConclusionTaken together, our results showed new mutations in the heme-binding pocket of caCYP51 that explain the resistance to fluconazole exhibited by the Candida isolates. So far, the L370S and P375H resistance-linked mutations have not been previously reported.

Constructing conformational library for amyloid-β42 dimers as the smallest toxic oligomers using two CHARMM force fields

The study of amyloid-β (Aβ) dimers as the smallest toxic aggregates in the human brain suffering from Alzheimer's disease is of great interest. The structural characterization of the dimers, which is important to rationally design inhibitors for Aβ dimerization, is limited by the low stability of these species and their high tendency to aggregate into protofibrils and amyloid fibrils. Therefore, an efficient sampling method is needed for the computational study of the Aβ dimers. In this regard, we build a conformational library of the Aβ42 dimers by a new computational protocol; the blockwise excursion sampling (BES); with the CHARMM27 and CHARMM36m force fields. The CHARMM27 overestimates helix content and underestimates β-sheet content, while secondary structure content for the dimers sampled by the CHARMM36m force field is in reasonably consistent with the circular dichroism data. The CHARMM36m force field also generates more Aβ42 dimers in line with experimentally measured collision cross sections values relative to the CHARMM27 force field. Our results demonstrate that the BES is an efficient protocol for fast generating a heterogeneous conformational library of the Aβ42 dimers in agreement with experimental data. Having a reliable structural library for the Aβ42 dimers is very important to identify binding “hot spots” of the dimers versus potential drug candidates using ensemble docking approach.

Computational prediction of potential inhibitors for SARS-COV-2 main protease based on machine learning, docking, MM-PBSA calculations, and metadynamics.

The development of new drugs is a very complex and time-consuming process, and for this reason, researchers have been resorting heavily to drug repurposing techniques as an alternative for the treatment of various diseases. This approach is especially interesting when it comes to emerging diseases with high rates of infection, because the lack of a quickly cure brings many human losses until the mitigation of the epidemic, as is the case of COVID-19. In this work, we combine an in-house developed machine learning strategy with docking, MM-PBSA calculations, and metadynamics to detect potential inhibitors for SARS-COV-2 main protease among FDA approved compounds. To assess the ability of our machine learning strategy to retrieve potential compounds we calculated the Enrichment Factor of compound datasets for three well known protein targets: HIV-1 reverse transcriptase (PDB 4B3P), 5-HT2A serotonin receptor (PDB 6A94), and H1 histamine receptor (PDB 3RZE). The Enrichment Factor for each target was, respectively, 102.5, 12.4, 10.6, which are considered significant values. Regarding the identification of molecules that can potentially inhibit the main protease of SARS-COV-2, compounds output by the machine learning step went through a docking experiment against SARS-COV-2 Mpro. The best scored poses were the input for MM-PBSA calculations and metadynamics using CHARMM and AMBER force fields to predict the binding energy for each complex. Our work points out six molecules, highlighting the strong interaction obtained for Mpro-mirabegron complex. Among these six, to the best of our knowledge, ambenonium has not yet been described in the literature as a candidate inhibitor for the SARS-COV-2 main protease in its active pocket.

Molecular Dynamics-Assisted Optimization of Protein NMR Relaxation Analysis.

NMR relaxation analysis of the mobile residues in globular proteins is sensitive to the form of the experimentally fitted internal autocorrelation function, which is used to represent that motion. Different order parameter representations can precisely fit the same set of 15N R1, R2, and heteronuclear NOE measurements while yielding significantly divergent predictions of the underlying autocorrelation functions, indicating the insufficiency of these experimental relaxation data for assessing which order parameter representation provides the most physically realistic predictions. Molecular dynamics simulations offer an unparalleled capability for discriminating among different order parameter representations to assess which representation can most accurately model a wide range of physically realistic autocorrelation functions. Six currently utilized AMBER and CHARMM force fields were applied to calculate autocorrelation functions for the backbone H–N bond vectors of ubiquitin as an operational test set. An optimized time constant-constrained triexponential (TCCT) representation was shown to markedly outperform the widely used (Sf2,τs,S2) extended Lipari–Szabo representation and the more closely related (Sf2,SH2, SN2) Larmor frequency-selective representation. Optimization of the TCCT representation at both 600 and 900 MHz 1H converged to the same parameterization. The higher magnetic field yielded systematically larger deviations in the back-prediction of the autocorrelation functions for the mobile amides, indicating little added benefit from multiple field measurements in analyzing amides that lack slower (∼ms) exchange line-broadening effects. Experimental 15N relaxation data efficiently distinguished among the different force fields with regard to their prediction of ubiquitin backbone conformational dynamics in the ps–ns time frame. While the earlier AMBER 99SB and CHARMM27 force fields underestimate the scale of backbone dynamics, which occur in this time frame, AMBER 14SB provided the most consistent predictions for the well-averaged highly mobile C-terminal residues of ubiquitin.

Electronic Polarization Is Essential for the Stabilization and Dynamics of Buried Ion Pairs in Staphylococcal Nuclease Mutants.

Buried charged residues play important roles in the modulation of protein stabilities and conformational dynamics and make crucial contributions to protein functions. Considering the generally nonpolar nature of protein interior, a key question concerns the contribution of electronic polarization to the stabilization and properties of buried charges. We answer this question by conducting free energy simulations using the latest polarizable CHARMM force field based on Drude oscillators for a series of Staphylococcal nuclease mutants that involve a buried Glu-Lys pair in different titration states and orientations. While a nonpolarizable model suggests that the ionized form of the buried Glu-Lys pair is more than 40 kcal/mol less stable than the charge-neutral form, the two titration states are comparable in stability when electronic polarization is included explicitly, a result better reconcilable with available experimental data. Analysis of free energy components suggests that additional stabilization of the ionized Glu-Lys pair has contributions from both the enhanced salt-bridge strength and stronger interaction between the ion-pair and surrounding protein residues and penetrated water. Despite the stronger direct interaction between Glu and Lys, the ion-pair exhibits considerably larger and faster structural fluctuations when polarization is included, due to compensation of interactions in the cavity. Collectively, observations from this work provide compelling evidence that electronic polarization is essential to the stability, hydration, dynamics, and therefore function of buried charges in proteins. Therefore, our study advocates for the explicit consideration of electronic polarization for mechanistic and engineering studies that implicate buried charged residues, such as enzymes and ion transporters.

Anti-enteric efficacy and mode of action of tridecanoic acid methyl ester isolated from Monochoria hastata (L.) Solms leaf.

Monochoria hastata (L.) Solms (family Pontederiaceae), an ethnomedicinal aquatic herb, is used to remedy several gastrointestinal diseases by various ethnic groups in India. The present study aimed to purify and characterize the antibacterial active ingredient against gastrointestinal (GI) diseases and its mode of action using in vitro experimental models. The active lead molecule in the ethyl acetate extract (EA-Mh) fraction has been purified and characterized through high-performance liquid chromatography (HPLC), proton nuclear magnetic resonance (1H NMR), and electrospray ionization mass spectrometry (ESI-MS) methods. The anti-enteric efficacy has been evaluated against enteropathogenic Gram-positive and Gram-negative bacteria by minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), lactate dehydrogenase (LDH), and scanning electron microscopy (SEM) studies. The synergistic and antagonistic studies were done on E. coli MTCC 723 using standard antibiotics (ampicillin and kanamycin, final conc. 50µg/ml) in a sterilized 96-well micro-plate, incubated at 37 ℃ for 24h. The chromatographic and spectroscopic analyses revealed the presence of tridecanoic acid methyl ester (TAME) in the bioactive fraction. The compound causes significant extracellular leakage activity by disrupting cellular morphology in the Enterococcus faecalis MCC 2041T and Salmonella enterica serovar Typhimurium MTCC 98, at a dose of 375μg/ml and 750μg/ml, respectively. The SEM study shows a significant rupturing of E. coli and E. faecalis cells due to TAME induced autolysis. It has synergistic activity with ampicillin. The in silico molecular docking through the AutoDock Vina 4.2 and GROMACS (ver. 5.1) Charmm27 force field results showed that the TAME had a strong binding affinity Escherichia coli DNA Gyrase B (PDB ID: 5l3j.pdb) protein and caused conformational changes. Thus, the manuscript reports the first time on the characterization of TAME from this plant with a detailed antibacterial mode of action studies.

CHARMM-GUI multicomponent assembler for modeling and simulation of complex multicomponent systems

CHARMM-GUI Multicomponent Assembler (MCA) provides a user-friendly web-interface for creating all-atom molecular dynamics simulation systems of any components described by the CHARMM force field. In combination with other CHARMM-GUI modules, it can create complex molecular systems composed of mixtures of biomacromolecules, polymers, nanoparticles, and small molecules. MCA's system building procedure considers periodicity of the whole system and of individual periodic components, allowing the solvation of proteins and other molecules with pre-equilibrated membranes and sheet-like polymers and nanomaterials.