Validation of the 53A6 GROMOS force field

Kernel-Based Minimal Distributed Charges: A Conformationally Dependent ESP-Model for Molecular Simulations

A kernel-based method (kernelized minimal distributed charge model (kMDCM)) to represent the molecular electrostatic potential (ESP) in terms of off-center point charges is introduced. The positions of the charges adapt to the molecular geometry and allow the description of intramolecular charge flow. Using Gaussian kernels and atom-atom distances as the features, the ESPs for water and methanol are shown to improve by at least a factor of 2 compared with point charge models fit to an ensemble of structures. The conformationally fluctuating molecular dipole moment of water is reproduced almost twice as accurately using kMDCM compared with static PCs, despite not fitting to the dipole directly. The role of hyperparameters in the kernelization is investigated and their implication on model performance and simulation stability is discussed. Combining kMDCM for the electrostatics and reproducing kernels for the bonded terms allows energy-conserving simulations of 2000 water molecules with periodic boundary conditions on the nanosecond time scale. These MD simulations sample geometries outside the training set but remain stable, which demonstrates the robustness of the model and its implementation.

Adjusting the Energy Profile for CH-O Interactions Leads to Improved Stability of RNA Stem-Loop Structures in MD Simulations

The role of ribonucleic acid (RNA) in biology continues to grow, but insight into important aspects of RNA behavior is lacking, such as dynamic structural ensembles in different environments, how flexibility is coupled to function, and how function might be modulated by small molecule binding. In the case of proteins, much progress in these areas has been made by complementing experiments with atomistic simulations, but RNA simulation methods and force fields are less mature. It remains challenging to generate stable RNA simulations, even for small systems where well-defined, thermostable structures have been established by experiments. Many different aspects of RNA energetics have been adjusted in force fields, seeking improvements that are transferable across a variety of RNA structural motifs. In this work, the role of weak CH···O interactions is explored, which are ubiquitous in RNA structure but have received less attention in RNA force field development. By comparing data extracted from high-resolution RNA crystal structures to energy profiles from quantum mechanics and force field calculations, it is shown that CH···O interactions are overly repulsive in the widely used Amber RNA force fields. A simple, targeted adjustment of CH···O repulsion that leaves the remainder of the force field unchanged was developed. Then, the standard and modified force fields were tested using molecular dynamics (MD) simulations with explicit water and salt, amassing over 300 μs of data for multiple RNA systems containing important features such as the presence of loops, base stacking interactions as well as canonical and noncanonical base pairing. In this work and others, standard force fields lead to reproducible unfolding of the NMR-based structures. Including a targeted CH···O adjustment in an otherwise identical protocol dramatically improves the outcome, leading to stable simulations for all RNA systems tested.

Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment

Ribonucleic acid (RNA) molecules can adopt a variety of secondary and tertiary structures in solution, with stem-loops being one of the more common motifs. Here, we present a systematic analysis of 15 RNA stem-loop sequences simulated with molecular dynamics simulations in an implicit solvent environment. Analysis of RNA cluster ensembles showed that the stem-loop structures can generally adopt the A-form RNA in the stem region. Loop structures are more sensitive, and experimental structures could only be reproduced with modification of CH···O interactions in the force field, combined with an implicit solvent nonpolar correction to better model base stacking interactions. Accurately modeling RNA with current atomistic physics-based models remains challenging, but the RNA systems studied herein may provide a useful benchmark set for testing other RNA modeling methods in the future.

Getting the intermolecular forces correct: introducing the ASTA strategy for a water model

Having a force field for water providing good bulk properties is paramount for modern studies of most biological systems. Some of the most common three-site force fields are TIP3, SPC/ε or OPC3, providing a decent range of bulk properties. That does not mean though, that they have realistic inter-atomic forces. These force fields have been parameterized with a top-down approach, meaning, by fitting the force field parameters to the experimental bulk properties. This approach has been the governing strategy also for many variants of four- and more-site models. We test a bottom-up approach, in which the force field is parameterized by optimizing the non-bonded inter-atomic forces. Our philosophy is that correct inter-atomic forces lead to correct geometrical and dynamical properties. The first system we try to optimize with the accurately system tailored atomic (ASTA) approach is water, but we aim to eventually probe other systems in the future as well. We applied our ASTA strategy to find a good set of parameters providing accurate bulk properties for the simple three-site force field forms, and also for AMOEBA, a more detailed and polarizable force field. Even though our bottom-up approach did not provide satisfactory results for the simple three-site force fields (with fixed charges), for the case of the AMOEBA force field it led to a modification of the original strategy, giving very good intra- and inter-molecular forces, as compared to accurate quantum chemically calculated reference forces. At the same time, important bulk properties, in this study restricted to the density and diffusion, were accurately reproduced with respect to the experimental values.

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.

One Descriptor to Fold Them All: Harnessing Intuition and Machine Learning to Identify Transferable Lasso Peptide Reaction Coordinates

Identifying optimal reaction coordinates for complex conformational changes and protein folding remains an outstanding challenge. This study combines collective variable (CV) discovery based on chemical intuition and machine learning with enhanced sampling to converge the folding free energy landscape of lasso peptides, a unique class of natural products with knot-like tertiary structures. This knotted scaffold imparts remarkable stability, making lasso peptides resistant to proteolytic degradation, thermal denaturation, and extreme pH conditions. Although their direct synthesis would enable therapeutic design, it has not yet been possible due to the improbable occurrence of spontaneous lasso folding. Thus, simulations characterizing the folding propensity are needed to identify strategies for increasing access to the lasso architecture by stabilizing the pre-lasso ensemble before isopeptide bond formation. Herein, harmonic linear discriminant analysis (HLDA) is combined with metadynamics-enhanced sampling to discover CVs capable of distinguishing the pre-lasso fold and converging the folding propensity. Intuitive CVs are compared to iterative rounds of HLDA to identify CVs that not only accomplish these goals for one lasso peptide but also seem to be transferable to others, establishing a protocol for the identification of folding reaction coordinates for lasso peptides.

Effectiveness of a formulation based on Ocimum gratissimum essential oil and cashew gum as inhibitors of quality loss and melanosis in shrimp

In this study, two nanoemulsions were formulated with essential oil (EO) of Ocimum gratissimum with (EON) or without (EOE) cashew gum (CG). Subsequently, inhibition of melanosis and preservation of the quality of shrimp stored for 16 days at 4 ± 0.5 °C were evaluated. A computational approach was performed to predict the system interactions. Dynamic light scattering (DLS) and atomic force microscopy (AFM) were used for nanoparticle analysis. Gas chromatography and flame ionization detector (GC-FID) determined the chemical composition of the EO constituents. Shrimps were evaluated according to melanosis's appearance, psychrotrophic bacteria's count, pH, total volatile basic nitrogen, and thiobarbituric acid reactive substances. EON exhibited a particle size three times smaller than EOE. The shrimp treated with EON showed a more pronounced sensory inhibition of melanosis, which was considered mild by the 16th day. Meanwhile, in the other groups, melanosis was moderate (EOE) or severe (untreated group). Both EON and EOE treatments exhibited inhibition of psychrotrophic bacteria and demonstrated the potential to prevent lipid oxidation, thus extending the shelf life compared to untreated fresh shrimp. EON with cashew gum, seems more promising due to its physicochemical characteristics and superior sensory performance in inhibiting melanosis during shrimp preservation.

Hit discovery of potential CDK8 inhibitors and analysis of amino acid mutations for cancer therapy through computer-aided drug discovery

Cyclin-dependent kinase 8 (CDK8) has emerged as a promising target for inhibiting cancer cell function, intensifying efforts towards the development of CDK8 inhibitors as potential cancer therapeutics. Mutations in CDK8, a protein kinase, are also implicated as a primary factor associated with tumor formation. In this study, we identified potential inhibitors through virtual screening for CDK8 and single amino acid mutations in CDK8, namely D173A (Aspartate 173 mutate to Alanine), D189N (Aspartate 189 mutate to Asparagine), T196A (Threonine 196 mutate to Alanine) and T196D (Threonine 196 mutate to Aspartate). Four databases (CHEMBEL, ZINC, MCULE, and MolPort) containing 65,209,131 molecules have been searched to identify new inhibitors for CDK8 and its single mutations. In the first step, structure-based pharmacophore modeling in the Pharmit server was used to select the compounds to know the inhibitors. Then molecules with better predicted drug-like molecule properties were selected. The final filter used to select more effective inhibitors among the previously selected molecules was molecular docking. Finally, 13 hits for CDK8, 11 hits for D173A, 11 hits for D189N, 15 hits for T196A, and 12 hits for T196D were considered potential inhibitors. A majority of the virtual screening hits exhibited satisfactorily predict pharmacokinetic characteristics and toxicity properties.

Deciphering the structure of a distinctive trimodular cellulosomal licheninase (RfGH16_21), a family 16 glycoside hydrolase from Ruminococcus flavefaciens by computational and experimental methods

In order to know the insights of a unique naturally existing trimodular licheninase from GH16 family, sub-family 21 (RfGH16_21) from Ruminococcus flavefaciens, its structure was modeled to understand its functional relations to reveal information regarding modifying the enzyme for improved properties with enhanced catalytic efficiency. Homology modeling revealed three tandem repeats of β-jelly roll like folds linked by natural linkers. Catalytic pockets and the catalytically important amino acids in each tandem repeat of RfGH16_21 determined by multiple sequence alignment and structure superposition with its homologues indicated that two Glu residues are involved in a retaining-type of catalytic mechanism. Sequential molecular docking revealed maximum binding energy with mixed linked cellotriose showing that cellotriose is the lowest oligomeric hydrolysed product formed by the catalytic action of endo-β-1,3-1,4-glucanase. Molecular dynamic (MD) simulation of RfGH16_21-cellotriose complex confirmed the structural specificity of catalytic residues and increased stability of enzyme in presence of ligand as compared to simulated RfGH16_21 alone. The binding affinity of cellotriose towards the three tandem repeats of RfGH16_21 was also confirmed by calculating total binding Gibbs free energy, i.e. -100.8 ± 2.6 KJ/mol, by using g_mmpbsa tool. The stability of the protein was determined by protein melting analysis that showed Ca2+ and Mg2+ ions imparted structural stability to RfGH16_21. Dynamic light scattering analysis of RfGH16_21 showed monodispersity and hydrodynamic radius of 4.0 nm at 2.0 mg/mL protein concentration, which was comparable with the radius of gyration of 3.2 nm determined by MD simulation showing the protein to be in monomeric form.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening of anti-breast cancer compounds from Artemisia absinthium-insights through molecular docking, pharmacokinetics, and molecular dynamic simulations

Breast cancer is the world's second most frequent malignancy, with a significant mortality and morbidity rate. Nowadays, natural breast cancer medicine has piqued attention as disease-curing agent with low side effects. Herein, the leaf powder of Artemisia absinthium was extracted with ethanol, and GC-MS and LC-MS methods were employed to identify the phytocompounds. Using commercial software SeeSAR-9.2 and StarDrop, identified phytocompounds were docked with estrogen and progesterone breast cancer receptors as they promote breast cancer growth to find the binding affinity of the ligands, drugability, and toxicity. Hormone-mediated breast cancer accounts for about 80% of all cases of breast cancer. Cancer cells proliferate when estrogen and progesterone hormones are attached to these receptors. The molecular docking results demonstrated that 3',4',5,7-Tetrahydroxyisoflavanone (THIF) has stronger binding efficacy than standard drugs and other phytocompounds with -28.71 (3 hydrogen bonds) and -24.18 kcal/mol (6 hydrogen bonds) binding energies for estrogen and progesterone receptors, respectively. Pharmacokinetics and toxicity analysis were done to predict the drug-likeness of THIF which results in good drugability and less toxicity. The best fit THIF was subjected to a molecular dynamics simulation analysis by using Gromacs to analyze the conformational changes that occurred during protein-ligand interaction and found that, the structural changes were observed. The results from MD simulation and pharmacokinetic studies suggested that THIF can be expected that in vitro and in vivo research on this compound may lead to the development of a potent anti-breast cancer drug in the future.Communicated by Ramaswamy H. Sarma.

Lasso Peptides: Exploring the Folding Landscape of Nature's Smallest Interlocked Motifs

Lasso peptides make up a class of natural products characterized by a threaded structure. Given their small size and stability, chemical synthesis would offer tremendous potential for the development of novel therapeutics. However, the accessibility of the pre-folded lasso architecture has limited this advance. To better understand the folding process de novo, simulations are used herein to characterize the folding propensity of microcin J25 (MccJ25), a lasso peptide known for its antimicrobial properties. New algorithms are developed to unambiguously distinguish threaded from nonthreaded precursors and determine handedness, a key feature in natural lasso peptides. We find that MccJ25 indeed forms right-handed pre-lassos, in contrast to past predictions but consistent with all natural lasso peptides. Additionally, the native pre-lasso structure is shown to be metastable prior to ring formation but to readily transition to entropically favored unfolded and nonthreaded structures, suggesting that de novo lasso folding is rare. However, by altering the ring forming residues and appending thiol and thioester functionalities, we are able to increase the stability of pre-lasso conformations. Furthermore, conditions leading to protonation of a histidine imidazole side chain further stabilize the modified pre-lasso ensemble. This work highlights the use of computational methods to characterize lasso folding and demonstrates that de novo access to lasso structures can be facilitated by optimizing sequence, unnatural modifications, and reaction conditions like pH.

Size Matters: Free-Energy Calculations of Amino Acid Adsorption over Pristine Graphene

There is still growing interest in graphene interactions with proteins, both for its possible biological applications and due to concerns over detrimental effects at the cellular level. As with any process involving proteins, an understanding of amino acid composition is desirable. In this work, we systematically studied the adsorption process of amino acids onto pristine graphene via rigorous free-energy calculations. We characterized the free energy, potential energy, and entropy of the adsorption of all proteinogenic amino acids. The energetic components were further separated into pair interaction contributions. A linear correlation was found between the free energy and the solvent accessible surface area change during adsorption (ΔSASAads) over pristine graphene and uncharged amino acids. Free energies over pristine graphene were compared with adsorption onto graphene oxide, finding an almost complete loss of the favorability of amino acid adsorption onto graphene. Finally, the correlation with ΔSASAads was used to successfully predict the free energy of adsorption of several penta-l-peptides in different structural states and sequences. Due to the relative ease of calculating the ΔSASAads compared to free-energy calculations, it could prove to be a cost-effective predictor of the free energy of adsorption for proteins onto nonpolar surfaces.

Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations

Medin is a principal component of localized amyloid found in the vasculature of individuals over 50 years old. Its amyloid aggregation has been linked to endothelial dysfunction and vascular inflammation, contributing to the pathogenesis of various vascular diseases. Despite its significance, the structures of the medin monomer, oligomer, and fibril remain elusive, and the dynamic processes of medin aggregation are not fully understood. In this study, we comprehensively investigated the medin folding and dimerization dynamics and conformations using atomistic discrete molecular dynamics simulations. Our simulation results suggested that the folding initiation of the medin involved the formation of β-sheets around medin30-41 and medin42-50, with subsequent capping of other segments to their β-sheet edges. Medin monomers typically consisted of three or four β-strands, along with a dynamic N-terminal helix. Two isolated medin peptides readily aggregated into a β-sheet-rich dimer, displaying a strong aggregation propensity. Dimerization of medin not only enhanced the β-sheet conformations but also led to the formation of β-barrel oligomers. The aggregation tendencies of medin1-18 and medin19-29 were relatively weak. However, the segments of medin30-41 and medin42-50 played a crucial role as they primarily formed a β-sheet core and facilitated medin1-18 and medin19-29 to form intra- and interpeptide β-sheets. The findings highlight the critical role of the medin30-41 and medin42-50 regions in stabilizing the monomer structure and driving the medin amyloid aggregation. These regions could potentially serve as promising targets for designing antiamyloid inhibitors against amyloid aggregation of medin. Additionally, our study provides a full picture of the monomer conformations and dimerization dynamics for medin, which will help better understand the pathology of medin aggregation.

Brain-derived neurotrophic factor G196A (rs6265) gene polymorphism increases Turner syndrome susceptibility

Brain-derived neurotrophic factor (BDNF) is a member of the nerve growth factor family. It plays a significant role in the regulation of brain metabolic activity, modification of synaptic efficacy, and enhances neuronal survival. A common naturally occurring allelic variation, i.e. G196A (Val66 Met, rs6265) of the BDNF gene is implicated in neuroplasticity. This study analyzes its expression levels and determines the frequency of BDNF G196A gene polymorphism in women with Turner syndrome (TS) compared to the controls. This case-control study comprised 14 TS patients and 8 healthy individuals. The expression levels of BDNF gene in TS patients were checked by qPCR. For BDNF gene, a dynamic expression range along with the presence of G196A polymorphism was found across all TS patients. The effects of Val66 Met mutation on BDNF protein structure and function were studied by molecular dynamics simulations of wild and mutant (Val66 Met) forms. The analysis of different trajectories generated by simulation showed that there was a significant change in the protein structure due to Val66 Met polymorphism, which might lead to functional impairment. This is first time we are reporting the association of BDNF G196A gene polymorphism with TS risk. Our study suggests that in turner patients, BDNF G196A polymorphism may be an important genetic factor predisposing to neuroplasticity risk and can be exploited as diagnostic/prognostic marker for TS. Further study on a large number of TS samples will prove this point beyond doubts or otherwise enriching the much desired repertoire of personalized medicine.

Recent advances on molecular dynamics-based techniques to address drug membrane permeability with atomistic detail

Several factors affect the passive membrane permeation of small molecules, including size, charge, pH, or the presence of specific chemical groups. Understanding these features is paramount to identifying or designing drug candidates with optimal ADMET properties and this can be achieved through experimental/knowledge-based methodologies or using computational approaches. Empirical methods often lack detailed information about the underlying molecular mechanism. In contrast, Molecular Dynamics-based approaches are a powerful strategy, providing an atomistic description of this process. This technique is continuously growing, featuring new related methodologies. In this work, the recent advances in this research area will be discussed.

At the origin of the selectivity of the chlorophyll-binding sites in light harvesting complex II (LHCII)

The photosynthetic light-harvesting complexes (LHCs) are responsible for light absorption due to their pigment-binding properties. These pigments are primarily Chlorophyll (Chl) molecules of type a and b, which ensure an excellent coverage of the visible light spectrum. To date, it is unclear which factors drive the selective binding of different Chl types in the LHC binding pockets. To gain insights into this, we employed molecular dynamics simulations on LHCII binding different Chl types. From the resulting trajectories, we have calculated the binding affinities per each Chl-binding pocket using the Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) model. To further examine the importance of the nature of the axial ligand in tuning the Chl selectivity of the binding sites, we used Density Functional Theory (DFT) calculations. The results indicate that some binding pockets have a clear Chl selectivity, and the factors governing these selectivities are identified. Other binding pockets are promiscuous, which is consistent with previous in vitro reconstitution studies. DFT calculations show that the nature of the axial ligand is not a major factor in determining the Chl binding pocket selectivity, which is instead probably controlled by the folding process.

Crucial roles of ion-specific effects in the flotation of water-soluble KCl and NaCl crystals with fatty acid salts

HYPOTHESIS

Flotation of water-soluble KCl and NaCl minerals in brines is significant for K-fertilizer production, but its mechanism is controversial. Dissolved salt ions are expected to change the physicochemical properties of solvents, interfaces, and collector colloids, thereby affecting flotation significantly.

EXPERIMENTS

Flotation experiments of KCl and NaCl crystals in brines were conducted using potassium and sodium laurates as collectors. Contact angle (CA) and surface tension measurements, X-ray photoelectron spectroscopy (XPS) analysis, and molecular dynamics simulations (MD) were applied to gain a molecular understanding of changing interfacial properties and crystal-collector colloid interactions in the presence of dissolved ions in terms of salt flotation.

FINDINGS

While K⁺ ions activate the NaCl crystal flotation, Na⁺ ions depress the KCl crystal flotation, in agreement with the studies of CA, XPS, and MD results with these crystals. XPS results showed no collector adsorption at crystal surfaces which is a requirement of conventional flotation and presents a new theoretical challenge. We argue the crucial role of ion specificity: Na-laurate colloids adsorb at the bubble surface as a monolayer but solvent-separated from KCl crystals, inhibiting their flotation, or in interactive contact with NaCl crystals, enhancing their flotation. Increasing K⁺ concentration weakens NaCl crystal hydration, increasing Na-laurate colloid attraction with crystals for better flotation. The Contact Interactive Collector Colloid (CICC) and Solvent-separated Interactive Collector Colloid (SICC) hydration states are critical to salt crystal flotation via collector colloid-crystal attraction by dispersion forces.

pH-responsive phthalate cashew gum nanoparticles for improving drugs delivery and anti-Trypanosoma cruzi efficacy

Nanotechnology is a crucial technology in recent years has resulted in new and creative applications of nanomedicine. Polymeric nanoparticles have increasing demands in pharmaceutical applications and require high reproducibility, homogeneity, and control over their properties. Work explores the use of cashew phthalate gum (PCG) as a particle-forming polymer. PCG exhibited a pH-sensitive behavior due to the of acid groups on its chains, and control drug release. We report the development of nanoparticles carrying benznidazole. Formulations were characterized by DLS, encapsulation efficiency, drug loading, FTIR, pH-responsive behavior, release, and in vitro kinetics. Interaction between polymer and drug was an evaluated by molecular dynamics. Morphology was observed by SEM, and in vitro cytotoxicity by MTT assay. Trypanocidal effect for epimastigote and trypomastigote forms was also evaluated. NPs responded to the slightly basic pH, triggering the release of BNZ. In acidic medium, they presented small size, spherical shape, and good stability. It was indicated NP with enhanced biological activity, reduced cytotoxicity, high anti T. cruzi performance, and pH-sensitive release. This work investigated properties related to the development and enhancement of nanoparticles. PCG has specific physicochemical properties that make it a promising alternative to drug delivery, however, there are still challenges to be overcome.

Effect of substrate charge density on the adsorption of intrinsically disordered protein amyloid β40: a molecular dynamics study

The inhibitory effect of negatively charged gold nanoparticles (AuNPs) on amyloidogenic protein fibrillation has been established from experiments and computer simulations. Here, we investigate the effect of the charge density (σ) of gold (Au) surfaces on the adsorption of the intrinsically disordered amyloid β40 (Aβ40) monomer using molecular dynamics (MD) simulations. On the basis of the binding free energy, some key residues (ARG5, LYS16, LYS28, LEU17-ALA21, ILE31-VAL38) were found to be responsible for preventing the β-sheet formation, which is known to be a precursor for fibrillation. Until a critical charge density (σ_c) of -0.167 e nm^-2, the key residues remained adsorbed on the Au slab. A saturation in the number of condensed counterions (Na⁺) on Aβ40 was also observed at σ_c. Beyond σ_c, the condensation of Na⁺ occurs only on the Au slab, leading to competition between positively charged key residues and condensed ions. This competition was found to be responsible for the lack of adsorption of the key residues, leading to β-sheet formation for σ > -0.167 e nm^-2. This study suggests that if the key residues are not adsorbed, then β-sheet formation is observed, which can then lead to the development of proto-fibrils and subsequently fibrillation. Therefore the surface should have an optimal charge density to be an effective inhibitor of fibrillation.

The origin of pigment-binding differences in CP29 and LHCII: the role of protein structure and dynamics

The first step of photosynthesis in plants is performed by the light-harvesting complexes (LHC), a large family of pigment-binding proteins embedded in the photosynthetic membranes. These complexes are conserved across species, suggesting that each has a distinct role. However, they display a high degree of sequence homology and their static structures are almost identical. What are then the structural features that determine their different properties? In this work, we compared the two best-characterized LHCs of plants: LHCII and CP29. Using molecular dynamics simulations, we could rationalize the difference between them in terms of pigment-binding properties. The data also show that while the loops between the helices are very flexible, the structure of the transmembrane regions remains very similar in the crystal and the membranes. However, the small structural differences significantly affect the excitonic coupling between some pigment pairs. Finally, we analyzed in detail the structure of the long N-terminus of CP29, showing that it is structurally stable and it remains on top of the membrane even in the absence of other proteins. Although the structural changes upon phosphorylation are minor, they can explain the differences in the absorption properties of the pigments observed experimentally.

Discovery, synthesis and in silico approach of pyrrolo [3,4-c]pyrroles as SARS-CoV-2 mpro inhibitors

A new coronavirus has been identified as the contributing agent of the severe acute respiratory syndrome (SARS). The main viral protease (Mpro), which controls the activities of the coronavirus replication complex, which is an essential target for the treatment of coronavirus disease. With the primary objective of targeting this receptor, we designed a new series of pyrrolo [3,2-c] pyrroles, synthesized and characterized using various analytical techniques including FT-IR, UV-Vis and NMR spectroscopic studies. The biological descriptors of the synthesized compounds were investigated using DFT calculation. The mode of binding and reactivity of the target compounds with SARS-CoV-2 main protease (Mpro) were studied using molecular docking and molecular dynamics (MD) simulation. Molecular docking of the compounds (4a and 5a) showed a promising binding affinity towards Mpro protein with the binding energy of -7.8 kcal/mol and -7.0 kcal/mol, respectively. The results of MD simulation and prime MM-GBSA calculation were consistent with molecular docking. The absorption, distribution, metabolism and excretion (ADME) properties of the compounds are in the acceptable range, as they are orally active and obey Lipinski's rule of five without violation. In addition, in silico toxicity prediction using the Pro-Tox II revealed the non-toxic nature of the compounds. Hence the obtained results suggest that these compounds could be a possible anti-viral candidate and highlight this series of compounds for further drug design and development against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Ligand-receptor interaction in the specific targeting of biomimetic peptide nanoparticles to lysophosphatidylcholine

As nanotechnology is applied clinical medicine, nanoparticle-based therapy is emerging as a novel approach for the treatment of atherosclerosis. Ligand-receptor interaction affects the effectiveness of nanoparticle targeting therapy. In this study, the biomimetic peptide (BP-KFFVLK-WYKDGD) ligand specifically targeting the lysophosphatidylcholine (LPC) receptor in atherosclerotic plaques was constructed. The corresponding ligand-receptor interaction under different pH values was investigated by molecular dynamics simulation and experimental measurements. Results show that the interaction force between the peptide and LPC is greater than that of the peptide and human umbilical vein endothelial cell, clearly demonstrating the specific targeting of the peptide ligand to the LPC receptor. The ligand-receptor binding of peptide and LPC dominantly depends on Coulomb and van der Waals interactions. The YKDG amino acids of the peptide are the main fragment that binds to LPC. Compared with neutral environment at pH 7.4, the interaction forces between the peptide and oxidized low-density lipoprotein (oxLDL) decreased by 18.22 % and 45.87 % under acidic environments at pH 6.5 and 5.5, respectively, because of the change in oxLDL secondary structure and the release of LPC from oxLDL. Nevertheless, the peptide still has a strong binding capacity with oxLDL for the treatment of atherosclerosis.

CADD, AI and ML in drug discovery: A comprehensive review

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest because of its potential to expedite and lower the cost of the drug development process. Drug discovery research is expensive and time-consuming, and it frequently took 10-15 years for a drug to be commercially available. CADD has significantly impacted this area of research. Further, the combination of CADD with Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies to handle enormous amounts of biological data has reduced the time and cost associated with the drug development process. This review will discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process. It will also provide a detailed overview of the different in silico tools used and how these approaches interact.

In Vitro Screening and MD Simulations of Thiourea Derivatives against SARS-CoV-2 in Association with Multidrug Resistance ABCB1 Transporter

Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is considered a global public health concern since it causes high morbidity and mortality. Recently, it has been reported that repurposed anti-COVID-19 drugs might interact with multidrug resistance ABC transporter, particularly ABCB1. In the current study, a series of thiourea derivatives were screened as potential inhibitors against SARS-CoV-2 by targeting the attachment of receptor binding domain (RBD) of spike protein with ACE2 and their interaction with human ABCB1 has also been explored. The results indicated strong impairment of RBD-ACE2 attachment by BB IV-46 with a percentage inhibition of 95.73 ± 1.79% relative to the positive control, while BB V-19 was proven inactive with a percentage inhibition of 50.90 ± 0.84%. The same compound (BB IV-46) interacted with ABCB1 and potentially inhibited cell proliferation of P-gp overexpressing cell line with an IC₅₀ value of 4.651 ± 0.06 μM. BB V-19, which was inactive against SARS-CoV-2, was inactive against ABCB1 with a higher IC₅₀ value of 35.72 ± 0.09 μM. Furthermore, molecular dynamics simulations followed by binding free-energy analysis explored the binding interaction of BB IV-46 and BB V-19 to RBD region of spike protein of SARS-CoV-2. The results confirmed that compound BB IV-46 interacted strongly with RBD with a significant binding energy (-127.0 kJ/mol), while BB V-19 interacted weakly (-29.30 kJ/mol). The key interacting residues of the RBD involved in binding included Leu441, Lys444, and Tyr449. This study highlights the importance of BB IV-46 against SARS-CoV-2; however, further pharmacokinetic and pharmacodynamics studies are needed to be done.

Change in membrane fluidity induced by polyphenols is highly dependent on the position and number of galloyl groups

The cell membrane fluidity was very important in adipogenesis and galloyl groups on polyphenolic structures could enhance their antiadipogenic activity. However, the effect of polyphenols on membrane fluidity and the role of galloyl groups in fluidity changes remain unclear. Therefore, the present study chose structurally different polyphenols to compare their effects on the membrane morphology and fluidity of 3T3-L1 preadipocytes, and then the reasons behind the changes of membrane fluidity induced by galloylated polyphenols were explored from structural and molecular insights using liposome model and molecular dynamic simulation technology. Our results indicated that galloylated polyphenols could significantly change 3T3-L1 cell membrane morphology and decrease membrane fluidity, while non-galloylated ones could not. The membrane interference effect of polyphenols was enhanced as the number of galloyl groups increased. Morever, the decrease in membrane fluidity induced by galloylated polyphenols was due to the disturbance of polyphenols on lipid alkyl chains in the cell membrane. Galloylated polyphenols could not only locate in the polar head, but also insert into hydrophobic center of lipid bilayer to interfere with the lipid alkyl chains arrangement, thus decreasing the membrane fluidity and showing strong affinity for the membrane. In addition, differences in position of galloyl groups in polyphenols induced distinct effect on cell membranes interactions, thus affecting the binding manner and bioactivity. The results expanded the understanding on the strong antiadipogenic activity of galloylated polyphenols through the aspect of their effects on cell membrane by both experimental and theoretically simulated ways.

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.

Structural basis for directional chitin biosynthesis

Chitin, the most abundant aminopolysaccharide in nature, is an extracellular polymer consisting of N-acetylglucosamine (GlcNAc) units1. The key reactions of chitin biosynthesis are catalysed by chitin synthase2-4, a membrane-integrated glycosyltransferase that transfers GlcNAc from UDP-GlcNAc to a growing chitin chain. However, the precise mechanism of this process has yet to be elucidated. Here we report five cryo-electron microscopy structures of a chitin synthase from the devastating soybean root rot pathogenic oomycete Phytophthora sojae (PsChs1). They represent the apo, GlcNAc-bound, nascent chitin oligomer-bound, UDP-bound (post-synthesis) and chitin synthase inhibitor nikkomycin Z-bound states of the enzyme, providing detailed views into the multiple steps of chitin biosynthesis and its competitive inhibition. The structures reveal the chitin synthesis reaction chamber that has the substrate-binding site, the catalytic centre and the entrance to the polymer-translocating channel that allows the product polymer to be discharged. This arrangement reflects consecutive key events in chitin biosynthesis from UDP-GlcNAc binding and polymer elongation to the release of the product. We identified a swinging loop within the chitin-translocating channel, which acts as a 'gate lock' that prevents the substrate from leaving while directing the product polymer into the translocating channel for discharge to the extracellular side of the cell membrane. This work reveals the directional multistep mechanism of chitin biosynthesis and provides a structural basis for inhibition of chitin synthesis.

Molecular insights into the oligomerization dynamics and conformations of amyloidogenic and non-amyloidogenic amylin from discrete molecular dynamics simulations

The amyloid aggregation of human islet amyloid polypeptide (hIAPP) is associated with pancreatic β-cell death in type 2 diabetes. The S20G substitution of hIAPP (hIAPP(S20G)), found in Japanese and Chinese people, is more amyloidogenic and cytotoxic than wild-type hIAPP. Rat amylin (rIAPP) does not have aggregation propensity or cytotoxicity. Mounting evidence suggests that soluble low-molecular-weight amyloid oligomers formed during early aggregation are more cytotoxic than mature fibrils. The self-assembly dynamics and oligomeric conformations remain unknown because the oligomers are heterogeneous and transient. The molecular mechanism of sequence-variation rendering dramatically different aggregation propensity and cytotoxicity is also elusive. Here, we investigate the oligomerization dynamics and conformations of amyloidogenic hIAPP, hIAPP(S20G), and non-amyloidogenic rIAPP using atomistic discrete molecular dynamics (DMD) simulations. Our simulation results demonstrated that all three monomeric amylin peptides mainly adopted an unstructured formation with partial dynamical helices near the N-terminus. Relatively transient β-hairpins were more abundant in hIAPP and hIAPP(S20G) than in rIAPP. The S20G-substituting mutant of hIAPP altered the turn region of the β-hairpin motif, resulting in more hydrophobic residue-pairwise contacts within the β-hairpin. Oligomerization dynamic investigation revealed that all three peptides spontaneously accumulated into helix-populated oligomers. The conformational conversion to form β-sheet-rich oligomers was only observed in hIAPP and hIAPP(S20G). The population of high-β-sheet-content oligomers was enhanced by S20G substitution. Interestingly, both hIAPP and hIAPP(S20G) could form β-barrel formations, and the β-barrel propensity of hIAPP(S20G) was three times larger than that of hIAPP. No β-sheet-rich or β-barrel formations were observed in rIAPP. Our direct observation of the correlation between β-barrel oligomer formation and cytotoxicity suggests that β-barrels might play a critically important role in the cytotoxicity of amyloidosis.

The Transport Properties of Semi-Crystalline Polyetherimide BPDA-P3 in Amorphous and Ordered States: Computer Simulations

The effect of polymer chain ordering on the transport properties of the polymer membrane was examined for the semi-crystalline heterocyclic polyetherimide (PEI) BPDA-P3 based on 3,3',4,4'-biphenyltetracarboxylic dianhydride (BPDA) and diamine 1,4-bis [4-(4-aminophenoxy)phenoxy]benzene (P3). All-atom Molecular Dynamics (MD) simulations were used to investigate the gas diffusion process carried through the pores of a free volume several nanometers in size. The long-term (~30 μs) MD simulations of BPDA-P3 were performed at T = 600 K, close to the experimental value of the melting temperature (Tm ≈ 577 K). It was found during the simulations that the transition of the PEI from an amorphous state to an ordered one occurred. We determined a decrease in solubility for both the gases examined (CO2 and CH4), caused by the redistribution of free volume elements occurring during the structural ordering of the polymer chains in glassy state (Tg ≈ 487 K). By analyzing the diffusion coefficients in the ordered state, the presence of gas diffusion anisotropy was found. However, the averaged values of the diffusion coefficients did not differ from each other in the amorphous and ordered states. Thus, permeability in the observed system is primarily determined by gas solubility, rather than by gas diffusion.

Molecular Insights into the Self-Assembly of Block Copolymer Suckerin Polypeptides into Nanoconfined β-Sheets

Suckerin in squid sucker ring teeth is a block-copolymer peptide comprised of two repeating modules-the alanine and histidine-rich M1 and the glycine-rich M2. Suckerin self-assemblies display excellent thermo-plasticity and pH-responsive properties, along with the high biocompatibility, biodegradability, and sustainability. However, the self-assembly mechanism and the detailed role of each module are still elusive, limiting the capability of applying and manipulating such biomaterials. Here, the self-assembly dynamics of the two modules and two minimalist suckerin-mimetic block-copolymers, M1-M2-M1 and M2-M1-M2, in silico is investigated. The simulation results demonstrate that M2 has a stronger self-association but weaker β-sheet propensities than M1. The high self-assembly propensity of M2 allows the minimalist block-copolymer peptides to coalesce with microphase separation, enabling the formation of nanoconfined β-sheets in the matrix formed by M1-M2 contacts. Since these glycine-rich fragments with scatted hydrophobic and aromatic residues are building blocks of many other block-copolymer peptides, the study suggests that these modules function as the "molecular glue" in addition to the flexible linker or spacer to drive the self-assembly and microphase separation. The uncovered molecular insights may help understand the structure and function of suckerin and also aid in the design of functional block-copolymer peptides for nanotechnology and biomedicine applications.

Scorpion Neurotoxin Syb-prII-1 Exerts Analgesic Effect through Nav1.8 Channel and MAPKs Pathway

Trigeminal neuralgia (TN) is a common type of peripheral neuralgia in clinical practice, which is usually difficult to cure. Common analgesic drugs are difficult for achieving the desired analgesic effect. Syb-prII-1 is a β-type scorpion neurotoxin isolated from the scorpion venom of Buthus martensi Karsch (BmK). It has an important influence on the voltage-gated sodium channel (VGSCs), especially closely related to Nav1.8 and Nav1.9. To explore whether Syb-prII-1 has a good analgesic effect on TN, we established the Sprague Dawley (SD) rats’ chronic constriction injury of the infraorbital nerve (IoN-CCI) model. Behavioral, electrophysiological, Western blot, and other methods were used to verify the model. It was found that Syb-prII-1 could significantly relieve the pain behavior of IoN-CCI rats. After Syb-prII-1 was given, the phosphorylation level of the mitogen-activated protein kinases (MAPKs) pathway showed a dose-dependent decrease after IoN-CCI injury. Moreover, Syb-prII-1(4.0 mg/kg) could significantly change the steady-state activation and inactivation curves of Nav1.8. The steady-state activation and inactivation curves of Nav1.9 were similar to those of Nav1.8, but there was no significant difference. It was speculated that it might play an auxiliary role. The binding mode, critical residues, and specific interaction type of Syb-prII-1 and VSD2^rNav1.8 were clarified with computational simulation methods. Our results indicated that Syb-prII-1 could provide a potential treatment for TN by acting on the Nav1.8 target.

Identification of novel and potential PPARγ stimulators as repurposed drugs for MCAO associated brain degeneration

Peroxisome proliferator-activated receptor-gamma (PPARγ) has been shown to have therapeutic promise in the treatment of ischemic stroke and is supported by several studies. To identify possible PPARγ activators, the current study used an in silico technique in conjunction with molecular simulations and in vivo validation. FDA-approved drugs were evaluated using molecular docking to determine their affinity for PPARγ. The findings of molecular simulations support the repurposing of rabeprazole and ethambutol for the treatment of ischemic stroke. Adult Sprague Dawley rats were subjected to transient middle cerebral artery occlusion (t-MCAO). Five groups were made as a sham-operated, t-MCAO group, rabeprazole +t-MCAO, ethambutol +t-MCAO, and pioglitazone +t-MCAO. The neuroprotective effects of these drugs were evaluated using the neurological deficit score and the infarct area. The inflammatory mediators and signaling transduction proteins were quantified using Western blotting, ELISA, and immunohistochemistry. The repurposed drugs mitigated cerebral ischemic injury by PPARγ mediated downregulation of nods like receptor protein 3 inflammasomes (NLRP3), tumor necrosis factor-alpha (TNF-α), cyclooxygenase 2 (COX-2), nuclear factor kappa-light-chain-enhancer of activated B cells (p-NF-kB), and c-Jun N-terminal kinase (p-JNK). Our data demonstrated that rabeprazole and ethambutol have neuroprotective potential via modulating the cytoprotective stress response, increasing cellular survival, and balancing homeostatic processes, and so may be suitable for future research in stroke therapy.

Impact of collagen-like peptide (CLP) heterotrimeric triple helix design on helical thermal stability and hierarchical assembly: a coarse-grained molecular dynamics simulation study

Collagen-like peptides (CLP) are multifunctional materials garnering a lot of recent interest from the biomaterials community due to their hierarchical assembly and tunable physicochemical properties. In this work, we present a computational study that links the design of CLP heterotrimers to the thermal stability of the triple helix and their self-assembly into fibrillar aggregates and percolated networks. Unlike homotrimeric helices, the CLP heterotrimeric triple helices in this study are made of CLP strands of different chain lengths that result in 'sticky' ends with available hydrogen bonding groups. These 'sticky' ends at one end or both ends of the CLP heterotrimer then facilitate inter-helix hydrogen bonding leading to self-assembly into fibrils (clusters) and percolated networks. We consider the cases of three sticky end lengths - two, four, and six repeat units - present entirely on one end or split between two ends of the CLP heterotrimer. We observe in CLP heterotrimer melting curves generated using coarse grained Langevin dynamics simulations at low CLP concentration that increasing sticky end length results in lower melting temperatures for both one and two sticky ended CLP designs. At higher CLP concentrations, we observe non-monotonic trends in cluster sizes with increasing sticky end length with one sticky end but not for two sticky ends with the same number of available hydrogen bonding groups as the one sticky end; this nonmonotonicity stems from the formation of turn structures stabilized by hydrogen bonds at the single, sticky end for sticky end lengths greater than four repeat units. With increasing CLP concentration, heterotrimers also form percolated networks with increasing sticky end length with a minimum sticky end length of four repeat units required to observe percolation. Overall, this work informs the design of thermoresponsive, peptide-based biomaterials with desired morphologies using strand length and dispersity as a handle for tuning thermal stability and formation of supramolecular structures.

Identification of Natural Products as SENP2 Inhibitors for Targeted Therapy in Heart Failure

Aims: Sentrin-specific protease -2 (SENP2) is involved in deSUMOylation. Increased deSUMOylation in murine hearts by SENP2 upregulation resulted in cardiac dysfunction and congenital heart defects. Natural compounds via regulating cell proliferation and survival, induce cell cycle cessation, cell death, apoptosis, and producing reactive oxygen species and various enzyme systems cause disease prevention. Then, natural compounds can be suitable inhibitors and since SENP2 is a protein involved in heart disease, so our aim was inhibition of SENP2 by natural products for heart disease treatment. Material and methods: Molecular docking and molecular dynamics simulation of natural products i.e. Gallic acid (GA), Caffeic acid (CA), Thymoquinone (TQ), Betanin, Betanidin, Fisetin, and Ebselen were done to evaluate the SENP2 inhibitory effect of these natural products. The toxicity of compounds was also predicted. Results: The results showed that Betanin constituted a stable complex with SENP2 active site as it revealed low RMSD, high binding energy, and hydrogen bonds. Further, as compared to Ebselen, Betanin demonstrated low toxicity, formed a stable complex with SENP2 via four to seven hydrogen bonds, and constituted more stable MD plots. Therefore, depending upon the outcomes presented herein, Betanin significantly inhibited SENP2 and hence may be considered as a suitable natural compound for the treatment of heart failure. Further clinical trials must be conducted to validate its use as a potential SENP2 inhibitor.

Understanding the Interactions between Triolein and Cosolvent Binary Mixtures Using Molecular Dynamics Simulations

Biodiesel is one of the emerging renewable sources of energy to replace fossil-fuel-based resources. It is produced by a transesterification reaction in which a triglyceride reacts with methanol in the presence of a catalyst. The reaction is slow because of the low solubility of methanol in triglycerides, which results in low concentrations of methanol available to react with triglyceride. To speed up the reaction, cosolvents are added to create a single phase which helps to improve the concentration of methanol in the triglyceride phase. In this study, molecular dynamics simulations are used to help understand the role of cosolvents in the solvation of triglyceride (triolein). Six binary mixtures of triolein/cosolvent were used to study the solvation of triolein at 298.15 K. Results of 100 ns simulations at constant temperature and pressure to simulate mixing experiments show that in the first 10 ns all the binary mixtures remain largely unmixed. However, for the cosolvents that are fully miscible with triolein, the partial densities across the simulation boxes show that the systems are fully mixed in the final 10 ns. Some solvents were found to interact strongly with the polar part of triolein, while others interacted with the aliphatic part. The radial distribution functions and clustering of the solvents around triolein were also used as indicators for solvation. The presence of cosolvents also influenced the conformation of triolein molecules. In the presence of solvents that solubilize it, triolein preferred a propeller conformation but took up a trident conformation when there is less or no solubilization. The results show that tetrahydrofuran is the best solvent at solubilizing triolein, followed by cyclopentyl methyl ether, diethyl ether, and hexane. With 1,4-dioxane, the solubility improves with an increase in temperature. The miscibility of a solvent in triolein is aided by its ability to interact with both the polar and nonpolar parts of triolein.

Effect of Ionic Strength on Ibuprofenate Adsorption on a Lipid Bilayer of Dipalmitoylphosphatidylcholine from Molecular Dynamics Simulations

In this work, the free energy change in the process of transferring ibuprofenate from the bulk solution to the center of a model of the dipalmitoylphosphatidylcholine bilayer at different NaCl concentrations was calculated. Two minima were found in the free energy profile: a local minimum, located in the vicinity of the membrane, and the global free energy minimum, found near the headgroup region. The downward shift of free energy minima with increasing NaCl concentration is consistent with the results of previous works. Conversely, the upward shift of the free energy maximum with increasing ionic strength is due to the competition of sodium ions and lipids molecules to coordinate with ibuprofenate and neutralize its charge. In addition, normal molecular dynamics simulations were performed to study the effects of the ibuprofenate on the lipid bilayer and in the presence of a high ibuprofenate concentration. The effect of ionic strength on the properties of the lipid bilayer and on lipid-drug interactions was analyzed. The area per lipid shrinking with increasing ionic strength, volume of lipids, and thickness of the bilayer is consistent with the experimental results. At a very high ibuprofenate concentration, the lipid bilayer dehydrates, and it consequently transforms into the gel phase, thus blocking the permeation.

Protein-protein interactions enhance the thermal resilience of SpyRing-cyclized enzymes: A molecular dynamic simulation study

Recently a technique based on the interaction between adhesion proteins extracted from Streptococcus pyogenes, known as SpyRing, has been widely used to improve the thermal resilience of enzymes, the assembly of biostructures, cancer cell recognition and other fields. It was believed that the covalent cyclization of protein skeleton caused by SpyRing reduces the conformational entropy of biological structure and improves its rigidity, thus improving the thermal resilience of the target enzyme. However, the effects of SpyTag/ SpyCatcher interaction with this enzyme are poorly understood, and their regulation of enzyme properties remains unclear. Here, for simplicity, we took the single domain enzyme lichenase from Bacillus subtilis 168 as an example, studied the interface interactions in the SpyRing by molecular dynamics simulations, and examined the effects of the changes of electrostatic interaction and van der Waals interaction on the thermal resilience of target enzyme. The simulations showed that the interface between SpyTag/SpyCatcher and the target enzyme is different from that found by geometric matching method and highlighted key mutations at the interface that might have effect on the thermal resilience of the enzyme. Our calculations highlighted interfacial interactions between enzyme and SpyTag/SpyCatcher, which might be useful in rational designs of the SpyRing.

Hydrogen/Deuterium Exchange Behavior During Denaturing/Refolding Processes Determined in Tetragonal Hen Egg-White Lysozyme Crystals

The hydrogen/deuterium (H/D) exchange of main-chain amide hydrogens in the protein that denatured and refolded in deuterated solvent is considered to contain the traces of hydrogen bond cleavages or the exposure to solvent of the buried part of the protein during the denaturing and refolding (denaturing/refolding) processes. Here, we report the H/D exchange behaviors in hen egg-white lysozymes denatured under acidic conditions, basic conditions, and thermal conditions and then refolded in deuterated solvents, using crystallographic methods. The results indicate that the space containing the Trp28 side chain was hardly exposed to the solvent in acidic conditions, but exposed under basic or heated conditions. Moreover, the β-bridges between Tyr53 and Ile58 in strands β2 and β3, which are in a highly conserved region, show some tolerance to changes in pD. The results indicate that crystallographic method is one of the powerful tools to analyze the denaturing/refolding processes of proteins.

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.

Membrane Structure of Aquaporin Observed with Combined Experimental and Theoretical Sum Frequency Generation Spectroscopy

High-resolution structural information on membrane proteins is essential for understanding cell biology and for the structure-based design of new medical drugs and drug delivery strategies. X-ray diffraction (XRD) can provide angstrom-level information about the structure of membrane proteins, yet for XRD experiments, proteins are removed from their native membrane environment, chemically stabilized, and crystallized, all of which can compromise the conformation. Here, we describe how a combination of surface-sensitive vibrational spectroscopy and molecular dynamics simulations can account for the native membrane environment. We observe the structure of a glycerol facilitator channel (GlpF), an aquaporin membrane channel finely tuned to selectively transport water and glycerol molecules across the membrane barrier. We find subtle but significant differences between the XRD structure and the inferred in situ structure of GlpF.

Computational spectroscopy of complex systems

Numerous linear and non-linear spectroscopic techniques have been developed to elucidate structural and functional information of complex systems ranging from natural systems, such as proteins and light-harvesting systems, to synthetic systems, such as solar cell materials and light-emitting diodes. The obtained experimental data can be challenging to interpret due to the complexity and potential overlapping spectral signatures. Therefore, computational spectroscopy plays a crucial role in the interpretation and understanding of spectral observables of complex systems. Computational modeling of various spectroscopic techniques has seen significant developments in the past decade, when it comes to the systems that can be addressed, the size and complexity of the sample types, the accuracy of the methods, and the spectroscopic techniques that can be addressed. In this Perspective, I will review the computational spectroscopy methods that have been developed and applied for infrared and visible spectroscopies in the condensed phase. I will discuss some of the questions that this has allowed answering. Finally, I will discuss current and future challenges and how these may be addressed.

Computational screening of potential inhibitors targeting MurF of Brugia malayi Wolbachia through multi-scale molecular docking, molecular dynamics and MM-GBSA analysis

Lymphatic filariasis is a parasitic disease caused by the worms Wuchereria bancrofti, Brugia malayi and Brugia timori. Three anti-filarial drugs namely Diethylcarbamazine, Ivermectin and Albendazole and their combinations are used as the control strategies for filariasis. The disease has received much attention in drug discovery due to the unavailability of vaccines and the toxic pharmaceutical properties of the existing drugs. In Wolbachia endosymbiont Brugia malayi, the UDP-N-acetylmuramoyl-tripeptide-d-alanyl-d-alanine ligase (MurF) plays a key role in peptidoglycan biosynthesis pathway and therefore can be considered as effective drug target against filariasis disease. Therefore, in the present study, MurF was selected as the therapeutic target to identify specific inhibitors against filariasis. Homology modeling was performed to predict the three-dimensional structure of MurF due to the absence of the experimental structure. Further molecular dynamics simulation and structure-based high throughput virtual screening with three different chemical databases (Zinc, Maybridge and Specs) were carried out to identify potent inhibitors and also to check their conformations inside the binding site of MurF, respectively. Top three compounds with high docking score and high relative binding affinity against MurF were selected. Further, validation studies, including predicted ADME (Absorption, Distribution, Metabolism, Excretion) assessment, binding free energy using MM-GBSA (Molecular Mechanics Generalized Born Surface Area) and DFT (Density Functional Theory) calculations were performed for the top three compounds. From the results, it was observed that all the three compounds were predicted to show high reactivity, acceptable range of pharmacokinetic properties and high binding affinity with the drug target MurF. Overall, the results could provide more understanding on the inhibition of MurF enzyme and the screened compounds could lead to the development of new specific anti-filarial drugs.