GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation

Click estradiol dimers with novel aromatic bridging units: synthesis and anticancer evaluation

Estradiol dimers (EDs) possess significant anticancer activity by targeting tubulin dynamics. In this study, we synthesised 12 EDs variants via copper-catalysed azide-alkyne cycloaddition (CuAAC) reaction, focusing on structural modifications within the aromatic bridge connecting two estradiol moieties. In vitro testing of these EDs revealed a marked improvement in selectivity towards cancerous cells, particularly for ED1-8. The most active compounds, ED3 (IC50 = 0.38 μM in CCRF-CEM) and ED5 (IC50 = 0.71 μM in CCRF-CEM) demonstrated cytotoxic effects superior to 2-methoxyestradiol (IC50 = 1.61 μM in CCRF-CEM) and exhibited anti-angiogenic properties in an endothelial cell tube-formation model. Cell-based experiments and in vitro assays revealed that EDs interfere with mitotic spindle assembly. Additionally, we proposed an in silico model illustrating the probable binding modes of ED3 and ED5, suggesting that dimers with a simple linker and a single substituent on the aromatic central ring possess enhanced characteristics compared to more complex dimers.

Using ion mobility spectrometry to understand signal dilution during tandem mass spectrometry sequencing of digital polymers: Experimental evidence of intramolecular cyclization

RATIONALE

Optimizing the structure of digital polymers is an efficient strategy to ensure their tandem mass spectrometry (MS/MS) readability. In block-truncated poly(phosphodiester)s, homolysis of C-ON bonds in long chains permits the release of smaller blocks amenable to sequencing. Yet the dissociation behavior of diradical blocks was observed to strongly depend on their charge state.

METHODS

Polymers were ionized in negative mode electrospray and activated in-source so that blocks released as primary fragments can be investigated using ion mobility spectrometry (IMS) or sequenced in the post-IMS collision cell. Collision cross sections (CCS) were derived from arrival times using a calibration procedure developed for polyanions using the IMSCal software. A multistep protocol based on quantum methods and classical molecular dynamics was implemented for molecular modeling and calculation of theoretical CCS.

RESULTS

Unlike their triply charged homologues, dissociation of diradical blocks at the 2- charge state produces additional fragments, with +1 m/z shift for those holding the nitroxide α-termination and -1 m/z for those containing the carbon-centered radical ω-end. These results suggest cyclization of these diradical species, followed by H• transfer on activated reopening of this cycle. This assumption was validated using IMS resolution of the cyclic/linear isomers and supported by molecular modeling.

CONCLUSIONS

Combining IMS with molecular modeling provided new insights into how the charge state of digital blocks influences their dissociation. These results permit to define new guidelines to improve either ionization conditions or the structural design of these digital polymers for best MS/MS readability.

NPEX: Never give up protein exploration with deep reinforcement learning

Elucidating unknown structures of proteins, such as metastable states, is critical in designing therapeutic agents. Protein structure exploration has been performed using advanced computational methods, especially molecular dynamics and Markov chain Monte Carlo simulations, which require untenably long calculation times and prior structural knowledge. Here, we developed an innovative method for protein structure determination called never give up protein exploration (NPEX) with deep reinforcement learning. The NPEX method leverages the soft actor-critic algorithm and the intrinsic reward system, effectively adding a bias potential without the need for prior knowledge. To demonstrate the method's effectiveness, we applied it to four models: a double well, a triple well, the alanine dipeptide, and the tryptophan cage. Compared with Markov chain Monte Carlo simulations, NPEX had markedly greater sampling efficiency. The significantly enhanced computational efficiency and lack of prior domain knowledge requirements of the NPEX method will revolutionize protein structure exploration.

Engineered nanoparticles as Selinexor drug delivery systems across the cell membrane and related signaling pathways in cancer cells

In the present work, molecular dynamics simulation is applied to evaluate the drug carrier efficiency of graphene oxide nanoflake (GONF) for loading of Selinexor (SXR) drug as well as the drug delivery by 2D material through the membrane in aqueous solution. In addition, to investigate the adsorption and penetration of drug-nanocarrier complex into the cell membrane, well-tempered metadynamics simulations and steered molecular dynamics (SMD) simulations were performed. Based on the obtained results, it is evident that intermolecular hydrogen bonds (HBs) and π-π interactions play a significant role in expediting the interaction between drug molecules and the graphene oxide (GO) nanosheet, ultimately resulting in the formation of a stable SXR-GO complex. The Lennard-Jones (L-J) energy value for the interaction of SXR with GONF is calculated to be approximately -98.85 kJ/mol. In the SXR-GONF complex system, the dominant interaction between SXR and GONF is attributed to the L-J term, resulting from the formation of a strong π-π interaction between the drug molecules and the substrate surface. Moreover, our simulations show by decreasing the distance of GONF with respect to cell membrane, the interaction energy of GONF-membrane significantly decrease to -1500 kJ/mol resulting in fast diffusion of SXR-GONF complex toward the bilayer surface that is favored opening the way to natural drug nanocapsule.

Deciphering molecular mechanisms underlying the inhibition of β-glucuronidase by xanthones from Centaurium spicatum

Herein, we scrutinized the inhibitory potential of five xanthones and a flavonoid, sourced from Centaurium spicatum, against β-glucuronidase activity. The results showed that gentisin and azaleatin emerged as the most potent inhibitors, with significantly lower IC50 values of 0.96 ± 0.10 and 0.57 ± 0.04 μM, respectively. The evaluation of enzyme kinetics unveiled that the isolated xanthones manifested inhibition of β-glucuronidase through a mixed inhibition mode, whereas azaleatin exhibited a noncompetitive inhibition mechanism. The findings from molecular docking analysis unveiled that the compounds under investigation, particularly azaleatin, displayed comparatively diminished binding affinities towards β-glucuronidase. Furthermore, the tested drugs were shown to occupy a common binding site as the employed reference drug. Our comprehensive Molecular Dynamics (MD) simulations analysis revealed consistent trajectories for the investigated drugs, wherein azaleatin and gentisin demonstrated notable stabilization of energy levels. Analysis of various MD parameters revealed that drugs with the lowest IC50 values maintained relatively stable interactions with β-glucuronidase. These drugs were shown to exert notable alterations in their conformation or flexibility upon complexation with the target enzyme. Conversely, the flexibility and accessibility of β-glucuronidase was reduced upon drug binding, particularly with azaleatin and gentisin, underscoring the stability of the drug-enzyme complexes. Analysis of Coul-SR and LJ-SR interaction energies unveiled consistent and stable interactions between certain isolated drugs and β-glucuronidase. Azaleatin notably displayed the lowest average Coul-SR interaction energy, suggesting strong electrostatic interactions with the enzyme's active site and significant conformational variability during simulation. Remarkably, LJ-SR interaction energies across different xanthones complexes were more negative than their Coul-SR counterparts, emphasizing the predominant role of van der Waals interactions, encompassing attractive dispersion and repulsive forces, in stabilizing the drug-enzyme complexes rather than electrostatic interactions.

Accurate estimation of the normalized mutual information of multidimensional data

While the linear Pearson correlation coefficient represents a well-established normalized measure to quantify the inter-relation of two stochastic variables X and Y, it fails for multidimensional variables, such as Cartesian coordinates. Avoiding any assumption about the underlying data, the mutual information I(X, Y) does account for multidimensional correlations. However, unlike the normalized Pearson correlation, it has no upper bound (I ∈ [0, ∞)), i.e., it is not clear if say, I = 0.4 corresponds to a low or a high correlation. Moreover, the mutual information (MI) involves the estimation of high-dimensional probability densities (e.g., six-dimensional for Cartesian coordinates), which requires a k nearest-neighbor algorithm, such as the estimator by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)]. As existing methods to normalize the MI cannot be used in connection with this estimator, a new approach is presented, which uses an entropy estimation method that is invariant under variable transformations. The algorithm is numerically efficient and does not require more effort than the calculation of the (un-normalized) MI. After validating the method by applying it to various toy models, the normalized MI between the Cα-coordinates of T4 lysozyme is considered and compared to a correlation analysis of inter-residue contacts.

Application of the molecular dynamics simulation GROMACS in food science

Food comprises proteins, lipids, sugars and various other molecules that constitute a multicomponent biological system. It is challenging to investigate microscopic changes in food systems solely by performing conventional experiments. Molecular dynamics (MD) simulation serves as a crucial bridge in addressing this research gap. The Groningen Machine for Chemical Simulations (GROMACS) is an open-source, high-performing molecular dynamics simulation software that plays a significant role in food science research owing to its high flexibility and powerful functionality; it has been used to explore the molecular conformations and the mechanisms of interaction between food molecules at the microcosmic level and to analyze their properties and functions. This review presents the workflow of the GROMACS software and emphasizes the recent developments and achievements in its applications in food science research, thus providing important theoretical guidance and technical support for obtaining an in-depth understanding of the properties and functions of food.

Computational screening and MM/GBSA-based MD simulation studies reveal the high binding potential of FDA-approved drugs against Cutibacterium acnes sialidase

Cutibacterium acnes is an opportunistic pathogen linked with acne vulgaris, affecting 80-90% of teenagers globally. On the leukocyte (WBCs) cell surface, the cell wall anchored sialidase in C. acnes virulence factor, catalysing the sialoconjugates into sialic acids and nutrients for C. acnes resulting in human skin inflammation. The clinical use of antibiotics for acne treatments has severe adverse effects, including microbial dysbiosis and resistance. Therefore, identifying inhibitors for primary virulence factors (Sialidase) was done using molecular docking of 1030 FDA-approved drugs. Initially, based on binding energies (ΔG), Naloxone (ZINC000000389747), Fenoldopam (ZINC000022116608), Labetalol (ZINC000000403010) and Thalitone (ZINC000000057255) were identified that showed high binding energies as -10.2, -10.1, -9.9 and -9.8 kcal/mol, respectively. In 2D analysis, these drugs also showed considerable structural conformer of hydrogen and hydrophobic interactions. Further, a 100 ns MD simulation study found the lowest deviation and fluctuations with various intermolecular interactions to stabilise the complexes. Out of 4, the Naloxone molecule showed robust, steady, and stable RMSD 0.23 ± 0.18 nm. Further, MMGBSA analysis supports MD results and found strong binding energy (ΔG) -29.71 ± 4.97 kcal/mol. In Comparative studies with Neu5Ac2en (native substrate) revealed naloxone has a higher affinity for sialidase. The PCA analysis showed that Naloxone and Thalitone were actively located on the active site, and other compounds were flickered. Our extensive computational and statistical report demonstrates that these FDA drugs can be validated as potential sialidase inhibitors.Communicated by Ramaswamy H. Sarma.

Adsorption-Driven Deformation and Footprints of the RBD Proteins in SARS-CoV-2 Variants on Biological and Inanimate Surfaces

Respiratory viruses, carried through airborne microdroplets, frequently adhere to surfaces, including plastics and metals. However, our understanding of the interactions between viruses and materials remains limited, particularly in scenarios involving polarizable surfaces. Here, we investigate the role of the receptor-binding domain (RBD) of the spike protein mutations on the adsorption of SARS-CoV-2 to hydrophobic and hydrophilic surfaces employing molecular simulations. To contextualize our findings, we contrast the interactions on inanimate surfaces with those on native biological interfaces, specifically the angiotensin-converting enzyme 2. Notably, we identify a 2-fold increase in structural deformations for the protein's receptor binding motif (RBM) onto inanimate surfaces, indicative of enhanced shock-absorbing mechanisms. Furthermore, the distribution of adsorbed amino acids (landing footprints) on the inanimate surface reveals a distinct regional asymmetry relative to the biological interface, with roughly half of the adsorbed amino acids arranged in opposite sites. In spite of the H-bonds formed at the hydrophilic substrate, the simulations consistently show a higher number of contacts and interfacial area with the hydrophobic surface, where the wild-type RBD adsorbs more strongly than the Delta or Omicron RBDs. In contrast, the adsorption of Delta and Omicron to hydrophilic surfaces was characterized by a distinctive hopping-pattern. The novel shock-absorbing mechanisms identified in the virus adsorption on inanimate surfaces show the embedded high-deformation capacity of the RBD without losing its secondary structure, which could lead to current experimental strategies in the design of virucidal surfaces.

Dissecting molecular mechanisms underlying the inhibition of β-glucuronidase by alkaloids from Hibiscus trionum: Integrating in vitro and in silico perspectives

β-Glucuronidase, a crucial enzyme in drug metabolism and detoxification, represents a promising target for therapeutic intervention due to its potential to modulate drug pharmacokinetics and enhance therapeutic efficacy. Herein, we assessed the inhibitory potential of phytochemicals from Hibiscus trionum against β-glucuronidase. Grossamide and grossamide K emerged as the most potent β-glucuronidase inhibitors with IC50 values of 0.73 ± 0.03 and 1.24 ± 0.03 μM, respectively. The investigated alkaloids effectively inhibited β-glucuronidase-catalyzed PNPG hydrolysis through a noncompetitive inhibition mode, whereas steppogenin displayed a mixed inhibition mechanism. Molecular docking analyses highlighted grossamide and grossamide K as inhibitors with the lowest binding free energy, all compounds successfully docked into the same main binding site occupied by the reference drug Epigallocatechin gallate (EGCG). We explored the interaction dynamics of isolated compounds with β-glucuronidase through a 200 ns molecular dynamics (MD) simulation. Analysis of various MD parameters revealed that grossamide and grossamide K maintained stable trajectories and demonstrated significant energy stabilization upon binding to β-glucuronidase. Additionally, these compounds exhibited the lowest average interaction energies with the target enzyme. The MM/PBSA calculations further supported these findings, showing the lowest binding free energies for grossamide and grossamide K. These computational results are consistent with experimental data, suggesting that grossamide and grossamide K could be potent inhibitors of β-glucuronidase.

Stable zinc anode solid electrolyte interphase via inner Helmholtz plane engineering

The inner Helmholtz plane and thus derived solid-electrolyte interphase (SEI) are crucial interfacial structure to determine the electrochemical stability of Zn-ion battery (ZIB). In this work, we demonstrate that introducing β-cyclodextrins (CD) as anion-receptors into Zn(OTf)2 aqueous electrolyte could significantly optimize the Zn anode SEI structure for achieving stable ZIB. Specifically, β-CD with macrocyclic structure holds appropriate cavity size and charge distribution to encase OTf- anions at the Zn metal surface to form β-CD@OTf- dominated inner Helmholtz structure. Meanwhile, the electrochemically triggered β-CD@OTf- decomposition could in situ convert to the organic-inorganic hybrid SEI (ZnF2/ZnCO3/ZnS‒(C-O-C/*CF/*CF3)), which could efficiently hinder the Zn dendrite growth with maintain the proper SEI mechanical strength stability to guarantee the long-term stability. The thus-derived Zn | |Zn pouch cell (21 cm2 size) with β-CD-containing electrolyte exhibits a cumulative capacity of 6450 mAh-2 cm-2 at conditions of 10 mAh cm-2 high areal capacity. This work gives insights for reaching stable ZIB via electrolyte additive triggered SEI structure regulation.

Crystallization and the liquid-liquid critical point in nonbonded modified-WAC models

For decades, it has been known that Liquid-Liquid Critical Points (LLCPs) can exist in one-component liquids, yet a comprehensive understanding of the conditions under which they arise remains elusive. To better comprehend the possible interplay between the LLCP and the crystalline phase, we conduct molecular dynamics simulations using the nonbonded family of modified-WAC (mWAC) models, which are known to exhibit a LLCP for certain parameter values. By comparing different versions of the mWAC model-those featuring a LLCP and those lacking one-we identify several key differences between the models relating to crystallization. Those models that do have a LLCP are found to have multiple stable crystalline phases, one of them being a solid-state ionic conductor similar to superionic ice. Moreover, we find that for models that do not have a LLCP, the liquid becomes a glass at a larger range of temperatures, possibly preventing the occurrence of a LLCP. Further studies are required to determine if these results are general or model-specific.

A Temperature-Transferable Coarse-Grained Model for Poly(lactic Acid) Melts

We present a temperature-transferable coarse-grained (CG) model for poly(lactic acid) (PLA), specifically designed to replicate its volumetric properties and solubility parameter in the molten state. The CG-bonded potentials were derived by using the iterative Boltzmann inversion (IBI) optimization method to match structural properties from detailed atomistic models. A parametrization workflow was employed to determine nonbonded interaction parameters with temperature-dependent corrections that provide agreement with the target properties across the melting temperature range. The CG model successfully replicates key features of the PLA melt. It satisfactory reproduces the density and solubility parameter, maintains the dependence of chain conformation on molecular weight, and captures the dynamic behavior through agreement in scaled mean squared displacement and diffusion coefficients with the atomistic model. Additionally, the CG model offers much faster equilibration compared with the atomistic model. The proposed model is expected to be particularly useful for investigating the miscibility characteristics of PLA in various blends and composites that remain challenging to explore using fully atomistic simulations or experiments.

Are NaTFSI and NaFSI Salt-Based Water-in-Salt Electrolytes Structurally Similar or Different?

Water-in-salt electrolytes (WiSEs) are a promising class of electrolytes due to their wide electrochemical stability window and nonflammability. In this study, we explore the structural organization of sodium bis(trifluoromethylsulfonyl)imide (NaTFSI) and sodium bis(fluorosulfonyl)imide (NaFSI) salt-based aqueous electrolytes, covering dilute to highly concentrated regions, by employing an all-atom molecular dynamics simulation. For the NaTFSI-based electrolyte, we observe that Na+ ions are mostly surrounded by water molecules at all the salt concentrations due to the very strong interaction between them. While TFSI anions weakly coordinate with Na+ ions and other TFSI anions, they also mostly prefer to be surrounded by water molecules. These interactions were found to have moderate dependence on the concentration of the NaTFSI salt. For the NaFSI-based electrolyte, while the Na+-water interaction is stronger at lower salt concentrations, the number of nearest neighbor FSI anions is found to be more than that of water at higher concentrations (≥20 m). This is because the increase in the salt concentration leads to expulsion of water molecules from the solvation shell of Na+ ions and enhances the interaction between Na+ ions and oxygen atoms of FSI. At the highest salt concentration (solubility limit), the bulk-like water structure is completely disrupted and dominated by an anionic network in the FSI-based electrolyte. In contrast, water-water hydrogen bonding network is still present even in the highly concentrated TFSI-based electrolyte. The simulated X-ray scattering pattern displays a low-q peak, revealing the presence of an intermediate range ordering due to alternating anion-rich and water/Na+-rich regions in both the electrolytes. However, the characteristic length scale corresponding to the low-q peak decreases with increasing the salt content in both the electrolytes.

High Antifouling Performance of Weakly Hydrophilic Polymer Brushes: A Molecular Dynamics Study

The antifouling performance of polymer brushes usually improves with increasing hydrophilicity of the grafted polymer. However, in some cases, less hydrophilic polymers show comparable or better antifouling performance than do more hydrophilic polymers. We investigate the mechanism of this anomalous behavior using molecular dynamics (MD) simulations of coarse-grained (CG) models of weakly and strongly hydrophilic polymers. The antifouling performance is evaluated from the potential of mean force of a model protein. The strongly hydrophilic polymer exhibits a better antifouling performance than the weakly hydrophilic polymer when the substrate of the polymer brush is repulsive. However, when the substrate is sufficiently attractive, the weakly hydrophilic polymer brush becomes more effective than the strongly hydrophilic brush in a certain range of grafting density. This is because the weakly hydrophilic polymer chains form a tightly packed layer that prevents the adsorbate molecule from contacting the substrate. We also perform all-atom (AA) MD simulations for several standard polymers to examine the correspondence with the CG polymer models. The weakly hydrophilic CG polymer is found to be similar to poly[N-(2-hydroxypropyl)methacrylamide] and poly(2-hydroxyethyl methacrylate), both of which have a hydroxyl group in a monomer unit. The strongly hydrophilic CG polymer resembles zwitterionic poly(carboxybetaine methacrylate). A discussion referring to the adsorption free energies of proteins on surfaces calculated in previous AA MD studies suggests that the higher antifouling performance of less hydrophilic polymer brushes can be realized for various combinations of protein and surface.

Exploring the Functional Landscape of the p53 Regulatory Domain: The Stabilizing Role of Post-Translational Modifications

This study focuses on the intrinsically disordered regulatory domain of p53 and the impact of post-translational modifications. Through fully atomistic explicit water molecular dynamics simulations, we show the wealth of information and detailed understanding that can be obtained by varying the number of phosphorylated amino acids and implementing a restriction in the conformational entropy of the N-termini of that intrinsically disordered region. The take-home message for the reader is to achieve a detailed understanding of the impact of phosphorylation with respect to (1) the conformational dynamics and flexibility, (2) structural effects, (3) protein interactivity, and (4) energy landscapes and conformational ensembles. Although our model system is the regulatory domain p53 of the tumor suppressor protein p53, this study contributes to understanding the general effects of intrinsically disordered phosphorylated proteins and the impact of phosphorylated groups, more specifically, how minor changes in the primary sequence can affect the properties mentioned above.

Molecular Dynamics Simulation on the Suppression Mechanism of Phosphorylation to Ser222 by Allosteric Inhibitors Targeting MEK1/2 Kinase

Allosteric inhibitors of mitogen-activated protein kinase 1 (MEK1) reveal distinct interactions with MEK1 activation loop residues. The structural analyses will determine whether, and how, distinct inhibitors suppress the phosphorylation of MEK1 and may guide future therapeutic development. In this study, we explored the suppression mechanism of the phosphorylation process in the presence of MEK allosteric inhibitors, such as selumetinib, trametinib, cobimetinib, and CH5126766, by employing molecular dynamics simulations accompanied by principal component analysis. The simulations of wildtype MEK1 show that Ser222 can come close to γ-phosphate but not Ser218. We have found the conformation where Ser222 is within 5 Å of distance, which makes Ser222 accessible for γ-phosphate. The conformation analysis from the simulations of MEK1 in the presence of allosteric inhibitors reveals that the inhibitor restricts the flexibility of Ser222 through strong interactions with the activation loop, Lys97, and water mediates interactions with amino acids in the vicinity. The results reveal that all the inhibitors act as screeners between the activation loop and Mg-ATP and restricting the flexibility of the activation loop through strong interaction causes the suppression of the phosphorylation process of MEK1. The results conclude that a strong interaction of allosteric inhibitors with the activation loop restricts the movement of Ser222 toward Mg-ATP, which could be the dominant factor for the suppression of phosphorylation in MEK1. This research will provide novel insights to design effective anticancer therapeutics for targeting MEK1 in the future.

Replica Exchange of Expanded Ensembles: A Generalized Ensemble Approach with Enhanced Flexibility and Parallelizability

Generalized ensemble methods such as Hamiltonian replica exchange (HREX) and expanded ensemble (EE) have been shown effective in free energy calculations for various contexts, given their ability to circumvent free energy barriers via nonphysical pathways defined by states with different modified Hamiltonians. However, both HREX and EE methods come with drawbacks, such as limited flexibility in parameter specification or the lack of parallelizability for more complicated applications. To address this challenge, we present the method of replica exchange of expanded ensembles (REXEE), which integrates the principles of HREX and EE methods by periodically exchanging coordinates of EE replicas sampling different yet overlapping sets of alchemical states. With the solvation free energy calculation of anthracene and binding free energy calculation of the CB7-10 binding complex, we show that the REXEE method achieves the same level of accuracy in free energy calculations as the HREX and EE methods, while offering enhanced flexibility and parallelizability. Additionally, we examined REXEE simulations with various setups to understand how different exchange frequencies and replica configurations influence the sampling efficiency in the fixed-weight phase and the weight convergence in the weight-updating phase. The REXEE approach can be further extended to support asynchronous parallelization schemes, allowing looser communications between larger numbers of loosely coupled processors such as cloud computing and therefore promising much more scalable and adaptive executions of alchemical free energy calculations. All algorithms for the REXEE method are available in the Python package ensemble_md, which offers an interface for REXEE simulation management without modifying the source code in GROMACS.

Do All Paths Lead to Rome? How Reliable is Umbrella Sampling Along a Single Path?

Molecular dynamics (MD) simulations are widely applied to estimate absolute binding free energies of protein-ligand and protein-protein complexes. A routinely used method for binding free energy calculations with MD is umbrella sampling (US), which calculates the potential of mean force (PMF) along a single reaction coordinate. Surprisingly, in spite of its widespread use, few validation studies have focused on the convergence of the free energy computed along a single path for specific cases, not addressing the reproducibility of such calculations in general. In this work, we therefore investigate the reproducibility and convergence of US along a standard distance-based reaction coordinate for various protein-protein and protein-ligand complexes, following commonly used guidelines for the setup. We show that repeating the complete US workflow can lead to differences of 2-20 kcal/mol in computed binding free energies. We attribute those discrepancies to small differences in the binding pathways. While these differences are unavoidable in the established US protocol, the popularity of the latter could hint at a lack of awareness of such reproducibility problems. To test if the convergence of PMF profiles can be improved if multiple pathways are sampled simultaneously, we performed additional simulations with an adaptive-biasing method, here the accelerated weight histogram (AWH) approach. Indeed, the PMFs obtained from AHW simulations are consistent and reproducible for the systems tested. To the best of our knowledge, our work is the first to attempt a systematic assessment of the pitfalls in one the most widely used protocols for computing binding affinities. We anticipate therefore that our results will provide an incentive for a critical reassessment of the validity of PMFs computed with US, and make a strong case to further benchmark the performance of adaptive-biasing methods for computing binding affinities.

Identification and Validation of New DNA-PKcs Inhibitors through High-Throughput Virtual Screening and Experimental Verification

DNA-PKcs is a crucial protein target involved in DNA repair and response pathways, with its abnormal activity closely associated with the occurrence and progression of various cancers. In this study, we employed a deep learning-based screening and molecular dynamics (MD) simulation-based pipeline, identifying eight candidates for DNA-PKcs targets. Subsequent experiments revealed the effective inhibition of DNA-PKcs-mediated cell proliferation by three small molecules (5025-0002, M769-1095, and V008-1080). These molecules exhibited anticancer activity with IC50 (inhibitory concentration at 50%) values of 152.6 μM, 30.71 μM, and 74.84 μM, respectively. Notably, V008-1080 enhanced homology-directed repair (HDR) mediated by CRISPR/Cas9 while inhibiting non-homologous end joining (NHEJ) efficiency. Further investigations into the structure-activity relationships unveiled the binding sites and critical interactions between these small molecules and DNA-PKcs. This is the first application of DeepBindGCN_RG in a real drug screening task, and the successful discovery of a novel DNA-PKcs inhibitor demonstrates its efficiency as a core component in the screening pipeline. Moreover, this study provides important insights for exploring novel anticancer therapeutics and advancing the development of gene editing techniques by targeting DNA-PKcs.

Novel Inhibitors of SARS-CoV-2 RNA Identified through Virtual Screening

We currently lack antivirals for most human viruses. In a quest for new molecules, focusing on viral RNA, instead of viral proteins, can represent a promising strategy. In this study, new inhibitors were identified starting from a published crystal structure of the tertiary SARS-CoV-2 RNA involved in the -1 programmed ribosomal frameshift. The pseudoknot structure was refined, and a virtual screening was performed using the repository of binders to the nucleic acid library, taking into consideration RNA flexibility. Hit compounds were validated against the wild-type virus and with a dual-luciferase assay measuring the frameshift efficiency. Several active molecules were identified. Our study reveals new inhibitors of SARS-CoV-2 but also highlights the feasibility of targeting RNA starting from virtual screening, a strategy that could be broadly applied to drug development.

A Joint Experimental and Theoretical Study on the Structural and Spectroscopic Properties of the Piv-Pro-d-Ser-NHMe Peptide

In this paper, we investigate the secondary structure of the Piv-Pro-d-Ser-NHMe peptide by means of nuclear magnetic resonance (NMR) and electronic circular dichroism (ECD) experiments, in conjunction with theoretical simulations based on molecular dynamics and time-dependent density functional theory calculations including polarizable embedding to account for solvent effects. The various experimental and theoretical protocols are assessed and validated, and are shown to provide a consistent description of the turn structure adopted by this peptide in solution. In addition, a simple fitting procedure is proposed to make the simulated and experimental ECD almost perfectly match. This full methodology is finally tested on another small peptide, enlightening its efficiency and robustness.

Accumulation of Hydrogen Bonds and van der Waals Interactions Determines Force Response between Two Parallel Cellulose Chains: Steered Molecular Dynamics Simulations

We investigated the response forces between two parallel cellulose chains during the shearing and tearing processes by using steered molecular dynamics simulations. It was found that there are two logarithmic dependencies between response force and pulling speed in shearing processes but only one in tearing, according to Bell's equation by fitting the f-ln v curve. The mechanism is that there are 2-fold interactions determining the force response between two parallel cellulose chains resisting chain separation during a shearing process. Our results indicate that hydrogen bonds dominate the interchain interactions in the fast pull mode (FPM) for shearing, while van der Waals interactions dominate in the slow pull mode (SPM). For tearing, the one-by-one breaking of hydrogen bonds and van der Waals interactions plays a main role.

MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics

Molecular dynamics (MD) simulation is a powerful tool for characterizing ligand-protein conformational dynamics and offers significant advantages over docking and other rigid structure-based computational methods. However, setting up, running, and analyzing MD simulations continues to be a multi-step process making it cumbersome to assess a library of ligands in a protein binding pocket using MD. We present an automated workflow that streamlines setting up, running, and analyzing Desmond MD simulations for protein-ligand complexes using machine learning (ML) models. The workflow takes a library of pre-docked ligands and a prepared protein structure as input, sets up and runs MD with each protein-ligand complex, and generates simulation fingerprints for each ligand. Simulation fingerprints (SimFP) capture protein-ligand compatibility, including stability of different ligand-pocket interactions and other useful metrics that enable easy rank-ordering of the ligand library for pocket optimization. SimFPs from a ligand library are used to build & deploy ML models that predict binding assay outcomes and automatically infer important interactions. Unlike relative free-energy methods that are constrained to assess ligands with high chemical similarity, ML models based on SimFPs can accommodate diverse ligand sets. We present two case studies on how SimFP helps delineate structure-activity relationship (SAR) trends and explain potency differences across matched-molecular pairs of (1) cyclic peptides targeting PD-L1 and (2) small molecule inhibitors targeting CDK9.

Cluster analysis as a tool for quantifying structure-transport properties in simulations of superconcentrated electrolyte

Using molecular dynamics simulations and graph-theory-based cluster analysis, we investigate the structure-transport properties of typical water-in-salt electrolytes. We demonstrate that ions exhibit distinct dynamics across different ionic clusters-namely, solvent-separated ion pairs (SSIPs), contact ion pairs (CIPs), and aggregates (AGGs). We assess the average proportions of various ionic species and their lifetimes. Our method reveals a dynamic decoupling of ion kinetics, with each species independently contributing to the overall molecular motion. This is evidenced by the fact that the total velocity autocorrelation function (VACF) and power spectrum can be expressed as a weighted sum of independent functions for each species. The experimental data on the ionic conductivity of the studied LiTFSI electrolytes align well with our theoretical predictions at various concentrations, based on the proportions and diffusion coefficients of free ions derived from our analysis. The insights gained into the solvation structures and dynamics of different ionic species enable us to elucidate the physical mechanisms driving ion transport in such superconcentrated electrolytes, providing a comprehensive framework for the future design and optimization of electrolytes.

New polycyclic polyprenylated acylphloroglucinols with antidepressant activities from Hypericum perforatum L

Six new polycyclic polyprenylated acylphloroglucinols (PPAPs), hyperidiones A-F (1-6), were obtained from Hypericum perforatum L. Their structures were characterized via extensive spectroscopic analyses, the circular dichroism data of the in situ formed [Mo2(OCOCH3)4] complexes, the nuclear magnetic resonance calculation with DP4 + probability analysis, and the calculated electronic circular dichroism (ECD) spectra. Compounds 1-6 are bicyclic polyprenylated acylphloroglucinols with a major bicyclo[3.3.1]nonane-2,4,9-trione skeleton. Notably, compound 1 is a rare PPAP with a hydroperoxy group, and a plausible biosynthetic pathway for 1 was proposed. Compounds 4 and 6 exhibited significant neuroprotective effects under 10 μM against corticosterone (CORT)-injured SH-SY5Y cells. Furthermore, compound 4 demonstrated a noteworthy antidepressant effect at the dose of 5 mg/kg in the tail suspension test (TST) of mice, which was equivalent to 5 mg/kg of fluoxetine. And it potentially exerted an antidepressant effect through the hypothalamic-pituitary-adrenal (HPA) axis.

HP35 Protein in the Mesopore of MIL-101(Cr) MOF: A Model to Study Cotranslocational Unfolding

The immobilization of enzymes in metal-organic framework (MOF) cages is important in biotechnology. In this context, the mechanism of translocation of proteins through the cavities of the MOF and the roles played by confinement and MOF chemistry in giving rise to stable protein intermediates that are otherwise transiently populated in the physiological environment are important questions to be addressed. These unexplored aspects are examined with villin headpiece (HP35) as a model protein confined within a mesopore of MIL-101(Cr) using molecular dynamics simulations. At equilibrium, the protein is located farther from the center of the cavity and closer to the MOF surface. Molecular interactions with the MOF partially unfold helix-1 at its N-terminus. Umbrella sampling simulations inform the range of conformations that HP35 undertakes during translocation from one cavity to another and associated changes in free energy. Relative to its equilibrium state within the cavity, the free energy barrier for the unfolded protein at the cage window is estimated to be 16 kcal/mol. This study of MOF-based protein conformation can also be a general approach to observing intermediates in folding-unfolding pathways.

Uncovering potential CDK9 inhibitors from natural compound databases through docking-based virtual screening and MD simulations

CONTEXT

Cyclin-dependent kinase 9 (CDK9) plays a significant role in gene regulation and RNA polymerase II transcription under basal and stimulated conditions. The upregulation of transcriptional homeostasis by CDK9 leads to various malignant tumors and therefore acts as a valuable drug target in addressing cancer incidences. Ongoing drug development endeavors targeting CDK9 have yielded numerous clinical candidate molecules currently undergoing investigation as potential CDK9 modulators, though none have yet received Food and Drug Administration (FDA) approval.

METHODS

In this study, we employ in silico approaches including the molecular docking and molecular dynamics simulations for the virtual screening over the natural compounds library to identify novel promising selective CDK9 inhibitors. The compounds derived from the initial virtual screening were subsequently employed for molecular dynamics simulations and binding free energy calculations to study the compound's stability under virtual physiological conditions. The first-generation CDK inhibitor Flavopiridol was used as a reference to compare with our novel hit compound as a CDK9 antagonist. The 500-ns molecular dynamics simulation and binding free energy calculation showed that two natural compounds showed better binding affinity and interaction mode with CDK9 receptors over the reference Flavopiridol. They also showed reasonable figures in the predicted absorption, distribution, metabolism, excretion, and toxicity (ADMET) calculations as well as in computational cytotoxicity predictions. Therefore, we anticipate that the proposed scaffolds could contribute to developing potential and selective CDK9 inhibitors subjected to further validations.

Mechanism of Cationic Lipid Induced DNA Condensation: Lipid-DNA Coordination and Divalent Cation Charge Fluctuations

The condensation of nucleic acids by lipids is a widespread phenomenon in biology with crucial implications for drug delivery. However, the mechanisms of DNA assembly in lipid bilayers remain insufficiently understood due to challenges in measuring and assessing each component's contribution in the lipid-DNA-cation system. This study uses all-atom molecular dynamics simulations to investigate DNA condensation in cationic lipid bilayers. Our exhaustive exploration of the thermodynamic factors reveals unique roles for phospholipid head groups and cations. We observed that bridging cations between lipid and DNA drastically reduce charges, while mobile magnesium cations "ping-ponging" between double strands create charge fluctuations. While the first factor stabilizes the DNA-lipid complex, the latter creates attractive forces to induce the spontaneous condensation of DNAs. This novel mechanism not only sheds light on the current data regarding cationic lipid-induced DNA condensation but also provides potential design strategies for creating efficient gene delivery vectors for drug delivery.

Inhibition of the Early-Stage Cross-Amyloid Aggregation of Amyloid-β and IAPP via EGCG: Insights from Molecular Dynamics Simulations

Amyloid-β (Aβ) and islet amyloid polypeptide (IAPP) are small peptides that have the potential to not only self-assemble but also cross-assemble and form cytotoxic amyloid aggregates. Recently, we experimentally investigated the nature of Aβ-IAPP coaggregation and its inhibition by small polyphenolic molecules. Notably, we found that epigallocatechin gallate (EGCG) had the ability to reduce heteroaggregate formation. However, the precise molecular mechanism behind the reduction of heteroaggregates remains unclear. In this study, the dimerization processes of Aβ40 and IAPP peptides with and without EGCG were characterized by the enhanced sampling technique. Our results showed that these amyloid peptides exhibited a tendency to form a stable heterodimer, which represented the first step toward coaggregation. Furthermore, we also found that the EGCG regulated the dimerization process. In the presence of EGCG, well-tempered metadynamics simulation indicated a notable shift in the bound state toward a greater center of mass (COM) distance. Additionally, the presence of EGCG led to a significant increase in the free energy barrier height (∼15k B T) along the COM distance, and we observed a transition state between the bound and unbound states. Our findings also unveiled that the EGCG formed a greater number of hydrogen bonds with Aβ40, effectively obstructing the dimer formation. In addition, we carried out microseconds of all-atom conventional molecular dynamics (cMD) simulations to investigate the formation of both hetero- and homo-oligomer states by these peptides. MD simulations illustrated that EGCG played a significant role in preventing oligomer formation by reducing the content of β-sheets in the peptide. Collectively, our results offered valuable insight into the mechanism of cross-amyloid aggregation between Aβ40 and IAPP and the inhibition effect of EGCG on the heteroaggregation process.

Discovery of Novel Allosteric SHP2 Inhibitor Using Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation, and Principal Component Analysis

SHP2 belongs to a cytoplasmic non-receptor protein tyrosine phosphatase class. It plays a critical role in the development of various cancers, such as gastric cancer, leukemia, and breast cancer. Thus, SHP2 has gained the interest of researchers as a potential target for inhibiting tumor cell proliferation in SHP2-dependent cancers. This study employed pharmacophore-based virtual screening, molecular docking, molecular dynamic (MD) simulations, MM/PBSA, and principal component analysis (PCA), followed by ADME prediction. We selected three potential hits from a collective database of more than one million chemical compounds. The stability of these selected hit-protein complexes was analyzed using 500 ns MD simulations and binding free energy calculations. The identified hits Lig_1, Lig_6, and Lig_14 demonstrated binding free energies of -161.49 kJ/mol, -151.28 kJ/mol, and -107.13 kJ/mol, respectively, compared to the reference molecule (SHP099) with a ΔG of -71.48 kJ/mol. Our results showed that the identified compounds could be used as promising candidates for selective SHP2 allosteric inhibition in cancer.

Deciphering the Selectivity of CBL-B Inhibitors Using All-Atom Molecular Dynamics and Machine Learning

We employ a combination of accelerated molecular dynamics and machine learning to unravel how the dynamic characteristics of CBL-B and C-CBL confer their binding affinity and selectivity for ligands from subtle structural disparities within their binding pockets and dissociation pathways. Our predictive model of dissociation rate constants (k off) demonstrates a moderate correlation between predicted k off and experimental IC50 values, which is consistent with experimental k off and τ-random accelerated molecular dynamics (τRAMD) results. By employing a linear regression of dissociation trajectories, we identified key amino acids in binding pockets and along the dissociation paths responsible for activity and selectivity. These amino acids are statistically significant in achieving activity and selectivity and contribute to the primary structural discrepancies between CBL-B and C-CBL. Moreover, the binding free energies calculated from molecular mechanics with generalized Born and surface area solvation (MM/GBSA) highlight the ΔG difference between CBL-B and C-CBL. The k off prediction, together with the key amino acids, provides important guides for designing drugs with high selectivity.

Self-association as a solubility limiting factor of riboflavin in aqueous media

Single crystal X-ray diffraction analysis of needle shaped riboflavin (RF) crystals revealed π-stacking of RF's isoalloxazine units (distance: 3.643-3.313 Å) with syn-orientated ribityl chains. In line with this, classical molecular dynamics (MD) (400 ns) using an isobaric-isothermal (NPT) ensemble of eight RF in a water box (〈V〉 ∼ 508.62 nm3, 〈p〉 = 1.11 bar) revealed anti-aligned aggregation of RF in water (COM-distance: 4 Å). Comparing umbrella sampling for the separation of two RF molecules to the separation of two lumichrome molecules, the similar mean potential force for the separation of RF and lumichrome (22.8 kJ mol-1; 24.4 kJ mol-1) proved dispersive interactions as the origin of RF's aggregation. Though stacking of RF is the major water-solubility limiting factor, the conformation of RF's ribityl chain may alter the solubility in water. Both, MD (in water) and COSMO-RS (in water continuum) predicted that conformations of RF with an extended ribityl chain are thermodynamically preferred over any conformations with internal hydrogen bonds between hydroxyl groups and nitrogen/oxygen atoms of the pyrimidine moiety of the flavin ring. Interestingly, COSMO-RS predicted the solubility of the extended conformation to be significantly lower than the latter leading to the very low average solubility of RF. Nuclear Overhauser effect measurements (NOESY) of the structurally related sodium riboflavin 5'-monophosphate (RF-PO4) in deuterium oxide confirmed π-stacking of the isoalloxazine rings. In conformity with the 350 times higher water-solubility of RF-PO4, NOESY also indicated a contorted conformation of the ribityl phosphate chain, whereas, for RF, indications for a contorted chain were not observed.

The secondary structure of diatom silaffin peptide R5 determined by two-dimensional infrared spectroscopy

Diatoms, unicellular marine organisms, harness short peptide repeats of the protein silaffin to transform silicic acid into biosilica nanoparticles. This process has been a white whale for material scientists due to its potential in biomimetic applications, ranging from medical to microelectronic fields. Replicating diatom biosilicification will depend on a thorough understanding of the silaffin peptide structure during the reaction, yet existing models in the literature offer conflicting views on peptide folding during silicification. In our study, we employed two-dimensional infrared spectroscopy (2DIR) within the amide I region to determine the secondary structure of the silaffin repeat unit 5 (R5), both pre- and post-interaction with silica. The 2DIR experiments are complemented by molecular dynamics (MD) simulations of pure R5 reacting with silicate. Subsequently, theoretical 2DIR spectra calculated from these MD trajectories allowed us to compare calculated spectra with experimental data, and to determine the diverse structural poses of R5. Our findings indicate that unbound R5 predominantly forms β-strand structures alongside various atypical secondary structures. Post-silicification, there's a noticeable shift: a decrease in β-strands coupled with an increase in turn-type and bend-type configurations. We theorize that this structural transformation stems from silicate embedding within R5's hydrogen-bond network, prompting the peptide backbone to contract and adapt around the biosilica precursors.

Nanostructured lipopeptide-based membranomimetics for stabilizing bacteriorhodopsin

Nanostructured 7-9-residue cyclic and unstructured lipopeptide-based facial detergents have been engineered to stabilize the model integral membrane protein, bacteriorhodopsin. Formation of a cylindrical-type micelle assembly induced by facial amphipathic lipopeptides resembles a biological membrane more effectively than conventional micelles. The hydrophobic face of this cylindrical-type micelle provides extended stability to the membrane protein and the hydrophilic surface interacts with an aqueous environment. In our present study, we have demonstrated experimentally and computationally that lipopeptide-based facial detergents having an unstructured or β-turn conformation can stabilize membrane proteins. However, constrained peptide detergents can provide enhanced stability to bacteriorhodopsin. In this study, we have computationally examined the structural stability of bacteriorhodopsin in the presence of helical, beta-strand, and cyclic unstructured peptide detergents, and conventional detergent-like peptides. Our study demonstrates that optimal membranomimetics (detergents) for stabilizing a specific membrane protein can be screened based on the following criteria: (i) hydrodynamic radii of the self-assembled peptide detergents, (ii) stability assay of detergent-encased membrane proteins, (iii) percentage covered area of detergent-encased membrane proteins obtained computationally and (iv) protein-detergent interaction energy.

Complex dynamics of partially freezable confined water revealed by combined experimental and computational studies

We investigate water dynamics in mesoporous silica across partial crystallization by combining broadband dielectric spectroscopy (BDS), nuclear magnetic resonance (NMR), and molecular dynamics simulations (MDS). Exploiting the fact that not only BDS but also NMR field-cycling relaxometry and stimulated-echo experiments provide access to dynamical susceptibilities in broad frequency and temperature ranges, we study both the fully liquid state above the melting point Tm and the dynamics of coexisting water and ice phases below this temperature. It is found that partial crystallization leads to a change in the temperature dependence of rotational correlation times τ, which occurs in addition to previously reported dynamical crossovers of confined water and depends on the pore diameter. Furthermore, we observe that dynamical susceptibilities of water are strongly asymmetric in the fully liquid state, whereas they are much broader and nearly symmetric in the partially frozen state. Finally, water in the nonfreezable interfacial layer below Tm does not exhibit a much debated dynamical crossover at ∼220 K. We argue that its dynamics is governed by a static energy landscape, which results from the interaction with the bordering silica and ice surfaces and features a Gaussian-like barrier distribution. Consistently, our MDS analysis of the motional mechanism reveals a hopping motion of water in thin interfacial layers. The rotational correlation times of the confined ice phases follow Arrhenius laws. While the values of τ depend on the pore diameter, freezable water in various types of confinements and mixtures shows similar activation energies of Ea ≈ 0.43 eV.

Stable peptide-assembled nanozyme mimicking dual antifungal actions

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

Organic-solvent ditch overlap in reversed-phase liquid chromatography: A molecular dynamics simulation study in cylindrical 6-12 nm-diameter pores

Mass transport through the mesopore space of a reversed-phase liquid chromatography (RPLC) column depends on the properties of the chromatographic interface, particularly on the extent of the organic-solvent ditch that favors the analyte surface diffusivity. Through molecular dynamics simulations in cylindrical RPLC mesopore models with pore diameters between 6 and 12 nm we systematically trace the evolution of organic-solvent ditch overlap due to spatial confinement in the mesopore space of RPLC columns for small-molecule separations. Each pore model of a silica-based, endcapped, C18-stationary phase is equilibrated with two mobile phases of comparable elution strength, namely 70/30 (v/v) water/acetonitrile and 60/40 (v/v) water/methanol, to consider the influence of the mobile-phase composition on the onset of organic-solvent ditch overlap. The simulations show that, as the pore diameter decreases from 9 to 6 nm, the bonded-phase density extends and compacts towards the pore center, which leads to increased accumulation of organic-solvent excess and thus enhanced organic-solvent diffusivity in the ditch. Because the acetonitrile ditch is more pronounced than the methanol ditch, acetonitrile ditch overlap sets in at less severe spatial confinement than methanol ditch overlap. The pore-averaged methanol and acetonitrile diffusivities are considerably raised by ditch overlap in the 6 nm-diameter pore, but also benefit from the ditch (without overlap) in the 7 to 12 nm-diameter pores, whereby local and pore-averaged effects are generally larger for acetonitrile than methanol.

Semiarbitrary qPCR for Sensitive Detection of Circulating miRNA via Terminal Deoxynucleotidyl Transferase-Assisted RNA-Primed DNA Polymerization

Circulating microRNAs (miRNAs) have recently emerged as noninvasive disease biomarkers. Quantitative detection of circulating miRNAs could offer significant information for clinical diagnosis due to its significance in the development of biological processes. In response to the current challenges of circulating miRNA detection, we introduce a sensitive, selective, and versatile circulating miRNA detection strategy using terminal deoxynucleotidyl transferase (TdT)-catalyzed RNA-primed DNA polymerization (TCRDP) coupled with semiarbitrary qPCR (SAPCR). Semiarbitrary qPCR was first developed here to detect long fragment targets with only a short-known sequence or to detect a short fragment target after extension with terminal transferase. Besides, the subsequent results show that TdT has a preference for RNA, particularly for extending RNAs with purine-rich and unstructured ends. Consequently, utilizing this assay, we have successfully applied it to the quantitative analysis of circulating miR-122 in animal models, a sensitive and informative biomarker for drug-induced liver injury, and as low as 200 zmol of the target is detected with desirable specificity and sensitivity, indicating that the TCRDP-SAPCR can offer a promising platform for nucleic acids analysis.

Membrane-mediated modulation of mitochondrial physiology by terahertz waves

Extensive studies have demonstrated the diverse impacts of electromagnetic waves at gigahertz and terahertz (THz) frequencies on cytoplasmic membrane properties. However, there is little evidence of these impacts on intracellular membranes, particularly mitochondrial membranes crucial for mitochondrial physiology. In this study, human neuroblast-like cells were exposed to continuous 0.1 THz radiation at an average power density of 33 mW/cm2. The analysis revealed that THz exposure significantly altered the mitochondrial ultrastructure. THz waves enhanced the enzymatic activity of the mitochondrial respiratory chain but disrupted supercomplex assembly, compromising mitochondrial respiration. Molecular dynamics simulations revealed altered rates of change in the quantity of hydrogen bonds and infiltration of water molecules in lipid bilayers containing cardiolipin, indicating the specific behavior of cardiolipin, a signature phospholipid in mitochondria, under THz exposure. These findings suggest that THz radiation can significantly alter mitochondrial membrane properties, impacting mitochondrial physiology through a mechanism related to mitochondrial membrane, and provide deeper insight into the bioeffects of THz radiation.

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

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

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

Organic Solvent Boosts Charge Storage and Charging Dynamics of Conductive MOF Supercapacitors

Conductive metal-organic frameworks (c-MOFs) and ionic liquids (ILs) have emerged as auspicious combinations for high-performance supercapacitors. However, the nanoconfinement from c-MOFs and high viscosity of ILs slow down the charging process. This hindrance can, however, be resolved by adding solvent. Here, constant-potential molecular simulations are performed to scrutinize the solvent impact on charge storage and charging dynamics of MOF-IL-based supercapacitors. Conditions for >100% enhancement in capacity and ≈6 times increase in charging speed are found. These improvements are confirmed by synthesizing near-ideal c-MOFs and developing multiscale models linking molecular simulations to electrochemical measurements. Fundamentally, the findings elucidate that the solvent acts as an "ionophobic agent" to induce a substantial enhancement in charge storage, and as an "ion traffic police" to eliminate convoluted counterion and co-ion motion paths and create two distinct ion transport highways to accelerate charging dynamics. This work paves the way for the optimal design of MOF supercapacitors.

Structural Evolution of Bacterial Polyphosphate Degradation Enzyme for Phosphorus Cycling

Living organisms ranging from bacteria to animals have developed their own ways to accumulate and store phosphate during evolution, in particular as the polyphosphate (polyP) granules in bacteria. Degradation of polyP into phosphate is involved in phosphorus cycling, and exopolyphosphatase (PPX) is the key enzyme for polyP degradation in bacteria. Thus, understanding the structure basis of PPX is crucial to reveal the polyP degradation mechanism. Here, it is found that PPX structure varies in the length of ɑ-helical interdomain linker (ɑ-linker) across various bacteria, which is negatively correlated with their enzymatic activity and thermostability - those with shorter ɑ-linkers demonstrate higher polyP degradation ability. Moreover, the artificial DrPPX mutants with shorter ɑ-linker tend to have more compact pockets for polyP binding and stronger subunit interactions, as well as higher enzymatic efficiency (kcat/Km) than that of DrPPX wild type. In Deinococcus-Thermus, the PPXs from thermophilic species possess a shorter ɑ-linker and retain their catalytic ability at high temperatures (70 °C), which may facilitate the thermophilic species to utilize polyP in high-temperature environments. These findings provide insights into the interdomain linker length-dependent evolution of PPXs, which shed light on enzymatic adaption for phosphorus cycling during natural evolution and rational design of enzyme.

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

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

Structural dynamics of clinically-reported VUS in the BARD1 ARD-BRCT region to predict the molecular basis of alterations

The functional domains of BARD1, comprise the Ankyrin Repeat Domain (ARD), C-Terminal domains (BRCTs), and a linker between ARD and the BRCTs, which are known to bind to Cleavage stimulation Factor complex-subunit of 50 kDa (CstF-50). The pathogenic mutation Q564H in the BARD1 ARD-linker-BRCT region has been reported to abrogate the binding between BARD1 and CstF-50. Intermediate penetrance variants of BARD1 are associated with the occurrence of breast cancer. Therefore, seven missense variants of unknown significance (VUS), L447V, P454L, N470S, V507M, I509T, C557S, and Q564H of BARD1, reported in the ARD domain and the linker region were evaluated via molecular dynamics (MD) simulations. The mutants revealed statistically significantly different distributions of RMSD (root mean square deviation), residuewise RMSF (root mean square fluctuation), Rg (radius of gyration), SASA (solvent accessible surface area), and COM (centre of mass)-to-COM distance between the ARD and the BRCT repeat, between the wild type and each mutant. The secondary structural composition of the mutants was slightly altered relative to that of the wild type. However, the reported in-silico based prediction require further validation using in-vitro, biophysical and structure-based approachCommunicated by Ramaswamy H. Sarma.

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

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

Chiral Supramolecular Nanofibers Regulated Tumor-Derived Exosomes Secretion for Constructing an Anti-Tumor Extracellular Microenvironment

Tumor-derived exosomes (TDEs) induced extracellular microenvironment has recently been validated to be critical for tumor progression and metastasis, however, remodeling it for oncotherapy still remains a major challenge due to difficulty in regulation of TDEs secretion. Herein, the supramolecular chiral nanofibers, composed of L/D-phenylalanine derivates (L/D-Phe) and linear hyaluronic acid (HA), are successfully employed to construct TDEs induced anti-tumor extracellular microenvironment. The left-handed L-Phe @HA nanofibers significantly inhibit TDEs secretion into extracellular microenvironment, which results in suppression of tumor proliferation and metastasis in vitro and vivo. Biological assays and theoretical modeling reveal that these results are mainly attributed to strong adsorption of the key exosomes transporters (Ras-related protein Rab-27A and synaptosome-associated protein 23) on left-handed L-Phe @HA nanofibers via enhanced stereoselective interaction, leading to degradation and phosphorylated dropping of exosomes transporters. Subsequently, transfer function of exosomes transporters is limited, which causes remarkable inhibition of TDEs secretion. These findings provide a promising novel insight of chiral functional materials to establish an anti-tumor extracellular microenvironment via regulation of TDEs secretion.

Repurposing phytochemicals of Citrullus colocynthis against maltase-glucoamylase using molecular docking, MMGBSA, MD simulation and linear regression to identify potential anti-diabetic compounds

Diabetes is a common lifestyle disorder found in populations of different age groups. Maltase-glucoamylase catalyses the release of the glucose molecule in the final enzymatic reaction of starch digestion; therefore, inhibition of maltase-glucoamylase is one of the approaches in the development of therapeutics for diabetes. Citrullus colocynthis is commonly recommended in Ayurveda for the treatment of diabetes. The current study applied a structure-based drug design approach to repurpose the phytochemicals of Citrullus colocynthis to identify potential inhibitors for maltase-glucoamylase. 70 phytochemicals of Citrullus colocynthis were screened against maltase-glucoamylase and top 5 molecules 8-p-hydroxybenzylisovitexin, isoorientin, cucurbitacin B, cucurbitacin E, and cucurbitacin I with significant binding energy of -10 kcal/mol, -9.9 kcal/mol, -9.6 kcal/mol, -9.2 kcal/mol, and -7.7 kcal/mol were identified. Furthermore, MMGBSA, pharmacokinetics properties and toxicity prediction were performed on the five identified molecules and top 3 molecules were selected for molecular dynamics (MD) simulation. It was observed from the structural flexibility and dynamic behaviour of the systems that conformational changes were noticed in the complexes as compared to its native state, which suggests that the 3 molecules, namely 8-p-hydroxybenzylisovitexin, isoorientin, and cucurbitacin I of Citrullus colocynthis may act as inhibitors for maltase-glucoamylase.Communicated by Ramaswamy H. Sarma.

Structure elucidation of a multi-modular recombinant endoglucanase, AtGH9C-CBM3A-CBM3B from Acetivibrio thermocellus ATCC 27405 and its substrate binding analysis

Cellulases from GH9 family show endo-, exo- or processive endocellulase activity, but the reason behind the variation is unclear. A GH9 recombinant endoglucanase, AtGH9C-CBM3A-CBM3B from Acetivibrio thermocellus was structurally characterized for conformation, binding and dynamics assessment. Modeled AtGH9C-CBM3A-CBM3B depicted (α/α)6-barrel structure with Asp98, Asp101 and Glu489 acting as catalytic triad. CD results revealed 25.2 % α-helix, 18.4 % β-sheet and rest 56.4 % of random coils, corroborating with predictions from PSIPRED and SOPMA. MD simulation of AtGH9C-CBM3A-CBM3B bound cellotetraose showed structural stability and global compactness with lowered RMSD values (1.5 nm) as compared with only AtGH9C-CBM3A-CBM3B (1.8 nm) for 200 ns. Higher fluctuation in RMSF values in far-positioned CBM3B pointed to its redundancy in substrate binding. Docking studies showed maximum binding with cellotetraose (ΔG = -5.05 kcal/mol), with reduced affinity towards ligands with degree of polymerization (DP) lower (DP < 4) or higher than 4 (DP > 4). Processivity index displayed the enzyme to be processive with loop 3 (342-379 aa) possibly blocking the non-reducing end of cellulose chain, resulting in cellotetraose release. SAXS analysis of AtGH9C-CBM3A-CBM3B at 5 mg/mL displayed monodispersed state with fist-and-elbow shape in solution. Negative zeta potential of -24 mV at 5 mg/mL indicated stability and free from aggregation.