Designing a structure-function alphabet of helix based on reduced amino acid clusters.

Several simple secondary structures could form complex and diverse functional proteins, meaning that secondary structures may contain a lot of hidden information and are arranged according to certain principles, to carry enough information of functional specificity and diversity. However, these inner information and principles have not been understood systematically. In our study, we designed a structure-function alphabet of helix based on reduced amino acid clusters to describe the typical features of helices and delve into the information. Firstly, we selected 480 typical helices from membrane proteins, zymoproteins, transcription factors, and other proteins to define and calculate the interval range, and the helices are classified in terms of hydrophilicity, charge and length: (1) hydrophobic helix (≤43%), amphiphilic helix (43%∼71%), and hydrophilic helix (≥71%). (2) positive helix, negative helix, electrically neutral helix and uncharged helix. (3) short helix (≤8 aa), medium-length helix (9-28 aa), and long helix (≥29 aa). Then, we designed an alphabet containing 36 triplet codes according to the above classification, so that the main features of each helix can be represented by only three letters. This alphabet not only preliminarily defined the helix characteristics, but also greatly reduced the informational dimension of protein structure. Finally, we present an application example to demonstrate the value of the structure-function alphabet in protein functional determination and differentiation.

Anti-necroptosis and anti-ferroptosis compounds from the Deep-Sea-Derived fungus Aspergillus sp. MCCC 3A00392.

Eight undescribed (1-8) and 46 known compounds (9-54) were isolated from the deep-sea-derived Aspergillus sp. MCCC 3A00392. Compounds 1-3 were three novel oxoindolo diterpenoids, 4-6 were three bisabolane sesquiterpenoids, while 7 and 8 were two monocyclic cyclopropanes. Their structures were established by exhaustive analyses of the HRESIMS, NMR, and theoretical calculations of the NMR data and ECD spectra. Compounds 10, 33, 38, and 39 were able to inhibit tumor necrosis factor (TNF)-induced necroptosis in murine L929 cell lines. Functional experiments verified that compounds 10 and 39 inhibited necroptosis by downregulating the phosphorylation of RIPK3 and MLKL. Moreover, compound 39 also reduced the phosphorylation of RIPK1. Compounds 10, 33, and 34 displayed potent inhibitory activities against RSL-3 induced ferroptosis with the EC50 value of 3.0 µM, 0.4 µM, and 0.1 µM, respectively. Compound 10 inhibited ferroptosis by the downregulation of HMOX1, while compounds 33 and 34 inhibited ferroptosis through regulation of NRF2/SLC7A11/GCLM axis. However, these compounds only showed weak effect in either the necroptosis or ferroptosis relative mouse disease models. Further studies of pharmacokinetics and pharmacodynamics might improve their in vivo bioactivities.

Ferroptosis Inhibitory Compounds from the Deep-Sea-Derived Fungus Penicillium sp. MCCC 3A00126.

Two new xanthones (1 and 2) were isolated from the deep-sea-derived fungus Penicillium sp. MCCC 3A00126 along with 34 known compounds (3-36). The structures of the new compounds were established by spectroscopic data. The absolute configuration of 1 was validated by comparison of experimental and calculated ECD spectra. All isolated compounds were evaluated for cytotoxicity and ferroptosis inhibitory activities. Compounds 14 and 15 exerted potent cytotoxicity against CCRF-CEM cells, with IC50 values of 5.5 and 3.5 µM, respectively, whereas 26, 28, 33, and 34 significantly inhibited RSL3-induced ferroptosis, with EC50 values of 11.6, 7.2, 11.8, and 2.2 µM, respectively.

Chemical Constituents of the Deep-sea Gammarid Shrimp-Derived Fungus Penicillium citrinum XIA-16.

One new alkaloid, (S)-2-acetamido-4-(2-(methylamino)phenyl)-4-oxobutanoic acid (1), was isolated from the deep-sea-derived Penicillium citrinum XIA-16, together with 25 known compounds including ten polyketones (2-11), eight alkaloids (12-19), six steroids (20-25), and a fatty acid (26). Their planar and relative structures were determined by an analysis of 1D and 2D nuclear magnetic resonance (NMR) as well as high resolution electrospray ionization mass spectroscopy (HR-ESI-MS) data. The absolute configuration of 1 was determined by comparison of the experimental and calculated electronic circular dichroism (ECD) spectra. Penicitrinol B (6) significantly inhibited RSL3-induced ferroptosis (EC50 =2.0 µM) by reducing lipid peroxidation and heme oxygenase 1 (HMOX1) expression. Under the concentration of 10 µM, penicitrinol A (7) was able to inhibit cuproptosis with the cell viabilities of 68.2 % compared to the negative control (copper and elesclomol) with the cell viabilities of 14.8 %.

Fast Feature Extraction Method for Brillouin Scattering Spectrum of OPGW Optical Cable Based on BOTDR.

Brillouin optical time domain reflectometry (BOTDR) detects fiber temperature and strain data and represents one of the most critical ways of identifying abnormal conditions such as ice coverage and lightning strikes on optical fiber composite overhead ground wire (OPGW) cable. Existing BOTDR extracts brillouin frequency shift (BFS) features with cumulative averaging and curve fitting. BFS feature extraction is slow for long-distance measurements, making realizing real-time measurements on fiber optic cables challenging. We propose a fast feature extraction method for block matching and 3D filtering (BM3D) + Sobel brillouin scattering spectroscopy (BGS). BM3D takes the advantage of non-local means (NLM) and wavelet denoising (WD) and utilizes the spatial-domain non-local principle to enhance the denoising in the transform domain. The global filtering capability of BM3D is utilized to filter out the low cumulative average BGS noise and the BFS feature extraction is completed using Sobel edge detection. Simulation verifies the feasibility of the algorithm, and the proposed method is embedded in BOTDR to measure 30 km of actual OPGW line. The experimental results show that under the same conditions, the processing time of this method is reduced by 37 times compared to that with the 50,000-time cumulative averaging + levenberg marquardt (LM) algorithm without severe distortion of the reference resolution. The method improves the sensor demodulation speed by using image processing technology without changing the existing hardware equipment, which is expected to be widely used in the new generation of BOTDR.

Isolation, Characterization, and Anti-Idiopathic Pulmonary Fibrosis Activity of a Fucoidan from Costaria costata.

Pulmonary fibrosis is a chronic, progressive, and fatal disease of the interstitial lung. There is currently a lack of efficient therapy to reverse the prognosis of patients. In this study, a fucoidan from Costaria costata was isolated, and its anti-idiopathic fibrosis activity was investigated both in vitro and in vivo. The chemical composition analysis showed that C. costata polysaccharide (CCP) consists of galactose and fucose as the main monosaccharides with a sulfate group content of 18.54%. Further study found that CCP could resist TGF-ß1-induced epithelial-mesenchymal transition (EMT) in A549 cells by inhibiting the TGF-ß/Smad and PI3K/AKT/mTOR signaling pathways. Moreover, in vivo study found that CCP treatment alleviated bleomycin (BLM)-stimulated fibrosis and inflammation in mice lung tissue. In conclusion, the present study suggests that CCP could protect the lung from fibrosis by relieving the EMT process and inflammation in lung cells.

Local charge transport at different interfaces in epoxy composites.

Charge transport in insulating composites is fundamental to designing high performance in electrical breakdown strength processes. A fundamental understanding of the charge transport at nanoscale in insulating composites remains elusive. Herein, we fabricate two types of interfaces in epoxy (EP) composites (Al2O3/EP and bubble/EP, respectively). Then the local dynamic charge mobility behavior and charge density are explored usingin situKelvin probe force microscopy. After the external voltage in the horizontal direction is applied, significant differences are demonstrated in the evolution of charge transport for epoxy matrix, filler/bubble, and their interface, respectively. The interface between Al2O3and epoxy is easier to accumulate the negative charges and introduce shallow traps. Lots of positive charges are located around a bubble where deeper traps are present and could prevent charge migration. Thus, this work offers extended experimental support to understanding the mechanism of charge transport in dielectric composites.

Heuristic Routing Algorithms for Time-Sensitive Networks in Smart Factories.

Over recent years, traditional manufacturing factories have been accelerating their transformation and upgrade toward smart factories, which are an important concept within Industry 4.0. As a key communication technology in the industrial internet architecture, time-sensitive networks (TSNs) can break through communication barriers between subsystems within smart factories and form a common network for various network flows. Traditional routing algorithms are not applicable for this novel type of network, as they cause unnecessary congestion and latency. Therefore, this study examined the classification of TSN flows in smart factories, converted the routing problem into two graphical problems, and proposed two heuristic optimization algorithms, namely GATTRP and AACO, to find the optimal solution. The experiments showed that the algorithms proposed in this paper could provide a more reasonable routing arrangement for various TSN flows with different time sensitivities. The algorithms could effectively reduce the overall delay by up to 74% and 41%, respectively, with promising operating performances.

Pattern-free generation and quantum mechanical scoring of ring-chain tautomers.

In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless, for some types of organic compounds, including sugars, warfarin analogs, fluorescein dyes and some drug-like compounds, ring-chain tautomerism cannot be ignored. In this work, a novel ring-chain tautomer generation algorithm is presented. It differs from previously proposed solutions in that it does not rely on hard-coded patterns of proton migrations and bond rearrangements, and should therefore be more general and maintainable. We deploy this algorithm as part of a workflow which provides an automated solution for tautomer generation and scoring. The workflow identifies protonatable and deprotonatable sites in the molecule using a previously described approach based on rapid micro-pKa prediction. These data are used to distribute the active protons among the protonatable sites exhaustively, at which point alternate resonance structures are considered to obtain pairs of atoms with opposite formal charge. These pairs are connected with a single bond and a 3D undistorted geometry is generated. The scoring of the generated tautomers is performed with a subsequent density functional theory calculation employing an implicit solvent model. We demonstrate the performance of our workflow on several types of organic molecules known to exist in ring-chain tautomeric equilibria in solution. In particular, we show that some ring-chain tautomers not found using previously published algorithms are successfully located by ours.

Tartary Buckwheat (Fagopyrum tataricum) NAC Transcription Factors FtNAC16 Negatively Regulates of Pod Cracking and Salinity Tolerant in Arabidopsis.

The thick and hard fruit shell of Fagopyrum tataricum (F. tataricum) represents a processing bottleneck. At the same time, soil salinization is one of the main problems faced by modern agricultural production. Bioinformatic analysis indicated that the F. tataricum transcription factor FtNAC16 could regulate the hull cracking of F. tataricum, and the function of this transcription factor was verified by genetic transformation of Arabidopsis thaliana (A. thaliana). Phenotypic observations of the wild-type (WT), OE-FtNAC16, nst1/3 and nst1/3-FtNAC16 plant lines confirmed that FtNAC16 negatively regulated pod cracking by downregulating lignin synthesis. Under salt stress, several physiological indicators (POD, GSH, Pro and MDA) were measured, A. thaliana leaves were stained with NBT (Nitroblue Tetrazolium) and DAB (3,3'-diaminobenzidine), and all genes encoding enzymes in the lignin synthesis pathway were analyzed. These experiments confirmed that FtNAC16 increased plant sensitivity by reducing the lignin content or changing the proportions of the lignin monomer. The results of this study may help to elucidate the possible association between changes in lignin monomer synthesis and salt stress and may also contribute to fully understanding the effects of FtNAC16 on plant growth and development, particularly regarding fruit pod cracking and environmental adaptability. In future studies, it may be useful to obtain suitable cracking varieties and salt-tolerant crops through molecular breeding.

Evaluation of Free Energy Calculations for the Prioritization of Macrocycle Synthesis.

A tremendous research and development effort was exerted toward combating chronic hepatitis C, ultimately leading to curative oral treatments, all of which are targeting viral proteins. Despite the advantage of numerous targets allowing for broad hepatitis C virus (HCV) genotype coverage, the only host target inhibitors that advanced into clinical development were Cyclosporin A based cyclophilin inhibitors. While cyclosporin-based molecules typically require a fermentation process, Gilead successfully pursued a fully synthetic, oral program based on Sanglifehrin A. The drug discovery process, though greatly helped by facile crystallography, was still hampered by the limitations in the accuracy of predictive computational methods for prioritizing compound ideas. Recent advances in accuracy and speed of free energy perturbation (FEP) methods, however, are attractive for prioritizing and derisking synthetically challenging molecules and potentially could have had a significant impact on the speed of the development of this program. Here in our simulated prospective study, the binding free energies of 26 macrocyclic cyclophilin inhibitors were blindly predicted using FEP+ to test this hypothesis. The predictions had a low mean unsigned error (MUE) (1.1 kcal/mol) and accurately reproduced many design decisions from the program, suggesting that FEP+ has the potential to drive synthetic chemistry efforts by more accurately ranking compounds with nonintuitive structure-activity relationships (SARs).

Revised M06-L functional for improved accuracy on chemical reaction barrier heights, noncovalent interactions, and solid-state physics.

We present the revM06-L functional, which we designed by optimizing against a larger database than had been used for Minnesota 2006 local functional (M06-L) and by using smoothness restraints. The optimization strategy reduced the number of parameters from 34 to 31 because we removed some large terms that increased the required size of the quadrature grid and the number of self-consistent-field iterations. The mean unsigned error (MUE) of revM06-L on 422 chemical energies is 3.07 kcal/mol, which is improved from 3.57 kcal/mol calculated by M06-L. The MUE of revM06-L for the chemical reaction barrier height database (BH76) is 1.98 kcal/mol, which is improved by more than a factor of 2 with respect to the M06-L functional. The revM06-L functional gives the best result among local functionals tested for the noncovalent interaction database (NC51), with an MUE of only 0.36 kcal/mol, and the MUE of revM06-L for the solid-state lattice constant database (LC17) is half that for M06-L. The revM06-L functional also yields smoother potential curves, and it predicts more-accurate results than M06-L for seven out of eight diversified test sets not used for parameterization. We conclude that the revM06-L functional is well suited for a broad range of applications in chemistry and condensed-matter physics.

Generation of Tautomers Using Micro-p Ka's.

Solutions of organic molecules containing one or more heterocycles with conjugated bonds may exist as a mixture of tautomers, but typically only a few of them are significantly populated even though the potential number grows combinatorially with the number of protonation and deprotonation sites. Generating the most stable tautomers from a given input structure is an important and challenging task, and numerous algorithms to tackle it have been proposed in the literature. This work describes a novel approach for tautomer prediction that involves the combined use of molecular mechanics, semiempirical quantum chemistry, and density functional theory. The key idea in our method is to identify the protonation and deprotonation sites using estimated micro-p Ka's for every atom in the molecule as well as in its nearest protonated and deprotonated forms. To generate tautomers in a systematic way with minimal bias, we then consider the full set of tautomers that arise from the combinatorial distribution of all such mobile protons among all protonatable sites, with efficient postprocessing to screen away high-energy species. To estimate the micro-p Ka's, we present a new method designed for the current task, but we emphasize that any alternative method can be used in conjunction with our basic algorithm. Our approach is therefore grounded in the computational prediction of physical properties in aqueous solution, in contrast to other approaches that may rely on the use of hard-coded rules of proton distribution, previously observed tautomerization patterns from a known chemical space, or human input. We present examples of the application of our algorithm to organic and drug-like molecules, with a focus on novel structures where traditional methods are expected to perform worse.

Toward Atomistic Modeling of Irreversible Covalent Inhibitor Binding Kinetics.

Covalent inhibitors have emerged as an important drug class in recent years, largely due to their many unique advantages as compared to noncovalent inhibitors, including longer duration of action, lower prolonged systemic exposure, higher potency, and selectivity. However, the potential off-target toxicity of covalent inhibitors, particularly of irreversible covalent inhibitors, represents a great challenge in covalent drug development. Therefore, accurate calculation of protein covalent inhibitor reaction kinetics to guide the design of selective inhibitors would greatly benefit covalent drug discovery efforts. In the present paper, we present a computational method to calculate the relative reaction kinetics between congeneric irreversible covalent inhibitors and their protein receptors. The method combines density functional theory calculations of the transition state barrier height of the rate-limiting step for reaction between the warhead of the inhibitor and a single protein residue, and molecular-mechanics-based free energy calculations to account for the interactions between the ligand in the transition state and the protein environment. The method was tested on four pharmaceutically interesting irreversible covalent binding systems involving 28 ligands; the mean unsigned error (MUE) of the relative reaction rate for all pairs of ligands between the predictions and experimental results for these tested systems is 0.79 log unit. This is to our knowledge the first time where the reaction kinetics of protein irreversible covalent inhibition have been directly calculated with physics-based free energy calculation methods and transition state theory. We anticipate the outstanding accuracy demonstrated here across a broad range of target classes will have a strong impact on the design of selective covalent inhibitors.

Energetics of van der Waals Adsorption on the Metal-Organic Framework NU-1000 with Zr6-oxo, Hydroxo, and Aqua Nodes.

We report measurements of adsorption isotherms and the determination of the isosteric heats of adsorption of several small gases (H2, D2, Ne, N2, CO, CH4, C2H6, Ar, Kr, and Xe) on the metal-organic framework (MOF) NU-1000, which is one of the most thermally stable MOFs. It has transition-metal nodes of formula Zr6(µ3-OH)4(µ3-O)4(OH)4(OH2)4 that resemble hydrated ZrO2 clusters and can serve as catalysts or catalyst supports. The linkers in this MOF are pyrenes linked to the nodes via the carboxylate groups of benzoates. The broad range of adsorbates studied here allows us to compare trends both with adsorption on other surfaces and with density functional calculations also presented here. The experimental isotherms indicate similar filling of the MOF surface by the different gases, starting with strong adsorption sites near the Zr atoms, a result corroborated by the density functional calculations. This adsorption is followed by the filling of other adsorption sites on the nodes and organic framework. Capillary condensation occurs in wide pores after completion of a monolayer. The total amount adsorbed for all the gases is the equivalent of two complete monolayers. The experimental isosteric heats of adsorption are nearly proportional to the atom-atom (or molecule-molecule) Lennard-Jones well-depth parameters of the adsorbates but ∼13-fold larger. The density functional calculations show a similar trend but with much more scatter and heats that are usually greater (by 30%, on average).

Weighted Averaging Scheme and Local Atomic Descriptor for pKa Prediction Based on Density Functional Theory.

As a continuation of our work on developing a density functional theory-based pKa predictor, we present conceptual improvements to our previously published shell model, which is a hierarchical organization of pKa training sets and which, in principle, covers all chemical space. The improvements concern the way the studied chemical compound is associated with the data points from the training sets. By introducing a new descriptor of the local atomic environment which foregoes dependence on chemical bonding and connectivity, we are able to automatically locate molecules from the training set that are most relevant to the proton dissociation equilibrium under study. This new scheme leads to the prediction of a single pKa value weighted across multiple training sets and thus patches a defect disclosed in the formulation of our previous model. Using the new parametrization approach, the pKa prediction gets rid of outliers reported in previous applications of our approach, eliminates ambiguity in interpreting the results, and improves the overall accuracy. Our new treatment accounts for multiple conformations both on the level of energetics and parametrization. Illustrative results are shown for several types of chemical structures containing guanidine, amidine, amine, and phenol functional groups, and which are representative of practically important large and flexible drug-like molecules. Our method's performance is compared to the performance of other previously published pKa prediction methods. Further possible improvements to the organization of the training sets and the potential application of our new local atomic descriptor to other kinds of parametrizations are discussed.

On the Upper Limits of Oxidation States in Chemistry.

The concept of oxidation state (OS) is based on the concept of Lewis electron pairs, in which the bonding electrons are assigned to the more electronegative element. This approach is useful for keeping track of the electrons, predicting chemical trends, and guiding syntheses. Experimental and quantum-chemical results reveal a limit near +8 for the highest OS in stable neutral chemical substances under ambient conditions. OS=+9 was observed for the isolated [IrO4 ]+ cation in vacuum. The prediction of OS=+10 for isolated [PtO4 ]2+ cations is confirmed computationally for low temperatures only, but hasn't yet been experimentally verified. For high OS species, oxidation of the ligands, for example, of O-2 with formation of . O-1 and O-O bonds, and partial reduction of the metal center may be favorable, possibly leading to non-Lewis type structures.

Perspective: Kohn-Sham density functional theory descending a staircase.

This article presents a perspective on Kohn-Sham density functional theory (KS-DFT) for electronic structure calculations in chemical physics. This theory is in widespread use for applications to both molecules and solids. We pay special attention to several aspects where there are both concerns and progress toward solutions. These include: 1. The treatment of open-shell and inherently multiconfigurational systems (the latter are often called multireference systems and are variously classified as having strong correlation, near-degeneracy correlation, or high static correlation; KS-DFT must treat these systems with broken-symmetry determinants). 2. The treatment of noncovalent interactions. 3. The choice between developing new functionals by parametrization, by theoretical constraints, or by a combination. 4. The ingredients of the exchange-correlation functionals used by KS-DFT, including spin densities, the magnitudes of their gradients, spin-specific kinetic energy densities, nonlocal exchange (Hartree-Fock exchange), nonlocal correlation, and subshell-dependent corrections (DFT+U). 5. The quest for a universal functional, where we summarize some of the success of the latest Minnesota functionals, namely MN15-L and MN15, which were obtained by optimization against diverse databases. 6. Time-dependent density functional theory, which is an extension of DFT to treat time-dependent problems and excited states. The review is a snapshot of a rapidly moving field, and-like Marcel Duchamp-we hope to convey progress in a stimulating way.

Oxidation State 10 Exists.

In a recent paper, Wang et al. found an iridium-containing compound with a formal oxidation state of 9. This is the highest oxidation state ever found in a stable compound. To learn if this is the highest chemical oxidation state possible, Kohn-Sham density functional theory was used to study various compounds, including PdO4 (2+) , PtO4 (2+) , PtO3 F2 (2+) , PtO4 OH(+) , PtO5 , and PtO4 SH(+) , in which the metal has an oxidation state of 10. It was found that PtO4 (2+) has a metastable state that is kinetically stable with a barrier height for decomposition of 31 kcal mol(-1) and a calculated lifetime of 0.9 years. All other compounds studied would readily decompose to lower oxidation states.

Nonseparable exchange-correlation functional for molecules, including homogeneous catalysis involving transition metals.

The goal of this work is to develop a gradient approximation to the exchange-correlation functional of Kohn-Sham density functional theory for treating molecular problems with a special emphasis on the prediction of quantities important for homogeneous catalysis and other molecular energetics. Our training and validation of exchange-correlation functionals is organized in terms of databases and subdatabases. The key properties required for homogeneous catalysis are main group bond energies (database MGBE137), transition metal bond energies (database TMBE32), reaction barrier heights (database BH76), and molecular structures (database MS10). We also consider 26 other databases, most of which are subdatabases of a newly extended broad database called Database 2015, which is presented in the present article and in its ESI. Based on the mathematical form of a nonseparable gradient approximation (NGA), as first employed in the N12 functional, we design a new functional by using Database 2015 and by adding smoothness constraints to the optimization of the functional. The resulting functional is called the gradient approximation for molecules, or GAM. The GAM functional gives better results for MGBE137, TMBE32, and BH76 than any available generalized gradient approximation (GGA) or than N12. The GAM functional also gives reasonable results for MS10 with an MUE of 0.018 Å. The GAM functional provides good results both within the training sets and outside the training sets. The convergence tests and the smooth curves of exchange-correlation enhancement factor as a function of the reduced density gradient show that the GAM functional is a smooth functional that should not lead to extra expense or instability in optimizations. NGAs, like GGAs, have the advantage over meta-GGAs and hybrid GGAs of respectively smaller grid-size requirements for integrations and lower costs for extended systems. These computational advantages combined with the relatively high accuracy for all the key properties needed for molecular catalysis make the GAM functional very promising for future applications.