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Shiv Nadar University

(SoNS) School of Natural Sciences

Optimization of lead structures is crucial for drug discovery. However, the accuracy of such a prediction using the traditional molecular docking approach remains a major concern. Our study demonstrates that the employment of quantum crystallographic approach-counterpoise corrected kernel energy method (KEM-CP) can improve the accuracy by and large. We select human aldose reductase at 0.66 Å, cyclin dependent kinase 2 at 2.0 Å and estrogen receptor β at 2.7 Å resolutions with active site environment ranging from highly hydrophilic to moderate to highly hydrophobic and several of their known ligands. Overall, the use of KEM-CP alongside the GoldScore resulted superior prediction than the GoldScore alone. Unlike GoldScore, the KEM-CP approach is neither environment-specific nor structural resolution dependent, which highlights its versatility. Further, the ranking of the ligands based on the KEM-CP results correlated well with that of the experimental IC50 values. This computationally inexpensive yet simple approach is expected to ease the process of virtual screening of potent ligands, and it would advance the drug discovery research. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

World University root node

Chemistry

Fulltext

Molecules

Predicting accurate lead structures for screening molecular libraries: A quantum crystallographic approach

Exploration of the properties of monomers by modulating their stereochemistry is not well reported in polybenzoxazines (PBzs). Isosorbide contains a rigid bicyclic (endo-exo-configuration) core that has shown promise in high-performance thermoplastic polymers. In this report, new chiral PBzs were prepared from industrially available feedstocks, carbohydrate-derived (isosorbide), and lignin- or cashew nut waste-sourced renewable phenols (cardanol and guaiacol). A fully biobased benzoxazine monomer based on a one-step condensation reaction of isosorbide diamine (isa) with phenols was carried out for 15 min under microwave and solvent- and catalyst-free conditions. Structural elucidation of monomers was achieved by two-dimensional (2D) NMR spectroscopy [heteronuclear single quantum correlation (HSQC) and COSY (correlated spectroscopy)]. The "isa"-based monomer revealed a comparable ring-opening polymerization temperature and a good processing window for the widely available bisphenol-A/aniline-based monomer. The resultant polymers showed a higher Tg, better thermomechanical properties, and adhesive strength compared to other classical petrobased PBzs. The current work extends the importance of the major component of the sugar-derived isohexide family member, isosorbide, in polybenzoxazine chemistry and suggests that stereocontrol in the monomer is another approach to affect the thermomechanical properties of this upcoming class of high-performance phenolic polymer. © 2021 American Chemical Society.

ACS Sustainable Chemistry and Engineering

Understanding the Stereochemical Effect on the Properties of Emerging Thermosets: Sustainable Polybenzoxazines

In $\rm\Lambda$CDM cosmology, Dark Matter (DM) and neutrinos are assumed to be non-interacting. However, it is possible to have scenarios, where DM-neutrino interaction may be present, leading to scattering of DM with neutrinos and annihilation of DM into neutrinos. We investigate the viability of such scenarios in the light of cosmological data by making use of the PLANCK-2018 and BOSS-BAO 2014 dataset and constrain these processes in the light of the same. We also discuss a particle DM model where DM-neutrino interaction is present and map the constraints to the parameter space of the model.

Physics

https://arxiv.org/abs/2104.

Shedding Light on Dark Matter and Neutrino Interactions from Cosmology

In this paper, we explore mutual information based stock networks to build regular vine copula structure on high frequency log returns of stocks and use it for the estimation of Value at Risk (VaR) of a portfolio of stocks. Our model is a data driven model that learns from a high frequency time series data of log returns of top 50 stocks listed on the National Stock Exchange (NSE) in India for the year 2014. The Ljung-Box test revealed the presence of Autocorrelation as well as Heteroscedasticity in the underlying time series data. Analysing the goodness of fit of a number of variants of the GARCH model on each working day of the year 2014, that is, 229 days in all, it was observed that ARMA(1,1)-EGARCH(1,1) demonstrated the best fit. The joint probability distribution of the portfolio is computed by constructed an R-Vine copula structure on the data with the mutual information guided minimum spanning tree as the key building block. The joint PDF is then fed into the Monte- Carlo simulation procedure to compute the VaR. If we replace the mutual information by the Kendall's Tau in the construction of the R-Vine copula structure, the resulting VaR estimations were found to be inferior suggesting the presence of non-linear relationships among stock returns. © 2021 Sharma, Sahni. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Mathematics

PLoS ONE

A mutual information based R-vine copula strategy to estimate VaR in high frequency stock market data

Unfortunately, in the original version of this article the updated Fig. 3 was not replaced. Please find below the updated Fig. 3. This has been corrected by publishing this correction article. The original article has been updated. (Figure presented.). © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

Journal of Materials Science: Materials in Electronics

Correction to: Annealing temperature-driven near-surface crystallization with improved luminescence in self‐patterned alumina films (Journal of Materials Science: Materials in Electronics, (2021), 32, 9, (11709-11718), 10.1007/s10854-021-05790-0)

The impact of annealing on luminescence properties of radio-frequency magnetron sputtering grown alumina films and their possible application in radiation measurement are presented. Here, grazing incidence X-ray diffraction study reveals the growth of amorphous alumina films, while the annealing treatment results in the gradual formation of nanocrystallites. They are found to be embedded in the amorphous matrix by cross-sectional Transmission Electron Microscopy for 1200 °C annealed thin film. The evolution of self-patterned wrinkles has also been observed at the surface by Scanning Electron Microscopy. A comprehensive analysis of optically active defect centers is carried out by room temperature photoluminescence (PL) measurement. This indicates a monotonic increase of oxygen vacancies (F centers) with increasing annealing temperature up to 1200 °C, though they are not directly correlated with the thermoluminescence (TL) results after exposing them to gamma radiation from a 60Co source. Based on PL analysis, the TL glow curves with increasing annealing temperature are elucidated in the light of the involvement of both trap centers and F-type recombination centers residing at grain boundaries. In terms of TL results, 1200 °C annealed alumina film is found to be superior to both the as-grown film, and the one annealed at 1100 °C. Finally, the linear TL response curves in the 1200 °C annealed film after exposing to both gamma radiation (up to 5 kGy) and energetic charged particles (80 MeV carbon ions) are demonstrated up to 130 kGy. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Annealing temperature-driven near-surface crystallization with improved luminescence in self‐patterned alumina films

In present article, we have fabricated micro/nano hierarchical structured aluminium surfaces with a vivid range of wettability and controllable adhesion using a facile and environment-friendly approach. The micropatterned surfaces show hydrophobicity with high adhesion due to impregnated wetting state, analogous to rose petal effect. Interestingly, the micro/nano hierarchical structured surfaces become superhydrophilic due to formation of aluminium oxide and hydroxide nanoflakes. After fluorination, these surfaces become superhydrophobic with a very low contact angle hysteresis. They also exhibit a very high chemical and thermal stability along with excellent self-cleaning capability. © 2021 Elsevier B.V.

Mechanical Engineering

(SoE) School of Engineering

Materials Letters

Structured aluminium surfaces with tunable wettability fabricated by a green approach

Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic. © 2021 The Authors.

Royal Society Open Science

Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic

Herein we have reported a blue LED mediated reaction of aryl diazoacetate with a stoichiometric amount of 1,4-dioxane/tetrahydropyran (THP) and various heterocycles like indoles, pyrroles, phthalimides, thiazolidinediones and hydantoins in water. During the reaction, various aryl diazoacetates were converted to oxonium ylides by reacting with 1,4-dioxane and THP. These ylides generated in aqueous medium (under metal- and base-free conditions) were then used for the amino etherification of the aforementioned heterocycles in excellent yield. The ylides underwent a [1,2] shift to afford substituted 1,4-dioxepanes. Phthalimide products were also converted to 1,4,7-dioxazonan-6-ones. Reaction kinetics, Hammett's plot and DFT calculations (solvent phase) rationalize the ylide formation and subsequent reactions with the nucleophiles. The reaction was also demonstrated at the multigram scale. This amino etherification reaction of aryl diazoacetates in aqueous medium demonstrated a sustainable process of converting toxic 1,4-dioxane in functionalizing heterocycles. This journal is © The Royal Society of Chemistry.

Green Chemistry

Photolytic amino etherification reactions of aryl diazoacetates with N-heterocycles and a stoichiometric amount of dioxane/tetrahydropyran in aqueous medium: Synthesis of 1,4-dioxepane/1,4,7-dioxazonan-6-one systems

Learning and associative memory are understood as emergent phenomena resulting from interactions between a complex network of neurons. It is well known that the structure of such a neural network heavily influences its function. Biological networks (e.g. neuronal network of the worm Caenorhabditis elegans) have been shown to exhibit small-world characteristics. To investigate the structure-function relationship in small-world networks, we simulate the Hopfield model of associative memory on a regular and Watts-Strogatz network. We obtain estimates of memory capacity on a regular and a WS network through numerical simulations. Further, we study how changing the probability of rewiring and local connectivity in a WS network affects the performance of associative memory. We find that the performance on small-world networks is as robust as that on random networks despite using only a fraction of connections, making the former biologically favorable. Our simulations are in agreement with experimental evidence found in the existing literature on small-world characteristics in biological networks and give deeper insights into this phenomenon. © 2021 Author(s).