Full Heuslers alloys are a fascinating class of materials leading to many technological applications. These have been studied widely under ambient conditions. However, less attention been paid to study them under the effect of compression and strain. Here in this work Co2YZ (Y= Cr, Nb, Ta, V and Z = Al, Ga) Heusler alloys have been studied comprehensively under pressure variations. Calculated lattice constants are in reasonable agreement with the available data. It is determined that lattice constant deceases with the increase in tensile stress and increases by increasing pressure in reverse direction. Band profiles reveals the half metallic nature of the studied compounds. The bond length decreases while band gap increases in compressive strain. The compounds are found to be reflective in visible region, as characteristics of the metals. The magnetic moments reveal the half-mettalic ferromagnetic nature of the compounds.
Metal nanoclusters have been considered as a new class of chemical sensors due to their unique electronic structures and the particular physicochemical properties. The interaction of N2 molecule with neutral and ionic magnesium nanoclusters Mg17q(q=0,±1), as well as neutral magnesium nanoclusters with the centrality of beryllium and calcium Mg16M (M=Be, Mg, and Ca) have been investigated using CAM-B3LYP/6-311+G(d) level of theory in the gas phase. The electronic properties of magnesium nanoclusters were significantly affected by the adsorption of N2 molecule. The NBO analysis revealed a charge transfer from the adsorbed N2 molecule to the nanocluster. Based on the adsorption energies and enthalpies, a thermodynamically favorable chemisorption process was predicted for the Mg16Ca-N2 complex. The negative value of the Gibbs free energy of Mg16Ca-N2 confirmed the spontaneous adsorption process. The estimated recovery time for Mg16Ca-N2 complex for 8-MR (0.089 s) and 4-MRs (0.075 s) illustrated a possible desorption process for N2 molecule from the surface of Mg16Ca. Our finding also revealed the Mg16Ca has the ability to use as a sensor for detection and absorption of N2 molecule.
Fused tricyclic organic compounds are an important class of organic electronic materials. In designing molecules for organic electronics, knowing what chemical structure that be used to tune the molecular property is one of the keys that can help to improve the material performance. In this research, we applied machine learning and data analytic approaches in addressing this problem. The energy states (Lowest Unoccupied Molecular Orbital (HOMO), Highest Occupied Molecular Orbitals (LUMO), singlet (Es) and triplet (ET) energy) of more than 10 thousand fused tricyclics are calculated. Corresponding descriptors are also generated. We find that the Coulomb matrix is a poorer descriptor than high-level descriptors in a multilayer perceptron neural network. Correlations as high as 0.95 is obtained using a multilayer perceptron neural network with Mean Absolute Error as low as 0.08 eV. The descriptors that are important in tuning the energy levels are revealed using the Random Forest algorithm. Correlations of such descriptors are also plotted. We found that the higher the number of tertiary amines, the deeper are the HOMO and LUMO levels. The presence of NN in the aromatic rings can be used to tune the ES. However, there is no single dominant descriptor that can be correlated with the ET. A collection of descriptors is found to give a far better correlation with ET. This research demonstrated that machine learning and data analytics in guiding how certain chemical substructures correlate with the molecule energy states.
Aptamers are short oligonucleotides that possess high specificity and affinity against their target. Generated via Systematic Evolution of Ligands by Exponential Enrichment, (SELEX) in vitro, they were screened and enriched. This review covering the study utilizing bioinformatics tools to analyze primary sequence, secondary and tertiary structure prediction, as well as docking simulation for various aptamers and their ligand interaction. Literature was pooled from Web of Science (WoS) and Scopus databases until December 18, 2020 using specific search string related to DNA aptamers, in silico, structure prediction, and docking simulation. Out of 330 published articles, 38 articles were assessed in the analysis based on the predefined inclusion and exclusion criteria. It was found that Mfold and RNA Composer web server is the most popular tool in secondary and tertiary structure prediction of DNA aptamers, respectively. Meanwhile, in docking simulation, ZDOCK and AutoDock are preferred to analyze binding interaction in the aptamer-ligand complex. This review reports a brief framework of recent developments of in silico approaches that provide predictive structural information of ssDNA aptamer.
Xylitol is a high-value low-calorie sweetener used as sugar substitute in food and pharmaceutical industry. Xylitol phosphate dehydrogenase (XPDH) catalyses the conversion of d-xylulose 5-phosphate (XU5P) and d-ribulose 5-phosphate (RU5P) to xylitol and ribitol respectively in the presence of nicotinamide adenine dinucleotide hydride (NADH). Although these enzymes have been shown to produce xylitol and ribitol, there is an incomplete understanding of the mechanism of the catalytic events of these reactions and the detailed mechanism has yet to be elucidated. The main goal of this work is to analyse the conformational changes of XPDH-bound ligands such as zinc, NADH, XU5P, and RU5P to elucidate the key amino acids involved in the substrate binding. In silico modelling, comparative molecular dynamics simulations, interaction analysis and conformational study were carried out on three XPDH enzymes of the Medium-chain dehydrogenase (MDR) family in order to elucidate the atomistic details of conformational transition, especially on the open and closed state of XPDH. The analysis also revealed the possible mechanism of substrate specificity that are responsible in the catalyse hydride transfer are the residues His58 and Ser39 which would act as the proton donor for reduction of XU5P and RU5P respectively. The structural comparison and MD simulations displayed a significant difference in the conformational dynamics of the catalytic and coenzyme loops between Apo and XPDH-complexes and highlight the contribution of newly found triad residues. This study would assist future mutagenesis study and enzyme modification work to increase the catalysis efficiency of xylitol production in the industry.
Critical to the applications of proteins in non-aqueous enzymatic processes is their structural dynamics in relation to solvent polarity. A pool of mutants derived from Geobacillus zalihae T1 lipase was screened in organic solvents (methanol, ethanol, propanol, butanol and pentanol) resulting in the selection of six mutants at initial screening (A83D/K251E, R21C, G35D/S195 N, K84R/R103C/M121I/T272 M and R106H/G327S). Site-directed mutagenesis further yielded quadruple mutants A83D/M121I/K251E/G327S and A83D/M121I/S195 N/T272 M, both of which had improved activity after incubation in methanol. The km and kcat values of these mutants vary marginally with the wild-type enzyme in the methanol/substrate mixture. Thermally induced unfolding of mutants was accompanied with some loss of secondary structure content. The root mean square deviations (RMSD) and B-factors revealed that changes in the structural organization are intertwined with an interplay of the protein backbone with organic solvents. Spatially exposed charged residues showed correlations between the solvation dynamics of the methanol solvent and the hydrophobicity of the residues. The short distances of the radial distribution function provided the required distances for hydrogen bond formation and hydrophobic interactions. These dynamic changes demonstrate newly formed structural interactions could be targeted and incorporated experimentally on the basis of solvent mobility and mutant residues.
Conformational search for the most stable geometry connection of 16 sets of polydopamine (PDA) tetramer subunits has been systematically investigated using density functional theory (DFT) calculations. Our results indicated that the more planar subunits are, the more stable they are. This finding is in good agreement with recent experimental observations, which have suggested that PDA are composed of the nearly planar subunits that appear to be stacked together via the π-π interactions to form graphite-like layered aggregates associated with the balance of the intramolecular hydrogen bonds and steric effects from the indole and catechol moieties. Molecular dynamics (MD) simulations of 16 spherical clusters of the tetramer subunits of PDA in the gas and aqueous phase were performed at 298 K and confirmed the stability of supramolecular tetramer aggregates. The complex formation and binding energy of all 16 clusters are very strong although the shapes of the clusters in aqueous solution are not spherical and are very much different from those in the gas phase. The aggregations of all 16 clusters in aqueous solution were also confirmed from the profiles of the Kratky plot and the radius of gyration of all clusters. Our MD results in both gas phase and aqueous solution pointed out that there are high possibilities of aggregations of the 16 kinds of tetramer subunits although the conformations of each tetramer subunit are not flat. In summary, this work brings an insight into the controversial structure of PDA tetramer units and explains some of the important structural features found in the aqueous phase in comparison to the gas phase.
Transthyretin (TTR) mediated amyloidosis is a highly ruinous illness that affects various organs by aggravating the deposition of misfolded or mutated TTR protein aggregates in tissues. Hence, hindering the formation of TTR amyloid aggregates could be a key strategy in finding an effective cure towards the aggravating disorder. In this analysis, we examined the subversive nature of point mutation, V30M, in TTR that promotes amyloidogenicity using discrete molecular dynamics (DMD) simulations. Besides, we probed the association of naturally occurring polyphenols: EGCG (a proven anti TTR aggregation agent as positive control), resveratrol and curcumin in mitigating the pathogenic repercussions of mutant TTR. Results from the computational studies endorsed that the resveratrol constitutes a restorative potential to subjugate TTR mediated amyloidosis, besides EGCG. Hence, this study could be a reminiscent aspect in understanding the inhibitory role of key polyphenols against the mutant TTR aggregates, which could be an aid towards structure-based drug design in the upcoming research era on familial amyloid disorders.
A Laplacian scoring algorithm for gene selection and the Gini coefficient to identify the genes whose expression varied least across a large set of samples were the state-of-the-art methods used here. These methods have not been trialed for their feasibility in cheminformatics. This was a maiden attempt to investigate a complete comparative analysis of an anthraquinone and chalcone derivatives-based virtual combinatorial library. This computational "proof-of-concept" study illustrated the combinatorial approach used to explain how the structure of the selected natural products (NPs) undergoes molecular diversity analysis. A virtual combinatorial library (1.6 M) based on 20 anthraquinones and 24 chalcones was enumerated. The resulting compounds were optimized to the near drug-likeness properties, and the physicochemical descriptors were calculated for all datasets including FDA, Non-FDA, and NPs from ZINC 15. UMAP and PCA were applied to compare and represent the chemical space coverage of each dataset. Subsequently, the Laplacian score and Gini coefficient were applied to delineate feature selection and selectivity among properties, respectively. Finally, we demonstrated the diversity between the datasets by employing Murcko's and the central scaffolds systems, calculating three fingerprint descriptors and analyzing their diversity by PCA and SOM. The optimized enumeration resulted in 1,610,268 compounds with NP-Likeness, and synthetic feasibility mean scores close to FDA, Non-FDA, and NPs datasets. The overlap between the chemical space of the 1.6 M database was more prominent than with the NPs dataset. A Laplacian score prioritized NP-likeness and hydrogen bond acceptor properties (1.0 and 0.923), respectively, while the Gini coefficient showed that all properties have selective effects on datasets (0.81-0.93). Scaffold and fingerprint diversity indicated that the descending order for the tested datasets was FDA, Non-FDA, NPs and 1.6 M. Virtual combinatorial libraries based on NPs can be considered as a source of the combinatorial compound with NP-likeness properties. Furthermore, measuring molecular diversity is supposed to be performed by different methods to allow for comparison and better judgment.
Recent evidence from in vitro and in vivo studies has shown that anthocyanins and anthocyanidins can reduce and inhibit the amyloid beta (Aβ) species, one of the hallmarks of Alzheimer's disease (AD). However, their inhibition mechanisms on Aβ species at molecular details remain elusive. Therefore, in the present study, molecular modelling methods were employed to investigate their inhibitory mechanisms on Aβ(1-42) peptide. The results highlighted that anthocyanidins effectively inhibited the conformational transitions of helices into beta-sheet (β-sheet) conformation within Aβ(1-42) peptide by two different mechanisms: 1) the obstruction of two terminals from coming into contact due to the binding of anthocyanidins with residues of N- and second hydrophobic core (SHC)-C-terminals, and 2) the prevention of the folding process due to the binding of anthocyanidin with the central polar (Asp23 and Lys28) and native helix (Asp23, Lys28, and Leu34) residues. These new findings on the inhibition of β-sheet formation by targeting both N- and SHC-C-terminals, and the long-established target, D23-K28 salt bridge residues, not with the conventional central hydrophobic core (CHC) as reported in the literature, might aid in designing more potent inhibitors for AD treatment.