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The purpose of this paper was to identify Serratia marcescens to extract and purify prodigiosin pigment to evaluate the antibacterial potential of the pigment.

Samples were collected from shrimp aquaculture ponds. Species identification was conducted using morphological, biochemical and molecular tests. Pigment extraction and purification were carried out using column chromatography. The antibacterial effect of crude and purified prodigiosin pigment was evaluated on Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa and Staphylococcus aureus as biofouling bacteria. In addition, the interaction between prodigiosin and proteins involved in biofilm formation was evaluated using molecular docking.

The results of prodigiosin extraction with solvents showed the highest percentage of pigment presence with methanol solvent in the second day of culture. The chemical structure of pure prodigiosin obtained from the column chromatography was confirmed by Fourier-transform infrared spectroscopy. Both crude and purified pigments exhibited antibacterial effects against selected bacterial strains. The antibacterial effect of the purified pigment was higher, and the highest antibacterial effect was observed on B. subtilis. Prodigiosin docking was carried out with all target proteins, and the docked energy in all of them was at an acceptable level.

Prodigiosin extracted from S. marcescens can be used as a bioactive compound to design and manufacture of anti-biofouling and anti-biofilm formation products to use extensively for industrial applications as a natural color in marine industries, food industry, cosmetics and textile productions.

The purpose of this paper is to propose two operators for diversity and mutation control in artificial immune systems (AISs).

The proposed operators are applied in substitution to the suppression and mutation operators used in AISs. The proposed mechanisms were tested in the opt-aiNet, a continuous optimization algorithm inspired in the theories of immunology. The traditional opt-aiNet uses a suppression operator based on the immune network principles to remove similar cells and add random ones to control the diversity of the population. This procedure is computationally expensive, as the Euclidean distances between every possible pair of candidate solutions must be computed. This work proposes a self-organizing suppression mechanism inspired by the self-organizing criticality (SOC) phenomenon, which is less dependent on parameter selection. This work also proposes the use of the q-Gaussian mutation, which allows controlling the form of the mutation distribution during the optimization process. The algorithms were tested in a well-known benchmark for continuous optimization and in a bioinformatics problem: the rigid docking of proteins.

The proposed suppression operator presented some limitations in unimodal functions, but some interesting results were found in some highly multimodal functions. The proposed q-Gaussian mutation presented good performance in most of the test cases of the benchmark, and also in the docking problem.

First, the self-organizing suppression operator was able to reduce the complexity of the suppression stage in the opt-aiNet. Second, the use of q-Gaussian mutation in AISs presented better compromise between exploitation and exploration of the search space and, as a consequence, a better performance when compared to the traditional Gaussian mutation.

Alzheimer’s disease (AD), the most common cause of dementia, is a neurodegenerative disorder caused by the aggregation of amyloid-beta (Aβ) at outside of neuron cells and also due to tau aggregation inside the cell. Corosolic acid is aimed to be selected as a main active constituent of Lagerstroemia speciosa for the study.

In the present study, molecular docking of corosolic acid and tau protein was examined using PyRx-v.0.8 software. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties were described and a molecular dynamics study of the bound complex was performed using Desmond.

The docking score and interactions suggested that the corosolic acid (CID:6918774) could bind to tau protein to prevent the fibrillar network, to prevent AD. During simulation corosolic acid-bound protein root mean square deviation (RMSD) values showed more stability when compared to the Apo form of protein. Molecular dynamics study of tau protein and corosolic acid complex gave the insights to develop a drug-like candidate against AD.

The use of corosolic acid of Lagerstroemia speciosa to prevent AD is supported by preliminary analysis on a computational basis. This compound should explore in terms of experimental strategies for the further drug development process. However, in vitro and in vivo evaluation studies are required to suggest the use of corosolic acid against AD.

Paper aims to preparation of new acid disperse dyes based on thiadiazol derivatives and evaluation of their use as antimicrobial colorants in digital transfer-printing ink formulations for printing onto polyester fabric substrates.

New disperse dyes based on 1,3,4 - thiadiazol derivative (dyes 1–3) were prepared and evaluated by different analysis then formulated as colored materials in the ink formulations. The viscosity, dynamic surface tension and particle size distribution of the prepared inks were measured. The printed polyester fabric substrates were tested using a variety of tests, including light fastness, washing, alkali perspiration and Crock fastness, as well as depth of penetration. Density-functional theory (DFT) calculations were carried out at the Becke3-Lee-Yang-parr (B3LYP) level using the 6–311** basis set, and the biological activity of the prepared disperse dyes was investigated.

The obtained results of the physical of the prepared ink revealed that thiadiazol disperse ink is a promising ink formulation for polyester printing and agrees with the quality of the printed polyester fabric. The optimization geometry for molecular structures agreed with the analysis of these compounds. The HOMO/LUMO and energy gap of the studied system were discussed. The molecular docking analysis showed strong interaction with DNA Gyrase and demonstrated to us the high ability of these inks to act as antimicrobial agents.

The prepared inks containing the prepared thiadiazol disperse dye were high-performance and suitable for this type of printing technique, according to the results. The prepared inks resist the growth of microorganisms and thus increase the ink's storage stability.

The prepared disperse dyes based on 1,3,4 - thiadiazol derivative (dyes 1–3) can be a promising colorant in different applications, like some types of paint formulations and as a colorant in printing of different fabric substrates.

Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.

Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10⁻⁷ M to 10⁻³ M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.

The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.

An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.

The purpose of this paper is to demonstrate how the information extracted from scientific text can be directly used in support of life science research projects. In modern digital‐based research and academic libraries, librarians should be able to support data discovery and organization of digital entities in order to foster research projects effectively; thus the paper aims to speculate that text mining and knowledge discovery tools could be of great assistance to librarians. Such tools simply enable librarians to overcome increasing complexity in the number as well as contents of scientific literature, especially in the emerging interdisciplinary fields of science. This paper seeks to present an example of how evidences extracted from scientific literature can be directly integrated into in silico disease models in support of drug discovery projects.

The application of text‐mining as well as knowledge discovery tools is explained in the form of a knowledge‐based workflow for drug target candidate identification. Moreover, an in silico experimentation framework is proposed for the enhancement of efficiency and productivity in the early steps of the drug discovery workflow.

The in silico experimentation workflow has been successfully applied to searching for hit and lead compounds in the World‐wide In Silico Docking On Malaria (WISDOM) project and to finding novel inhibitor candidates.

Direct extraction of biological information from text will ease the task of librarians in managing digital objects and supporting research projects. It is expected that textual data will play an increasingly important role in evidence‐based approaches taken by biomedical and translational researchers.

The proposed approach provides a practical example for the direct integration of text‐ and knowledge‐based data into life science research projects, with the emphasis on their application by academic and research libraries in support of scientific projects.

Mucorales has been described to be widely distributed during the most recent COVID-19 pandemic, with a greater frequency of disease in India, particularly among those with immune deficiencies. This study aims to use computational tools to develop a vaccine.

The authors investigated at Mucorales proteins that had previously been associated to virulence factors. Recent research suggests that a vaccine based on high-level cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B-cell lymphocyte (BCL) epitopes from diverse proteins might be developed. Furthermore, the vaccine assembly contains the targeted epitopes as well as PADRE peptides to induce an immune response. Computational approaches were used to analyze the immunological parameters used to build the suggested vaccine and validate its TLR-3 binding.

These studies show that the vaccination is capable of triggering a particular immune response. The authors offer a technique for developing and evaluating candidate vaccines using computational tools. To the best of their knowledge, this is the first immunoinformatic research of a prospective mucormycosis vaccine.

During this audit, a successful attempt was made to create a subunit MEV against black fungus. In the current study, MEV has been proposed as a suitable neutralizer candidate since it is immunogenic, secure, stable and interacts with human receptors. A stream study, on the other hand, is produced via a mixed vaccinosis approach. Following that, vaccinologists may perform more exploratory testing to evaluate whether the vaccine is effective.

The purpose of this paper is to review the nutritional and phytochemical value of Moringa oleifera L., along with health benefits. Moringa oleifera, a highly valued plant grown throughout the world and all parts of tree used in different food formulations, possess industrial and therapeutic uses. This plant is gaining popularity because of its nutrient-rich root, leaves, flowers and fruits, having immense traditional medicinal uses and proved pharmacological properties.

Major well-known bibliometric information sources such as Web of Science, Scopus, Mendeley and Google Scholar were searched with keywords such as nutrition value of Moringa oleifera, bioactive compounds, health benefits, processing and safety were chosen to obtain a database of 1,386 papers. A final database of 70 scientific sources was made after sorting and classifying them according to different criteria based on topic relevance, country of origin and year of publication.

The literature reflects that Moringa contains all necessary macro, micro-nutrients and bioactive compounds (terpenoids, polyphenols, flavonoids, glucosinolates, alkaloids, glycosides and carotenoids). Scientific studies illustrate that M. oleifera and its bioactive constituents could play a vital role in the prevention of several chronic and degenerative diseases associated with oxidation stress. The recent upsurge in consumer interest for health foods has opened up new vistas for plant products containing bioactive compounds in different food formulations.

This paper highlights phytochemicals, pharmacological properties, bio-accessibility, food and industrial applications of Moringa. Moringa pods are traditionally preferred for enlarged liver and spleen, intestinal worms, weakness, neurological disorders and skin disease. A seed is natural and an inexpensive coagulant used to remove organic particles from water.

The past two decades have witnessed the development of a new stream of research in the field of virtual reality. Its primary use was thought to be entertainment, but as research continued the applications to more practical areas, we see how all forms of businesses can and are benefiting from virtual reality research. Briefly discusses the research being conducted on behalf of various industries, and how that research will benefit and is benefiting those industries.

The purpose of this article is to analyse the literature of chemoinformatics, a subject that has arisen over the last few years and that draws on techniques from a range of disciplines, most notably chemistry (particularly computational and medicinal chemistry), computer science and information science.

Discusses subject, author and citation searches of (principally) the web of knowledge database.

The Journal of Chemical Information and Modeling (previously the Journal of Chemical Information and Computer Sciences) is the core journal for the subject, but with many significant papers being published in journals whose principal focus is molecular modelling, quantitative structure‐activity relationships or more general aspects of chemistry. The discipline is international in scope, and many of the most cited papers describe software packages that play a key role in modern chemoinformatics research.

This is the first bibliometric study of chemoinformatics, and one of only a very few that consider the bibliometrics of computational chemistry more generally.