Machine learning analysis of a large set of homopolymers to predict glass transition temperatures.

Glass transition temperature of polymers, Tg, is an important thermophysical property, which sometimes can be difficult to measure experimentally. In this regard, data-driven machine learning approaches are important alternatives to assess Tg values, in a high-throughput way. In this study, a large dataset of more than 900 polymers with reported glass transition temperature (T) was assembled from various public sources in order to develop a predictive model depicting the structure-property relationships.

Alkaloids from Piper longum L and their Anti-inflammatory Properties.

Piper longum L. (PL) is considered one of the most important species traditionally used for treating various ailments and has indicated the presence of alkaloids, flavonoids, and steroids. In this study, we isolated the chemical compounds of PL leaves, and measured NO, IL-6, iNOS, as well as COX-2 protein levels.

Design and evaluation of nanoscale materials with programmed responsivity towards epigenetic enzymes.

Self-assembled materials capable of modulating their assembly properties in response to specific enzymes play a pivotal role in advancing 'intelligent' encapsulation platforms for biotechnological applications. Here, we introduce a previously unreported class of synthetic nanomaterials that programmatically interact with histone deacetylase (HDAC) as the triggering stimulus for disassembly. These nanomaterials consist of co-polypeptides comprising poly(acetyl L-lysine) and poly(ethylene glycol) blocks.

Design and Evaluation of Nanoscale Materials with Programmed Responsivity towards Epigenetic Enzymes.

Self-assembled materials capable of modulating their assembly properties in response to specific enzymes play a pivotal role in advancing 'intelligent' encapsulation platforms for biotechnological applications. Here, we introduce a previously unreported class of synthetic nanomaterials that programmatically interact with histone deacetylase (HDAC) as the triggering stimulus for disassembly. These nanomaterials consist of co-polypeptides comprising poly (acetyl L-lysine) and poly(ethylene glycol) blocks.

Improved synthesis, molecular modeling and anti-inflammatory activity of new fluorinated dihydrofurano-naphthoquinone compounds.

A series of new fluorinated dihydrofurano-napthoquinone compounds were sucessfully synthesized in good yields using microwave-assisted multi-component reactions of 2-hydroxy-1,4-naphthoquinone, fluorinated aromatic aldehydes, and pyridinium bromide. The products were fully characterized using spectroscopic techniques and evaluated for their anti-inflammatory activity using lipopolysaccharide (LPS)-stimulated RAW264.7 macrophage cells.

Synthesis, molecular docking analysis and evaluation of new heterocyclic hybrids of 4-aza-podophyllotoxin as potent cytotoxic agents.

Two different synthetic approaches to novel heterocyclic hybrid compounds of 4-azapodophyllotoxin were investigated. The obtained products were characterized by infrared spectroscopy, nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry. MTT protocol was then performed to examine the cytotoxic activity of these products against KB, HepG2, A549, MCF7, and Hek-293 cell lines.

Stability Constant and Potentiometric Sensitivity of Heavy Metal-Organic Fluorescent Compound Complexes: QSPR Models for Prediction and Design of Novel Coumarin-like Ligands.

Industrial wastewater often consists of toxic chemicals and pollutants, which are extremely harmful to the environment. Heavy metals are toxic chemicals and considered one of the major hazards to the aquatic ecosystem. Analytical techniques, such as potentiometric methods, are some of the methods to detect heavy metals in wastewaters.

Development of Activity Rules and Chemical Fragment Design for In Silico Discovery of AChE and BACE1 Dual Inhibitors against Alzheimer's Disease.

Multi-target drug development has become an attractive strategy in the discovery of drugs to treat of Alzheimer's disease (AzD). In this study, for the first time, a rule-based machine learning (ML) approach with classification trees (CT) was applied for the rational design of novel dual-target acetylcholinesterase (AChE) and -site amyloid-protein precursor cleaving enzyme 1 (BACE1) inhibitors. Updated data from 3524 compounds with AChE and BACE1 measurements were curated from the ChEMBL database.

Chemical Profile and Biological Activities of Fungal Strains Isolated from Piper nigrum Roots: Experimental and Computational Approaches.

The current report describes the chemical investigation and biological activity of extracts produced by three fungal strains Fusarium oxysporum, Penicillium simplicissimum, and Fusarium proliferatum isolated from the roots of Piper nigrum L. growing in Vietnam. These fungi were namely determined by morphological and DNA analyses.

Comparison of the University Pharmacy Education Programs in Germany and Vietnam.

During the global COVID pandemic, the importance of professionals in the health care sector has been put in a new light, including pharmacists. In this context, the focus is also on how pharmacists are trained in different countries. Through an exchange of pharmacy teaching staff from a German to a Vietnamese university, the pharmacy education programs in both countries were compared.

Synthesis and biological activity, and molecular modelling studies of potent cytotoxic podophyllotoxin-naphthoquinone compounds.

A new approach for the synthesis of podophyllotoxin-naphthoquinone compounds using microwave-assisted three-component reactions is reported in this study. Novel podophyllotoxin-naphthoquinone derivatives with modification on ring E were synthesized. All the synthetic compounds were assessed in terms of their cytotoxicity profile against four cancer cell lines (KB, HepG2, A549, and MCF7), and noncancerous Hek-293 cell lines.

A Review of Computational Approaches Targeting SARS-CoV-2 Main Protease to the Discovery of New Potential Antiviral Compounds.

The new pandemic caused by the coronavirus (SARS-CoV-2) has become the biggest challenge that the world is facing today. It has been creating a devastating global crisis, causing countless deaths and great panic. The search for an effective treatment remains a global challenge owing to controversies related to available vaccines.

Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer's disease treatment.

The enzyme acetylcholinesterase (AChE) is currently a therapeutic target for the treatment of neurodegenerative diseases. These diseases have highly variable causes but irreversible evolutions. Although the treatments are palliative, they help relieve symptoms and allow a better quality of life, so the search for new therapeutic alternatives is the focus of many scientists worldwide.

Essential oils of - chemical composition, bioactivity, docking, and ADMET profiling of selective major compounds.

Phytochemical investigation applying GC (gas chromatography)-MS (mass spectrometry)/GC-FID (flame ionization detection) on the hydro-distilled essential oils of the Vietnamese medicinal plant leaf and twig lead to the detection of 35 constituents (97.36%) in the leaf oil and 52 constituents (98.75%) in the twig oil.

Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree.

Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action.

Synthesis and biological evaluation of novel quinazoline-triazole hybrid compounds with potential use in Alzheimer's disease.

A library of twelve quinazoline-triazole hybrid compounds were designed, synthesized and evaluated as a novel class of acetylcholinesterase inhibitors to treat Alzheimer's disease (AD). The biological assay results demonstrated the ability of several hybrid compounds to inhibit AChE enzyme (IC range = 0.2-83.

Design, Synthesis and Bioevaluation of Two Series of 3-[(1-Benzyl-1H-1,2,3-triazol-4-yl)methyl]quinazolin-4(3H)-ones and N-(1-Benzylpiperidin-4-yl)quinazolin-4-amines.

Two series of 3-[(1-benzyl-1H-1,2,3-triazol-4-yl)methyl]quinazolin-4(3H)-ones and N-(1-benzylpiperidin-4-yl)quinazolin-4-amines were designed initially as potential acetylcholine esterase inhibitors. Biological evaluation demonstrated that N-(1-benzylpiperidin-4-yl)quinazolin-4-amines significantly inhibited AChE activity. Especially, two compounds of them were found to be the most potent with relative AChE inhibition percentages of 87 % in comparison to donepezil.

Emerging Role of Circulating Tumor Cells in Gastric Cancer.

With over 1 million incidence cases and more than 780,000 deaths in 2018, gastric cancer (GC) was ranked as the 5th most common cancer and the 3rd leading cause of cancer deaths worldwide. Though several biomarkers, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4), have been identified, their diagnostic accuracies were modest. Circulating tumor cells (CTCs), cells derived from tumors and present in body fluids, have recently emerged as promising biomarkers, diagnostically and prognostically, of cancers, including GC.

Higher-Order and Mixed Discrete Derivatives such as a Novel Graph- Theoretical Invariant for Generating New Molecular Descriptors.

Background: Recently, some authors have defined new molecular descriptors (MDs) based on the use of the Graph Discrete Derivative, known as Graph Derivative Indices (GDI). This new approach about discrete derivatives over various elements from a graph takes as outset the formation of subgraphs. Previously, these definitions were extended into the chemical context (N-tuples) and interpreted in structural/physicalchemical terms as well as applied into the description of several endpoints, with good results.

Beyond model interpretability using LDA and decision trees for α-amylase and α-glucosidase inhibitor classification studies.

In this report are used two data sets involving the main antidiabetic enzyme targets α-amylase and α-glucosidase. The prediction of α-amylase and α-glucosidase inhibitory activity as antidiabetic is carried out using LDA and classification trees (CT). A large data set of 640 compounds for α-amylase and 1546 compounds in the case of α-glucosidase are selected to develop the tree model.

(E)-N'-Arylidene-2-(4-oxoquinazolin-4(3H)-yl) acetohydrazides: Synthesis and evaluation of antitumor cytotoxicity and caspase activation activity.

In our search for novel small molecules activating procaspase-3, we have designed and synthesised a series of novel acetohydrazides incorporating quinazolin-4(3H)-ones (5, 6, 7). Biological evaluation revealed eight compounds with significant cytotoxicity against three human cancer cell lines (SW620, colon cancer; PC-3, prostate cancer; NCI-H23, lung cancer). The most potent compound 5t displayed cytotoxicity up to 5-fold more potent than 5-FU.

Radicular cyst in a primary molar following pulp therapy with gutta percha: A case report and literature review.

A radicular cyst (RC) in deciduous dentition is relatively rare. This clinical report presents a case of RC that condition derived from a primary molar undergone an endodontic treatment with gutta-percha approximately one year ago. In addition, we also considered whether intracanal medicaments and gutta-percha filling material related to the formation and development of the cyst or not.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling.

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability.

Computational Identification of Chemical Compounds with Potential Activity against Leishmania amazonensis using Nonlinear Machine Learning Techniques.

Leishmaniasis is a poverty-related disease endemic in 98 countries worldwide, with morbidity and mortality increasing daily. All currently used first-line and second-line drugs for the treatment of leishmaniasis exhibit several drawbacks including toxicity, high costs and route of administration. Consequently, the development of new treatments for leishmaniasis is a priority in the field of neglected tropical diseases.

Design, synthesis and evaluation of novel hybrids between 4-anilinoquinazolines and substituted triazoles as potent cytotoxic agents.

In this research several series of novel dioxygenated ring fused 4-anilinoquinazolines (10a-d) and 4-anilinoquinazoline-substituted triazole hybrid compounds (11-14) have been designed and synthesized. Their biological significance was highlighted by evaluating in vitro for anticancer activities, wherein several compounds displayed excellent activity specifically against three human cancer cell lines (KB, epidermoid carcinoma; HepG2, hepatoma carcinoma; SK-Lu-1, non-small lung cancer). Especially, compound 13a exhibited up to 100-fold higher cytotoxicity in comparison with erlotinib.