A review on the structural characterization of nanomaterials for nano-QSAR models.

Quantitative structure-activity relationship (QSAR) models are routinely used to predict the properties and biological activity of chemicals to direct synthetic advances, perform massive screenings, and even to register new substances according to international regulations. Currently, nanoscale QSAR (nano-QSAR) models, adapting this methodology to predict the intrinsic features of nanomaterials (NMs) and quantitatively assess their risks, are blooming. One of the challenges is the characterization of the NMs.

A New Hyaluronic Emulgel of Hesperetin for Topical Application-An In Vitro Evaluation.

The present study aimed to formulate and characterize a hesperetin formulation to achieve adequate deposition and retention of hesperetin in the epidermis as a target for some cosmetic/dermatological actions. To derive the final emulgel, various formulations incorporating different proportions of Polysorbate 80 and hyaluronic acid underwent testing through a Box-Behnken experimental design. Nine formulations were created until the targeted emulgel properties were achieved.

Intranasal Drug Administration in Alzheimer-Type Dementia: Towards Clinical Applications.

Alzheimer-type dementia (ATD) treatments face limitations in crossing the blood-brain barrier and systemic adverse effects. Intranasal administration offers a direct route to the brain via the nasal cavity's olfactory and trigeminal pathways. However, nasal physiology can hinder drug absorption and limit bioavailability.

Unveiling the Stereoselectivity and Regioselectivity of the [3+2] Cycloaddition Reaction between N-methyl-C-4-methylphenyl-nitrone and 2-Propynamide from a MEDT Perspective.

[3+2] cycloaddition reactions play a crucial role in synthesizing complex organic molecules and have significant applications in drug discovery and materials science. In this study, the [3+2] cycloaddition (32CA) reactions of N-methyl-C-4-methyl phenyl-nitrone and 2-propynamide , which have not been extensively studied before, were investigated using molecular electron density theory (MEDT) at the B3LYP/6-311++G(d,p) level of theory. According to an electron localization function (ELF) study, N-methyl-C-4-methyl phenyl-nitrone is a zwitterionic species with no pseudoradical or carbenoid centers.

Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays.

A method to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC) is developed. A set of structurally heterogeneous agents against MTBC was used to obtain a mathematical model based on topological descriptors. This model was statistically validated through a Leave-n-Out test.

Nanoliposomes in Cancer Therapy: Marketed Products and Current Clinical Trials.

The drugs used for cancer treatment have many drawbacks, as they damage both tumor and healthy cells and, in addition, they tend to be poorly soluble drugs. Their transport in nanoparticles can solve these problems as these can release the drug into tumor tissues, as well as improve their solubility, bioavailability, and efficacy, reducing their adverse effects. This article focuses on the advantages that nanotechnology can bring to medicine, with special emphasis on nanoliposomes.

Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method.

The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure.

Computational Evaluation and In Vitro Validation of New Epidermal Growth Factor Receptor Inhibitors.

Background: The Epidermal Growth Factor Receptor (EGFR) is a transmembrane protein that acts as a receptor of extracellular protein ligands of the epidermal growth factor (EGF/ErbB) family. It has been shown that EGFR is overexpressed by many tumours and correlates with poor prognosis. Therefore, EGFR can be considered as a very interesting therapeutic target for the treatment of a large variety of cancers such as lung, ovarian, endometrial, gastric, bladder and breast cancers, cervical adenocarcinoma, malignant melanoma and glioblastoma.

Molecular Rearrangement of an Aza-Scorpiand Macrocycle Induced by pH: A Computational Study.

Rearrangements and their control are a hot topic in supramolecular chemistry due to the possibilities that these phenomena open in the design of synthetic receptors and molecular machines. Macrocycle aza-scorpiands constitute an interesting system that can reorganize their spatial structure depending on pH variations or the presence of metal cations. In this study, the relative stabilities of these conformations were predicted computationally by semi-empirical and density functional theory approximations, and the reorganization from closed to open conformations was simulated by using the Monte Carlo multiple minimum method.

Discriminating Drug-Like Compounds by Partition Trees with Quantum Similarity Indices and Graph Invariants.

The search for new drug candidates in databases is of paramount importance in pharmaceutical chemistry. The selection of molecular subsets is greatly optimized and much more promising when potential drug-like molecules are detected a priori. In this work, about one hundred thousand molecules are ranked following a new methodology: a drug/non-drug classifier constructed by a consensual set of classification trees.

The prediction of human intestinal absorption based on the molecular structure.

Human Intestinal Absorption (HIA) has been modeled many times by using classification models. However, regression models are scarce. Here, Artificial Neural Networks (ANNs) are implemented for this purpose.

A probabilistic analysis about the concepts of difficulty and usefulness of a molecular ranking classification.

Discerning between the concepts of difficulty and usefulness of a molecular ranking classification is of significant importance in virtual design chemistry. Here, both concepts are viewed from the statistical and practical point of view according to the standard definitions of enrichment and statistical significance p-values. These parameters are useful not only to compare distinct rankings obtained for the same molecular database, but also in order to compare the ones established in distinct molecular sets from an objective point of view.

Modeling anti-allergic natural compounds by molecular topology.

Molecular topology has been applied to the search of QSAR models able to identify the anti-allergic activity of a wide group of heterogeneous compounds. Through the linear discriminant analysis and artificial neural networks, correct classification percentages above 85% for both the training set and the test set have been obtained. After carrying out a virtual screening with a natural product library, about thirty compounds with theoretical anti-allergic activity have been selected.

Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds.

Trichomonas vaginalis (Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline.

Trends and plot methods in MLR studies.

Regression toward the mean effects are presented within the field of quantitative structure-activity relationship modeling and in situations in which multilinear regression techniques are considered for model building. The concept is related to the graphical aspect of some scatter plots (experimental vs fitted and fitted vs experimental values). These graphs demonstrate how the point cloud is not always symmetrically distributed along the so-called "ideal" or "desired" line, that is, the bisector of the first and third quadrants.

True prediction of lowest observed adverse effect levels.

A database of structurally heterogeneous chemical structures with their experimental values of Lowest Observed Adverse Effect Levels (LOAELs) was modeled using graph theoretical descriptors. Variable selection for multiple linear regression (MLR) and linear discriminant analysis (LDA) was accomplished by the Internal Test Set (ITS) method in order to achieve true predicted LOAEL values. The results obtained can be considered good if we take in count the structural diversity of the training set.

Identification of new antimalarial drugs by linear discriminant analysis and topological virtual screening.

Objectives: A quantitative structure-activity relationship study using a database of 395 compounds previously tested against chloroquine-susceptible strains of the blood stages of Plasmodium falciparum to predict new in vitro antimalarial drugs has been developed.

Methods: Topological indices were used as structural descriptors and were related to antimalarial activity by using linear discriminant analysis (LDA) and multilinear regression (MLR). Two discriminant equations were obtained (FD1 and FD2), which allowed us to carry out successful classification of 90% and 80% of compounds, respectively.

In vitro activity of linezolid, clarithromycin and moxifloxacin against clinical isolates of Mycobacterium kansasii.

Objectives: To compare the activity of linezolid with a range of drugs used in the treatment of Mycobacterium kansasii infections.

Results: The percentages of resistant isolates against isoniazid, rifampicin and ethambutol were 2.9%, 1.

Search of chemical scaffolds for novel antituberculosis agents.

A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three techniques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear regression, and shrinkage estimation-ridge regression.

Predictability and prediction of lowest observed adverse effect levels in a structurally heterogeneous set of chemicals.

A database of chronic lowest observed adverse effect levels (LOAELs) for 234 compounds, previously compiled from different sources (Toxicology Letters79, 131-143 (1995)), was modelled using graph theoretical descriptors. This study reveals that data are not homogeneous. Only those data originating from the U.

Structural analysis of chiral complexes of palladium(0) with 15-membered triolefinic macrocyclic ligands.

The complete structural analysis of the palladium complexes of the triolefinic macrocycles (E,E,E)-1,6,11-tris(arylsulfonyl)-1,6,11-triazacyclopentadeca-3,8,13-trienes, which featured from three identical to three different aryl groups, was achieved by performing X-ray diffraction studies, NMR spectroscopy, and other calculations. The stereochemical complexity is determined by the different isomers formed through complexation of the metal to one or other face of each of the three olefins involved. The palladacyclopropane formulation of the palladium-olefin interaction offers a clear picture of the stereogenicity of the olefin carbon atoms that are complexed to the metal.

Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans.

Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published.

Virtual generation of agents against Mycobacterium tuberculosis. A QSAR study.

A QSAR approach based on the use of various topological indices as new theoretical molecular descriptors was applied to the study of a set of 64 anti-tuberculosis agents involving the substituted benzoxazines and phenylquinazolines. In order to evaluate the reliability of the proposed linear QSAR model, several statistical tests were proposed. The resulting model was subsequently applied to a wider virtual molecular library, which, together with the original set of 64 molecules with known activities contained another 512 molecules for which the predictions were made.

New agents active against Mycobacterium avium complex selected by molecular topology: a virtual screening method.

Objectives: In order to select new drugs and to predict their in vitro activity against Mycobacterium avium complex (MAC), new quantitative structure-activity relationship (QSAR) models were developed.

Methods: The activities against MAC of 29 structurally heterogeneous drugs were examined by means of linear discriminant analysis (LDA) and multilinear regression analysis (MLRA) by using topological indices (TI) as structural descriptors. In vitro antimycobacterial activities were determined by a broth microdilution method with 7H9 medium.