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.

Unveiling the Ro60-Ro52 complex.

The coexistence within a subcellular complex of inter-cellular proteins Ro60, responsible for preserving ncRNA quality, and Ro52, involved in intracellular proteolysis, has been a subject of ongoing debate. Employing molecular docking in tandem with experimental methods like Quartz Crystal Microbalance with Dissipation (QCM-D), Proximity Ligation Assay (PLA), and Indirect Immunofluorescence (IIF), we reveal the presence of Ro60 associating with Ro52 within the cytoplasm. This result unveils the formation of a weak transient complex with a K ≈ (3.

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.

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.

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.

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.