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 1 and 2-propynamide 2, 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 1 is a zwitterionic species with no pseudoradical or carbenoid centers. Conceptual density functional theory (CDFT) indices were used to predict the global electronic flux from the strong nucleophilic N-methyl-C-4-methyl phenylnitrone 1 to the electrophilic 2-propynamide 2 functions. The 32CA reactions proceeded through two pairs of stereo- and regioisomeric reaction pathways to generate four different products: 3, 4, 5, and 6. The reaction pathways were irreversible owing to their exothermic characters: -136.48, -130.08, -130.99, and -140.81 kJ mol-1, respectively. The enthalpy of the 32CA reaction leading to the formation of cycloadduct 6 was lower compared with the other path owing to a slight increase in its polar character, observed through the global electron density transfer (GEDT) during the transition states and along the reaction path. A bonding evolution theory (BET) analysis showed that these 32CA reactions proceed through the coupling of pseudoradical centers, and the formation of new C-C and C-O covalent bonds did not begin in the transition states.

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. Therefore, the physicochemical characteristics of formulations must be optimized by means of technological strategies. Among the strategies that have been explored, lipid-based nanosystems, particularly nanostructured lipid carriers, are promising in preclinical investigations with minimal toxicity and therapeutic efficacy due to their ability to overcome challenges associated with other nanocarriers. We review the studies of nanostructured lipid carriers for intranasal administration in the treatment of ATD. Currently, no drugs for intranasal administration in ATD have marketing approval, with only three candidates, insulin, rivastigmine and APH-1105, being clinically investigated. Further studies with different candidates will eventually confirm the potential of the intranasal route of administration in the treatment of ATD.

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. For this, a review has been made of the nanoliposomal systems marketed for the treatment of cancer, as well as those that are in the research phase, highlighting the clinical trials being carried out. All marketed liposomes studied are intravenously administered, showing a reduced intensity of side-effects compared with the nonliposomal form. Doxorubicin is the active ingredient most frequently employed. Ongoing clinical trials expand the availability of liposomal medicines with new clinical indications. In conclusion, the introduction of drugs in nanoliposomes means an improvement in their efficacy and the quality of life of patients. The future focus of research could be directed to develop multifunctional targeted nanoliposomes using new anticancer drugs, different types of existing drugs, or new standardized methodologies easily translated into industrial scale.

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. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Receiver Operating Characteristic (AU-ROC) values of 0.95 (leukemia prediction) and 0.80-0.90 (prostate). The preferential selected descriptors here are specific gene expressions, and this is potentially useful to point to possible key genes.

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. METHODS: We have followed a structure-based virtual screening (SBVS) procedure with a library composed of several commercial collections of chemicals (615,462 compounds in total) and the 3D structure of EGFR obtained from the Protein Data Bank (PDB code: 1M17). The docking results from this campaign were then ranked according to the theoretical binding affinity of these molecules to EGFR, and compared with the binding affinity of erlotinib, a well-known EGFR inhibitor. A total of 23 top-rated commercial compounds displaying potential binding affinities similar or even better than erlotinib were selected for experimental evaluation. In vitro assays in different cell lines were performed. A preliminary test was carried out with a simple and standard quick cell proliferation assay kit, and six compounds showed significant activity when compared to positive control. Then, viability and cell proliferation of these compounds were further tested using a protocol based on propidium iodide (PI) and flow cytometry in HCT116, Caco-2 and H358 cell lines. RESULTS: The whole six compounds displayed good effects when compared with erlotinib at 30 µM. When reducing the concentration to 10µM, the activity of the 6 compounds depends on the cell line used: the six compounds showed inhibitory activity with HCT116, two compounds showed inhibition with Caco-2, and three compounds showed inhibitory effects with H358. At 2 µM, one compound showed inhibiting effects close to those from erlotinib. CONCLUSION: Therefore, these compounds could be considered as potential primary hits, acting as promising starting points to expand the therapeutic options against a wide range of cancers.

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. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show pronounced cytocidal activity at the concentration of 100 mug/ml at 24 h (48 h) within the range of 98.66%-100% (99.40%-100%), while only two molecules (chemicals VA7-37 and VA7-38) show high cytocidal activity at the concentration of 10 mug/ml at 24 h (48 h): 98.38% (94.23%) and 97.59% (98.10%), correspondingly. The LDA-assisted QSAR models presented here could significantly reduce the number of synthesized and tested compounds and could increase the chance of finding new chemical entities with anti-trichomonal activity.

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. The IC50 values of the compounds were introduced to get an MLR equation model suitable to predict their in vitro activities. RESULTS: Using this model, a set of 27 drugs against a chloroquine-susceptible clone (3D7) of P. falciparum have been selected and evaluated in vitro. Among these drugs are monensin, nigericin, vincristine, vindesine, ethylhydrocupreine and salinomycin with in vitro IC50s at nanomolar concentrations (0.3, 0.4, 2, 6, 26 and 188 nM, respectively). Other compounds such as hycanthone, amsacrine, aphidicolin, bepridil, amiodarone, ranolazine and triclocarban showed in vitro IC50 values below 5 microM in the mathematical model. CONCLUSIONS: These results demonstrate the usefulness of the approach for the selection and design of new lead drugs active against P. falciparum.

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. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N',N'-tetrakis-(2-pyridylmethyl)-ethylenediamine (TPEN), trifluoperazine, pentamidine, and 2-methyl-4,6-dinitro-phenol (DNOC). They show activity comparable to or superior to ethambutol, used in combination with other drugs for the prevention and treatment of Mycobacterium avium complex and drug-resistant tuberculosis.

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%, 1.9% and 2.9%, respectively. All isolates were susceptible to clarithromycin and moxifloxacin both with MIC(90) values of 0.125 mg/L. Linezolid was active against all isolates with MIC(50) and MIC(90) values of 0.5 and 1 mg/L, respectively, both below the susceptibility breakpoint established for mycobacteria. CONCLUSION: Linezolid, clarithromycin or moxifloxacin, could be used as alternative drugs for treatment of infections due to rifampicin-resistant isolates as well as short-course or intermittent therapy of M. kansasii lung disease.

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. RESULTS: The topological model obtained successfully classifies over 80% of compounds as active or inactive; consequently, it was applied in the search for new molecules active against MAC. From among the selected candidates demonstrating in vitro activity, aflatoxin B1, benzalkonium chloride and pentamidine stand out, with MIC50s between 4 and 32 mg/L. CONCLUSION: The method described in this work is able to select molecules active against MAC.

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. Based on this prediction some new structures were proposed as especially promising candidates for active anti-tuberculotic drugs.