Comprehensive analysis of crystal structure, spectroscopic properties, quantum chemical insights, and molecular docking studies of two pyrazolopyridine compounds: potential anticancer agents

In this study, two pyrazolo[3,4-b]pyridine derivatives (4a and 4b) were grown using a slow evaporation solution growth technique and characterized by FT-IR, HRMS, 1H/13C NMR spectroscopy, and X-ray crystallography. The 4a and 4b structures crystallized in monoclinic and triclinic systems with space groups P21/n and P1̄, respectively. Theoretical calculations were performed at the DFT/B3LYP level for the optimized geometries. The results were in excellent agreement with the experimental data (spectroscopic and XRD). This investigation encompasses molecular modeling studies including Hirshfeld surface analysis, energy framework calculations, and frontier molecular orbital analysis. Intermolecular interactions within the crystal structures of the compounds were explored through Hirshfeld surface analysis, which revealed the notable presence of hydrogen bonding and hydrophobic interactions. This insight provides valuable information on the structural stability and potential solubility characteristics of these compounds. The research was extended to docking analysis with eight distinct kinases (BRAF, HER2, CSF1R, MEK2, PDGFRA, JAK, AKT1, and AKT2). The results of this analysis demonstrate that both 4a and 4b interact effectively with the kinase-binding sites through a combination of hydrophobic interactions and hydrogen bonding. Compound 4a had the best affinity for proteins; this is related to the fact that the compound is not rigid and has a small size, allowing it to sit well at any binding site. This study contributes to the advancement of kinase inhibitor research and offers potential avenues for the development of new therapeutic agents for cancer treatment.

Piperonal chalcone derivative incorporating the pyrazolo[3,4-b]pyridine moiety; crystal structure, spectroscopic characterization and quantum chemical investigations

A single crystal of a piperonal chalcone derivative was obtained, fully characterized, and crystallized by a slow evaporation technique. The synthesized compound was characterized by UV-Visible, FT-IR, HRMS, ¹H NMR, and ¹³C NMR spectroscopic studies and X-ray crystallography, revealing that the crystal belongs to a triclinic crystal system with a P1̄ space group, Z = 2. In the present work, we focus on molecular modeling studies such as Hirshfeld surface analysis, energy framework calculations, frontier molecular orbital analysis, natural bond orbital analysis, and NLO properties of a π-conjugate system combining the chalcone and the pyrazole[3,4-b]pyridine scaffolds to describe the in-depth structural analysis thereof. Good agreement was found between the calculated results and experimental data. In addition, Hirshfeld surface analysis of the crystal structure showed that the intermolecular stabilization in the crystal packing comes mainly from H⋯H bond interactions. The chalcone crystal exhibits significant NLO properties suggesting that it could be considered a potential candidate for application in nonlinear optical devices.

Rational Design of Novel Glycomimetic Peptides for E-Selectin Targeting

E-selectin is a cell-adhesion receptor with specific recognition capacity toward sialo-fucosylated Lewis carbohydrates present in leukocytes and tumor cells. E-selectin interactions mediate the progress of inflammatory processes and tumor metastasis, which aroused the interest in using this protein as a biomolecular target to design glycomimetic inhibitors for active targeting or therapeutic purposes. In this work, we report the rational discovery of two novel glycomimetic peptides targeting E-selectin based on mutations of the reference selectin-binding peptide IELLQAR. Sixteen single or double mutants at Ile1, Leu3, Leu4, and Arg7 residues were evaluated as potential candidates for E-selectin targeting using 50 ns molecular dynamics (MD) simulations. Nine peptides showing a stable association with the functional pocket were modified by adding a cysteine residue to the N-terminus to confer versatility for further chemical conjugation. Subsequent 50 ns MD simulations resulted in five cysteine-modified peptides with retained or improved E-selectin binding potential. Then, 300 ns accelerated MD (aMD) simulations were used to examine the binding properties of the best five cysteine-modified peptides. CIEELQAR and CIELFQAR exhibit the most selective association with the functional pocket of E-selectin, as revealed by potential of mean force profiles. Microscale thermophoresis experiments confirmed the E-selectin binding capacity of the selected peptides with K_D values in the low micromolar range (CIEELQAR K_D = 35.0 ± 1.4 μM; CIELFQAR K_D = 16.4 ± 0.7 μM), which are 25-fold lower than the reported value for the native ligand sLe^x (K_D = 878 μM). Our findings support the potential of CIEELQAR and CIELFQAR as novel E-selectin-targeting peptides with high recognition capacity and versatility for chemical conjugation, which are critical for enabling future applications in active targeting.

NanoMIPs Design for Fucose and Mannose Recognition: A Molecular Dynamics Approach

Nanoscale molecularly imprinted polymers (nanoMIPs) are powerful molecular recognition tools with broad applications in the diagnosis, prognosis, and treatment of complex diseases. In this work, fully atomistic molecular dynamics (MD) simulations are used to assist the design of nanoMIPs with recognition capacity toward l-fucose and d-mannose as prototype disease biomarkers. MD simulations were conducted on prepolymerization mixtures containing different molar ratios of the monomers N-isopropylacrylamide (NIPAM), methacrylamide (MAM), and (4-acrylamidophenyl)(amino)methaniminium acetate (AB) and fixed molar ratios of the cross-linker ethylene glycol dimethacrylate (EGDMA) in explicit acetonitrile as the porogenic solvent. Prepolymerization mixtures containing ternary mixtures of NIPAM (50%), MAM (25%), and AB (25%) exhibit the best imprinting potential for both l-fucose and d-mannose, as they maximize (i) the stability of template-monomer plus template-cross-linker interactions, (ii) the number of functional monomers plus cross-linkers organized around the template, and (iii) the number of hydrogen bonds participating in template recognition. The studied prepolymerization mixtures exhibit an overall increased recognition capacity toward d-mannose over l-fucose, which is attributed to the higher hydrogen-bonding capacity of the former template. Our results are valuable to guide the synthesis of efficient nanoMIPs for sugar recognition and provide a computational framework extensible to any other template, monomer, or cross-linker combination, thus constituting a promising strategy for the rational design of molecularly imprinted materials.

Polyamidoamine-based nanovector for the efficient delivery of methotrexate to U87 glioma cells

The purpose of this study was to design a polyamidoamine (PAMAM)-based nanovector for the efficient delivery of methotrexate to U87 glioma cells. To this end, 0-100% acetylated PAMAM dendrimers of the fourth generation were synthesized and evaluated using drug encapsulation measurements, molecular dynamics simulations, neurotoxicity assays and neuronal internalization experiments. The best system was tested as a nanovector for methotrexate delivery to U87 glioma cells. The authors found that 25% acetylated PAMAM dendrimers of the fourth-generation combine low intrinsic toxicity, large drug complexation capacity and efficient internalization into hippocampal neurons. Nanovector complexation enhances the cytotoxic response of methotrexate against U87 glioma cells compared with free drug solutions. In conclusion, 25% acetylated PAMAM dendrimers of the fourth-generation increase drug uptake by glioma cells and thereby act as efficient nanovectors for methotrexate delivery.

Mechanism-Based Rational Discovery and In Vitro Evaluation of Novel Microtubule Stabilizing Agents with Non-Taxol-Competitive Activity

Microtubules (MT) are cytoskeletal polymers of αβ-tubulin dimers that play a critical role in many cellular functions. Diverse antimitotic drugs bind to MT and disrupt their dynamics acting as MT stabilizing or destabilizing agents. The occurrence of undesired side effects and drug resistance encourages the search for novel MT binding agents with chemically diverse structures and different interaction profiles compared to known active compounds. This work reports the rational discovery of seven novel MT stabilizers using a combination of molecular modeling methods and in vitro experimental assays. Virtual screening, similarity filtering, and molecular mechanics generalized Born surface area (MM/GBSA) binding free energy refinement were employed to select seven potential candidates with high predicted affinity toward the non-taxoid site for MT stabilizers on β-tubulin. MD simulations of 150 ns on reduced MT models suggest that candidate compounds strengthen the longitudinal interactions between tubulin dimers across protofilaments, which is a primary molecular mechanism of action for known MT stabilizers. In vitro MT polymerization assays confirmed that all candidates promote MT assembly at concentrations of >50 mM and exhibit noncompetitive MT polymerization profiles when cotreating with Taxol. Preliminary HeLa cell viability assays revealed a moderate cytotoxic effect for the compounds under study at 100 μM concentration. These results support the validity of our rational discovery strategy and the use of molecular modeling methods to pursue the search and optimization of new MT targeting agents.

In Silico Design of Novel Mutant Anti-MUC1 Aptamers for Targeted Cancer Therapy

The transmembrane glycoprotein mucin 1 (MUC1) is an attractive tumor marker for cancer therapy and diagnosis. The nine amino acid extracellular epitope APDTRPAPG of this protein is selectively recognized by the S2.2 single-stranded DNA anti-MUC1 aptamer, which has emerged as a promising template for designing novel targeting agents for MUC1-directed therapy. In this work, 100 ns molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, and conformational analysis were employed to propose a novel prospective anti-MUC1 aptamer with increased affinity toward the MUC1 epitope resulting from the double mutation of the T11 and T12 residues with PSU and U nucleosides, respectively. The double mutant aptamer exhibits a tight interaction with the MUC1 epitope and adopts a groove conformation that structurally favors the intermolecular contact with the epitope through the intermediate T11-A18 region leaving the 3' and 5' ends free for further chemical conjugation with a nanocarrier or pharmaceutical. These results are valuable to gain understanding about the molecular features governing aptamer-epitope interactions and constitute a first key step for the design of novel aptamer-based nanocarriers for MUC1-targeted cancer therapy.

Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein

High-risk strains of human papillomavirus (HPV) have been identified as the etiologic agent of some anogenital tract, head, and neck cancers. Although prophylactic HPV vaccines have been approved; it is still necessary a drug-based treatment against the infection and its oncogenic effects. The E6 oncoprotein is one of the most studied therapeutic targets of HPV, it has been identified as a key factor in cell immortalization and tumor progression in HPV-positive cells. E6 can promote the degradation of p53, a tumor suppressor protein, through the interaction with the cellular ubiquitin ligase E6AP. Therefore, preventing the formation of the E6-E6AP complex is one of the main strategies to inhibit the viability and proliferation of infected cells. Herein, we propose an in silico pipeline to identify small-molecule inhibitors of the E6-E6AP interaction. Virtual screening was carried out by predicting the ADME properties of the molecules and performing ensemble-based docking simulations to E6 protein followed by binding free energy estimation through MM/PB(GB)SA methods. Finally, the top-three compounds were selected, and their stability in the E6 docked complex and their effect in the inhibition of the E6-E6AP interaction was corroborated by molecular dynamics simulation. Therefore, this pipeline and the identified molecules represent a new starting point in the development of anti-HPV drugs.

The role of conserved arginine in the GH70 family: a computational study of the structural features and their implications on the catalytic mechanism of GTF-SI from Streptoccocus mutans

This manuscript provides novel insights into the structural and mechanistic roles of the conserved residue R475 of GTF-SI, a member of the GH70 family.

A QM/MM approach on the structural and stereoelectronic factors governing glycosylation by GTF-SI fromStreptococcus mutans

This manuscript contains novel insights into the reaction mechanism catalyzed by GTF-SI. Structural and electronic features of the system are revealed, such as the strong hydrogen bond depicted above.

Rhodium(i) diphenylphosphine complexes supported on porous organic polymers as efficient and recyclable catalysts for alkene hydrogenation

Highly stable, chemoselective and recyclable immobilized Rh(i) homogeneous catalysts for alkene hydrogenation.

Biotransformation of Indole Derivatives by Mycelial Cultures

Biotransformation of tryptophan to tryptamine and 3-methyl-indole by Psilocybe coprophila was performed. On the other hand, Aspergillus niger was able to transform tryptophan to 5-hydroxy-tryptophan. P. coprophila biotransformed 5-hydroxy-tryptophan to 5-hydroxytryptamine. These results prove once more that fungi are good tools to establish hydroxyindole derivatives.

Colorectal cancer chemoprevention by 2 beta-cyclodextrin inclusion compounds of auraptene and 4'-geranyloxyferulic acid

The inhibitory effects of novel prodrugs, inclusion complexes of 3-(4'-geranyloxy-3'-methoxyphenyl)-2-trans propenoic acid (GOFA) and auraptene (AUR) with beta-cyclodextrin (CD), on colon carcinogenesis were investigated using an azoxymethane (AOM)/dextran sodium sulfate (DSS) model. Male CD-1 (ICR) mice initiated with a single intraperitoneal injection of AOM (10 mg/kg body weight) were promoted by the addition of 1.5% (w/v) DSS to their drinking water for 7 days. They were then given a basal diet containing 2 dose levels (100 and 500 ppm) of GOFA/beta-CD or AUR/beta-CD for 15 weeks. At Week 18, the development of colonic adenocarcinoma was significantly inhibited by feeding with GOFA/beta-CD at dose levels of 100 ppm (63% reduction in multiplicity, p < 0.05) and 500 ppm (83% reduction in the multiplicity, p < 0.001), when compared with the AOM/DSS group (multiplicity: 3.36 +/- 3.34). In addition, feeding with 100 and 500 ppm (p < 0.01) of AUR/beta-CD suppressed the development of colonic adenocarcinomas. The dietary administration with GOFA/beta-CD and AUR/beta-CD inhibited colonic inflammation and also modulated proliferation, apoptosis and the expression of several proinflammatory cytokines, such as nuclear factor-kappaB, tumor necrosis factor-alpha, Stat3, NF-E2-related factor 2, interleukin (IL)-6 and IL-1beta, which were induced in the adenocarcinomas. Our findings indicate that GOFA/beta-CD and AUR/beta-CD, especially GOFA/beta-CD, are therefore able to inhibit colitis-related colon carcinogenesis by modulating inflammation, proliferation and the expression of proinflammatory cytokines in mice.

Bioreduction of Some Common Carbonylic Compounds Mediated by Yeasts

Bioreduction of several prochiral carbonylic compounds such as acetophenone (1), ethyl acetoacetate (2) and ethyl phenylpropionate (3) to the corresponding optically active secalcohols 1a - 3a was performed using wild-type strains of Pichia pastoris UBB 1500, Rhodotorula sp., and Saccharomyces cerevisiae. The reductions showed moderate to excellent conversion and high enantiomeric excess, in an extremely mild and environmentally benign manner in aqueous medium, using glucose as cofactor regeneration system. The obtained alcohols follow Prelog’s rule, but in the reduction of 1 with P. pastoris UBB 1500 the anti- Prelog enantiopreference was observed

Structural studies of native Paecilomyces sp. Exopolysaccharide

A polysaccharide separated from Paecilomyces sp. was determined by gel permeation chromatography to be homogeneous. HPLC showed a monosaccharide containing D-glucose and D-fructose at a ratio of about 2:1. The results obtained from IR, 1H NMR, and 13C NMR analyses confirmed the proposed structure.

Production of Exopolysaccharides by a Submerged Culture of an Entomopathogenic Fungus, Paecilomyces sp

Exopolysaccharide basic was obtained from a submerged culture of a native Paecilomyces sp. strain isolated from Chilean soil

Biotransformation of tryptophan by liquid medium culture of Psilocybe coprophila (Basidiomycetes)

Chemical reactions performed by fungi have been used as a modern tool in chemistry. In this work, we show the tryptophan biotransformation with Psilocybe coprophila on liquid culture medium. The results prove once more the versatility of fungi in performing a wide range of industrially attractive chemical reactions.

Cytotoxicity, antitumoral and antimycobacterial activity of tetrazole and oxadiazole derivatives

In this study, the antimycobacterial activity of mono and di-substituted tetrazole and oxadiazole derivatives and their precursors was assayed on Mycobacterium tuberculosis H37Rv, and cytotoxicity was evaluated on J774 macrophages and on tumoral cell lines. Structure Activity Relationship (SAR) analysis was performed using Principal Component Analysis (PCA) to determine the relationship between these compounds and their biological activities.

Quantum-connectivity descriptors in modeling solubility of environmentally important organic compounds

Quantum-connectivity indices are topographic descriptors combining quantum-chemical and topological information. They are used to describe the water solubility of a noncongeneric data set of organic compounds. A QSPR model is obtained with two quantum-connectivity indices that accounts for more than 90% of the variance in the water solubility of these chemicals. This model is compared to other five QSPR models using constitutional, electrostatic, geometric, quantum-chemical, and topological descriptors calculated by CODESSA. None of these models accounts for more than 85% of the variance in water solubility of the compounds in this data set. The QSPR model obtained with quantum-connectivity indices is also better than that generated from the general pool of 508 CODESSA indices. Models with up to five variables were explored and compared with the model obtained here. It is shown that quantum-connectivity indices contain more structural information than other classes of descriptors at least for describing the water solubility of these 53 chemicals. Structural interpretation of the QSPR model developed as well as the role of the quantum-connectivity indices included in it are also analyzed.

On the Aggregation State and QSPR Models. The Solubility of Herbicides as a Case Study

The goal of this article is to stress the importance of considering the phase in QSPR studies. It is found that the phase plays a fundamental role in the QSPR models from both a statistical and a physical point of view. From a statistical point of view, it is observed that the predictive performance drops drastically when the QSPR model, obtained for a given phase, is used to predict the solubility of the same set of compounds but in another phase. From a physical point of view, when the compounds in the training set are in different phases, the physical interpretation of the descriptors involved in the model is obscured because the descriptors which appear in the correlation equation are a sort of average encoding the different physical mechanisms underlying the property. It is shown that the use of compounds in the same phase, instead, allows a more transparent physical interpretation of the descriptors involved in the model and, at the same time, improves the statistics of the models.

A Simple QSPR Model for Predicting Soil Sorption Coefficients of Polar and Nonpolar Organic Compounds from Molecular Formula

A quantitative structure-property relationship (QSPR) model is developed to predict the logarithm of the soil sorption coefficient of 82 organic compounds. The data set contains polar and nonpolar, saturated, unsaturated, aliphatic, aromatic, and polycyclic aromatic compounds covering a log K(oc) range from about 1 to 6 log units. The best correlation equation, containing only five constitutional descriptors (number of benzene rings, molecular weight, number of N, O, and S atoms), predicts log K(oc) with a squared correlation coefficient of 0.94, having a standard deviation, s, of 0.33. The model is validated with an external set of 43 compounds not included in the training set. The descriptors involved in the model can be obtained easily from the molecular formula without any further calculation; therefore, the model is ready to use by environmental scientists with no background in quantum chemistry or chemical graph theory or when no software is available.

Prediction of Henry's law constants of triazine derived herbicides from quantum chemical continuum solvation models

The Henry's law constants (H) for triazine derived herbicides are calculated using quantum chemical solvation models, SM2, SM3, PCM-DFT, and CPCM-DFT, and their performances are discussed. The results show considerable differences in performance among the different levels of theory. The values of H calculated by the semiempirical methods agree much better with the experimental values than those obtained at the DFT level. The differences are discussed in terms of the different contributions, electrostatic and no-electrostatic, to Gibbs free energy of solvation. In addition, the Henry's law constants of some triazine derived herbicides whose values have not been reported earlier are predicted as well.