An Fe(III)-carbonato six-coordinate picket fence porphyrin complex with the formula [K(2,2,2-crypt)][FeIII(TpivPP)(CO3)]·C6H5Cl·3H2O (I) has been synthesized and characterized by UV-Vis and FT-IR spectra. The structure of (carbonato)(α,α,α,α-tetrakis(o-pivalamidophenyl)porphinato)ferrate(III) was also established by XRD. The iron atom is hexa-coordinated by the four nitrogen atoms of the pyrrol rings and the two oxygen atoms of the CO32- group. Complex I, characterized as a ferric high-spin complex (S = 5/2), presented higher Fe-Np (2.105(6) Å) and Fe-PC (0.654(2) Å) distances. Both X-ray molecular structure and Hirshfeld surface analysis results show that the crystal packing of I is made by C-H⋯O and C-H⋯Cg weak intermolecular hydrogen interactions involving neighboring [FeIII(TpivPP)(CO3)]- ion complexes. Computational studies were carried out at DFT/B3LYP-D3/LanL2DZ to investigate the HOMO and LUMO molecular frontier orbitals and the reactivity within the studied compound. The stability of compound I was investigated by analyzing both intra- and inter-molecular interactions using the 2D and 3DHirshfeld surface (HS) analyses. Additionally, the frontier molecular orbital (FMO) calculations and the molecular electronic potential (MEP) analyses were conducted to determine the electron localizations, electrophilic, and nucleophilic regions, as well as charge transfer (ECT) within the studied system.

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Flavin-dependent monooxygenases (FMOs) are a valuable group of biocatalysts that can regioselectively introduce a hydroxy group for the targeted modification of biologically active compounds. Here, we present the fdeE, the FMO from Herbaspirillum seropedicae SmR1 that is a part of the naringenin degradation pathway and is active towards a wide range of flavonoids-flavanones, flavones, isoflavones, and flavonols. Bioinformatics and biochemical analysis revealed a high similarity between the analyzed enzyme and other F8H FMOs what might indicate convergent evolutionary mechanism of flavonoid degradation pathway emergence by microorganism. A simple approach with the manipulation of the reaction environment allowed the stable formation of hydroxylation products, which showed very high reactivity in both in vivo and in vitro assays. This approach resulted in an 8-hydroxyquercetin-gossypetin titer of 0.16 g/L and additionally it is a first report of production of this compound.

Colon cancer is a prevalent and potentially fatal disease that demands early and accurate diagnosis for effective treatment. Traditional diagnostic approaches for colon cancer often face limitations in accuracy and efficiency, leading to challenges in early detection and treatment. In response to these challenges, this paper introduces an innovative method that leverages artificial intelligence, specifically convolutional neural network (CNN) and Fishier Mantis Optimizer, for the automated detection of colon cancer. The utilization of deep learning techniques, specifically CNN, enables the extraction of intricate features from medical imaging data, providing a robust and efficient diagnostic model. Additionally, the Fishier Mantis Optimizer, a bio-inspired optimization algorithm inspired by the hunting behavior of the mantis shrimp, is employed to fine-tune the parameters of the CNN, enhancing its convergence speed and performance. This hybrid approach aims to address the limitations of traditional diagnostic methods by leveraging the strengths of both deep learning and nature-inspired optimization to enhance the accuracy and effectiveness of colon cancer diagnosis. The proposed method was evaluated on a comprehensive dataset comprising colon cancer images, and the results demonstrate its superiority over traditional diagnostic approaches. The CNN-Fishier Mantis Optimizer model exhibited high sensitivity, specificity, and overall accuracy in distinguishing between cancer and non-cancer colon tissues. The integration of bio-inspired optimization algorithms with deep learning techniques not only contributes to the advancement of computer-aided diagnostic tools for colon cancer but also holds promise for enhancing the early detection and diagnosis of this disease, thereby facilitating timely intervention and improved patient prognosis. Various CNN designs, such as GoogLeNet and ResNet-50, were employed to capture features associated with colon diseases. However, inaccuracies were introduced in both feature extraction and data classification due to the abundance of features. To address this issue, feature reduction techniques were implemented using Fishier Mantis Optimizer algorithms, outperforming alternative methods such as Genetic Algorithms and simulated annealing. Encouraging results were obtained in the evaluation of diverse metrics, including sensitivity, specificity, accuracy, and F1-Score, which were found to be 94.87%, 96.19%, 97.65%, and 96.76%, respectively.

Psilocin, or 4-HO-DMT (or 3-(2-dimethylaminoethyl)-1H-indol-4-ol), is a psychoactive alkaloid substance from the tryptamine family, isolated from Psilocybe mushrooms. This substance is being studied by various research groups because it has a clear therapeutic effect in certain dosages. In this work, the study of the structure and properties of psilocin was carried using theoretical methods: the effects of polar solvents (acetonitrile, dimethylsulfoxide, water, and tetrahydrofuran) on the structural parameters, spectroscopic properties (Raman, IR, and UV-Vis), frontier molecular orbital (FMO), molecular electrostatic potential (MEP) surface, and nonlinear optical parameters (NLO). Theoretical calculations were performed at the B3LYP/6-311++G(d,p) level by the density functional theory (DFT) method. IEFPCM was used to account for solvent effects. The types and nature of non-covalent interactions (NCI) between psilocin and solvent molecules were determined using Atoms in Molecules (AIM), the reduced density gradient method (RDG), the electron localization function (ELF), and the localization orbital locator (LOL). Experimental and calculated FT-IR, FT-Raman, and UV-Vis spectra were compared and found to be in good agreement.

BACKGROUND: Alzheimer\'s disease, akin to coronary artery disease of the heart, is a progressive brain disorder driven by nerve cell damage.
METHODS: This study utilized computational methods to explore 14 anti-acetylcholinesterase (AChE) derivatives (1 ̶ 14) as potential treatments. By scrutinizing their interactions with 11 essential target proteins (AChE, Aβ, BChE, GSK-3β, MAO B, PDE-9, Prion, PSEN-1, sEH, Tau, and TDP-43) and comparing them with established drugs such as donepezil, galantamine, memantine, and rivastigmine, ligand 14 emerged as notable. During molecular dynamics simulations, the protein boasting the strongest bond with the critical 1QTI protein and exceeding drug-likeness criteria also exhibited remarkable stability within the enzyme\'s pocket across diverse temperatures (300 ̶ 320 K). In addition, we utilized density functional theory (DFT) to compute dipole moments and molecular orbital properties, including assessing the thermodynamic stability of AChE derivatives.
RESULTS: This finding suggests a welldefined, potentially therapeutic interaction further supported by theoretical and future in vitro and in vivo investigations.
CONCLUSIONS: Ligand 14 thus emerges as a promising candidate in the fight against Alzheimer\'s disease.

The enhancement of the peptide bond order by a resonance in the lone pair of N and the π-bond of CO is analyzed. A decomposition of the bond order in terms of localized molecular orbitals is developed and applied to the peptide bond. A combination of two rotations of hybrid orbitals is proposed to improve the boundary treatment in the fragment molecular orbital method. The developed approach is applied to peptide bonds, and it is found crucial to retain the π orbital in the variational space of both fragments across the boundary. The interaction energies between conventional amino acid residues in Trp-cage (1L2Y) are discussed.

The Flavin Monooxygenase (FMO) gene superfamily in plants is involved in various processes most widely documented for its involvement in auxin biosynthesis, specialized metabolite biosynthesis, and plant microbial defense signaling. The roles of FMOs in defense signaling and disease resistance have recently come into focus as they may present opportunities to increase immune responses in plants including leading to systemic acquired resistance, but are not well characterized. We present a comprehensive catalogue of FMOs found in genomes across vascular plants and explore, in depth, 170 wheat TaFMO genes for sequence architecture, cis-acting regulatory elements, and changes due to Transposable Element insertions. A molecular phylogeny separates TaFMOs into three clades (A, B, and C) for which we further report gene duplication patterns, and differential rates of homoeologue expansion and retention among TaFMO subclades. We discuss Clade B TaFMOs where gene expansion is similarly seen in other cereal genomes. Transcriptome data from various studies point towards involvement of subclade B2 TaFMOs in disease responses against both biotrophic and necrotrophic pathogens, substantiated by promoter element analysis. We hypothesize that certain TaFMOs are responsive to both abiotic and biotic stresses, providing potential targets for enhancing disease resistance, plant yield and other important agronomic traits. Altogether, FMOs in wheat and other crop plants present an untapped resource to be exploited for improving the quality of crops.

Background: Flavin monooxygenases (FMOs) are enzymes responsible for the oxidation of a broad spectrum of exogenous and endogenous amines. There is increasing evidence that trimethylamine (TMA), a compound produced by gut bacteria and also recognized as an industrial pollutant, contributes to cardiovascular diseases. FMOs convert TMA into trimethylamine oxide (TMAO), which is an emerging marker of cardiovascular risk. This study hypothesized that blood pressure phenotypes in rats might be associated with variations in the expression of FMOs. Methods: The expression of FMO1, FMO3, and FMO5 was evaluated in the kidneys, liver, lungs, small intestine, and large intestine of normotensive male Wistar-Kyoto rats (WKY) and two distinct hypertensive rat models: spontaneously hypertensive rats (SHRs) and WKY rats with angiotensin II-induced hypertension (WKY-ANG). Plasma concentrations of TMA and TMAO were measured at baseline and after intravenous administration of TMA using liquid chromatography-mass spectrometry (LC-MS). Results: We found that the expression of FMOs in WKY, SHR, and WKY-ANG rats was in the descending order of FMO3 > FMO1 >> FMO5. The highest expression of FMOs was observed in the liver. Notably, SHRs exhibited a significantly elevated expression of FMO3 in the liver compared to WKY and WKY-ANG rats. Additionally, the plasma TMAO/TMA ratio was significantly higher in SHRs than in WKY rats. Conclusion: SHRs demonstrate enhanced expression of FMO3 and a higher plasma TMAO/TMA ratio. The variability in the expression of FMOs and the metabolism of amines might contribute to the hypertensive phenotype observed in SHRs.

Drug oxygenation is mainly mediated by cytochromes P450 (P450s, CYPs) and flavin-containing monooxygenases (FMOs). Polymorphic variants of P450s and FMOs are known to influence drug metabolism.　Species differences exist in terms of drug metabolism and can be important when determining the contributions of individual enzymes. The success of research into drug-metabolizing enzymes and their impacts on drug discovery and development has been remarkable. Dogs and pigs are often used as preclinical animal models. This research update provides information on P450 and FMO enzymes in dogs and pigs and makes comparisons with their human enzymes. Newly identified dog CYP3A98, a testosterone 6β- and estradiol 16α-hydroxylase, is abundantly expressed in small intestine and is likely the major CYP3A enzyme in small intestine, whereas dog CYP3A12 is the major CYP3A enzyme in liver. The roles of recently identified dog CYP2J2 and pig CYP2J33/34/35 were investigated. FMOs have been characterized in humans and several other species including dogs and pigs. P450 and FMO family members have been characterized also in cynomolgus macaques and common marmosets. P450s have industrial applications and have been the focus of attention of many pharmaceutical companies. The techniques used to investigate the roles of P450/FMO enzymes in drug oxidation and clinical treatments have not yet reached maturity and require further development. The findings summarized here provide a foundation for understanding individual pharmacokinetic and toxicological results in dogs and pigs as preclinical models and will help to further support understanding of the molecular mechanisms of human P450/FMO functionality.