Inhibition of Acetylcholinesterase by Coumarin-Linked Amino Acids Synthetized via Triazole Associated with Molecule Partition Coefficient

A previous study for the identification of acetylcholinesterase (AChE) inhibitors demonstrated that the hybrid between tyrosol, the 1,2,3-triazole nucleus, and the coumarin group, namely 7-({1-[2-(4-hydroxyphenyl)ethyl]-1H-1,2,3-triazol-4-yl}methoxy)-4-methyl-2H-chromen-2-one (10), has a high enzyme inhibitory activity. Here, we synthesized analogues of 10 via triazole with pharmacophoric groups represented by tyrosine, phenylalanine, tryptophan, and glycine in addition to evaluating the impact of coumarin-linked amino acids on AChE inhibition. We obtained eight triazoles, six of which are undescribed. In general, the presence of carboxylic acid decreased the inhibitory activity, while aromatic amino acids increased enzymatic inhibition compared to glycine. The derivative containing tyrosine, structurally most similar to 10, presented the lowest inhibition percentage, indicating that phenolic hydroxyl is not the preponderant factor for inhibition. Molecular docking was not enough to explain in vitro experiments. On the other hand, MlogP (logP calculated by the Moriguchi method) was related positively to enzymatic inhibition. To increase the hydrophobicity of the molecules, we tested the esterified triazole derivatives comparatively with the enzyme. The compound ethyl 2-(4-(((4-methyl-2-oxo-2H-chromen-7-yl)oxy)methyl)-1H-1,2,3-triazol-1-yl)acetate (6) presented an increment of inhibitory activity of 46.97 ± 1.75% at 100 μmol L-1. We also associated the best activity with the lowest van der Waals volume and molar mass values.

Molecular Docking and QSAR Studies of Coumarin Derivatives as NMT Inhibitors: Simple Structural Features as Potential Modulators of Antifungal Activity

Background: Treatments of fungal diseases, including Candidiasis, remain not up to scratch in spite of the mounting catalog of synthetic antifungal agents. These have served as the impetus for investigating new antifungal agents based on natural products. Consequently, genetic algorithm-multiple linear regression (GA-MLR) based QSAR (Quantitative Structure-Activity Relationship) studies of coumarin analogues along with molecular docking were carried out. Methods: Coumarin analogues with their MIC values were used to generate the training and test sets of compounds for QSAR models development; the analogues were also docked into the binding pocket of NMT (MyristoylCoA: protein N-myristoyltransferase). Results and Discussion: The statistical parameters for internal and external validation of QSAR analysis (R2 = 0.830, Q2 = 0.758, R2Pred = 0.610 and R2m overall = 0.683 ), Y Randomization, Ridge trace, VIF, tolerance and model criteria of Golbraikh and Tropsha data illustrate the robustness of the best proposed QSAR model. Most of the analogues bind to the electrostatic, hydrophobic clamp and display hydrogen bonding with amino acid residues of NMT. Interestingly, the most active coumarin analogue (MolDock score of -189.257) was docked deeply within the binding pocket of NMT, thereby displaying hydrogen bonding with Tyr107, Leu451, Leu450, Gln226, Cys393 and Leu394 amino acid residues. Conclusion: The combinations of descriptors from various descriptor subsets in QSAR analysis have highlighted the role of atomic properties such as polarizability and atomic van der Waals volume to explain the inhibitory activity. The models and related information may pave the way for important insight into the designing of putative NMT inhibitors for Candida albicans.

GA-SMLR-Based QSAR Modeling and Molecular Docking Studies of Bisamidine Derivatives as NMT Inhibitors

The present investigation deals with a combination of genetic algorithm-stepwise multiple linear regression (GA-SMLR)-based QSAR modeling and molecular docking applied to bisamidine analogues in an attempt to explore their role as novel NMT inhibitors of Candida albicans. In this regard, 43 bisamidine analogues were investigated for the development of mathematical models. The robustness of the proposed QSAR model was not only ascertained through traditionally used internal and external validation statistical parameters (Q2= 0.740, R2 = 0.819, R_Pred^2 = 0.636) but also through various R_(m)^2 metrics proposed by Roy and Mitra. The descriptors recognized in the QSAR analysis have culminated a significant role of atomic van der Waals volume, topology, nature of bond and dipole moment to modulate the antifungal activity of compounds under investigation. The most active compound revealed enhanced binding potency with MolDock score of -183.451 kcal/mol and displayed hydrogen bond interactions with active amino acids Leu177, Thr211, Tyr225, and IIe111 of NMT.

Quantitative Structure-Properties Relationships and Molecular Dynamic Simulations of Some Lubricant Additives (LAs)

The degradation of this zinc-dialkyl-dithiophosphate (ZDDP), at a temperature less than 246K often leads to the release of phosphorus, sulphur, and zinc which are indirectly responsible for the emission of poisonous gas from the exhaust pipe of the motor cars. Four QSPR mathematical models were generated from 39 structures of lubricant additives (LAs) and the structural features were found to corresponds to the coefficients of; internal correlation (R2 ) of 0.95, adjusted squared correlation (R2 adj) of 0.94, Cross-validation (Q2cv) of 0.90, and the external validation (R2 pred) of 0.54. The model suggests that new LAs with improved onset temperatures (Tonset) could be designed by interpreting and increasing the value of the molecular descriptor such as IC5 (Information Content index/neighborhood symmetry of 5-order) and Ve (V total size index/weighted by Sanderson electronegativity) and at the same time decreasing the values of RDF080m (Radial Distribution Function-080/weighted by mass), RDF110m (Radial Distribution Function-110/weighted by mass), P2v (2nd component shape directional WHIM index/weighted by Van der Waals volume) and R1e+ (R maximal autocorrelation of lag 1/weighted by Sanderson electronegativity). Moreover, the LAs with an experimental onset temperature of 351.6K agreed with the predicted onset temperature of 351.7K13a. And was also in agreement with the result of molecular dynamics simulations in which the LAs with the best dynamic binding energy of -2112.06 kcal/mol was tightly bounded on the simulated DLC mechanical coated boundary inter-surface and was also found to be better than the commercial LAs, ZDDP in term of binding energy and onset temperature. This investigation will help in rational additive design and synthesis of new and better selective Las

Exceptional aggregation propensity of amino acids in polyglutamine amino-acid-homopolymer

Similar aggregation and β-sheet propensity of amino acids in globular proteins and amyloids, suggests comparable principles of their formation. Here we show that during the process of aggregation into amyloid-like fibers, these rules are not the same in an amino-acid-homopolymer (AAHP) polyglutamine (PolyGln). An aggregation kinetic analysis on nine-point mutants of a forty-six long PolyGln peptide was carried in physiological conditions. At the dynamic equilibrium state of aggregation, critical-concentration derived free-energy differences, signifying aggregation propensity of incorporated amino acids were obtained. None of the obtained propensities correlated with existing conventional aggregation and β-sheet propensities of the amino acids in proteins and amyloids. Further, the differential aggregation behavior of all the peptides only correlated with van der Waals volume of the incorporated amino acid and not with any other physicochemical characteristic of amino acids. The new rules obtained from PolyGln AAHP provide an opportunity to explore physiological relevance of a mutation within AAHP in human proteome. Additionally, this study opens up new avenues for protein model design exploring folding and aggregation behavior of other amino-acid-homopolymer (AAHP) existing in the human proteome.SignificanceMutational analysis within PolyGln sequences adds to the knowledge of unique aggregation propensities of amino acids within PolyGln AAHP. This study highlights the importance of van der Waals volume in dictating stability-instability of an aggregation fold and in turn aggregation kinetics and thermodynamic stability of aggregates. The analysis signifies the role of Gln-Gln interlocking system within PolyGln folding motif and extent of disruption caused by van der Waals volume of an amino acid. The results can be taken as a starting point to evaluate the possible impact of amino acid insertions in PolyGln stretches of other proteins. It also opens opportunities to study the structural and functional relationship of other AAHPS for their unique folding and aggregation behavior. Learning outcome can be utilized as a bottom–up approach to design amyloid biomaterial with different strengths for biomedical applications.

Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms

Because of the rapid development of multidrug resistance, conventional antibiotics cannot kill pathogenic bacteria efficiently. New antibiotic treatments such as antimicrobial peptides (AMPs) can provide a possible solution to the antibiotic-resistance crisis. However, the identification of AMPs using experimental methods is expensive and time-consuming. Meanwhile, few studies use amino acid compositions (AACs) and physicochemical properties with different sequence lengths against different organisms to predict AMPs. Therefore, the major purpose of this study is to identify AMPs on seven categories of organisms, including amphibians, humans, fish, insects, plants, bacteria, and mammals. According to the one-rule attribute evaluation, the selected features were used to construct the predictive models based on the random forest algorithm. Compared to the accuracies of iAMP-2L (a web-server for identifying AMPs and their functional types), ADAM (a database of AMP), and MLAMP (a multi-label AMP classifier), the proposed method yielded higher than 92% in predicting AMPs on each category. Additionally, the sensitivities of the proposed models in the prediction of AMPs of seven organisms were higher than that of all other tools. Furthermore, several physicochemical properties (charge, hydrophobicity, polarity, polarizability, secondary structure, normalized van der Waals volume, and solvent accessibility) of AMPs were investigated according to their sequence lengths. As a result, the proposed method is a practical means to complement the existing tools in the characterization and identification of AMPs in different organisms.

Quantitative Structure-activity Relationship Analysis for Predicting Lipophilicity of Aniline Derivatives (Including some Pharmaceutical Compounds)

Background: In this study, we used a hierarchical approach to develop quantitative structureactivity relationship (QSAR) models for modeling lipophilicity of a set of 81 aniline derivatives containing some pharmaceutical compounds. Objective: The multiple linear regression (MLR), principal component regression (PCR) and partial least square regression (PLSR) methods were utilized to construct QSAR models. Materials & Methods: Quantum mechanical calculations at the density functional theory level and 6- 311++G** basis set were carried out to obtain the optimized geometry and then, the comprehensive set of molecular descriptors was computed by using the Dragon software. Genetic algorithm (GA) was applied to select suitable descriptors which have the most correlation with lipophilicity of the studied compounds. Results: It was identified that such descriptors as Barysz matrix (SEigZ), hydrophilicity factor (Hy), Moriguchi octanol-water partition coefficient (MLOGP), electrophilicity (ω/eV) van der Waals volume (vWV) and lethal concentration (LC50/molkg-1) are the best descriptors for QSAR modeling. The high correlation coefficients and the low prediction errors for MLR, PCR and PLSR methods confirmed good predictability of the three models. Conclusion: In present study, the high correlation between experimental and predicted logP values of aniline derivatives indicated the validation and the good quality of the resulting three regression methods, but MLR regression procedure was a little better than the PCR and PLSR methods. It was concluded that the studied aniline derivatives are not hydrophilic compounds and this means these compounds hardly dissolve in water or an aqueous solvent.

QSAR Analysis of Multimodal Antidepressants Vortioxetine Analogs Using Physicochemical Descriptors and MLR Modeling

Background: Vortioxetine is a multimodal antidepressant drug with combined effects on SERT as an inhibitor, 5-HT1A as agonist and 5-HT3A as an antagonist. Series of vortioxetine analogs have been reported as multi antidepressant compounds and they block serotonin transport into the neuronal cells, activate the postsynaptic 5-HT1A receptors and eliminate the low activity of 5-HT3A receptors. Objective: To explore the important properties of vortioxetine analogs involved in antidepressant activity by developing 2D QSAR models. Methods: Selections of significant descriptors were performed by Least Absolute Shrinkage and Selection Operator (LASSO) method and, the Multiple Linear Regression (MLR) method and All Subsets and GA algorithm included in QSARINS software were used for generating QSAR models. Further, the virtual screening was performed based on bioactivity and structure similarity using the PubChem database. Results: The four descriptor model of complementary information content (CIC2), solubility (bcutp3), mass (bcutm8) and partial charge in van der Waals surface area (PEOEVSA7) of the molecules is obtained for SERT inhibition with the significant statistics of R2= 0.69, RMSEtr= 0.44, R2 ext= 0.62 and CCCext= 0.78. For 5-HT1A agonist, the two descriptor model of molecular shape (Kappm3) and van der Waals volume of the atoms (bcutv11) with R2= 0.78, RMSEtr= 0.33, R2 ext = 0.83, and CCCext= 0.87 is established. The three descriptor model of information content (IC3), solubility (bcutp9) and electronegativity (GATSe5) of the molecules with R2= 0.61, RMSEtr= 0.34, R2 ext= 0.69 and CCCext= 0.72 is obtained for 5-HT3A antagonist. The antidepressant activities of 16 virtual screened compounds were predicted using the developed models. Conclusion: The developed QSAR models may be useful to predict antidepressant activity for the newly synthesized vortioxetine analogs.

Characterization and identification of antimicrobial peptides with different functional activities

In recent years, antimicrobial peptides (AMPs) have become an emerging area of focus when developing therapeutics hot spot residues of proteins are dominant against infections. Importantly, AMPs are produced by virtually all known living organisms and are able to target a wide range of pathogenic microorganisms, including viruses, parasites, bacteria and fungi. Although several studies have proposed different machine learning methods to predict peptides as being AMPs, most do not consider the diversity of AMP activities. On this basis, we specifically investigated the sequence features of AMPs with a range of functional activities, including anti-parasitic, anti-viral, anti-cancer and anti-fungal activities and those that target mammals, Gram-positive and Gram-negative bacteria. A new scheme is proposed to systematically characterize and identify AMPs and their functional activities. The 1st stage of the proposed approach is to identify the AMPs, while the 2nd involves further characterization of their functional activities. Sequential forward selection was employed to extract potentially informative features that are possibly associated with the functional activities of the AMPs. These features include hydrophobicity, the normalized van der Waals volume, polarity, charge and solvent accessibility—all of which are essential attributes in classifying between AMPs and non-AMPs. The results revealed the 1st stage AMP classifier was able to achieve an area under the receiver operating characteristic curve (AUC) value of 0.9894. During the 2nd stage, we found pseudo amino acid composition to be an informative attribute when differentiating between AMPs in terms of their functional activities. The independent testing results demonstrated that the AUCs of the multi-class models were 0.7773, 0.9404, 0.8231, 0.8578, 0.8648, 0.8745 and 0.8672 for anti-parasitic, anti-viral, anti-cancer, anti-fungal AMPs and those that target mammals, Gram-positive and Gram-negative bacteria, respectively. The proposed scheme helps facilitate biological experiments related to the functional analysis of AMPs. Additionally, it was implemented as a user-friendly web server (AMPfun, http://fdblab.csie.ncu.edu.tw/AMPfun/index.html) that allows individuals to explore the antimicrobial functions of peptides of interest.

The QSAR study for antibacterial activity of structurally diverse nitroaromatics

The antibacterial activity of a series of structurally diverse nitroaromatic compounds (NACs) (nitrobenzene and nitroheterocyclic derivatives) was estimated in terms of the minimum inhibitory concentrations (MICs) against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli bacteria strains in vitro. The resultant log of 1/MICs (pMICs) was subjected to a quantitative structure–activity relationship analysis (QSAR) using a set of molecular descriptors of the compounds assessed by means of quantum mechanical computation and other methods. The estimated pMIC values of NACs tentatively increased with an increase in their electrophilic potency (in terms of LUMO energy) along with the LUMO–HOMO energy gap (or chemical hardness) towards both bacteria strains. No reliable contribution of lipophilicity (octanol/water log P) of nitroaromatics was found to both bacteria strains. The activity of NACs towards S. aureus increased with an increase in their molecular weight and van der Waals volume, and it also tended to increase with an increase in their polar surface area (PSA) and in the number of hydrogen bond-acceptors (HBAs), whereas using these descriptors against E. coli strain, no satisfactory correlations were obtained. The activity of NACs towards both bacteria strains showed a parabolic type dependence upon the highest positive values of molecular electrostatic potentials (VS, max) that might partially be associated with the non-specific interaction of nitroaromatics with the surfaces of the negatively charged envelopes of bacteria at the initial stage of NACs’ action.