Molecular modeling and LC-MS-based metabolomics of a glutamine-valproic acid (Gln-VPA) derivative on HeLa cells.

Glutaminase plays an important role in carcinogenesis and cancer cell growth. This biological target is interesting against cancer cells. Therefore, in this work, in silico [docking and molecular dynamics (MD) simulations] and in vitro methods (antiproliferative and LC-MS metabolomics) were employed to assay a hybrid compound derived from glutamine and valproic acid (Gln-VPA), which was compared with 6-diazo-5-oxo-L-norleucine (DON, a glutaminase inhibitor) and VPA (contained in Gln-VPA structure). Docking results from some snapshots retrieved from MD simulations show that glutaminase recognized Gln-VPA and DON. Additionally, Gln-VPA showed antiproliferative effects in HeLa cells and inhibited glutaminase activity. Finally, the LC-MS-based metabolomics studies on HeLa cells treated with either Gln-VPA (IC60 = 8 mM) or DON (IC50 = 3.5 mM) show different metabolomics behaviors, suggesting that they modulate different biological targets of the cell death mechanism. In conclusion, Gln-VPA is capable of interfering with more than one pharmacological target of cancer, making it an interesting drug that can be used to avoid multitherapy of classic anticancer drugs.

In vitro and in silico evaluation of fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor.

The fucosterol has been reported numerous biological activities. In this study, the activity in vitro of the fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor was evaluated. The structural identification was obtained by nuclear magnetic resonance (NMR) spectroscopy and based on experimental data, we combined docking and molecular dynamics simulations coupled to the molecular-mechanics-generalized-born-surface-area approach to evaluating the structural and energetic basis for the molecular recognition of fucosterol and neostigmine at the binding site of acetylcholinesterase (AChE). In addition, the Lineweaver-Burk plot showed the nature of a non-competitive inhibition. The maximum velocity (Vmax) and the constant of Michaelis-Menten (Km) estimated for fucosterol (0.006 µM) were 0.015 1/Vo (ΔA/h and 6.399 1/[ACh] mM-1, respectively. While, for neostigmine (0.14 µM), the Vmax was 0.022 1/Vo (ΔA/h) and Km of 6.726 1/[ACh] mM-1, these results showed a more effective inhibition by fucosterol respect to neostigmine. Structural analysis revealed that neostigmine reaches the AChE binding site reported elsewhere, whereas fucosterol can act as a no-competitive and competitive acetylcholinesterase inhibitor, in agree with kinetic enzymatic experiments. Binding free energy calculations revealed that fucosterol reaches the acetylcholinesterase binding site with higher affinity than neostigmine, which is according to experimental results. Whereas the per-residue decomposition free energy analysis let us identify crucial residues involved in the molecular recognition of ligands by AChE. Results corroborate the ability of theoretical methods to provide crucial information at the atomic level about energetic and structural differences in the binding interaction and affinity from fucosterol with AChE. Communicated by Ramaswamy H. Sarma.

QSAR, docking, dynamic simulation and quantum mechanics studies to explore the recognition properties of cholinesterase binding sites.

A set of 84 known N-aryl-monosubstituted derivatives (42 amides: series 1 and 2, and 42 imides: series 3 an 4, from maleic and succinic anhydrides, respectively) that display inhibitory activity toward both acetylcholinesterase and butyrylcholinesterase (ChEs) was considered for Quantitative structure-activity relationship (QSAR) studies. These QSAR studies employed docking data from both ChEs that were previously submitted to molecular dynamics (MD) simulations. Donepezil and galanthamine stereoisomers were included to analyze their quantum mechanics properties and for validating the docking procedure. Quantum parameters such as frontier orbital energies, dipole moment, molecular volume, atomic charges, bond length and reactivity parameters were measured, as well as partition coefficients, molar refractivity and polarizability were also analyzed. In order to evaluate the obtained equations, four compounds: 1a (4-oxo-4-(phenylamino)butanoic acid), 2a ((2Z)-4-oxo-4-(phenylamino)but-2-enoic acid), 3a (2-phenylcyclopentane-1,3-dione) and 4a (2-phenylcyclopent-4-ene-1,3-dione) were employed as independent data set, using only equations with r(m(test))²>0.5. It was observed that residual values gave low value in almost all series, excepting in series 1 for compounds 3a and 4a, and in series 4 for compounds 1a, 2a and 3a, giving a low value for 4a. Consequently, equations seems to be specific according to the structure of the evaluated compound, that means, series 1 fits better for compound 1a, series 3 or 4 fits better for compounds 3a or 4a. Same behavior was observed in the butyrylcholinesterase (BChE). Therefore, obtained equations in this QSAR study could be employed to calculate the inhibition constant (Ki) value for compounds having a similar structure as N-aryl derivatives described here. The QSAR study showed that bond lengths, molecular electrostatic potential and frontier orbital energies are important in both ChE targets. Docking studies revealed that despite the multiple conformations obtained through MD simulations on both ChEs, the ligand recognition properties were conserved. In fact, the complex formed between ChEs and the best N-aryl compound reproduced the binding mode experimentally reported, where the ligand was coupled into the choline-binding site and stabilized through π-π interactions with Trp82 or Trp86 for BChE and AChE, respectively, suggesting that this compound could be an efficient inhibitor and supporting our model.

Mapping myeloperoxidase to identify its promiscuity properties using docking and molecular dynamics simulations.

Myeloperoxidase (MPO) is the most abundant heme protein in neutrophils, and MPO catalyzes hypochlorous acid (HOCl) formation. MPO inhibitors (MPOis) can be used to treat several diseases in which MPO and HOCl levels are elevated. The molecular details of several MPOis have not been extensively studied to elucidate their molecular recognition properties. In addition, it is not known whether MPO has only one binding site or more binding sites for aryl compounds, which would explain its promiscuity properties. Therefore, docking simulations were performed to analyze the MPO binding site recognition using several X-ray structures and snapshots retrieved from molecular dynamics (MD) simulations to simulate the binding of MPO with several known aryl ligands. All of the evaluated ligands were recognized by MPO at the same site, which was identified by the Q-Site Finder as being one of the principal sites and named herein as the "principal binding site" (PBS). The PBS is composed of Q91, H95, F99, R239, E242, F366 and F407. The results indicate that the MPO ligand recognition is mediated by π-π interactions with an aromatic cluster (F99, F366, F407 and a heme group), giving rise to high MPO promiscuity. In addition, MD simulations and X-ray crystallography show limited conformational variations in the MPO. In addition, either MPOis or another substrate (tyrosine) reaches the same site, but different interactions were observed. Therefore, the results indicate minor movement in the side chain of the mentioned amino acids that allow ligands to be recognized in the same MPO site with different interactions that are dependent on their chemical structures. Furthermore, docking study samples of several conformations retrieved from the MD simulations showed that ABAH was one of the ligands that always had the same interaction. This result provides potential evidence for hydrazides being very good MPOis.

In silico methods to assist drug developers in acetylcholinesterase inhibitor design.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by a low acetylcholine (ACh) concentration in the hippocampus and cortex. ACh is a neurotransmitter hydrolyzed by acetylcholinesterase (AChE). Therefore, it is not surprising that AChE inhibitors (AChEIs) have shown better results in the treatment of AD than any other strategy. To improve the effects of AD, many researchers have focused on designing and testing new AChEIs. One of the principal strategies has been the use of computational methods (structural bioinformatics or in silico methods). In this review, we summarize the in silico methods used to enhance the understanding of AChE, particularly at the binding site, to design new AChEIs. Several computational methods have been used, such as docking approaches, molecular dynamics studies, quantum mechanical studies, electronic properties, hindrance effects, partition coefficients (Log P) and molecular electrostatic potentials surfaces, among other physicochemical methods that exhibit quantitative structure-activity relationships.

Molecular modeling applied to anti-cancer drug development.

In the past, anti-cancer drugs were identified and developed without focusing on a particular macromolecular target. Currently, the fields of molecular biochemistry, molecular biology, genetics and pharmacology, among other disciplines, have grown considerably in their ability to identify biological targets. These disciplines are now searching for specific targets to treat cancer. These targets exist in different cellular compartments (membrane, cytoplasm, nucleus) as proteins, glycoproteins, nucleic acids, etc. Computational tools have recently been used to explore such targets and to corroborate previously obtained experimental data. These methods have also been used to design new drugs with the aim of decreasing illness and the economic resources needed to discover drug candidates. Some of these computational methods include quantum mechanics (ab initio and density functional theories) and molecular mechanics (docking, molecular dynamics, and protein folding). Docking and molecular dynamics are the most commonly used computational tools for elucidating cancer targets. Using these tools, one can identify the recognition processes between ligands and targets at the atomic level. In addition, one can identify the affinity and conformational changes of these molecular complexes. In conclusion, we propose that the use of such tools is necessary in order to identify new anti-cancer drugs.

Synthesis and theoretical calculations of 5-aminosalicylic acid derivatives as potential analgesic agents.

5-Aminosalicylic acid is one of the drugs most commonly used for inflammatory bowel disease treatment, although its use is limited due to side effects. The aim of this work was to synthesize four 5-ASA derivatives (1-4) and analyze their pharmacological effects. The compound structures were elucidated by spectral (IR and 1H and 13C-NMR) analysis, and their analgesic effects and lethal doses 50 (LD50) were evaluated in the mouse model. In addition, their Log Ps and affinities for both cyclooxygenase enzymes (COX I and COX II) were evaluated through theoretical calculations. All compounds showed analgesic activities from 0.1 mg/Kg to 16 mg/Kg in the mouse model. The imides showed more affinity by COX enzymes and their Log Ps were the highest. The docking calculations showed that all compounds have good affinities for COX I and COX II ( identical with 1 microM), making pi-pi, van der Waals interactions and hydrogen bonds. The toxicities of all compounds were low, judging by the LD50. Finally, the docking analysis show that the compounds act on COX enzymes and their analgesic effects could be mediated in part by the inhibition of these enzymes.

Catalytic activity of acetylcholinesterase immobilized on mesoporous molecular sieves.

MCM-41 and FSM-16 were used for enzyme immobilization on account of their good physical and chemical properties. In this work, the catalytic activity of acetylcholinesterase (AChE) immobilized on these materials was investigated, using neostigmina as AChE inhibitor. The results show that AChE was adsorbed on MCM-41 and on FSM-16-TIPB. AChE immobilized on the latter material maintained 70% of its activity and the material did not hydrolyze ACh (as MCM-41) by itself. Therefore, FSM-16-TIPB was the best material, considering also that when neostigmine was applied to AChE immobilized on FSM-16-TIPB, the activity of AChE decreased as occurs in its free from. Hence, this model could be useful in the evaluation of different kinds of AChE inhibitors, allowing the recycling of enzymes and making possible several assays and thereby, lowering cost.