Letícia Cristina Assis

QSAR Models Guided by Molecular Dynamics Applied to Human Glucokinase Activators

In this study, quantitative structure–activity relationship studies which make use of molecular dynamics trajectories were performed on a set of 54 glucokinase protein activators. The conformations obtained by molecular dynamics simulation were superimposed according to the twelve alignments tested in a virtual three‐dimensional box comprised of 2 Å cells. The models were generated by the technique that combines genetic algorithms and partial least squares. The best alignment models generated with a determination coefficient (r2) between 0.674 and 0.743 and cross‐validation (q2) between 0.509 and 0.610, indicating good predictive capacity. The 4D‐QSAR models developed in this study suggest novel molecular regions to be explored in the search for better glucokinase activators.

Quantitative Structure-Activity Relationship Studies for Potential Rho-Associated Protein Kinase Inhibitors

A series of pyridylthiazole derivatives developed by Lawrence et al. as Rho-associated protein kinase inhibitors were subjected to four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis. The models were generated applying genetic algorithm (GA) optimization combined with partial least squares (PLS) regression. The best model presented validation values of , , , , , , and . Furthermore, analyzing the descriptors it was possible to propose new compounds that predicted higher inhibitory concentration values than the most active compound of the series.

Design of Novel N-Miristoiltransferase Inhibitors of Leishmania donovani Using Four-Dimensional Quantitative Structure-Activity Relationship Analysis

N-Myristoylation protein is catalyzed by N-myristoyltransferase (NMT), an essential target in Leishmania donovani, the causative agent of kala-azar. Four-dimensional quantitative structureactivity relationship (4D-QSAR) analysis was applied to a series of 77 Leishmania donovani NMT inhibitors. Then, three new compounds were proposed using QSAR models. In addition, molecular docking was performed to predict the binding affinities and interaction modes among the proposed compounds and the NMT active site. In silico absorption, distribution, metabolism and excretion (ADME) evaluation was performed and potential inhibitors demonstrated satisfactory pharmacokinetic properties.

Interactions of cantharidin-like inhibitors with human protein phosphatase-5 in a Mg2+ system: molecular dynamics and quantum calculations

AbstractThe serine/threonine protein phosphatase type 5 (PP5) is a promising target for designing new antitumor drugs. This enzyme is a member of the PPP phosphatases gene family, which catalyzes a dephosphorylation reaction: a regulatory process in the signal transduction pathway that controls various biological processes. The aim of this work is to study and compare the inhibition of PP5 by ten cantharidin-like inhibitors in order to bring about contributions relevant to the better comprehension of their inhibitory activity. In this theoretical investigation, we used molecular dynamics techniques to understand the role of key interactions that occur in the protein active site; QM calculations were employed to study the interaction mode of these inhibitors in the enzyme. In addition, atoms in molecules (AIM) calculations were carried out to characterize the chemical bonds among the atoms involved and investigate the orbital interactions with their respective energy values. The obtained results suggest that the Arg275, Asn303, His304, His352, Arg400, His427, Glu428, Val429, Tyr451, and Phe446 residues favorably contribute to the interactions between inhibitors and PP5. However, the Asp271 and Asp244 amino acid residues do not favor such interactions for some inhibitors. Through the QM calculations, we can suggest that the reactional energy of the coordination mechanism of these inhibitors in the PP5 active site is quite important and is responsible for the inhibitory activity. The AIM technique employed in this work was essential to get a better comprehension of the transition states acquired from the mechanism simulation. This work offers insights of how cantharidin-like inhibitors interact with human PP5, potentially allowing the design of more specific and even less cytotoxic drugs for cancer treatments. Graphical AbstractInteractions of cantharidin-like inhibitors with human protein phosphatase-5 in a Mg2+ system

QSPR Models of β-dihydroagarofuran Derivatives: Exploring Lead Compounds for Pesticides

The use of chemical pesticides, although the most effective method for controlling insects, may in the long-term result in pest resistance development as well as it may impact on food quality, the environment and human health. Therefore, the botanical insecticides are interesting alternatives to minimize these undesirable effects, including a secondary metabolite in the Celastraceae family. Thus, a QSPR study was conducted for β-dihidroagarofuran derivatives with pesticide properties in order to identify features that may improve the potency thereof. The best model obtained from alignment 3 showed values of Q2=0.657, R2=0.757, R2p=0672 and R2m(test)=0.509, indicating good predictive ability and statistical robustness. Moreover, the descriptors presented important pharmacophore groups for the development of new pesticides. KEywoRDS β-dihidroagarofuran, Mortality, Natural Pesticides, QSPR

Toxoplasmosis: Perspectives on the Study of New Therapeutic Targets

Toxoplasma gondii is an intracellular parasite responsible for causing the disease known as toxoplasmosis. This protozoan is easily found in nature and can cause infections in birds and mammals. Currently the toxoplasmosis treatment presents some limitations since the drugs used show low efficiency and can cause serious side-effects. Based on these therapeutic limitations arises the need for design and discovering more potent and selective new drugs against toxoplasmosis. In this context, the computational medicinal chemistry has been used as an important tool in the discovery of new therapeutic targets in the causative agents of several diseases, including toxoplasmosis. This work aims to quickly discuss some new molecular targets such as adenosine kinase, dihydrofolatereductase and thymidylate synthase enzymes, which have been exploited by computational techniques (docking and comparative modeling) in order to direct the planning of new drugs against toxoplasmosis.