How do physicochemical properties contribute to inhibitory activity of promising peptides against Zika Virus NS3 protease?

CONTEXT AND RESULTS: Flavivirus diseases' cycles, especially Dengue and Yellow Fever, can be observed all over Brazilian territory, representing a great health concern. Additionally, there are no drugs available in therapy. In this scenario, in silico methodologies were applied to obtain physicochemical properties, as well as to better understand the ligand-biological target interaction mode of 20 previously reported NS2B/NS3 protease inhibitors of Dengue virus. Since catalytic site of flavivirus hold similarities, such as the same catalytic triad (His51, Asp75 e Ser135), the ability of this series of molecules to fit in Zika NS3 domains can be achieved. We performed an exploratory data analysis, using statistical methodologies, such as PCA (Principal Component Analysis) and HCA (Hierarchical Component Analysis), to assist the comprehension of how physicochemical properties impact the interaction observed by the docking studies, as well as to build a correlation between the respective ranked characteristics. Based on these previous studies, peptides were selected for the dynamics simulations, which were useful to better understand the ligand-protein interactions. Information relating to, for instance, energy, ΔG, average number of hydrogen bonds and distance from Ser135 (one of the main amino acids in the catalytic pocket) were discussed. In this sense, peptides 15 (considering ΔG value and Hbond number), 7 (ΔG and energy) and 1, 6, 7 and 15 (the proximity to Ser135 throughout the dynamics simulation) were highlighted as promising. Those interesting results could contribute to future studies regarding Zika virus drug design, since this infection represents a great concern in neglected populations. METHODS: The models were constructed in the ChemDraw software. The ligand parametrization was performed in the CHEM3D 17.0, UCSF Chimera. Docking simulations were carried out in the GOLD software, after the redocking validation. We used ASP as the function score. Additionally, for dynamics simulations we applied GROMACS software, exploring, mainly, free binding energy calculations. Exploratory analysis was carried out in Minitab 17.3.1 statistical software. Prior to the exploratory analysis, data of quantum chemical properties of the peptides were collected in Microsoft Excel spreadsheet and organized to obtain Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA).

Zika Virus NS2B-NS3 Protease: Quantum Chemical Properties Insights into Designing Inhibitory Peptides.

BACKGROUND: Zika fever affects poor and vulnerable populations, presenting cycles observed in, at least 86 countries, with no vaccine prevention or treatment available. It is known that the genus Flavivirus causes Zika Virus (ZIKV), as Dengue and Yellow Fever, whose genetic material decodes, among other proteins, a series of non-structural (NS) proteins essential for viral replication, such as NS2B-NS3 protease. Additionally, chemical and biological systems are commonly studied using molecular modeling approaches allowing, among several other processes, to elucidate mechanisms of action, molecule reactivity and/or chemical properties and the design of new drugs. Thus, considering the in silico complexes between the biological target and the bioactive molecule, it is possible to understand better experimental results based on molecular properties, which are compared with the findings of the biological activity. OBJECTIVE: Accordingly, this study aimed to present computational docking simulations of five previously reported active peptides against NS2B-NS3 protease of ZIKV and analyze some quantum chemical properties to identify the main contribution to improving the action. METHODS: The compounds were described by Rut and coworkers (2017) and Hill and coworkers (2018), submitted to docking simulation in Gold software and quantum chemical properties calculations in Wavefunction Spartan software. RESULTS: Total energy, electrophilicity index (ω) and energy gap (GAP) appeared to be the best properties to justify the peptide's biological activity. Moreover, the most promising compound (P1, Km 4.18 µM) had the best value of total energy (- 2763.04001 au), electrophilicity index (8.04 eV) and GAP (6.49 eV), indicating an energetically favorable molecule with good interaction with the target and, when compared to other peptides, presented moderate reactivity. P4 showed the highest electrophilicity index value (28.64 eV), which justified the interaction ability visualized in the docking simulation. However, its GAP value (4.24 eV) was the lowest in the series, suggesting high instability, possibly validating its low biological activity value (Km 19 uM). GAP was important to understand the chemical instability, and high values can promote damage to biological response. CONCLUSION: Furthermore, it was also noted that high electron affinity, related to the electrophilicity index, promoted electron-accepting characteristics, which was important to improve the biological activity of the peptides. A larger compound series must be studied to access features more precisely. However, these results have paramount importance in guiding future effort in this extremely-need health area.

Targeting Groups Employed in Selective Dendrons and Dendrimers.

The design of compounds with directed action to a defined organ or tissue is a very promising approach, since it can decrease considerably the toxicity of the drug/bioactive compound. For this reason, this kind of strategy has been greatly important in the scientific community. Dendrimers, on the other hand, comprise extremely organized macromolecules with many peripheral functionalities, stepwise controlled synthesis, and defined size. These nanocomposites present several biological applications, demonstrating their efficiency to act in the pharmaceutical field. Considering that, the main purpose of this review was describing the potential of dendrons and dendrimers as drug targeting, applying different targeting groups. This application has been demonstrated through interesting examples from the literature considering the last ten years of publications.