Identification of potential modulator of Anopheles gambiae odorant binding protein 1 by hierarchical virtual screening and molecular dynamics.

Malaria is a protozoan infection transmitted by the bite of the infected female mosquito belonging to the genus Anopheles spp., which causes more than 445 million annual deaths worldwide. Available drugs have serious adverse effects (e.g. blurred vision, hypotension and headache) and species-dependent efficacy. An alternative to overcome these problems involve the use of molecules with affinity to the Anopheles gambiae mosquito odor receptors, minimizing the reinfection process as well as reducing the problems related to pharmacological therapy. The vector control can interrupt the epidemiological cycle and, therefore, control the malaria incidence. In the olfactory pathway, odorant binding protein 1 acts on the first level of odor recognition on malarial vector and thus can be used to modulate mosquito behavior and development of new attracts or repellents. Thus, this study applied ligand-based (2D-chemical similarity) and structure-based (docking and molecular dynamics) computational approaches to prioritize potential olfactory modulators on natural products catalogs at ZINC15 database (n = 98,379). Hierarchical virtual screening prioritized a potential olfactory modulator (Z8217) against Anopheles gambiae odorant binding protein 1 (AgOBP1). Next, it was submitted to molecular dynamics routine to identify structural requirements and the interactions profile required for binding-site affinity. This promising natural compound can interact like experimental ligand and will be used in repellency assay to confirm its sensorial behavior.Communicated by Ramaswamy H. Sarma.

Identification of Potential Inhibitors from Pyriproxyfen with Insecticidal Activity by Virtual Screening.

Aedes aegypti is the main vector of dengue fever transmission, yellow fever, Zika, and chikungunya in tropical and subtropical regions and it is considered to cause health risks to millions of people in the world. In this study, we search to obtain new molecules with insecticidal potential against Ae. aegypti via virtual screening. Pyriproxyfen was chosen as a template compound to search molecules in the database Zinc_Natural_Stock (ZNSt) with structural similarity using ROCS (rapid overlay of chemical structures) and EON (electrostatic similarity) software, and in the final search, the top 100 were selected. Subsequently, in silico pharmacokinetic and toxicological properties were determined resulting in a total of 14 molecules, and these were submitted to the PASS online server for the prediction of biological insecticide and acetylcholinesterase activities, and only two selected molecules followed for the molecular docking study to evaluate the binding free energy and interaction mode. After these procedures were performed, toxicity risk assessment such as LD50 values in mg/kg and toxicity class using the PROTOX online server, were undertaken. Molecule ZINC00001624 presented potential for inhibition for the acetylcholinesterase enzyme (insect and human) with a binding affinity value of -10.5 and -10.3 kcal/mol, respectively. The interaction with the juvenile hormone was -11.4 kcal/mol for the molecule ZINC00001021. Molecules ZINC00001021 and ZINC00001624 had excellent predictions in all the steps of the study and may be indicated as the most promising molecules resulting from the virtual screening of new insecticidal agents.

An In Silico Study of the Antioxidant Ability for Two Caffeine Analogs Using Molecular Docking and Quantum Chemical Methods.

The antioxidant activity of molecules constitutes an important factor for the regulation of redox homeostasis and reduction of the oxidative stress. Cells affected by oxidative stress can undergo genetic alteration, causing structural changes and promoting the onset of chronic diseases, such as cancer. We have performed an in silico study to evaluate the antioxidant potential of two molecules of the zinc database: ZINC08706191 (Z91) and ZINC08992920 (Z20). Molecular docking, quantum chemical calculations (HF/6-31G**) and Pearson's correlation have been performed. Molecular docking results of Z91 and Z20 showed both the lower binding affinity (BA) and inhibition constant (Ki) values for the receptor-ligand interactions in the three tested enzymes (cytochrome P450-CP450, myeloperoxidase-MP and NADPH oxidase-NO) than the control molecules (5-fluorouracil-FLU, melatonin-MEL and dextromethorphan-DEX, for each receptor respectively). Molecular descriptors were correlated with Ki and strong correlations were observed for the CP450, MP and NO receptors. These and other results attest the significant antioxidant ability of Z91 and Z20, that may be indicated for further analyses in relation to the control of oxidative stress and as possible antioxidant agents to be used in the pharmaceutical industry.

Rational Design of Antimalarial Drugs Using Molecular Modeling and Statistical Analysis.

Artemisinin is an antimalarial compound isolated from Artemisia annua L. that is effective against Plasmodium falciparum. This paper proposes the development of new antimalarial derivatives of artemisinin from a SAR study and statistical analysis by multiple linear regression (MLR). The HF/6-31G** method was used to determine the molecular properties of artemisinin and 10 derivatives with antimalarial action. MEP maps and molecular docking were used to study the interface between ligand and receptor (heme). The Pearson correlation was used to choose the most important properties interrelated to the antimalarial activity: Hydration Energy (HE), Energy of the Complex (Ecplex), bond length (FeO1), and maximum index of R/Electronegativity of Sanderson (RTe+). After the Pearson correlation, 72 MLR models were built between antimalarial activity and molecular properties; the statistical quality of the models was evaluated by means of correlation coefficient (r), squared correlation coefficient (r(2)), explained variance (adjusted R(2)), standard error of estimate (SEE), and variance ratio (F), and only four models showed predictive ability. The selected models were used to predict the antimalarial activity of ten new artemisinin derivatives (test set) with unknown activity, and only eight of these compounds were predicted to be more potent than artemisinin, and were therefore subjected to theoretical studies of pharmacokinetic and toxicological properties. The test set showed satisfactory results for six new artemisinin compounds which is a promising factor for future synthesis and biological assays.