Alex Gutterres Taranto

Bio: Alex Gutterres Taranto is an academic researcher from Universidade Federal de São João del-Rei. The author has contributed to research in topics: Virtual screening & Moniliophthora perniciosa. The author has an hindex of 16, co-authored 80 publications receiving 750 citations. Previous affiliations of Alex Gutterres Taranto include State University of Feira de Santana & Federal Fluminense University.

Structure-Based Virtual Screening: From Classical to Artificial Intelligence.

Abstract: The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

Immunoinformatics Design of Multi-Epitope Peptide-Based Vaccine Against Schistosoma mansoni Using Transmembrane Proteins as a Target.

Abstract: Schistosomiasis remains a serious health issue nowadays for an estimated one billion people in 79 countries around the world. Great efforts have been made to identify good vaccine candidates during the last decades, but only three molecules reached clinical trials so far. The reverse vaccinology approach has become an attractive option for vaccine design, especially regarding parasites like Schistosoma spp. that present limitations for culture maintenance. This strategy also has prompted the construction of multi-epitope based vaccines, with great immunological foreseen properties as well as being less prone to contamination, autoimmunity, and allergenic responses. Therefore, in this study we applied a robust immunoinformatics approach, targeting S. mansoni transmembrane proteins, in order to construct a chimeric antigen. Initially, the search for all hypothetical transmembrane proteins in GeneDB provided a total of 584 sequences. Using the PSORT II and CCTOP servers we reduced this to 37 plasma membrane proteins, from which extracellular domains were used for epitope prediction. Nineteen common MHC-I and MHC-II binding epitopes, from eight proteins, comprised the final multi-epitope construct, along with suitable adjuvants. The final chimeric multi-epitope vaccine was predicted as prone to induce B-cell and IFN-γ based immunity, as well as presented itself as stable and non-allergenic molecule. Finally, molecular docking and molecular dynamics foresee stable interactions between the putative antigen and the immune receptor TLR 4. Our results indicate that the multi-epitope vaccine might stimulate humoral and cellular immune responses and could be a potential vaccine candidate against schistosomiasis.

21-Benzylidene Digoxin: A Proapoptotic Cardenolide of Cancer Cells That Up-Regulates Na,K-ATPase and Epithelial Tight Junctions

Abstract: Cardiotonic steroids are used to treat heart failure and arrhythmia and have promising anticancer effects. The prototypic cardiotonic steroid ouabain may also be a hormone that modulates epithelial cell adhesion. Cardiotonic steroids consist of a steroid nucleus and a lactone ring, and their biological effects depend on the binding to their receptor, Na,K-ATPase, through which, they inhibit Na+ and K+ ion transport and activate of several intracellular signaling pathways. In this study, we added a styrene group to the lactone ring of the cardiotonic steroid digoxin, to obtain 21-benzylidene digoxin (21-BD), and investigated the effects of this synthetic cardiotonic steroid in different cell models. Molecular modeling indicates that 21-BD binds to its target Na,K-ATPase with low affinity, adopting a different pharmacophoric conformation when bound to its receptor than digoxin. Accordingly, 21-DB, at relatively high µM amounts inhibits the activity of Na,K-ATPase α1, but not α2 and α3 isoforms. In addition, 21-BD targets other proteins outside the Na,K-ATPase, inhibiting the multidrug exporter Pdr5p. When used on whole cells at low µM concentrations, 21-BD produces several effects, including: 1) up-regulation of Na,K-ATPase expression and activity in HeLa and RKO cancer cells, which is not found for digoxin, 2) cell specific changes in cell viability, reducing it in HeLa and RKO cancer cells, but increasing it in normal epithelial MDCK cells, which is different from the response to digoxin, and 3) changes in cell-cell interaction, altering the molecular composition of tight junctions and elevating transepithelial electrical resistance of MDCK monolayers, an effect previously found for ouabain. These results indicate that modification of the lactone ring of digoxin provides new properties to the compound, and shows that the structural change introduced could be used for the design of cardiotonic steroid with novel functions.

Detection of the antiviral activity of epicatechin isolated from Salacia crassifolia (Celastraceae) against Mayaro virus based on protein C homology modelling and virtual screening

Abstract: Mayaro fever, caused by Mayaro virus (MAYV) is a sub-lethal disease with symptoms that are easily confused with those of dengue fever, except for polyarthralgia, which may culminate in physical incapacitation. Recently, outbreaks of MAYV have been documented in metropolitan areas, and to date, there is no therapy or vaccine available. Moreover, there is no information regarding the three-dimensional structure of the viral proteins of MAYV, which is important in the search for antivirals. In this work, we constructed a three-dimensional model of protein C of MAYV by homology modelling, and this was employed in a manner similar to that of receptors in virtual screening studies to evaluate 590 molecules as prospective antiviral agents. In vitro bioassays were utilized to confirm the potential antiviral activity of the flavonoid epicatechin isolated from Salacia crassifolia (Celastraceae). The virtual screening showed that six flavonoids were promising ligands for protein C. The bioassays showed potent antiviral action of epicatechin, which protected the cells from almost all of the effects of viral infection. An effective concentration (EC50) of 0.247 μmol/mL was observed with a selectivity index (SI) of 7. The cytotoxicity assay showed that epicatechin has low toxicity, with a 50% cytotoxic concentration (CC50) greater than 1.723 µmol/mL. Epicatechin was found to be twice as potent as the reference antiviral ribavirin. Furthermore, a replication kinetics assay showed a strong inhibitory effect of epicatechin on MAYV growth, with a reduction of at least four logs in virus production. Our results indicate that epicatechin is a promising candidate for further testing as an antiviral agent against Mayaro virus and other alphaviruses.

Identification of Zika Virus NS2B-NS3 Protease Inhibitors by Structure-Based Virtual Screening and Drug Repurposing Approaches.

Abstract: The NS2B-NS3 protease has been identified as an attractive target for drug development against Zika virus (ZIKV) and combined drug repurposing and structure-based virtual screening has improved the development of antiviral drugs. In this study, we performed a structure-based virtual screening of 1861 Food and Administration (FDA) approved drugs available in DrugBank by the selection and docking validation of crystal structure of ZIKV NS2B-NS3 protease (PDB ID 5H4I ) using Glide and DOCK 6 software. The antihistaminic chlorcyclizine (Grid score -24.8 kcal/mol) exhibited the most promising interaction with NS2B-NS3 protease in comparison to crystallography ligand (Grid score -15.6 kcal/mol) by interaction to Tyr161 by hydrophobic interactions in the binding site of NS2B-NS3 which is recognized as an important amino acid in substrate molecular recognition. Cytotoxicity and global antiviral activity assay in Vero cells by MTT method showed that chlorcyclizine reduced the ZIKV induced cytopathic effect (EC50 of 69.0 ± 7.3 μM and SI = 1.9), and explicit molecular dynamics simulations implemented on a NAMD program indicated great stability of chlorcyclizine in protease binding site, suggesting the repurposing of chlorcyclizine as a promising finding in anti-ZIKV drug development.

Virtual screening for potential inhibitors of human hexokinase II for the development of anti-dengue therapeutics

Abstract: Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Hu-man hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Al-pha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we pro-posed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity.

Structure-Based Virtual Screening: From Classical to Artificial Intelligence.

Abstract: The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

Bioactive Natural Compounds and Antioxidant Activity of Essential Oils from Spice Plants: New Findings and Potential Applications.

Abstract: Spice plants have a great influence on world history. For centuries, different civilizations have used them to condiment the foods of kings and nobles and applied them as embalming preservatives, perfumes, cosmetics, and medicines in different regions of the world. In general, these plants have formed the basis of traditional medicine and some of their derived substances have been utilized to treat different human diseases. Essential oils (EOs) obtained from these plants have been also used as therapeutic agents and have shown supportive uses in remedial practices. The discovery and development of bioactive compounds from these natural products, based on their traditional uses, play an important role in developing the scientific evidence of their potential pharmaceutical, cosmetic, and food applications. In the present review, using recent studies, we exhibit a general overview of the main aspects related to the importance of spice plants widely used in traditional medicine: Cinnamomum zeylanicum (true cinnamon), Mentha piperita (peppermint), Ocimum basilicum (basil), Origanum vulgare (oregano), Piper nigrum (black pepper), Rosmarinus officinalis (rosemary), and Thymus vulgaris (thyme); and we discuss new findings of the bioactive compounds obtained from their EOs, their potential applications, as well as their molecular mechanisms of action, focusing on their antioxidant activity. We also exhibit the main in vitro methods applied to determine the antioxidant activities of these natural products.