Evolution and functional role prediction of the CYP6DE and CYP6DJ subfamilies in Dendroctonus (Curculionidae: Scolytinae) bark beetles.

Dendroctonus-bark beetles are natural components and key ecological agents of coniferous forests. They spend most of their lives under the bark, where they are exposed to highly toxic terpenes present in the oleoresin. Cytochrome P450 (CYP) is a multigene family involved in the detoxification of these compounds. It has been demonstrated that CYP6DE and CYP6DJ subfamilies hydroxylate monoterpenes, whose derivatives can act as pheromone synergist compounds or be pheromones themselves in these insects. Given the diversity and functional role of CYPs, we investigated whether these cytochromes have retained their function throughout the evolution of these insects. To test this hypothesis, we performed a Bayesian phylogenetic analysis to determine phylogenetic subgroups of cytochromes in these subfamilies. Subgroups were mapped and reconciled with the Dendroctonus phylogeny. Molecular docking analyses were performed with the cytochromes of each subgroup and enantiomers of α-pinene and ß-pinene, (+)-3-carene, ß-myrcene and R-(+)-limonene. In addition, functional divergence analysis was performed to identify critical amino acid sites that influence changes in catalytic site conformation and/or protein folding. Three and two phylogenetic subgroups were recovered for the CYP6DE and CYP6DJ subfamilies, respectively. Mapping and reconciliation analysis showed different gain and loss patterns for cytochromes of each subgroup. Functional predictions indicated that the cytochromes analyzed are able to hydroxylate all monoterpenes; however, they showed preferential affinities to different monoterpenes. Functional divergence analyses indicated that the CYP6DE subfamily has experimented type I and II divergence, whereas the CYP6DJ subfamily has evolved under strong functional constraints. Results suggest cytochromes of the CYP6DE subfamily evolve to reinforce their detoxifying capacity hydroxylating mainly α- and ß-pinene to (+) and (-)-trans-verbenol, being the negative enantiomer used as a pheromone by several Dendroctonus species; whereas cytochromes of the CYP6DJ subfamily appear to retain their original function related to the detoxification of these compounds.

A rational in silico approach to identify inhibitors of Batroxrhagin from Bothrops atrox.

Bothrops atrox venom comprises several types of bioactive molecules, enzymatic and non-enzymatic, among those, Batroxrhagin is the most predominant SVMP P-III enzyme, which are responsible for induction of local and systemic hemorrhage and muscle fibers damage, impairing regeneration. Due to great difficulties in establishing an antibothropic drug, new strategies must be addressed to achieve a more effective and efficient treatment. There are no studies of specific catalytic inhibitors of Batroxrhagin. However, there are in vitro studies that have described similar metalloprotease inhibitors. The inhibitor batimastat was used as a leading compound for the search and selection of similar candidates. This molecule is widely cited as a metalloprotease inhibitor and as an antimetastatic. In addition to batimastat-like molecules, four other reported metalloprotease inhibitors were included to compose the study's positive control group. Hence, 580 molecules were tested. The three-dimensional structure of B. atrox Batroxrhagin was predicted based on homologous structures using Modeller 9.20. Molecular docking calculation was performed using Autodock 4.2 and molecular surfaces and interactions were analyzed using Biovia/Discovery Studio 2017. Among 576 molecules, 42 similar to batismast resulted in a better energy of interaction than all positive controls, including batimastat itself. The batimastat-like molecules with lowest energy and positive controls were subjected to molecular dynamics for 30 ns in Gromacs 2019.4. This batimastat-like molecule produced better stability among all the Batroxrhagin-ligand complexes analyzed. Overall, the proposed compounds present justifiable evidence for future in vitro tests aiming to inhibit Batroxrhagin. Communicated by Ramaswamy H. Sarma.

In silico, in vitro and in vivo studies indicate resveratrol analogue as a potential alternative for neuroinflammatory disorders.

Inflammaging is known as an imbalance between pro-inflammatory and anti-inflammatory immune mechanisms, being related to the onset of neurological disorders, such as major depression and Alzheimer's disease. Considering the known disadvantages regarding the FDA approved drug to manage such illnesses, resveratrol emerges as a natural drug candidate, despite its low bioavailability. In this study, resveratrol analogues were evaluated for their capacity of inhibiting acetylcholinesterase in silico, in vitro, and in vivo. Molecular docking simulations pointed out RSVA1 and RSVA6 as potent inhibitors, even more than resveratrol. Ellman's assay demonstrated RSVA6 as capable of inhibiting 92.4% of the enzyme activity. Further, male Swiss mice were pretreated with RSVA6 (100 mg kg-1) 60 min before receiving scopolamine (1 mg kg-1). The Novel Recognition Object (NOR), Object Location (OLT), and Buried Pellet tests (BPL) demonstrated an RSVA6 neuroprotective effect. In the second round of tests, mice received a single intraperitoneal injection of lipopolysaccharide (0.5 mg kg-1) 24 h before treatment with RSVA6 (1, 10, and 100 mg kg-1). The Open Field (OFT), Tail Suspension (TST), and Splash tests (ST) were evaluated. LPS had no significant effect on the crossing and rearing number, indicating an association between the immobility time and anhedonia observed in the TST and ST, respectively, with depressive-like behavior. RSVA6 significantly reduced the depressive-like behavior triggered by LPS in the TST and ST. Altogether, our data suggest RSVA6 as a potential drug candidate for the treatment of neuroinflammatory conditions.

Molecular dynamics simulation revealed binding of nucleotide inhibitors to ZIKV polymerase over 444 nanoseconds.

In the year 2015, new Zika virus (ZIKV) broke out in Brazil and spread away in more than 80 countries. Scientists directed their efforts toward viral polymerase in attempt to find inhibitors that might interfere with its function. In this study, molecular dynamics simulation (MDS) was performed over 444 ns for a ZIKV polymerase model. Molecular docking (MD) was then performed every 10 ns during the MDS course to ensure the binding of small molecules to the polymerase over the entire time of the simulation. MD revealed the binding ability of four suggested guanosine inhibitors (GIs); (Guanosine substituted with OH and SH (phenyl) oxidanyl in the 2' carbon of the ribose ring). The GIs were compared to guanosine triphosphate (GTP) and five anti-hepatitis C virus drugs (either approved or under clinical trials). The mode of binding and the binding performance of GIs to ZIKV polymerase were found to be the same as GTP. Hence, these compounds were capable of competing GTP for the active site. Moreover, GIs bound to ZIKV active site more tightly compared to ribavirin, the wide-range antiviral drug.

Multi-objective Optimization of Benzamide Derivatives as Rho Kinase Inhibitors.

Despite recent advances in Computer Aided Drug Discovery and High Throughput Screening, the attrition rates of drug candidates continue to be high, underscoring the inherent complexity of the drug discovery paradigm. Indeed, a compromise between several objectives is often required to obtain successful clinical drugs. The present manuscript details a multi-objective workflow that integrates the 4D-QSAR and molecular docking methods in the simultaneous modeling of the Rho Kinase inhibitory activity and acute toxicity of Benzamide derivatives. To this end, the pIC50 /pLD50 ratio is considered as the response variable, permitting the concurrent modeling of both properties and representing a shift from classical step-by-step evaluations. The 4D-QSAR strategy is used to generate the Grid Cell Occupancy Descriptors (GCODs), and Stochastic Gradient Boosting (SGB) and Partial Least Squares (PLS) methods as the model fitting techniques. While the statistical parameters for the PLS model do not meet established criteria for acceptability, the SGB model yields satisfactory performance, with correlation coefficients r2 =0.95 and r2 pred=0.65 for the training and test set, respectively. Posteriorly, the structural interpretation of the most relevant GCODs according to the SGB model is performed, allowing for the proposal of 139 novel benzamide derivatives, which are then screened using the same model. Of these 9 compounds were predicted to possess pIC50 /pLD50 ratio values higher than those for the employed dataset. Finally, in order to corroborate the results obtained with the SGB model, a docking simulation was formed to evaluate the binding affinity of the proposed molecules to the ROCK2 active site and 3 chemical structures (i. e. p6, p14 and p131) showed higher binding affinity than the most active compound in the training set, while the rest generally demonstrated comparable behavior. It may therefore be concluded that the consensus models that intertwine the 4D-QSAR and molecular docking methods contribute to more reliable virtual screening and compound optimization experiments. Additionally, the use of multi-objective modeling schemes permits the simultaneous evaluation of different chemical and biological profiles, which should contribute to the control a priori of causative factors for the high attrition rates in later drug discovery phases.

Novel FXa Inhibitor Identification through Integration of Ligand- and Structure-Based Approaches.

Factor Xa (FXa), a vitamin K-dependent serine protease plays a pivotal role in the coagulation cascade, one of the most interesting targets for the development of new anticoagulants. In the present work, we performed a virtual screening campaign based on ligand-based shape and electrostatic similarity search and protein-ligand docking to discover novel FXa-targeted scaffolds for further development of inhibitors. From an initial set of 260,000 compounds from the NCI Open database, 30 potential FXa inhibitors were identified and selected for in vitro biological evaluation. Compound 5 (NSC635393, 4-(3-methyl-4H-1,4-benzothiazin-2-yl)-2,4-dioxo-N-phenylbutanamide) displayed an IC50 value of 2.02 nM against human FXa. The identified compound may serve as starting point for the development of novel FXa inhibitors.

Receptor-ligand molecular docking.

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein-ligand applications. We summarise the main topics and recent computational and methodological advances in protein-ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.