Molecular modeling approaches of selective adenosine receptor type 2A agonists as potential anti-inflammatory drugs

Sequential virtual screening collaborated with machine-learning strategies for the discovery of precise medicine against non-small cell lung cancer

Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to diminish this pathway activity. Hence, we have aimed to discover potent MEK inhibitors by integrating virtual screening and machine learning-based strategies. Preliminary screening was conducted on 11,808 compounds using the cavity-based pharmacophore model AADDRRR. Further, seven ML models were accessed to predict the MEK active compounds using six molecular representations. The LGB model with morgan2 fingerprints surpasses other models ensuing 0.92 accuracy and 0.83 MCC value versus test set and 0.85 accuracy and 0.70 MCC value with external set. Further, the binding ability of screened hits were examined using glide XP docking and prime-MM/GBSA calculations. Note that we have utilized three ML-based scoring functions to predict the various biological properties of the compounds. The two hit compounds such as DB06920 and DB08010 resulted excellent binding mechanism with acceptable toxicity properties against MEK. Further, 200 ns of MD simulation combined with MM-GBSA/PBSA calculations confirms that DB06920 may have stable binding conformations with MEK thus step forwarded to the experimental studies in the near future.Communicated by Ramaswamy H. Sarma.

Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation

The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK. ADHRR and DHHRR were modeled as a pharmacophore hypothesis for RAF and MEK respectively. Importantly, these hypotheses resulted an AUC value of > 0.90 with the external data set. As a result of phase screening, glide docking, and prime-MM/GBSA scoring, it is determined that DB08424 and DB08907 have the best chances of acting as multi-kinase inhibitors. The pi-cation interaction with key amino acid residues of both target receptors may responsible for the stronger binding with these kinases. Cumulative 600 ns MD simulation studies validate the binding ability of these compounds. Significantly, the hit compounds resulted higher number of stable conformational state with less atomic movements than the reference compound against both targets. The anti-cancer efficacy of the lead compounds was validated through machine learning-based approaches. These findings suggest that DB08424 and DB08907 might be novel molecules to be explored further experimentally to block the MAPK signaling in lung cancer patients.

Multivariate QSAR, similarity search and ADMET studies based in a set of methylamine derivatives described as dopamine transporter inhibitors

The dopamine transporter (DAT), responsible for the regulation of dopaminergic neurotransmission, is implicated in the etiology of several neuropsychiatric disorders which, in turn, have contributed to high rates of disability and numerous deaths in recent years, significantly impacting the global health system. Although the research for new drugs for the treatment of neuropsychiatric disorders has evolved in recent years, the availability of DAT-selective drugs that do not generate the same psychostimulant effects observed in drugs of abuse remains scarce. Therefore, we performed a QSAR study based on a dataset of 36 methylamine derivatives described as DAT inhibitors. The model was obtained based only in descriptors derived from 2D structures, and it was validated and generated satisfactory results considering the metrics used for internal and external validation. Subsequently, a virtual screening step also based on 2D similarity was performed, where it was possible to identify a total of 1157 compounds. After a series of reductions of the set using toxicity filters, applicability domain evaluation, and pharmacokinetic properties in silico assessment, seven hit compounds were selected as the most promising to be used, in future studies, as new scaffolds for the development of new DAT inhibitors.

Antiplasmodial activity of coumarins isolated from Polygala boliviensis: in vitro and in silico studies

Polygala boliviensis is found in the Brazilian semiarid region. This specie is little chemically and biologically studied. Polygala spp. have different metabolites, especially coumarins. Studies indicate that coumarins have antimalarial potential, denoting the importance of researching new active compounds from plants, since the resistance of Plasmodium strains to conventional therapy has increased. The present study aimed to evaluate the antiplasmodial activity of auraptene and poligalen against a chloroquine-resistant strain of Plasmodium falciparum. Coumarins were isolated from P. boliviensis by open column chromatography and identified by Nuclear Magnetic Resonance Spectroscopy. A cytotoxicity assay was carried out using MTT test, and the in vitro antiplasmodial activity was evaluated using the W2 strain. The antiplasmodial activity results found were IC50=0.171 ± 0.016 for auraptene and 0.164 ± 0.012 for poligalen; the selectivity indexes were 78.71 and 609.76, respectively. Inverse virtual screening in the BRAMMT database by OCTOPUS 1.2 was applied to coumarins to find potential P. falciparum targets and showed higher affinity energy of auraptene for purine nucleoside phosphorylase (PfPNP) and of poligalen for dihydroorotate dehydrogenase (PfDHODH). Molecular Dynamics studies (MD and MM-GBSA) approach were applied to calculate binding energies against selected P. falciparum targets and showed that all coumarins were stable at the binding site during simulations. Furthermore, energies were favorable for complexation. This is the first report of auraptene in P. boliviensis species and of in vitro antiplasmodial activity of auraptene and poligalen. In silico studies indicated that the mechanism of action of coumarins is the inhibition of PfPNP and PfDHODH.Communicated by Ramaswamy H. Sarma.

In Silico Evaluation of the Antimicrobial Activity of Thymol-Major Compounds in the Essential Oil of Lippia thymoides Mart. & Schauer (Verbenaceae)

In this paper, we evaluated the drug-receptor interactions responsible for the antimicrobial activity of thymol, the major compound present in the essential oil (EO) of Lippia thymoides (L. thymoides) Mart. & Schauer (Verbenaceae). It was previously reported that this EO exhibits antimicrobial activity against Candida albicans (C. albicans), Staphylococcus aureus (S. aureus), and Escherichia coli (E. coli). Therefore, we used molecular docking, molecular dynamics simulations, and free energy calculations to investigate the interaction of thymol with pharmacological receptors of interest to combat these pathogens. We found that thymol interacted favorably with the active sites of the microorganisms’ molecular targets. MolDock Score results for systems formed with CYP51 (C. albicans), Dihydrofolate reductase (S. aureus), and Dihydropteroate synthase (E. coli) were −77.85, −67.53, and −60.88, respectively. Throughout the duration of the MD simulations, thymol continued interacting with the binding pocket of the molecular target of each microorganism. The van der Waals (ΔE_vdW = −24.88, −26.44, −21.71 kcal/mol, respectively) and electrostatic interaction energies (ΔE_ele = −3.94, −11.07, −12.43 kcal/mol, respectively) and the nonpolar solvation energies (ΔG_NP = −3.37, −3.25, −2.93 kcal/mol, respectively) were mainly responsible for the formation of complexes with CYP51 (C. albicans), Dihydrofolate reductase (S. aureus), and Dihydropteroate synthase (E. coli).

Molecular Modeling Approaches Can Reveal the Molecular Interactions Established between a Biofilm and the Bioactive Compounds of the Essential Oil of Piper divaricatum

Molecular modeling approaches are used in a versatile way to investigate the properties of diverse organic and inorganic structures such as proteins, biomolecules, nanomaterials, functionalized nanoparticles, and membranes. However, more detailed studies are needed to understand the molecular nature of interactions established in gelatin biofilms impregnated with bioactive compounds. Because of this, we used computational methods to evaluate how the major compounds of Piper divaricatum essential oil can interact with the gelatin biofilm structure. For this, we used as inspiration the paper published, where various properties of the essential oil impregnated gelatin biofilm P. divaricatum are reported. After our computer simulations, we related our molecular observations to biofilm’s structural and mechanical properties. Our results suggest that the major compounds of the essential oil were able to interrupt intermolecular interactions between the chains of the biofilm matrix. However, the compounds also established interactions with the amino acid residues of these chains. Our molecular analyses also explain changes in the structural and mechanical properties of the essential oil-impregnated biofilm. These results can support the planning of functional packaging impregnated with bioactive compounds that can protect food against microorganisms harmful to human health.

Molecular dynamics and structure-based virtual screening and identification of natural compounds as Wnt signaling modulators: possible therapeutics for Alzheimer's disease

Wnt signaling pathway is an evolutionarily conserved pathway responsible for neurogenesis, axon outgrowth, neuronal polarity, synapse formation, and maintenance. Downregulation of Wnt signaling has been found in patients with Alzheimer’s disease (AD). Several experimental approaches to activate Wnt signaling pathway have proven to be beneficial in alleviating AD, which is one of the new therapeutic approaches for AD. The current study focuses on the computational structure-based virtual screening followed by the identification of potential phytomolecules targeting different markers of Wnt signaling like WIF1, DKK1, LRP6, GSK-3β, and acetylcholine esterase. Initially, screening of 1924 compounds from the plant-based library of Zinc database was done for the selected five proteins using docking approach followed by MM-GBSA calculations. The top five hit molecules were identified for each protein. Based on docking score, and binding interactions, the top two hit molecules for each protein were selected as promising molecules for the molecular dynamic (MD) simulation study with the five proteins. Therefore, from this in silico based study, we report that Mangiferin could be a potential molecule targeting Wnt signaling pathway modulating the LRP6 activity, Baicalin for AChE activity, Chebulic acid for DKK1, ZINC103539689 for WIF1, and Morin for GSk-3β protein. However, further validation of the activity is warranted based on in vivo and in vitro experiments for better understanding and strong claim. This study provides an in silico approach for the identification of modulators of the Wnt signaling pathway as a new therapeutic approach for AD.

Energy and reactivity profile and proton affinity analysis of rimegepant with special reference to its potential activity against SARS-CoV-2 virus proteins using molecular dynamics

Rimegepant is a new medicine developed for the management of chronic headache due to migraine. This manuscript is an attempt to study the various structural, physical, and chemical properties of the molecules. The molecule was optimized using B3LYP functional with 6-311G + (2d,p) basis set. Excited state properties of the compound were studied using CAM-B3LYP functional with same basis sets using IEFPCM model in methanol for the implicit solvent atmosphere. The various electronic descriptors helped to identify the reactivity behavior and stability. The compound is found to possess good nonlinear optical properties in the gas phase. The various intramolecular electronic delocalizations and non-covalent interactions were analyzed and explained. As the compound contain several heterocyclic nitrogen atoms, they have potential proton abstraction features, which was analyzed energetically. The most important result from this study is from the molecular docking analysis which indicates that rimegepant binds irreversibly with three established SARS-CoV-2 proteins with ID 6LU7, 6M03, and 6W63 with docking scores − 9.2988, − 8.3629, and − 9.5421 kcal/mol respectively. Further assessment of docked complexes with molecular dynamics simulations revealed that hydrophobic interactions, water bridges, and π–π interactions play a significant role in stabilizing the ligand within the binding region of respective proteins. MMGBSA-free energies further demonstrated that rimegepant is more stable when complexed with 6LU7 among the selected PDB models. As the pharmacology and pharmacokinetics of this molecule are already established, rimegepant can be considered as an ideal candidate with potential for use in the treatment of COVID patients after clinical studies.

Methoxylated flavonols from Vellozia dasypus Seub ethyl acetate active myeloperoxidase extract: in vitro and in silico assays

This study aimed to evaluate the effect of a methoxylated fraction from Vellozia dasypus Seub on myeloperoxidase (MPO)-chlorinating activity and subsequent in silico assays for binding profile prediction. Therefore, the ethyl acetate extract of aerial parts from Vellozia dasypus Seub was fractionated on open-column chromatography containing SiO₂ and eluted with solvent in crescent polarity to yield a fraction with a mixture of flavonols quercetin 3-O-methyl ether (1) and 6-C-methyl quercetin 3-O-methyl ether (2). Their chemical structures were proposed by HPLC coupled to photodiode array (HPLC-DAD) and mass spectrometer using electrospray ionization multistage analysis (HPLC-MS/MS). The fraction enriched with compounds 1 and 2 inhibited more efficiently the in vitro MPO-chlorinating activity (IC₅₀ = 40 µg/mL) than the ethyl acetate extract (IC₅₀ = 64.0 µg/mL). Molecular docking studies revealed that these compounds interact with MPO active pocket similarly to trifluoromethyl-substituted aromatic hydroxamate, a well-known MPO inhibitor, co-crystallized at the MPO binding site (PDB ID: 4C1M). Molecular dynamics trajectories confirmed that these two molecules interact with the MPO binding site with a similar energetic pattern when compared to the crystallographic ligand. Taken together, these data expand the sources of phenolic natural compounds that may be further investigated against inflammation-related diseases.Communicated by Ramaswamy H. Sarma.

First report on the Annona exsucca DC. Essential oil and in silico identification of potential biological targets of its major compounds

In the present study, the essential oil (EO) of Annona exsucca DC. or Rollinia exsucca was extracted by hydrodistillation, and the identification and quantification of volatile compounds were performed by GC-MS and GC-FID. A. exsucca leaves were collected from the Magalhães Barata, northeast of the State of Pará (Brazil) in March and September of 2019. Moreover, we used computational approaches to evaluate possible biological targets for the major compounds of the EO. In the sample obtained in March, 50 compounds were identified, with hydrocarbon sesquiterpenes being the predominant ones with the content of 80.52%. In the sample collected in September, 58 compounds were identified, and the chemical class of hydrocarbon monoterpenes and sesquiterpenes were the dominant ones with contents of 43.36 and 31.29%, respectively. Computational methods demonstrated that some major compounds have potential biological activity against some strains of pathogenic bacteria, as well as against molecular targets involved in cancer development.

Extraction Yield, Chemical Composition, Preliminary Toxicity of Bignonia nocturna (Bignoniaceae) Essential Oil and in Silico Evaluation of the Interaction

Bignonia nocturna (Bignoniaceae) is a plant used for medicinal purposes by the Amazonian indigenous peoples. To date, there have been no reported studies on its toxicity. The present study aimed to evaluate the chemical composition of essential oils obtained from Bignonia nocturna by different extraction techniques. In addition, an in silico study of the molecular interactions was performed using molecular docking and molecular dynamics. The extractions were carried out by hydrodistillation, simultaneous distillation-extraction, and steam distillation, using samples collected from the Amazon in summer and winter. The chemical composition was analyzed by GC/FID and GC/MS, and the cytotoxic activity in Artemia salina Leach was evaluated. The maximum yield (1.38 % w/w) was obtained by hydrodistillation. The results indicated that benzaldehyde predominated in all the fractions of both the volatile concentrate and the essential oils. In addition, the oil proved to be highly toxic to Artemia salina. The computer simulation results indicated that benzaldehyde strongly interacts with acetylcholinesterase, which is the likely interaction mechanism responsible for the cytotoxicity.

Physicochemical characterization of paclitaxel prodrugs with cytochrome 3A4 to correlate solubility and bioavailability implementing molecular docking and simulation studies

Prodrugs are biologically inactive drug molecules that may be developed through rational drug design with an objective to improve a drug's pharmaceutical and pharmacokinetic properties. Paclitaxel, a highly potent anticancer drug, is directed against many cancers like breast cancer, ovarian cancer, lung cancer, head and neck tumors, non-small cell lung cancer, and Kaposi's sarcoma, etc. Along with its excellent antitumor activity the drug had a major limitation of low water solubility. To overcome this limitation of this nanomolar active drug many prodrugs were formed in the past. Though increase in the solubility of the drug was obtained but that may or may not account for its increase in bioavailability. CYP3A4 liver enzymes are responsible for the metabolism of fifty percent of the drugs and are major metabolizing enzyme for paclitaxel. Phosphate prodrugs are well known to account the insolubility of many drugs and thus increasing their bioavailability also. In this study, we calculated the ADMET properties of a dataset of twenty phosphate prodrugs of paclitaxel. On the basis of reflection of three favourable properties, ten prodrugs were chosen for further docking studies against CYP3A4. Finally, three prodrugs showing unfavourable binding affinities were selected for Molecular Dynamics Simulations and from this in-silico study we identified that all the three selected prodrugs were unstable as compared to the paclitaxel. The instability of these prodrugs showed their lesser interaction with the CYP3A4 and hence contributing more towards its bioavailability. Thus the three suggested prodrugs those were studied in-silico for oral bioavailability can be further validated for gastrointestinal cancer.Communicated by Ramaswamy H. Sarma.

Identification of novel potential cyclooxygenase-2 inhibitors using ligand- and structure-based virtual screening approaches

Cyclooxygenase 2 (COX-2) is a well-established target for the design of anti-inflammatory intermediates. Celecoxib was selected as a template molecule to perform ligand-based virtual screening, i.e. to search for structures with similarity in shape and electrostatic potential, with a gradual increase in accuracy through the combined fitting of several steps using eight commercial databases. The molecules ZINC408709 and ZINC2090319 reproduced values within the limits established in an initial study of absorption and distribution in the body. No alert was fired for possible toxic groups when these molecules were subjected to toxicity prediction. Molecular docking results with these compounds showed a higher binding affinity in comparison to rofecoxib for the COX-2 target. Additionally, ZINC408709 and ZINC2090319 were predicted to be potentially biologically active. In in silico prediction of endocrine disruption potential, it was established that the molecule ZINC2090319 binds strongly to the target related to cardiovascular risk in a desirable way as a non-steroidal antagonist and ZINC408709 binds strongly to the target that is associated with the treatment of inflammatory pathologies and similar to celecoxib. Metabolites generated from these compounds are less likely to have side effects. Simulations were used to evaluate the interaction of compounds with COX-1 and COX-2 during 200 ns. Despite the differences, ZINC408709 molecule showed better stability for COX-2 during molecular dynamics simulation. In the calculations of free energy MM/PBSA, the molecule ZINC408709 ΔGbind value has a higher affinity to celecoxib and rofecoxib COX-2. This demonstrates that the selected substances can be considered as promising COX-2 inhibitors. Communicated by Ramaswamy H. Sarma.

In silico design and analysis of NS4B inhibitors against hepatitis C virus

The hepatitis C virus is a communicable disease that gradually harms the liver leading to cirrhosis and hepatocellular carcinoma. Important therapeutic interventions have been reached since the discovery of the disease. However, its resurgence urges the need for new approaches against this malady. The NS4B receptor is one of the important proteins for Hepatitis C Virus RNA replication that acts by mediating different viral properties. In this work, we opt to explore the relationships between the molecular structures of biologically tested NS4B inhibitors and their corresponding inhibitory activities to assist the design of novel and potent NS4B inhibitors. For that, a set of 115 indol-2-ylpyridine-3-sulfonamides (IPSA) compounds with inhibitory activity against NS4B is used. A hybrid genetic algorithm combined with multiple linear regressions (GA-MLR) was implemented to construct a predictive model. This model was further used and applied to a set of compounds that were generated based on a pharmacophore modeling study combined with virtual screening to identify structurally similar lead compounds. Multiple filtrations were implemented for selecting potent hits. The selected hits exhibited advantageous molecular features, allowing for favorable inhibitory activity against HCV. The results showed that 7 out of 1285 screened compounds, were selected as potent candidate hits where Zinc14822482 exhibits the best predicted potency and pharmacophore features. The predictive pharmacokinetic analysis further justified the compounds as potential hit molecules, prompting their recommendation for a confirmatory biological evaluation. We believe that our strategy could help in the design and screening of potential inhibitors in drug discovery.Communicated by Ramaswamy H. Sarma.

In silico improvement of the cyanobacterial lectin microvirin and mannose interaction

Lectins that bind to HIV envelope glycoprotein can inhibit virus-cell fusion and be used for rational drug design. This paper presents the results of an in silico approach to improve affinity interaction between the cyanobacterial lectin microvirin and its ligand Manα(1-2)Man. Comparative modeling and molecular dynamics tools were used. Additionally, the alanine scanning webserver was used to study the importance of protein residues in the binding site and to guide mutant production. The model obtained presented two homologous domains designated as domains A and B, each consisting of a single strand with triple and antiparallel β-sheets of (β1-β3 and β6-β8). Disulfide bonds between the cysteines (Cys60-Cys80, Cys63-Cys78 and Cys8-Cys24) were also found. The highly conserved binding site, including residues Asn44, Ile45, Asp46, Gln54, Asn55, Glu58, Thr59, Gln81, Thr82 and Met83. The RMSD values of the di-mannose and the interaction site were very stable during the molecular dynamics. Calculations of the occupation time of the hydrogen bonds were made for the residues that showed interaction in the complex lectin and ligand. The residue that contributed most to the interaction with Manα(1-2)Man was Asn55. After validation, the model generated remained stable during the entire simulation. Despite its structural similarity with the template we used, our mutant (Thr82Arg) showed a higher affinity interaction with Manα(1-2)Man. Communicated by Ramaswamy H. Sarma.

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R² = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC₅₀ (−log IC₅₀) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.

Chemometric methods in antimalarial drug design from 1,2,4,5-tetraoxanes analogues

A set of 23 steroidal 1,2,4,5-tetraoxane analogues were studied using quantum-chemical method (B3LYP/6-31 G*) and multivariate analyses (PCA, HCA, KNN and SIMCA) in order to calculate the properties and correlate them with antimalarial activity (log RA) against Plasmodium falciparum clone D-6 from Sierra Leone. PCA results indicated 99.94% of the total variance and it was possible to divide the compounds into two classes: less and more active. Descriptors responsible for separating were: highest occupied molecular orbital energy (HOMO), bond length (O1-O2), Mulliken electronegativity (χ) and Bond information content (BIC0). We use HCA, KNN and SIMCA to explain relationships between molecular properties and biological activity of a training set and to predict antimalarial activity (log RA) of 13 compounds (#24-36) with unknown biological activity. We apply molecular docking simulations to identify intermolecular interactions with a selected biological target. The results obtained in multivariate analysis aided in the understanding of the activity of the new compound's design (#24-36). Thus, through chemometric analyses and docking molecular study, we propose theoretical synthetic routes for the most promising compounds 28, 30, 32 and 36 that can proceed to synthesis steps and in vitro and in vivo assays.

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = -11.0 kcal/mol), LMQC36 (∆G = -10.6 kcal/mol), and LMQC50 (∆G = -10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = -10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = -45.31 kcal/mol; LMQC72: ΔGbind = -38.58 kcal/mol; LMQC36: ΔGbind = -36.10 kcal/mol; and LMQC50: ΔGbind = -39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

Identification of novel Aedes aegypti odorant-binding protein 1 modulators by ligand and structure-based approaches and bioassays

Arboviruses are a group of viruses (e.g. Dengue, Chikungunya and Yellow fever virus) that are transmitted by arthropod vectors, which Aedes aegipty is the vector of main viruses in Americas. This vector is responsible to 2.4 millions of arboviruses cases in Brazil with less than a thousand deaths annually. Despite of epidemiological data, arboviruses treatment is symptomatic and the vaccine control is not effective, which makes the vector control against A. aegipty a promising strategy to diseases control. One way to achieve this goal is to development of A. aegipty sensitive olfactory modulators. Odorant binding protein 1 from A. aegypti (AaegOBP1) is essential in sensory communication, and is the first filter in odorant selection, which makes this target promising to development of new repellents. For this reason, hierarchical virtual screening (ligand-based pharmacophore model and molecular docking) together volatility filter was applied at Sigma-Aldrich database (n = 126.851) to prioritize potential molecules to repellency assays. Three compounds showed adequate stereo-electronic requirements (QFIT> 81.53), score to AaegOBP1 binding site (Score > 36.0) and volatile properties and it was chosen for repellency assays. ZINC00170981 and ZINC00131924 showed a dose-response behavior, while ZINC01621824 did not showed activity in repellency assays. Finally, Molecular Dynamics (MD) was employed to hypothesize the stability of protein-ligand complexes. According to RMSD, RMSF and binding free energy data, ZINC00170981 and ZINC00131924 were able to stabilize AaegOBP1 binding-site during the trajectory by interactions with key residues such as His77, Leu89 and Trp114). Communicated by Ramaswamy H. Sarma.