Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening

Analgesic Activity of 5-Acetamido-2-Hydroxy Benzoic Acid Derivatives and an In-Vivo and In-Silico Analysis of Their Target Interactions

The design, synthesis, and evaluation of novel non-steroidal anti-inflammatory drugs (NSAIDs) with better activity and lower side effects are big challenges today. In this work, two 5-acetamido-2-hydroxy benzoic acid derivatives were proposed, increasing the alkyl position (methyl) in an acetamide moiety, and synthesized, and their structural elucidation was performed using 1H NMR and 13C NMR. The changes in methyl in larger groups such as phenyl and benzyl aim to increase their selectivity over cyclooxygenase 2 (COX-2). These 5-acetamido-2-hydroxy benzoic acid derivatives were prepared using classic methods of acylation reactions with anhydride or acyl chloride. Pharmacokinetics and toxicological properties were predicted using computational tools, and their binding affinity (kcal/mol) with COX-2 receptors (Mus musculus and Homo sapiens) was analyzed using docking studies (PDB ID 4PH9, 5KIR, 1PXX and 5F1A). An in-silico study showed that 5-acetamido-2-hydroxy benzoic acid derivates have a better bioavailability and binding affinity with the COX-2 receptor, and in-vivo anti-nociceptive activity was investigated by means of a writhing test induced by acetic acid and a hot plate. PS3, at doses of 20 and 50 mg/kg, reduced painful activity by 74% and 75%, respectively, when compared to the control group (20 mg/kg). Regarding the anti-nociceptive activity, the benzyl showed reductions in painful activity when compared to acetaminophen and 5-acetamido-2-hydroxy benzoic acid. However, the proposed derivatives are potentially more active than 5-acetamido-2-hydroxy benzoic acid and they support the design of novel and safer derivative candidates. Consequently, more studies need to be conducted to evaluate the different pharmacological actions, the toxicity of possible metabolites that can be generated, and their potential use in inflammation and pain therapy.

Receptor Interacting Ser/Thr-Protein Kinase 2 as a New Therapeutic Target

Receptor interacting serine/threonine protein kinase 2 (RIPK2) is a downstream signaling molecule essential for the activation of several innate immune receptors, including the NOD-like receptors (NOD1 and NOD2). Recognition of pathogen-associated molecular pattern proteins by NOD1/2 leads to their interaction with RIPK2, which induces release of pro-inflammatory cytokines through the activation of NF-κB and MAPK pathways, among others. Thus, RIPK2 has emerged as a key mediator of intracellular signal transduction and represents a new potential therapeutic target for the treatment of various conditions, including inflammatory diseases and cancer. In this Perspective, first, an overview of the mechanisms that underlie RIPK2 function will be presented along with its role in several diseases. Then, the existing inhibitors that target RIPK2 and different therapeutic strategies will be reviewed, followed by a discussion on current challenges and outlook.

RIPK2 inhibitors for disease therapy: Current status and perspectives

Receptor-interacting protein kinase 2 (RIPK2) belongs to the receptor-interacting protein family (RIPs), which is mainly distributed in the cytoplasm. RIPK2 is widely expressed in human tissues, and its mRNA level is highly expressed in the spleen, leukocytes, placenta, testis, and heart. RIPK2 is a dual-specificity kinase with multiple domains, which can interact with tumor necrosis factor receptor (TNFR), and participate in the Toll-like receptor (TLR) and nucleotide-binding oligomerization domain (NOD) signaling pathways. It is considered as a vital adapter molecule involved in the innate immunity, adaptive immunity, and apoptosis. Functionally, RIPK2 and its targeted small molecules are of great significance in inflammatory responses, autoimmune diseases and tumors. The present study reviews the molecule structure and biological functions of RIPK2, and its correlation between human diseases. In addition, we focus on the structure-activity relationship of small molecule inhibitors of RIPK2 and their therapeutic potential in human diseases.

Ponatinib: An update on its drug targets, therapeutic potential and safety

Leukemia is a malignancy of the hematopoietic system, and as its pathogenesis has become better understood, three generations of tyrosine kinase inhibitors (TKIs) have been developed. Ponatinib is the third-generation breakpoint cluster region (BCR) and Abelson (ABL) TKI, which has been influential in the leukemia therapy for a decade. Moreover, ponatinib is a potent multi-target kinase inhibitor that acts on various kinases, such as KIT, RET, and Src, making it a promising treatment option for triple-negative breast cancer (TNBC), lung cancer, myeloproliferative syndrome, and other diseases. The drug's significant cardiovascular toxicity poses a significant challenge to its clinical use, requiring the development of strategies to minimize its toxicity and side effects. In this article, the pharmacokinetics, targets, therapeutic potential, toxicity and production mechanism of ponatinib will be reviewed. Furthermore, we will discuss methods to reduce the drug's toxicity, providing new avenues for research to improve its safety in clinical use.

Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2

When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts' angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein's crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport^®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of -8.645 kcal·mol^-1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC₅₀ values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.

Virtual screening of natural compounds as selective inhibitors of polo-like kinase-1 at C-terminal polo box and N-terminal catalytic domain

The over-expression of Polo-like kinase-1 (PLK1) is associated with cancer prognosis due to its pivotal role in cell proliferation. The N-terminal catalytic domain (NCD) and C-terminal polo box domain (PBD) of PLK1 are critical for the activity of the protein. Drugs that inhibit PLK1 by targeting these domains are on clinical trials, but so far, none has been approved by FDA. Thus, this study targets the two domains of PLK1 to identify compounds with inhibitory potential. Four validated e-pharmacophore models from NCD (PDB ID: 2OU7 and 4J52) and PBD (PDB ID: 5NEI and 5NN2) were used to screen over 26,000 natural compounds from NPASS database. Hits were identified after the well-fitted compounds were subjected to molecular docking study and ADME prediction. The pIC50 and electronic behaviour of the identified hits selectively targeting NCD and PBD of PLK1 were predicted via an externally validated QSAR model and quantum mechanics. The results showed that CAA180504, CAA197326, CAA74619, CAA328856 modulating PLK1 at NCD, and CBB130581, CBB230713, CBB206123, CBB12656 and CBB267117 modulating PLK1 at PBD had better molecular docking scores, pharmacokinetics and drug-like properties than NCD (volasertib) and PBD (purpurogallin) reference inhibitors. The compounds all had satisfactory inhibitory (pIC50) values which range from 6.187 to 7.157. The electronic behaviours of understudied compounds using HOMO/LUMO and global descriptive parameters revealed the atomic portion of the compounds prone to donating and accepting electrons. In conclusion, the hit compounds identified from the library of natural compounds are worthy of further experimental validation.Communicated by Ramaswamy H. Sarma.

Acute Toxicity and Anti-Inflammatory Activity of Trattinnickia rhoifolia Willd (Sucuruba) Using the Zebrafish Model

The species Trattinnickia rhoifolia Willd, (T. rhoifolia), which belongs to the Burseraceae family, is widely used in ethnopharmacological cultural practices by traditional Amazonian people for anti-inflammatory purposes, sometimes as their only therapeutic resource. Although it is used in teas, infusions, macerations and in food, the species is still unexplored in regard to its pharmacophoric potential and chemical profile. Therefore, the aim of this study was to conduct a phytochemical characterization of the hydroethanolic extract of T. rhoifolia leaves (HELTr) and to evaluate the acute toxicity and anti-inflammatory activity of this species using zebrafish (Danio rerio). The extract was analyzed by gas chromatography−mass spectrometry (GC-MS). The evaluation of the acute toxicity of the HELTr in adult zebrafish was determined using the limit test (2000 mg/kg), with behavioral and histopathological evaluations, in addition to the analysis of the anti-inflammatory potential of HELTr in carrageenan-induced abdominal edema, followed by the use of the computational method of molecular docking. The phytochemical profile of the species is chemically diverse, suggesting the presence of the fatty acids, ester, alcohol and benzoic acid classes, including propanoic acid, ethyl ester and hexadecanoic acid. In the studies of zebrafish performed according to the index of histopathological changes (IHC), the HELTr did not demonstrate toxicity in the behavioral and histopathological assessments, since the vital organs remained unchanged. Carrageenan-induced abdominal edema was significantly reduced at all HELTr doses (100, 200 and 500 mg/kg) in relation to the negative control, dimethyl sulfoxide (DMSO), while the 200 mg/kg dose showed significant anti-inflammatory activity in relation to the positive control (indomethacin). With these activities being confirmed by molecular docking studies, they showed a good profile for the inhibition of the enzyme Cyclooxygenase-2 (COX-2), as the interactions established at the sites of the receptors used in the docking study were similar to the controls (RCX, IMN and CEL). Therefore, the HELTr has an acceptable degree of safety for acute toxicity, defined in the analysis of behavioral changes, mortality and histopathology, with a significant anti-inflammatory action in zebrafish at all doses, which demonstrates the high pharmacophoric potential of the species. These results may direct future applications and drug development but still require further elucidation.

Hierarchical Virtual Screening and Binding Free Energy Prediction of Potential Modulators of Aedes Aegypti Odorant-Binding Protein 1

The Aedes aegypti mosquito is the main hematophagous vector responsible for arbovirus transmission in Brazil. The disruption of A. aegypti hematophagy remains one of the most efficient and least toxic methods against these diseases and, therefore, efforts in the research of new chemical entities with repellent activity have advanced due to the elucidation of the functionality of the olfactory receptors and the behavior of mosquitoes. With the growing interest of the pharmaceutical and cosmetic industries in the development of chemical entities with repellent activity, computational studies (e.g., virtual screening and molecular modeling) are a way to prioritize potential modulators with stereoelectronic characteristics (e.g., pharmacophore models) and binding affinity to the AaegOBP1 binding site (e.g., molecular docking) at a lower computational cost. Thus, pharmacophore- and docking-based virtual screening was employed to prioritize compounds from Sigma-Aldrich® (n = 126,851) and biogenic databases (n = 8766). In addition, molecular dynamics (MD) was performed to prioritize the most potential potent compounds compared to DEET according to free binding energy calculations. Two compounds showed adequate stereoelectronic requirements (QFIT > 81.53), AaegOBP1 binding site score (Score > 42.0), volatility and non-toxic properties and better binding free energy value (∆G < −24.13 kcal/mol) compared to DEET ((N,N-diethyl-meta-toluamide)) (∆G = −24.13 kcal/mol).

Hierarchical Virtual Screening Based on Rocaglamide Derivatives to Discover New Potential Anti-Skin Cancer Agents

Skin Cancer (SC) is among the most common type of cancers worldwide. The search for SC therapeutics using molecular modeling strategies as well as considering natural plant-derived products seems to be a promising strategy. The phytochemical Rocaglamide A (Roc-A) and its derivatives rise as an interesting set of reference compounds due to their in vitro cytotoxic activity with SC cell lines. In view of this, we performed a hierarchical virtual screening study considering Roc-A and its derivatives, with the aim to find new chemical entities with potential activity against SC. For this, we selected 15 molecules (Roc-A and 14 derivatives) and initially used them in docking studies to predict their interactions with Checkpoint kinase 1 (Chk1) as a target for SC. This allowed us to compile and use them as a training set to build robust pharmacophore models, validated by Pearson’s correlation (p) values and hierarchical cluster analysis (HCA), subsequentially submitted to prospective virtual screening using the Molport^® database. Outputted compounds were then selected considering their similarities to Roc-A, followed by analyses of predicted toxicity and pharmacokinetic properties as well as of consensus molecular docking using three software. 10 promising compounds were selected and analyzed in terms of their properties and structural features and, also, considering their previous reports in literature. In this way, the 10 promising virtual hits found in this work may represent potential anti-SC agents and further investigations concerning their biological tests shall be conducted.

New styrylquinoxaline: synthesis, structural, biological evaluation, ADMET prediction and molecular docking investigations

The organic compound (E)-3-(4-methylstyryl)quinoxalin-2(1H)-one (SQO) with molecular formula C₁₇H₁₄N₂O was synthesized and analyzed using single crystal X-ray diffraction, ¹H, ¹³C NMR and FTIR spectroscopic techniques. The geometric parameters of the molecule was optimized by density-functional theory (DFT) choosing B3LYP with 6-31++G(d,p) basis set. For compatibility, the theoretical structure and experimental structure were overlapped with each other. Frontier molecular orbitals of the title compound were made, and energy gap between HOMO and LUMO was calculated. Molecular electrostatic potential map was generated finding electrophilic and nucleophilic attack centers using DFT method. Hirshfeld surface analysis (HSA) confirms active regions at the circumference of N1 atoms and O1 atoms that form intermolecular N1-H1···O1 hydrogen bond. The acute oral toxicity study was carried out according to OECD guideline, which approve that the compound SQO was non-toxic. In addition, this quinoxaline derivative was evaluated for its in vitro antidiabetic activity against α-glucosidase and α-amylase enzymes and for antioxidant activity by utilizing several tests as 1,1-diphenyl-2-picryl hydrazyl, (2,2'-azino-bis(3-ethyl benzthiazoline-6-sulfonicacid), reducing power test (FRAP) and hydrogen peroxide activity H₂O₂. The molecular docking studies were performed to investigate the antidiabetic activity of SQO and compared with the experimental results. SQO is a potent antidiabetic from both the experimental and molecular docking results. Finally, the physicochemical, pharmacokinetic and toxicological properties of SQO have been evaluated by using in silico absorption, distribution, metabolism, excretion and toxicity analysis prediction.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Targeting p53-MDM2 interactions to identify small molecule inhibitors for cancer therapy: beyond "Failure to rescue"

At present, disrupting p53-MDM2 interactions through small molecule ligands is a promising approach to safe treatment and management of human cancer. Tumor cells unlike the normal cells, are rapidly evolving affecting the efficacy of many approved anti-cancer agents due to drug resistance. Therefore, identifying a potential anticancer compound is crucial. Pharmacophore based virtual screening, followed by molecular docking, ADMET evaluation, and molecular dynamics studies against MDM2 protein was investigated to identify potential ligands that may act as inhibitors. The model (AHRR_1) with survival score (4.176) was selected among the top ranked generated Pharmacophore hypothesis. Validation of the model hypothesis by an external dataset of actives and inactive compounds produced significant validation attributes including; AUC = 0.85, BEDROC = 0.56 at α = 20.0, RIE = 8.18, AUAC = 0.88, and EF of 6.2 at the top 2% of the dataset. The model was use for screening the ZINC database, and the top 1375 hits satisfying the model hypothesis were subjected to molecular docking studies to understand the molecular and structural basis of selectivity of compounds for MDM2 protein. A sub-set of 25 compounds with binding energy lower than the reference inhibitors were evaluated for pharmacokinetic properties. Four compounds (ZINC02639178, ZINC06752762, ZINC38933175, and ZINC77969611) showed the most desired pharmacokinetic profile. Lastly, investigation of the dynamic behaviour of leads-protein complexes through MD simulation showed similar RMSD, RMSF, and H-bond occupancy profile compared to a reference inhibitor, suggesting stability throughout the simulation time. However, ZINC02639178 was found to satisfy the molecular enumeration the most compared to the other three leads. It may emerge as potential treatment option after extensive experimental studies. 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.

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.

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 Chemical Entities for Adenosine Receptor Type 2A Using Molecular Modeling Approaches

Adenosine Receptor Type 2A (A_2AAR) plays a role in important processes, such as anti-inflammatory ones. In this way, the present work aimed to search for compounds by pharmacophore-based virtual screening. The pharmacokinetic/toxicological profiles of the compounds, as well as a robust QSAR, predicted the binding modes via molecular docking. Finally, we used molecular dynamics to investigate the stability of interactions from ligand-A_2AAR. For the search for A_2AAR agonists, the UK-432097 and a set of 20 compounds available in the BindingDB database were studied. These compounds were used to generate pharmacophore models. Molecular properties were used for construction of the QSAR model by multiple linear regression for the prediction of biological activity. The best pharmacophore model was used by searching for commercial compounds in databases and the resulting compounds from the pharmacophore-based virtual screening were applied to the QSAR. Two compounds had promising activity due to their satisfactory pharmacokinetic/toxicological profiles and predictions via QSAR (Diverset 10002403 pEC₅₀ = 7.54407; ZINC04257548 pEC₅₀ = 7.38310). Moreover, they had satisfactory docking and molecular dynamics results compared to those obtained for Regadenoson (Lexiscan^®), used as the positive control. These compounds can be used in biological assays (in vitro and in vivo) in order to confirm the potential activity agonist to A_2AAR.

Virtual Screening Approach to Identify High-Affinity Inhibitors of Serum and Glucocorticoid-Regulated Kinase 1 among Bioactive Natural Products: Combined Molecular Docking and Simulation Studies

Serum and glucocorticoid-regulated kinase 1 (SGK1) is a serine/threonine kinase that works under acute transcriptional control by several stimuli, including serum and glucocorticoids. It plays a significant role in the cancer progression and metastasis, as it regulates inflammation, apoptosis, hormone release, neuro-excitability, and cell proliferation. SGK1 has recently been considered as a potential drug target for cancer, diabetes, and neurodegenerative diseases. In the present study, we have performed structure-based virtual high-throughput screening of natural compounds from the ZINC database to find potential inhibitors of SGK1. Initially, hits were selected based on their physicochemical, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and other drug-like properties. Afterwards, PAINS filter, binding affinities estimation, and interaction analysis were performed to find safe and effective hits. We found four compounds bearing appreciable binding affinity and specificity towards the binding pocket of SGK1. The docking results were complemented by all-atom molecular dynamics simulation for 100 ns, followed by MM/PBSA, and principal component analysis to investigate the conformational changes, stability, and interaction mechanism of SGK1 in-complex with the selected compound ZINC00319000. Molecular dynamics simulation results suggested that the binding of ZINC00319000 stabilizes the SGK1 structure, and it leads to fewer conformational changes. In conclusion, the identified compound ZINC00319000 might be further exploited as a scaffold to develop promising inhibitors of SGK1 for the therapeutic management of associated diseases, including cancer.

Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24

BACKGROUND

The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking.

METHODS

An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively.

RESULTS

Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of -9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds.

CONCLUSION

The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.

Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening

Leukemias are neoplasms that affect hematopoietic cells, which are developed by genetic alterations (mutations) that lead to the loss of proliferation control mechanisms (maturation and/or cell death). The α4β1 integrin receptor is a therapeutic target for inflammation, autoimmune diseases and lymphoid tumors. This study was carried out to search through the antagonists-based virtual screening for α4β1 receptor. Initially, seventeen (17) structures were selected (based on the inhibitory activity values, IC₅₀) and the structure with the best value was chosen as the pivot. The pharmacophoric pattern was determined from the online PharmaGist server and resulted in a model of score value equal to 97.940 with 15 pharmacophoric characteristics that were statistically evaluated via Pearson correlations, principal component analysis (PCA) and hierarchical clustering analysis (HCA). A refined model generated four pharmacophoric hypotheses totaling 1.478 structures set of Zinc_database. After, the pharmacokinetic, toxicological and biological activity predictions were realized comparing with pivot structure that resulted in five (ZINC72088291, ZINC68842860, ZINC14365931, ZINC09588345 and ZINC91247798) structures with optimal in silico predictions. Therefore, future studies are needed to confirm antitumor potential activity of molecules selected this work with in vitro and in vivo assays.

In Silico Evaluation of Ibuprofen and Two Benzoylpropionic Acid Derivatives with Potential Anti-Inflammatory Activity

Inflammation is a complex reaction involving cellular and molecular components and an unspecific response to a specific aggression. The use of scientific and technological innovations as a research tool combining multidisciplinary knowledge in informatics, biotechnology, chemistry and biology are essential for optimizing time and reducing costs in the drug design. Thus, the integration of these in silico techniques makes it possible to search for new anti-inflammatory drugs with better pharmacokinetic and toxicological profiles compared to commercially used drugs. This in silico study evaluated the anti-inflammatory potential of two benzoylpropionic acid derivatives (MBPA and DHBPA) using molecular docking and their thermodynamic profiles by molecular dynamics, in addition to predicting oral bioavailability, bioactivity and toxicity. In accordance to our predictions the derivatives proposed here had the potential capacity for COX-2 inhibition in the human and mice enzyme, due to containing similar interactions with the control compound (ibuprofen). Ibuprofen showed toxic predictions of hepatotoxicity (in human, mouse and rat; toxicophoric group 2-arylacetic or 3-arylpropionic acid) and irritation of the gastrointestinal tract (in human, mouse and rat; toxicophoric group alpha-substituted propionic acid or ester) confirming the literature data, as well as the efficiency of the DEREK 10.0.2 program. Moreover, the proposed compounds are predicted to have a good oral bioavailability profile and low toxicity (LD50 < 700 mg/kg) and safety when compared to the commercial compound. Therefore, future studies are necessary to confirm the anti-inflammatory potential of these compounds.

In Silico Study to Identify New Antituberculosis Molecules from Natural Sources by Hierarchical Virtual Screening and Molecular Dynamics Simulations

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, responsible for 1.5 million documented deaths in 2016. The increase in reported cases of M. tuberculosis resistance to the main drugs show the need for the development of new and efficient drugs for better TB control. Based on these facts, this work aimed to use combined in silico techniques for the discovery of potential inhibitors to β-ketoacyl-ACP synthase (MtKasA). Initially compounds from natural sources present in the ZINC database were selected, then filters were sequentially applied by virtual screening, initially with pharmacophoric modeling, and later the selected compounds (based on QFIT scores) were submitted to the DOCK 6.5 program. After recategorization of the variables (QFIT score and GRID score), compounds ZINC35465970 and ZINC31170017 were selected. These compounds showed great hydrophobic contributions and for each established system 100 ns of molecular dynamics simulations were performed and the binding free energy was calculated. ZINC35465970 demonstrated a greater capacity for the KasA enzyme inhibition, with a ΔG_bind = -30.90 kcal/mol and ZINC31170017 presented a ΔG_bind = -27.49 kcal/mol. These data can be used in other studies that aim at the inhibition of the same biological targets through drugs with a dual action.

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.

Toward of Safer Phenylbutazone Derivatives by Exploration of Toxicity Mechanism

A drug design for safer phenylbutazone was been explored by reactivity and docking studies involving single electron transfer mechanism, as well as toxicological predictions. Several approaches about its structural properties were performed through quantum chemistry calculations at the B3LYP level of theory, together with the 6-31+G(d,p) basis sets. Molecular orbital and ionization potential were associated to electron donation capacity. The spin densities contribution showed a preferential hydroxylation at the para-positions of phenyl ring when compared to other positions. In addition, on electron abstractions the aromatic hydroxylation has more impact than alkyl hydroxylation. Docking studies indicate that six structures 1, 7, 8 and 13–15 have potential for inhibiting human as well as murine COX-2, due to regions showing similar intermolecular interactions to the observed for the control compounds (indomethacin and refecoxib). Toxicity can be related to aromatic hydroxylation. In accordance to our calculations, the derivatives here proposed are potentially more active as well safer than phenylbutazone and only structures 8 and 13–15 were the most promising. Such results can explain the biological properties of phenylbutazone and support the design of potentially safer candidates.

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.

Computational design of new protein kinase 2 inhibitors for the treatment of inflammatory diseases using QSAR, pharmacophore-structure-based virtual screening, and molecular dynamics

Receptor-interacting protein kinase 2 (RIPK2) plays an essential role in autoimmune response and is suggested as a target for inflammatory diseases. A pharmacophore model was built from a dataset with ponatinib (template) and 18 RIPK2 inhibitors selected from BindingDB database. The pharmacophore model validation was performed by multiple linear regression (MLR). The statistical quality of the model was evaluated by the correlation coefficient (R), squared correlation coefficient (R²), explanatory variance (adjusted R²), standard error of estimate (SEE), and variance ratio (F). The best pharmacophore model has one aromatic group (LEU24 residue interaction) and two hydrogen bonding acceptor groups (MET98 and TYR97 residues interaction), having a score of 24.739 with 14 aligned inhibitors, which were used in virtual screening via ZincPharmer server and the ZINC database (selected in function of the RMSD value). We determined theoretical values of biological activity (logRA) by MLR, pharmacokinetic and toxicology properties, and made molecular docking studies comparing binding affinity (kcal/mol) results with the most active compound of the study (ponatinib) and WEHI-345. Nine compounds from the ZINC database show satisfactory results, yielding among those selected, the compound ZINC01540228, as the most promising RIPK2 inhibitor. After binding free energy calculations, the following molecular dynamics simulations showed that the receptor protein's backbone remained stable after the introduction of ligands.

An Antioxidant Potential, Quantum-Chemical and Molecular Docking Study of the Major Chemical Constituents Present in the Leaves of Curatella americana Linn

Reactive oxygen species (ROS) are continuously generated in the normal biological systems, primarily by enzymes as xanthine oxidase (XO). The inappropriate scavenging or inhibition of ROS has been considered to be linked with aging, inflammatory disorders, and chronic diseases. Therefore, many plants and their products have been investigated as natural antioxidants for their potential use in preventive medicine. The leaves and bark extracts of Curatella americana Linn. were described in scientific research as anti-inflammatory, vasodilator, anti-ulcerogenic, and hypolipidemic effects. So, the aim of this study was to evaluate the antioxidant potentials of leaf hydroalcoholic extract from C. americana (HECA) through the scavenging DPPH assay and their main chemical constituents, evaluated by the following quantum chemical approaches (DFT B3LYP/6-31G**): Maps of Molecular Electrostatic Potential (MEP), Frontier Orbital’s (HOMO and LUMO) followed by multivariate analysis and molecular docking simulations with the xanthine oxidase enzyme. The hydroalcoholic extract showed significant antioxidant activity by free radical scavenging probably due to the great presence of flavonoids, which were grouped in the PCA and HCA analysis with the standard gallic acid. In the molecular docking study, the compounds studied presented the binding free energy (ΔG) values close each other, due to the similar interactions with amino acids residues at the activity site. The descriptors Gap and softness were important to characterize the molecules with antioxidant potential by capturing oxygen radicals.

In Silico Screening of Isocitrate Lyase for Novel Anti-Buruli Ulcer Natural Products Originating from Africa

Buruli ulcer (BU) is caused by Mycobacterium ulcerans and is predominant in both tropical and subtropical regions. The neglected debilitating disease is characterized by chronic necrotizing skin lesions attributed to a mycolactone, which is a macrolide toxin secreted by M. ulcerans. The preferred treatment is surgical excision of the lesions followed by a prolonged combination antibiotic therapy using existing drugs such as rifampicin and streptomycin or clarithromycin. These antibiotics appear not to be adequately potent and efficacious against persistent and late stage ulcers. In addition, emerging drug resistance to treatment poses great challenges. There is a need to identify novel natural product-derived lead compounds, which are potent and efficacious for the treatment of Buruli ulcer. Natural products present a rich diversity of chemical compounds with proven activity against various infectious diseases, and therefore, are considered in this study. This study sought to computationally predict natural product-derived lead compounds with the potential to be developed further into potent drugs with better therapeutic efficacy than the existing anti-buruli ulcer compounds. The three-dimensional (3D) structure of Isocitrate lyase (ICL) of Mycobacterium ulcerans was generated using homology modeling and was further scrutinized with molecular dynamics simulations. A library consisting of 885 compounds retrieved from the AfroDb database was virtually screened against the validated ICL model using AutoDock Vina. AfroDb is a compendium of “drug-like” and structurally diverse 3D structures of natural products originating from different geographical regions in Africa. The molecular docking with the ICL model was validated by computing a Receiver Operating Characteristic (ROC) curve with a reasonably good Area Under the Curve (AUC) value of 0.89375. Twenty hit compounds, which docked firmly within the active site pocket of the ICL receptor, were assessed via in silico bioactivity and pharmacological profiling. The three compounds, which emerged as potential novel leads, comprise ZINC38143792 (Euscaphic acid), ZINC95485880, and ZINC95486305 with reasonable binding energies (high affinity) of −8.6, −8.6, and −8.8 kcal/mol, respectively. Euscaphic acid has been reported to show minimal inhibition against a drug-sensitive strain of M. tuberculosis. The other two leads were both predicted to possess dermatological activity while one was antibacterial. The leads have shown promising results pertaining to efficacy, toxicity, pharmacokinetic, and safety. These leads can be experimentally characterized to assess their anti-mycobacterial activity and their scaffolds may serve as rich skeletons for developing anti-buruli ulcer drugs.