Synthesis of Some Benzothiazole Derivatives Based on 3-Hydroxypyridine-4-one and Benzaldehyde and Evaluation of Their ß-Amyloid Aggregation Inhibition Using both Experimental Methods and Molecular Dynamic Simulation.

Some novel inhibitors based on the (benzo[d]thiazol-2-yl)-1-phenylmethanimine derivatives were designed to reduce the aggregation process in Alzheimer's disease. These structures seem to mimic stilbene-like scaffold, while the benzothiazole moiety "locks" the thioflavin T binding site. Other inhibitors were designed based on 2-((benzo[d]thiazol-2-ylimino)methyl)-5-(benzyloxy)-1-methylpyridin-4(H)-one derivatives. Benzo[d]thiazol-2-amine derivatives were prepared by the reaction of aniline derivatives with ammonium thiocyanate in the presence of bromine/acetic acid. Then, the reaction of amines with benzaldehyde derivatives and 5-(benzyloxy)-1-methyl-4-oxo-1,4-dihydropyridine-2-carbaldehyde gave the desired compounds. The plate reader-based fibrillation assay was done to evaluate the inhibition of Aß aggregation. Also, molecular dynamic simulation was carried out to clarify the interaction manner of the designed compounds with Aß formation. The biological evaluation proved 5a and 7e as the best inhibitor of the Aß aggregation. compound 5a in the concentration of 50 µM inhibited Aß fibril formation better than 7e. MD simulation elucidated that the Aß aggregation inhibitors in different concentrations represented different binding conformations throughout the entire or in one area of Aß. MD showed the ligands in lower concentrations accumulate in an area of Aß aggregations and separate one fibril from the aggregated Aß. On the contrary, in higher concentrations, the ligands tend to be located through the entire Aß.

Discovery of novel RARα agonists using pharmacophore-based virtual screening, molecular docking, and molecular dynamics simulation studies.

Nuclear retinoic acid receptors (RARs) are ligand-dependent transcription factors involved in various biological processes, such as embryogenesis, cell proliferation, differentiation, reproduction, and apoptosis. These receptors are regulated by retinoids, i.e., retinoic acid (RA) and its analogs, as receptor agonists. RAR agonists are promising therapeutic agents for the treatment of serious dermatological disorders, including some malignant conditions. By inducing apoptosis, they are able to inhibit the proliferation of diverse cancer cell lines. Also, RAR agonists have recently been identified as therapeutic options for some neurodegenerative diseases. These features make retinoids very attractive molecules for medical purposes. Synthetic selective RAR agonists have several advantages over endogenous ones, but they suffer poor pharmacokinetic properties. These compounds are normally lipophilic acids with unfavorable drug-like features such as poor oral bioavailability. Recently, highly selective, potent, and less toxic RAR agonists with proper lipophilicity, thus, good oral bioavailability have been developed for some therapeutic applications. In the present study, ligand and structure-based virtual screening technique was exploited to introduce some novel RARα agonists. Pharmacokinetic assessment was also performed in silico to suggest those compounds which have optimized drug-like features. Finally, two compounds with the best in silico pharmacological features are proposed as lead molecules for future development of RARα agonists.

A GU-Net-Based Architecture Predicting Ligand-Protein-Binding Atoms.

Background: The first step in developing new drugs is to find binding sites for a protein structure that can be used as a starting point to design new antagonists and inhibitors. The methods relying on convolutional neural network for the prediction of binding sites have attracted much attention. This study focuses on the use of optimized neural network for three-dimensional (3D) non-Euclidean data. Methods: A graph, which is made from 3D protein structure, is fed to the proposed GU-Net model based on graph convolutional operation. The features of each atom are considered as attributes of each node. The results of the proposed GU-Net are compared with a classifier based on random forest (RF). A new data exhibition is used as the input of RF classifier. Results: The performance of our model is also examined through extensive experiments on various datasets from other sources. GU-Net could predict the more number of pockets with accurate shape than RF. Conclusions: This study will enable future works on a better modeling of protein structures that will enhance knowledge of proteomics and offer deeper insight into drug design process.

Design, Synthesis, Molecular Docking, and Molecular Dynamics Simulation Studies of Novel 3-Hydroxypyridine-4-one Derivatives as Potential Acetylcholinesterase Inhibitors.

Researchers have focused on inhibiting acetylcholinesterase for Alzheimer's disease treatment. In this study, some novel AChE inhibitors were synthesized using hydroxypyridin-4-one plus benzylpiperidine scaffolds which were evaluated using Ellman's method. Accordingly, ((1-(4-methoxyphenethyl)piperidin-4-yl)amino)methyl)-5-hydroxy-1-methylpyridin-4(1H)-one (VIId ) showed weaker but promising AChE inhibition compared to donepezil (IC50 =143.090 nM). The average RMSD values of VIId was found to be 2.25 indicated less structural changes in the active site residues. The phenyl group of the phenyl-ethyl-N-piperidine moiety of VIId formed hydrophobic interactions with Trp285 and Tyr340. There was a π-cation interaction between nitrogen atom of piperidine ring and Phe294. Another π-cation interaction was found between type 2 amine of linker and Trp85. Piperidine ring interacted with Tyr336, Tyr123, and Phe337 through hydrophobic interactions. Indeed, the VIId was predicted to be absorbed across the gastrointestinal tract, though it may be pumped out by P-gp. Indeed, VIId can permeate through the blood brain barrier. MD simulation studies revealed that benzyloxy moiety plays a role similar to benzylpiperidine moiety of donepezil in binding to the active site residues. Also, carbonyl group functioned similar to indanone ketone group. Overall; further research on VIId may lead to introduction of a novel class of AChE inhibitors.

Discovery of novel direct small-molecule inhibitors targeting HIF-2α using structure-based virtual screening, molecular dynamics simulation, and MM-GBSA calculations.

Hypoxia-inducible factors (HIFs) are the main regulatory factors implicated in the adaptation of cancer cells to hypoxic stress, which has provoked much interest as an attractive target for the design of promising chemotherapeutic agents. Since indirect HIF inhibitors (HIFIs) lead to the occurrence of various side effects, the need of the hour is to develop direct HIFIs, physically interacting with important functional domains within the HIF protein structure. Accordingly, in the present study, it was attempted to develop an exhaustive structure-based virtual screening (VS) process coupled with molecular docking, molecular dynamic (MD) simulation, and MM-GBSA calculations for the identification of novel direct inhibitors against the HIF-2α subunit. For this purpose, a focused library of over 200,000 compounds from the NCI database was used for VS against the PAS-B domain of the target protein, HIF-2α. This domain was suggested to be a possible ligand-binding site, which is characterized by a large internal hydrophobic cavity, unique to the HIF-2α subunit. The top-ranked compounds, NSC106416, NSC217021, NSC217026, NSC215639, and NSC277811 with the best docking scores were taken up for the subsequent in silico ADME properties and PAINS filtration. The selected drug-like hits were employed for carrying out MD simulation which was followed by MM-GBSA calculations to retrieve the candidates showing the highest in silico binding affinity towards the PAS-B domain of HIF-2α. The analysis of results indicated that all molecules, except the NSC277811, fulfilled necessary drug-likeness properties. Four selected drug-like candidates, NSC106416, NSC217021, NSC217026, and NSC215639 were found to expose the stability profiles within the cavity located inside the PAS-B domain of HIF-2α over simulation time. Finally, the results of the MM-GBSA rescoring method were indicative of the highest binding affinity of NSC217026 for the binding site of the HIF-2α PAS-B domain among selected final hits. Consequently, the hit NSC217026 could serve as a promising scaffold for further optimization toward the design of direct HIF-2α inhibitors for cancer therapy.

Preparing a database of corrected protein structures important in cell signaling pathways.

Background and purpose: Precise structures of macromolecules are important for structure-based drug design. Due to the limited resolution of some structures obtained from X-ray diffraction crystallography, differentiation between the NH and O atoms can be difficult. Sometimes a number of amino acids are missing from the protein structure. In this research, we intend to introduce a small database that we have prepared for providing the corrected 3D structure files of proteins frequently used in structure-based drug design protocols. Experimental approach: 3454 soluble proteins belonging to the cancer signaling pathways were collected from the PDB database from which a dataset of 1001 was obtained. All were subjected to corrections in the protein preparation step. 896 protein structures out of 1001 were corrected successfully and the decision on the remained 105 proposed twelve for homology modeling to correct the missing residues. Three of them were subjected to molecular dynamics simulation for 30 ns. Findings / Results: 896 corrected proteins were perfect and homology modeling on 12 proteins with missing residues in the backbone resulted in acceptable models according to Ramachandran, z-score, and DOPE energy plots. RMSD, RMSF, and Rg values verified the stability of the models after 30 ns molecular dynamics simulation. Conclusion and implication: A collection of 1001 proteins were modified for some defects such as adjustment of the bond orders and formal charges, and addition of missing side chains of residues. Homology modeling corrected the amino missing backbone residues. This database will be completed for quite a lot of water-soluble proteins to be uploaded to the internet.

New 2-alkylthio-1-benzylimidazole-5-carboxylic acid derivatives targeting gp41: design, synthesis and in vitro anti-HIV activity evaluation.

Background Although current available medications have increased the quality of life in HIV-infected patients, there are still some shortcomings in HIV treatment arising from viral resistance, drug side effects and high cost of medication. Therefore, there is an urgent need for some suitable HIV inhibitors with different mechanisms of action. Gp41, located on the HIV cell surface, plays an important role in the fusion of viral and host cell membranes. With the same structure in different HIV strains, gp41 seems to be a promising target for developing novel HIV fusion inhibitors. Objective Based on the essential structural elements of gp41 inhibitors, two series of compounds were prepared and their inhibitory effect on HIV cell growth was investigated. Compared to the known small-molecule gp41 inhibitors, 2-Alkylthio-1-benzylimidazole-5-carboxylic acid (series I) and (E)-4-{[5-(((1-benzyl-1H-1,2,3-triazol-4-yl)methoxyimino)methyl)-2-(alkylthio)-1H-imidazol-1-yl]methyl}benzoic acid derivatives (series II) had more flexible skeleton with extra moieties interacting with the gp41 key residues. Method In silico drug design approaches including molecular docking and molecular dynamics simulations were employed to design these novel compounds prior to preparation. The designed compounds exhibited proper chemical interactions and stable complexes with gp41. Then, the selected candidates were efficiently synthesized, and their anti-HIV-1 and anti-HIV-2 activities, as well as their cellular cytotoxicity in MT-4 cells were determined. Results None of the compounds belonging to the series I were active against HIV-1 and HIV-2 replication in cell cultures, and most of the compounds in series II exhibited significant cytotoxicity against MT-4 cells in low micro molar concentrations. Conclusion The smaller molecular structures of the compounds in series I might be responsible for their poor anti-HIV effects. The high toxicity of the series II compounds on the host cell makes it impossible to assess their anti-HIV activities.

Design, synthesis, in silico studies, and antiproliferative evaluations of novel indolin-2-one derivatives containing 3-hydroxy-4-pyridinone fragment.

Keeping in view the pharmacological properties of indolinones as promising scaffold as kinase inhibitors, herein, a novel series of 3-hydrazonoindolin-2-one derivatives bearing 3-hydroxy-4-pyridinone moiety were synthesized, studied by molecular docking, and fully characterized by spectroscopic techniques. All the prepared compounds were evaluated for their cytotoxicity attributes against a panel of tumor cell lines, including non-small cell lung cancer (A549), breast carcinoma (MCF-7), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). They displayed moderate to promising antiproliferative effects toward A549 and MCF-7 cells but remarkable results against AML and CML. Especially, compound 10k was found to be more potent against AML (EC50 = 0.69 µM) compare to the other halogen-substituted derivatives. FMS-like tyrosine kinase 3 (FLT3) is known to be expressed in AML cancer cells. The molecular docking studies demonstrated that our prepared compounds were potentially bound to AML active site through essential H-bond and other vital interactions with critical binding residues.

A Comparative DFT Study on the Antioxidant Activity of Some Novel 3-Hydroxypyridine-4-One Derivatives.

The current study on the antioxidant activity of kojic acid and 3-hydroxypyridine-4-one derivatives was performed by implementation of density functional theory calculations with the B3LYP hybrid functional and the 6-311++G** basis set in Polarizable Continuum Model of solvation. Compounds under evaluation were previously synthesized by our research group. The DPPH scavenging effect and the IC50 values in mM concentrations were evaluated. Subsequently, various electronic and energetic descriptors such as HOMO and LUMO energy gaps, bonding dissociation enthalpy of an OH bond, ionization potential, electron affinity, hardness, softness, NBOs and spin density of radical and neutral species were used to study antioxidant properties of investigated compounds. The computations detected two compounds, HP3 and HP4, with significant antioxidant activity. Energetic descriptors indicated that the SPLET mechanism is preferred over the other antioxidation mechanism and computational results were in accordance with the experimental results.

Accelerating Big Data Analysis through LASSO-Random Forest Algorithm in QSAR Studies.

MOTIVATION: The aim of quantitative structure-activity prediction (QSAR) studies is to identify novel drug-like molecules that can be suggested as lead compounds by means of two approaches, which are discussed in this article. First, to identify appropriate molecular descriptors by focusing on one feature-selection algorithms; and second to predict the biological activities of designed compounds. Recent studies have shown increased interest in the prediction of a huge number of molecules, known as Big Data, using deep learning models. However, despite all these efforts to solve critical challenges in QSAR models, such as over-fitting, massive processing procedures, is major shortcomings of deep learning models. Hence, finding the most effective molecular descriptors in the shortest possible time is an ongoing task. One of the successful methods to speed up the extraction of the best features from big datasets is the use of least absolute shrinkage and selection operator (LASSO). This algorithm is a regression model that selects a subset of molecular descriptors with the aim of enhancing prediction accuracy and interpretability because of removing inappropriate and irrelevant features. RESULTS: To implement and test our proposed model, a random forest was built to predict the molecular activities of Kaggle competition compounds. Finally, the prediction results and computation time of the suggested model were compared with the other well-known algorithms, i.e. Boruta-random forest, deep random forest and deep belief network model. The results revealed that improving output correlation through LASSO-random forest leads to appreciably reduced implementation time and model complexity, while maintaining accuracy of the predictions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In silico design of novel FAK inhibitors using integrated molecular docking, 3D-QSAR and molecular dynamics simulation studies.

Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase that plays a crucial role in integrin signaling that regulates essential cellular functions including growth, motility, proliferation and survival in different types of cells. Interestingly, it has also shown to be up-regulated in various types of tumors, hence it has emerged as a significant therapeutic target for the development of selective inhibitors. In present work, with the aim of achieving further insight into the structural characteristics required for the FAK inhibitory activity, a combined approach of molecular modeling studies including molecular docking, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) simulation were carried out on a series of 7H-pyrrolo[2,3-d]pyrimidine and thieno[3,2-d]pyrimidine FAK inhibitors. The probable binding modes and interactions of inhibitors into the FAK active site were predicted by molecular docking. The 3D-QSAR models were developed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, with three ligand-based, docking-based and receptor-based alignment techniques. Both CoMFA and CoMSIA models obtained from receptor-based alignment were superior to the ones obtained by other alignment methods. However, the CoMSIA model (q2 = 0.679, r2 = 0.954 and r2pred = 0.888) depicted almost better predictive ability than the CoMFA model (q2 = 0.617, r2 = 0.932 and r2pred = 0.856). The contour map analysis revealed the relationship between the structural features and inhibitory activity. The docking results and CoMFA and CoMSIA contour maps were in good accordance. Based on the information obtained from the molecular docking and contour map analysis, a series of novel FAK inhibitors were designed that showed better predicted inhibitory activity than the most potent compound 31 in the data set. Finally, the stability of the reference molecule 31 and the designed compounds D15 and D27 were evaluated through a 30 ns of MD simulation and their binding free energies were calculated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The result of MD simulation and binding free energy decomposition demonstrated the important role of van der Waals interactions alongside H-bond ones that were in consistent with the docking and contour maps analysis results. In sum, the results from this study may provide a significant insight for developing more effective novel FAK inhibitors.Communicated by Ramaswamy H. Sarma.

Synthesis, antioxidant activity, and density functional theory study of some novel 4-[(benzo[d]thiazol-2-ylimino)methyl]phenol derivatives: a comparative approach for the explanation of their radical scavenging activities.

BACKGROUND AND PURPOSE: Radicals produced by Fenton and Haber-Weiss reactions play detrimental roles in our body. Some oxidized proteins as toxic configurations are identified in amyloid-ß deposits. These deposits mostly occur in conditions, such as Alzheimer's disease. Here, we report the synthesis, evaluation of the antioxidant activity, and implementation of density functional theory (DFT) calculations of some4- [(benzo[d]thiazol-2-ylimino) methyl]phenol derivatives. The aim of this study was to provide a comparative theoretical-experimental approach to explain the antioxidant activities of the compounds. EXPERIMENTAL APPROACH: Compounds were synthesized by the reaction between para hydroxybenzaldehyde and aminobenzothiazole derivatives. The scavenging activity of the compounds was evaluated. Various electronic and energetic descriptors such as high occupied molecular orbital and low unoccupied molecular orbital energy gaps, bonding dissociation enthalpy of OH bond, ionization potential, electron affinity, hardness, softness, and spin density of the radical and neutral species were calculated. DFT calculations with B3LYP hybrid functional and 6-311++ G** basis set in the polarizable continuum model were utilized to obtain these descriptors. FINDINGS/RESULTS: Ascorbic acid showed the best DPPH scavenging activity. However, 4d and 4c showed promising antioxidant activity. The values of EHOMO for 4c and 4d were closer to zero, thus, they showed the best scavenging activities. The computational results were in accordance with the experimental ones. The energetic descriptors indicated that the sequential proton loss-electron transfer mechanism is preferred over other mechanisms. CONCLUSION AND IMPLICATION: Antioxidant activity of 4-[(Benzo[d]thiazol-2-ylimino) methyl]phenol derivatives confirmed by experimental and theoretical documents proves them as novel antioxidants against amyloid-ß based disease.

3D U-Net: A voxel-based method in binding site prediction of protein structure.

Binding site prediction for new proteins is important in structure-based drug design. The identified binding sites may be helpful in the development of treatments for new viral outbreaks in the world when there is no information available about their pockets with COVID-19 being a case in point. Identification of the pockets using computational methods, as an alternative method, has recently attracted much interest. In this study, the binding site prediction is viewed as a semantic segmentation problem. An improved 3D version of the U-Net model based on the dice loss function is utilized to predict the binding sites accurately. The performance of the proposed model on the independent test datasets and SARS-COV-2 shows the segmentation model could predict the binding sites with a more accurate shape than the recently published deep learning model, i.e. DeepSite. Therefore, the model may help predict the binding sites of proteins and could be used in drug design for novel proteins.

Synthesis, Molecular Docking and Molecular Dynamics Simulation of 2- Thioxothiazolidin-4-One Derivatives against Gp41.

INTRODUCTION: Gp41 and its conserved hydrophobic groove on the N-terminal heptad repeat region are attractive targets in the design of HIV-1 entry inhibitors. Linearly extended molecules have shown potent anti-HIV-1 activity for their effective interactions with the gp41 binding pocket. Rhodanine ring attached to substituted pyrrole or furan rings has been proved a preferred moiety to be inserted inside the molecular structure of the gp41 inhibitors. OBJECTIVES: Based on the previous findings we are going to describe some rhodanine derivatives in which a substituted imidazole ring is introduced in place of the pyrrole or furan rings. The compounds' flexibility is increased by inserting methylene groups inside the main scaffold. METHODS: Molecular docking and molecular dynamics simulations approaches were exploited to investigate the chemical interactions and the stability of the designed ligands-gp41 complex. All compounds were synthesized and their chemical structures were elucidated by 1HNMR, 13CNMR, FTIR and Mass spectroscopy. Biological activities of the compounds against HIV-1 and HIV-2 and their cellular toxicities against the T-lymphocyte (MT-4) cell line were determined. RESULTS: All the designed compounds showed proper and stable chemical interactions with gp41 according to the in silico studies. The results of the biological tests proved none of the compounds active against HIV-1 replication in cell cultures. CONCLUSION: Since all the studied compounds were potently toxic for the host cell; it was therefore not possible to assess their anti-HIV activities.

MTX-Loaded Dual Thermoresponsive and pH-Responsive Magnetic Hydrogel Nanocomposite Particles for Combined Controlled Drug Delivery and Hyperthermia Therapy of Cancer.

In recent years, the exploitation of magnetic nanoparticles in smart polymeric matrices have received increased attention in several fields as site-specific drug delivery systems. Here, ultrasonic-assisted emulsion copolymerization of N-isopropylacrylamide (NIPAM) and 2-(N,N-diethylaminoethyl) methacrylate (DEAEMA) in the presence of Fe3O4 nanoparticles was employed to prepare pH- and temperature-responsive magnetite nanocomposite particles (MNCPs). The obtained MNCPs were fully characterized by TEM, DSC, FT-IR, VSM, and XRD techniques. They had an average particle size of 70 nm with a lower critical solution temperature of 42 °C and superparamagnetic properties. In addition, MNCPs were loaded with methotrexate (MTX) as an anticancer drug, and their in vitro drug release was studied in different pH values and temperatures and in the presence of an alternating magnetic field. Noteworthy that the highest rate of MTX release was observed at pH 5.5 and 42 °C. Cell viability of the treated MCF-7 human breast cancer cell line with free MTX, MNCPs, and MTX-loaded MNCPs or in combination with magnetic hyperthermia (MHT) and water-based hyperthermia was comparatively studied. The obtained results showed about 17% higher antiproliferative activity for the MTX-loaded MNCPs accompanied by MHT relative to that of free MTX.

Protein kinase inhibitors' classification using K-Nearest neighbor algorithm.

Protein kinases are enzymes acting as a source of phosphate through ATP to regulate protein biological activities by phosphorylating groups of specific amino acids. For that reason, inhibiting protein kinases with an active small molecule plays a significant role in cancer treatment. To achieve this aim, computational drug design, especially QSAR model, is one of the best economical approaches to reduce time and save in costs. In this respect, active inhibitors are attempted to be distinguished from inactive ones using hybrid QSAR model. Therefore, genetic algorithm and K-Nearest Neighbor method were suggested as a dimensional reduction and classification model, respectively. Finally, to evaluate the proposed model's performance, support vector machine and Naïve Bayesian algorithm were examined. The outputs of the proposed model demonstrated significant superiority to other QSAR models.

Alternating Magnetic Field and Ultrasound Waves as Size Controlling Parameters in Preparation of Superparamagnetic Fe3O4 Nanoparticles.

Magnetic nanoparticles have been studied extensively owing to their widespread applications. Here, a novel and simple co-precipitation method is introduced in the presence of an external alternating magnetic field along with ultrasound waves for the synthesis of uniform magnetite (Fe3O4) nanoparticles with an average particle size of below 10 nm, the results of which were compared further. These agitating probes were employed to induce nucleation process of Fe3O4 nanoparticles resulting in creation of such particles with remarkable magnetic properties. These were assessed by XRD, TEM, vibrating sample magnetometer (VSM), AFM, and magnetic force microscopy (MFM) analyses. XRD patterns revealed the spinel phase of the obtained magnetite. The size and morphology of the nanoparticles were determined by AFM, TEM, and HR-TEM. The results indicated efficient control over size distribution in such new processes. The magnetic properties of the prepared Fe3O4 nanoparticles were characterized by MFM and VSM, demonstrating their superparamagnetic behavior. They showed saturation magnetization ranging from 57.4 to 79.4 emu/g with coercivity of 11.9 to 12.55 Oe, depending on the applied procedure.

Molecular dynamics simulation and 3D-pharmacophore analysis of new quinoline-based analogues with dual potential against EGFR and VEGFR-2.

Epidermal growth factor and vascular endothelial growth factor-2 are important targets of tyrosine kinase for the treatment of various cancerous diseases. Combination of inhibition of both targets to produce synergy in the signal pathway is a critical approach to identify novel tyrosine kinase inhibitors. In this study, a series of new compounds derived from the 4-aminoquinoline as dual inhibitors were synthesized. The obtained results of cytotoxicity assay against human carcinoma cell lines indicated 0.8 µM for 4c against A549 showing its high efficiency in comparison to erlotinib. Pharmacophore modeling as a structure-based method was investigated on dual inhibitors and 4c which was compared with co-crystallized in the active site of EGFR and VEGFR-2. They have shown the same binding orientation as vandetanib, erlotinib and sorafenib. Molecular dynamics simulation results approved that Met769, Lys721, Asp1046, and Lys868 are key residues in two binding sites for dual activity. Ala1050 and Pro968 were identified as new amino acid interaction sites for dual inhibition. 4c showed more favorable stability than vandetanib in VEGFR-2 receptor for a 50 ns dynamic simulation. The high correlation between essential pharmacophoric features of designed compounds and lead inhibitors interactions provided a deeper insight into the structural basis of 4-aminoquinoline inhibition.

Synthesis and evaluation of antioxidant activity of some novel hydroxypyridinone derivatives: a DFT approach for explanation of their radical scavenging activity.

BACKGROUND AND PURPOSE: Reactive oxygen species (ROSs) are continuously produced as byproducts of cell metabolism. Free radicals are an unstable form of ROSs with the tendency to react readily with biomolecules such as amino acids, lipids and DNA. These reactions lead to oxidative damages to the cell. Oxidative stress occurs when the concentration of the ROSs exceeds the capacity of antioxidative protection systems of the body. 5-Hydroxypyridin-4-one derivatives can chelate Fe2+ and Fe3+ due to their α-hydroxyketone moiety. Also, tautomerism in hydroxypyridinone ring leads to enough level of aromaticity resulting in a catechol-like behavior that provides them with good chelating and radical scavenging properties. EXPERIMENTAL APPROACH: Different compounds were synthesized with 5-hydroxypyridine-4-one moiety as the core. The antioxidant properties of molecules were evaluated experimentally by DPPH scavenging method and theoretically using DFT/B3LYP with a 6-31++G (d,p) basis set. Electronic properties were investigated using frontier molecular orbital theory calculations. Furthermore, global descriptive parameters were obtained to find the chemical reactivity of molecules. The natural bond orbital analysis was performed to investigate charge distribution and hydrogen bonding. FINDINGS/RESULTS: Structures of the synthesized compounds were confirmed using IR, 1H-NMR, and 13C-NMR spectral analyses. Among all the synthesized compounds, Va and Vb showed the best antioxidant effect experimentally and computationally. CONCLUSION AND IMPLICATIONS: Results of this study were valuable in terms of synthesis, in silico, and in vitro antioxidant evaluations and can be useful for future investigations about the design of novel 5-hydroxypyridin- 4-one derivatives possessing iron-chelating and radical scavenging abilities.

Pharmacophore Modeling, Synthesis, Scaffold Hopping and Biological ß- Hematin Inhibition Interaction Studies for Anti-malaria Compounds.

Backgound: Exploring potent compounds is critical to generating multi-target drug discovery. Hematin crystallization is an important mechanism of malaria. METHODS: A series of chloroquine analogues were designed using a repositioning approach to develop new anticancer compounds. Protein-ligand interaction fingerprints and ADMET descriptors were used to assess docking performance in virtual screenings to design chloroquine hybrid ß-hematin inhibitors. A PLS algorithm was applied to correlate the molecular descriptors to IC50 values. The modeling presented excellent predictive power with correlation coefficients for calibration and cross-validation of r2 = 0.93 and q2 = 0.72. Using the model, a series of 4-aminoquinlin hybrids were synthesized and evaluated for their biological activity as an external test series. These compounds were evaluated for cytotoxic cell lines and ß-hematin inhibition. RESULTS: The target compounds exhibited high ß-hematin inhibition activity and were 3-9 times more active than the positive control. Furthermore, all the compounds exhibited moderate to high cytotoxic activity. The most potent compound in the dataset was docked with hemoglobin and its pharmacophore features were generated. These features were used as input to the Pharmit server for screening of six databases. CONCLUSION: The compound with the best score from ChEMBL was 2016904, previously reported as a VEGFR-2 inhibitor. The 11 compounds selected presented the best Gold scores with drug-like properties and can be used for drug development.