A SAR and QSAR study of new artemisinin compounds with antimalarial activity

Identification of Potential New Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl Piperidine Derivatives: A Bioinformatics Approach

Aedes aegypti mosquitoes transmit several human pathogens that cause millions of deaths worldwide, mainly in Latin America. The indiscriminate use of insecticides has resulted in the development of species resistance to some such compounds. Piperidine, a natural alkaloid isolated from Piper nigrum, has been used as a hit compound due to its larvicidal activity against Aedes aegypti. In the present study, piperidine derivatives were studied through in silico methods: pharmacophoric evaluation (PharmaGist), pharmacophoric virtual screening (Pharmit), ADME/Tox prediction (Preadmet/Derek 10.0^®), docking calculations (AutoDock 4.2) and molecular dynamics (MD) simulation on GROMACS-5.1.4. MP-416 and MP-073 molecules exhibiting ΔG binding (MMPBSA −265.95 ± 1.32 kJ/mol and −124.412 ± 1.08 kJ/mol, respectively) and comparable to holo (ΔG binding = −216.21 ± 0.97) and pyriproxyfen (a well-known larvicidal, ΔG binding= −435.95 ± 2.06 kJ/mol). Considering future in vivo assays, we elaborated the theoretical synthetic route and made predictions of the synthetic accessibility (SA) (SwissADME), lipophilicity and water solubility (SwissADME) of the promising compounds identified in the present study. Our in silico results show that MP-416 and MP-073 molecules could be potent insecticides against the Aedes aegypti mosquitoes.

Targeting the Ubiquinol-Reduction (Qi) Site of the Mitochondrial Cytochrome bc1 Complex for the Development of Next Generation Quinolone Antimalarials

Antimalarials targeting the ubiquinol-oxidation (Q_o) site of the Plasmodium falciparum bc₁ complex, such as atovaquone, have become less effective due to the rapid emergence of resistance linked to point mutations in the Q_o site. Recent findings showed a series of 2-aryl quinolones mediate inhibitions of this complex by binding to the ubiquinone-reduction (Qi) site, which offers a potential advantage in circumventing drug resistance. Since it is essential to understand how 2-aryl quinolone lead compounds bind within the Qi site, here we describe the co-crystallization and structure elucidation of the bovine cytochrome bc₁ complex with three different antimalarial 4(1H)-quinolone sub-types, including two 2-aryl quinolone derivatives and a 3-aryl quinolone analogue for comparison. Currently, no structural information is available for Plasmodial cytochrome bc₁. Our crystallographic studies have enabled comparison of an in-silico homology docking model of P. falciparum with the mammalian's equivalent, enabling an examination of how binding compares for the 2- versus 3-aryl analogues. Based on crystallographic and computational modeling, key differences in human and P. falciparum Q_i sites have been mapped that provide new insights that can be exploited for the development of next-generation antimalarials with greater selective inhibitory activity against the parasite bc₁ with improved antimalarial properties.

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.

Systematic review on the application of machine learning to quantitative structure-activity relationship modeling against Plasmodium falciparum

Malaria accounts for over two million deaths globally. To flatten this curve, there is a need to develop new and high potent drugs against Plasmodium falciparum. Some major challenges include the dearth of suitable animal models for anti-P. falciparum assays, resistance to first-line drugs, lack of vaccines and the complex life cycle of Plasmodium. Gladly, newer approaches to antimalarial drug discovery have emerged due to the release of large datasets by pharmaceutical companies. This review provides insights into these new approaches to drug discovery covering different machine learning tools, which enhance the development of new compounds. It provides a systematic review on the use and prospects of machine learning in predicting, classifying and clustering IC₅₀ values of bioactive compounds against P. falciparum. The authors identified many machine learning tools yet to be applied for this purpose. However, Random Forest and Support Vector Machines have been extensively applied though on a limited dataset of compounds.

Ganoderma lucidum (Reishi) an edible mushroom; a comprehensive and critical review of its nutritional, cosmeceutical, mycochemical, pharmacological, clinical, and toxicological properties

Reishi owes an exceptional value in nutritional, cosmeceutical, and medical treatments; however, none of the studies has provided its future-driven critical assessment. This study documents an up-to-date review (2015-2020, wherever applicable) and provide valuable insights (preclinical and clinical evidence-based) with comprehensive and critical assessments. Various databases 'Google scholar', 'Web of Science', 'ScienceDirect', 'PubMed', 'Springer Link', books, theses, and library resources were used. The taxonomic chaos of G. lucidum and its related species was discussed in detail with solution-oriented emphasis. Reishi contains polysaccharides (α/β-D-glucans), alkaloids, triterpenoids (ganoderic acids, ganoderenic acids, ganoderol, ganoderiol, lucidenic acids), sterols/ergosterol, proteins (LZ-8, LZ-9), nucleosides (adenosine, inosine, uridine), and nucleotides (guanine, adenine). Some active drugs are explored at an optimum level to make them potential drug candidates. The pharmacological potential was observed in diabetes, inflammation, epilepsy, neurodegeneration, cancer, anxiety, sedation, cardiac diseases, depression, hepatic diseases, and immune disorders; however, most of the studies are preclinical with a number of drawbacks. In particular, quality clinical data are intensely needed to support pharmacological activities for human use. The presence of numerous micro-, macro, and trace elements imparts an essential nutritional and cosmeceutical value to Reishi, and various marketed products are available already, but the clinical studies regarding safety and efficacy, interactions with foods/drinks, chronic use, teratogenicity, mutagenicity, and genotoxicity are missing for Reishi. Reishi possesses many valuable pharmacological activities, and the number of patents and clinical trials is increasing for Reishi. Yet, a gap in research exists for Reishi, which is discussed in detail in the forthcoming sections.

Structure-Activity Relationships of the Antimalarial Agent Artemisinin 10. Synthesis and Antimalarial Activity of Enantiomers of rac-5β-Hydroxy-d-Secoartemisinin and Analogs: Implications Regarding the Mechanism of Action

An efficient synthesis of rac-6-desmethyl-5β–hydroxy-d-secoartemisinin 2, a tricyclic analog of R-(+)-artemisinin 1, was accomplished and the racemate was resolved into the (+)-2b and (−)-2a enantiomers via their Mosher Ester diastereomers. Antimalarial activity resided with only the artemisinin-like enantiomer R-(−)-2a. Several new compounds 9–16, 19a, 19b, 22 and 29 were synthesized from rac-2 but the C-5 secondary hydroxyl group was surprisingly unreactive. For example, the formation of carbamates and Mitsunobu reactions were unsuccessful. In order to assess the unusual reactivity of 2, a single crystal X-ray crystallographic analysis revealed a close intramolecular hydrogen bond from the C-5 alcohol to the oxepane ether oxygen (O-11). All products were tested in vitro against the W-2 and D-6 strains of Plasmodium falciparum. Several of the analogs had moderate activity in comparison to the natural product 1. Iron (II) bromide-promoted rearrangement of 2 gave, in 50% yield, the ring-contracted tetrahydrofuran 22, while the 5-ketone 15 provided a monocyclic methyl ketone 29 (50%). Neither 22 nor 29 possessed in vitro antimalarial activity. These results have implications in regard to the antimalarial mechanism of action of artemisinin.

Application of QSAR Method in the Design of Enhanced Antimalarial Derivatives of Azetidine-2-carbonitriles, their Molecular Docking, Drug-likeness, and SwissADME Properties

The resistance of the P. falciparum strain to some of the antimalarial drugs has been a dominant dilemma facing the treatment of this fetid disease. This necessitates the detection and development of new antimalarial agents targeting the P. falciparum. Azetidine-2-carbonitriles reported for its antimalarial activities, could provide an alternative to the customized antimalarial drugs. Leading to the use of quantitative structure-activity relationship (QSAR) studies, which relates the structures of Azetidine-2-carbonitriles with their activities to generate predictive models. The structures were optimized using density functional theory (DFT) DFT/B3LYP/6-31G* basis set to generate their molecular descriptors, where five predictive models were constructed using the generated descriptors. The models were constructed using the genetic function algorithm component of a material studio, where the model with good statistical parameters, high coefficient of determination (R2) = 0.9465, cross-validated R2 (Q2cv) = 0.8981, Q2 (L4O)cv = 0.9272, and highest external validated R2 (R2 pred) = 0.6915 was selected as the best model. These statistical results show the robustness, excellent power of prediction, and validity of the selected model. The descriptor, SpMax2_Bhp (the maximum absolute eigenvalue of Barysz matrix for n = 2 was weighted by polarizability), was revealed to be the most influential in the model due to its highest mean effect. The descriptor played a role in the design of sixteen (16) theoretical derivatives of Azetidine-2-carbonitriles using compound 25 as the design template by increasing polarizability of the compounds through substitution of the various group with electron deactivating groups (F, I, Cl, SO3H, CN, NO2, etc.) at different position of the template. The designed compounds were docked with Plasmodium falciparum dihydroorotate dehydrogenase (Pf-DHODH), giving compound D9 the highest binding energy. The designed compounds were further screened for their drug-likeness, where they all pass Lipinski's RO5. All the compounds show good skin permeability coefficient and have low Gastrointestinal absorption while few compounds D1, D2, D3, D14, and D15 inhibiting the CYP1A2.

Theoretical design of novel antimalarial agents against P. falciparum strain, Dd2 through the QSAR modeling of synthesized 2'-substituted triclosan derivatives

In an attempt to design compounds with higher antimalarial activities, quantitative structure-activity relationship (QSAR) technique was utilized in the development of a molecular model for some synthesized 2′-substituted triclosan derivatives through a hybrid of the GA-MLR method. The model was found to have excellent statistical parameters (R² = 0.8919, R²_Adj = 0.8728, LOF = 0.2563). The descriptors mean effect (MF) revealed BCUTw-1l, which increases with an increase in molecular weight, to be the most contributive to the antimalarial activity. Consequently, compound 3, with the highest activities (pEC₅₀ = 6.9586) was deployed as the design template. The molecular weight of the template was increasing through substitutions of its atoms at several positions with heavier atoms/groups to increases the descriptor (BCUTw-1l) value. Twelves (12) theoretical derivatives of the template were designed where six of the designed derivatives have better activity than the design template. The most active designed compound, 3L was found to have the highest antimalarial activity (pEC₅₀ = 7.930) than that of the design template.

QSAR modelling of larvicidal phytocompounds against Aedes aegypti using index of ideality of correlation

Aedes aegypti is the primary vector of several infectious viruses that cause yellow, dengue, chikungunya, and Zika fevers. Recently, plant-derived products have been tested as safe and eco-friendly larvicides against Ae. aegypti. The present study aimed to improve QSAR models for 62 larvicidal phytocompounds against Ae. aegypti via the Monte Carlo method based on the index of the ideality of correlation (IIC) criterion. The representation of structures was done with SMILES. Three splits were prepared randomly and three QSAR models were constructed using IIC target function. The molecular descriptors were selected from SMILES descriptors and the hydrogen-filled molecular graphs. The predictability of three models was evaluated on the validation sets, the r ² of which was 0.9770, 0.8660, and 0.8565 for models 1 to 3, respectively. The statistical results of three randomized splits indicated that robust, simple, predictive, and reliable models were obtained for different sets. From the modelling results, important descriptors were identified to enhance and reduce the larvicidal activity of compounds. Based on the identified important descriptors, some new structures of larvicidal compounds were proposed. The larvicidal activity of novel molecules designed further was supported by docking studies. Using the simple QSAR model, one can predict pLC₅₀ of new similarity larvicidal phytocompounds.

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.

Theoretical Study of Monoamine Oxidase B Inhibitors as Drug Candidates for Treatment of Parkinson's Disease

BACKGROUND

Drugs used for Parkinson's disease (PD) are mainly responsible for only relieving major symptoms, but may present several side effects that are typical of such pharmacological treatment.

METHODS

This study aimed to use in silico methods for drug designing inhibitors of the PD therapeutic target, monoamine oxidase B (MAO-B). Thus, 20 MAO-B inhibitors from the BindingDB database were selected followed by a calculation of their descriptors at DFT B3LYP/6-31G** level of theory.

RESULTS

Statistical analysis considering a Pearson correlation matrix led to the selection of electrophilicity index as a descriptor related to the biological activity of inhibitors. Furthermore, based on the prediction of suitable ADME/Tox properties, the molecule CID 54583085 was selected as a template to carry out structural modifications to obtain 3 analogues, whereas molecules B and C showed significant improvement in mutagenicity and carcinogenicity, in relation to the template.

CONCLUSION

Thus, it is concluded that the proposed modifications led us to satisfactory results, since there was an improvement in the toxicological properties of molecules, however, further studies must be carried out to evaluate their biological activities as possible MAO-B inhibitors for PD treatment.

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.

Antioxidant Effect of Flavonoids Present in Euterpe oleracea Martius and Neurodegenerative Diseases: A Literature Review

INTRODUCTION

Neurodegenerative diseases (NDDs) are progressive, directly affecting the central nervous system (CNS), the most common and recurrent are Alzheimer's disease (AD) and Parkinson's disease (PD). One factor frequently mentioned in the etiology of NDDs is the generation of free radicals and oxidative stress, producing cellular damages. Studies have shown that the consumption of foods rich in polyphenols, especially those of the flavonoid class, has been related to the low risk in the development of several diseases. Due to the antioxidant properties present in the food, a fruit that has been gaining prominence among these foods is the Euterpe oleracea Mart. (açaí), because it presents in its composition significant amounts of a subclass of the flavonoids, the anthocyanins.

METHODS

In the case review, the authors receive a basic background on the most common NDDs, oxidative stress and antioxidants. In addition, revisiting the various studies related to NDDs, including flavonoids and consumption of açaí.

RESULTS

Detailed analysis of the recently reported case studies reveal that dietary consumption of flavonoid-rich foods, such as açaí fruits, suggests the efficacy to attenuate neurodegeneration and prevent or reverse the age-dependent deterioration of cognitive function.

CONCLUSION

This systematic review points out that flavonoids presenting in açaí have the potential for the treatment of diseases such as PD and AD and are candidates for drugs in future clinical research. However, there is a need for in vitro and in vivo studies with polyphenol that prove and ratify the therapeutic potential of this fruit for several NDDs.

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.

Structure activity relationship (SAR) and quantitative structure activity relationship (QSAR) studies showed plant flavonoids as potential inhibitors of dengue NS2B-NS3 protease

Background

Due to dengue virus disease, half of the world population is at severe health risk. Viral encoded NS2B-NS3 protease complex causes cleavage in the nonstructural region of the viral polyprotein. The cleavage is essentially required for fully functional viral protein. It has already been reported that if function of NS2B-NS3 complex is disrupted, viral replication is inhibited. Therefore, the NS2B-NS3 is a well-characterized target for designing antiviral drug.

Results

In this study docking analysis was performed with active site of dengue NS2B-NS3 protein with selected plant flavonoids. More than 100 flavonoids were used for docking analysis. On the basis of docking results 10 flavonoids might be considered as the best inhibitors of NS2B-NS3 protein. The interaction studies showed resilient interactions between ligand and receptor atoms. Furthermore, QSAR and SAR studies were conducted on the basis of NS2B-NS3 protease complex docking results. The value of correlation coefficient (r) 0.95 shows that there was a good correlation between flavonoid structures and selected properties.

Conclusion

We hereby suggest that plant flavonoids could be used as potent inhibitors of dengue NS2B-NS3 protein and can be used as antiviral agents against dengue virus. Out of more than hundred plant flavonoids, ten flavonoid structures are presented in this study. On the basis of best docking results, QSAR and SAR studies were performed. These flavonoids can directly work as anti-dengue drug or with little modifications in their structures.

Episodic and electrical nervous system disorders caused by nonchannel genes

As noted in the separate introduction to this special topic section, episodic and electrical disorders can appear quite different clinically and yet share many overlapping features, including attack precipitants, therapeutic responses, natural history, and the types of genes that cause many of the genetic forms (i.e., ion channel genes). Thus, as we mapped and attempted to clone genes causing other episodic disorders, ion channels were always outstanding candidates when they mapped to the critical region of linkage in such a family. However, some of these disorders do not result from mutations in channels. This realization has opened up large and exciting new areas for the pathogenesis of these disorders. In some cases, the mutations occur in genes of unknown function or without understanding of molecular pathogenesis. Recently, emerging insights into a fascinating group of episodic movement disorders, the paroxysmal dyskinesias, and study of the causative genes and proteins are leading to the emerging concept of episodic electric disorders resulting from synaptic dysfunction. Much work remains to be done, but the field is evolving rapidly. As it does, we have come to realize that the molecular pathogenesis of electrical and episodic disorders is more complex than a scenario in which such disorders are simply due to mutations in the primary determinants of membrane excitability (channels).

A QSAR, pharmacokinetic and toxicological study of new artemisinin compounds with anticancer activity

The Density Functional Theory (DFT) method and the 6-31G** basis set were employed to calculate the molecular properties of artemisinin and 20 derivatives with different degrees of cytotoxicity against the human hepatocellular carcinoma HepG2 line. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to select the most important descriptors related to anticancer activity. The significant molecular descriptors related to the compounds with anticancer activity were the ALOGPS_log, Mor29m, IC5 and GAP energy. The Pearson correlation between activity and most important descriptors were used for the regression partial least squares (PLS) and principal component regression (PCR) models built. The regression PLS and PCR were very close, with variation between PLS and PCR of R² = ±0.0106, R²_ajust = ±0.0125, s = ±0.0234, F_(4,11) = ±12.7802, Q² = ±0.0088, SEV = ±0.0132, PRESS = ±0.4808 and S_PRESS = ±0.0057. These models were used to predict the anticancer activity of eight new artemisinin compounds (test set) with unknown activity, and for these new compounds were predicted pharmacokinetic properties: human intestinal absorption (HIA), cellular permeability (P_CaCO2), cell permeability Maden Darby Canine Kidney (P_MDCK), skin permeability (P_Skin), plasma protein binding (PPB) and penetration of the blood-brain barrier (C_Brain/Blood), and toxicological: mutagenicity and carcinogenicity. The test set showed for two new artemisinin compounds satisfactory results for anticancer activity and pharmacokinetic and toxicological properties. Consequently, further studies need be done to evaluate the different proposals as well as their actions, toxicity, and potential use for treatment of cancers.