Combinatorial Chemistry & High Throughput Screening - Volume 21, Issue 5, 2018

Aim and Objective: Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. Materials and Methods: We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. Results: These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Conclusion: Machine learning combined with molecular docking can help to predict ADRs for drug molecules and provide possible explanations for the ADR mechanisms.

Aim and Objective: Chromene derivatives are privileged heterocyclic systems that exhibit various types of biological properties such as antioxidant, anticancer, antimicrobial, hypotensive, and local anesthetic. Cadmium sulfide nanoparticles (CdS NPs) as an efficient heterogeneous catalyst is used in various organic transformations because of its certain unique and unusual physico-chemical properties. The effectiveness of catalytic activity of CdS NPs can be improved due to the combined effect of Ag particles. Results: Ag/CdS nanocomposite is a readily available, recyclable, and non-toxic catalyst used for the highly efficient synthesis of novel 8-aryl-8H-[1,3]dioxolo[4,5-g]chromrne-6-carboxylic acids. This reaction is conveniently performed under mild reaction conditions. All synthesized compounds were well characterized by their satisfactory elemental analyses, IR, 1H and 13C NMR spectroscopy. The synthesized catalyst was fully characterized by XRD, SEM, and EDX techniques. Materials and Methods: The present methodology focuses on the condensation reaction of arylmethylidenepyruvic acids with 3,4-methylenedioxyphenol, using a catalytic amount of Ag/CdS nanocomposite (15 mol%) in aqueous media at room temperature to afford 8-aryl-8H-[1,3]dioxolo [4,5-g]chromrne-6-carboxylic acids in high yields (90-97%) within short reaction times (2-4 h). The Ag/CdS nanocomposite was also prepared by an ultrasonic-assisted sol-gel method. Conclusion: In conclusion, we have successfully synthesized novel 8-aryl-8H-[1,3]dioxolo[4,5- g]chromrne-6-carboxylic acid derivatives by the Ag/CdS nanocomposite catalyzed cyclocondensation reaction of arylmethylidenepyruvic acids with 3,4-methylenedioxyphenol under mild reaction conditions. Environmentally benign procedure, high to excellent yields of products, simplicity of operation, and use of readily available and recyclable catalyst are the advantages of this new practical reaction.

Aim and Objective: Vitamin D3 (1,25(OH)2D3) is a biologically active metabolite and plays a wide variety of regulatory functions in human systems. Currently, several Vitamin D analogues have been synthesized and tested against VDR (Vitamin D Receptor). Electrostatic potential methods are greatly influence the structure-based drug discovery. In this study, ab inito (DFT, HF, LMP2) and semi-empirical (RM1, AM1, PM3, MNDO, MNDO/d) charges were examined on the basis of their concert in predicting the docking pose using Induced Fit Docking (IFD) and binding free energy calculations against the VDR. Materials and Methods: Initially, we applied ab initio and semi-empirical charges to the 38 vitamin D analogues. Further, the charged analogues have been docked in the VDR active site. We generated the structure-based 3D-QSAR from the docked conformation of vitamin D analogues. On the other hand, we performed pharmacophore-based 3D-QSAR. Results: The result shows that, AM1 is the good charge model for our study and AM1 charge based QSAR produced more accurate ligand poses. Furthermore, the hydroxyl group in the side chain of vitamin D analogues played an important role in the VDR antagonistic activity. Conclusion: Overall, we found that charge-based optimizations of ligands were out performed than the pharmacophore based QSAR model.

Aim and Objective: The importance of Chromeno[4,3-b]pyridines in bioactive compounds, highlighted the ongoing research on developing novel methods for the construction of this heterocyclic scaffold. Regarding the advantageous features of multi-component reactions in organic synthesis, we will try to synthesize pyridocoumarins through this method. Materials and Methods: Chromeno[4,3-b]pyridines were conveniently prepared from a threecomponent condensation reaction between 4-hydroxy coumarin, ammonia and ethyl 2,4-dioxo-4- arylbutanoates in refluxing n-propanol. The synthesized compounds were characterized by NMR, IR and Mass spectroscopy. Results: The reaction proceeded through an in situ formed 4-amino coumarin, affording eight new target compounds in good yields. Conclusion: This method introduce a novel approach to ethyl 4-aryl-5-oxo-5H-chromeno[4,3- b]pyridine-2-carboxylate derivatives and allow organic chemists to prepare 4-aminocoumarin in reaction medium.

Aim and Objective: In chemistry, there is a long tradition in classification. Usually, methods are adopted from the wide field of cluster analysis. The present study focusses on the application of partial ordering methodology for the classification of 21 alkyl substituted anilines. Materials and Methods: The analyses are based on the concepts from partial order methodology and cluster analyses. Here, with the example of 21 alkyl anilines, we show that concepts taken out from the mathematical discipline of partially ordered sets may be applied for classification. The chemical compounds are described by a multi-indicator system. For the present study four indicators, mainly taken from the field of environmental chemistry were applied and a graph of the ordering (Hasse diagram) was constructed. Results: A Hasse diagram is an acyclic, transitively reduced, triangle-free graph that may have several graph-theoretical components. The Hasse diagram has been directed from a structural chemical point of view. Two cluster analysis methods are applied (K-means and a hierarchical cluster method) and compared with the results from the Hasse diagram. In both cases, the partitioning of the set of 21 compounds by the component structure of the Hasse diagram appears to be better interpretable. Conclusion: It is shown that the partial ordering approach indeed can be used for classification in the present case. However, it must be clearly stated that a guarantee for meaningful results, in general, cannot be given. For that, further theoretical work is needed.

Background: The acetylated inclusions containing TDP-43 are found in the spinal cord of amyotrophic lateral sclerosis (ALS) patients, suggesting that aberrant TDP-43 acetylation and resulting disruption of RNA binding are linked to onset and progression of TDP-43 proteinopathy. Methods: Here, the consequences of TDP-43 acetylation at Lys145 within the RRM1 domain and Lys192 within the RRM2 domain were studied using experimentally verifiable molecular models, in which lysine residues (K) were substituted with glutamine (Q) as an acetylation mimic (K→Q) and with arginine (R) as a non-mimic (K→R) mutant. We used a series of computer simulations to characterize the impact of lysine acetylation on TDP-43 function and TDP-43 association with target RNA. Results: Using snapshots collected from the MD simulation trajectories, the cross-correlation and principal component analyses (PCA) were applied to shed light on the dynamic discrepancy among the ten studied systems and to discern TDP-43 subdomains that exhibit conformational plasticity in response to acetylation mimic and non-mimic mutations. Moreover, we also investigated the global network parameter, betweenness, to model communication pathways and identify a network of critical mediating nodes involved in long-range signaling. These nodes describe the functionally significant TDP-43 residues involved in TDP-43 regulation. Conclusion: The identification of the critical nodes and optimal path mediating the dynamical network communication could offer new strategies to manipulate TDP-43 function. Disrupting a specific network communication could represent a rational approach to the design of drugs with improved potency and selectivity.

Background: The interindividual genetic variations in drug metabolizing enzymes effects the impact and toxicity in plenty of drugs. Objective: CYP1A2, CYP2C9, CYP2C19 and CYP2D6 gene polymorphisms were characterized using high resolution melting analysis (HRMA) in follow-up patients in psychiatry clinic as a preliminary preparation for personalized medicine. Method: Genotyping of CYP1A2*1F, CYP2C9 *2, *3, CYP2C19 *2, *3 and *17 and CYP2D6 *3, *4 was conducted in 101 patients using HRMA. Genotype and allele frequencies of the CYP variants were found to be in equilibrium with the Hardy-Weinberg equation. Results: The frequency of the CYP1A2*1F allele in schizophrenia and bipolar disease was 0.694 and 0.255, respectively. The CYP2C9 allele frequencies were 0.087 (CYP2C9*2), and 0.549 (CYP2C9*3) for bipolar; 0.278 (CYP2C9*2) and 0.648 (CYP2C9*3) in schizophrenias. The CYP2C19*2 and *17 allele frequencies was 0.111 and 0.185 in schizophrenia and variant *2 was 0.117 and variant *17 was 0.255 in bipolar group. The frequency of the CYP2D6*3 allele was 0.027 in schizophrenias. The frequencies for the CYP2D6*4 variant were 0.092 and 0.096 in schizophrenia and bipolar groups, respectively. Conclusion: The knowledge in pharmacogenomic and also the developments in molecular genetics are growing rapidly. In future, this can be expected to provide new methodologies in the prediction of the activity in drug metabolizing enzymes. The HRMA is a rapid and useful technique to identify the genotypes for drug dosage adjustment before therapy in psychiatry patients.

Aim and Objective: Human dihydroorotate dehydrogenase (DHODH) catalyzes the fourth stage of the biosynthesis of pyrimidines in cells. Hence it is important to identify suitable inhibitors of DHODH to prevent virus replication. In this study, a quantitative structure-activity relationship was performed to predict the activity of one group of newly synthesized halogenated pyrimidine derivatives as inhibitors of DHODH. Materials and Methods: Molecular structures of halogenated pyrimidine derivatives were drawn in the HyperChem and then molecular descriptors were calculated by DRAGON software. Finally, the most effective descriptors for 32 halogenated pyrimidine derivatives were selected using bee algorithm. Results: The selected descriptors using bee algorithm were applied for modeling. The mean relative error and correlation coefficient were obtained as 2.86% and 0.9627, respectively, while these amounts for the leave one out−cross validation method were calculated as 4.18% and 0.9297, respectively. The external validation was also conducted using two training and test sets. The correlation coefficients for the training and test sets were obtained as 0.9596 and 0.9185, respectively. Conclusion: The results of modeling of present work showed that bee algorithm has good performance for variable selection in QSAR studies and its results were better than the constructed model with the selected descriptors using the genetic algorithm method.