http://www.hindawi.com The latest articles from Hindawi Publishing Corporation © 2013 , Hindawi Publishing Corporation . All rights reserved. Tue, 30 Apr 2013 08:48:33 +0000 http://www.hindawi.com/journals/jcm/2013/312728/ Sets of quinolizidinyl derivatives of bi- and tri-cyclic (hetero) aromatic systems were studied as selective inhibitors. On the pattern, quantitative structure-activity relationship (QSAR) study has been done on quinolizidinyl derivatives as potent inhibitors of acetylcholinesterase in alzheimer’s disease (AD). Multiple linear regression (MLR), partial least squares (PLSs), principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO) were used to create QSAR models. Geometry optimization of compounds was carried out by B3LYP method employing 6–31 G basis set. HyperChem, Gaussian 98 W, and Dragon software programs were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors. Finally, Unscrambler program was used for the analysis of data. In the present study, the root mean square error of the calibration and R2 using MLR method were obtained as 0.1434 and 0.95, respectively. Also, the R and R2 values were obtained as 0.79, 0.62 from stepwise MLR model. The R2 and mean square values using LASSO method were obtained as 0.766 and 3.226, respectively. The root mean square error of the calibration and R2 using PLS method were obtained as 0.3726 and 0.62, respectively. According to the obtained results, it was found that MLR model is the most favorable method in comparison with other statistical methods and is suitable for use in QSAR models. Ghasem Ghasemi, Sattar Arshadi, Alireza Nemati Rashtehroodi, Mahyar Nirouei, Shahab Shariati, and Zinab Rastgoo Copyright © 2013 Ghasem Ghasemi et al. All rights reserved. Thu, 04 Apr 2013 17:14:13 +0000 http://www.hindawi.com/journals/jcm/2013/406049/ Activators of PPARγ, Troglitazone (TGZ), Rosiglitazone (RGZ), and Pioglitazone (PGZ) were introduced for treatment of Type 2 diabetes, but TGZ and RGZ have been withdrawn from the market along with other promising leads due cardiovascular side effects and hepatotoxicity. However, the continuously improving understanding of the structure/function of PPARγ and its interactions with potential ligands maintain the importance of PPARγ as an antidiabetic target. Extensive structure activity relationship (SAR) studies have thus been performed on a variety of structural scaffolds by various research groups. Computer-aided drug discovery (CADD) approaches have also played a vital role in the search and optimization of potential lead compounds. This paper focuses on these approaches adopted for the discovery of PPARγ ligands for the treatment of Type 2 diabetes. Key concepts employed during the discovery phase, classification based on agonistic character, applications of various QSAR, pharmacophore mapping, virtual screening, molecular docking, and molecular dynamics studies are highlighted. Molecular level analysis of the dynamic nature of ligand-receptor interaction is presented for the future design of ligands with better potency and safety profiles. Recently identified mechanism of inhibition of phosphorylation of PPARγ at SER273 by ligands is reviewed as a new strategy to identify novel drug candidates. Vaibhav A. Dixit and Prasad V. Bharatam Copyright © 2013 Vaibhav A. Dixit and Prasad V. Bharatam. All rights reserved. Sun, 31 Mar 2013 13:49:22 +0000 http://www.hindawi.com/journals/jcm/2013/312183/ Cobalamins are the largest and structurally complex cofactors found in biological systems and have attracted considerable attention due to their participation in the metabolic reactions taking place in humans, animals, and microorganisms. Riboflavin (vitamin B2) is a micronutrient and is the precursor of coenzymes, FMN and FAD, required for a wide variety of cellular processes with a key role in energy-based metabolic reactions. As coenzymes of both vitamins are the part of enzyme systems, the possibility of their mutual interaction in the body cannot be overruled. A molecular docking study was conducted on riboflavin molecule with B12 coenzymes present in the enzymes glutamate mutase, diol dehydratase, and methionine synthase by using ArgusLab 4.0.1 software to understand the possible mode of interaction between these vitamins. The results from ArgusLab showed the best binding affinity of riboflavin with the enzyme glutamate mutase for which the calculated least binding energy has been found to be −7.13 kcal/mol. The results indicate a significant inhibitory effect of riboflavin on the catalysis of B12-dependent enzymes. This information can be utilized to design potent therapeutic drugs having structural similarity to that of riboflavin. Ambreen Hafeez, Zafar Saied Saify, Afshan Naz, Farzana Yasmin, and Naheed Akhtar Copyright © 2013 Ambreen Hafeez et al. All rights reserved. Sun, 03 Feb 2013 08:55:35 +0000 http://www.hindawi.com/journals/jcm/2013/972970/ Magnetic resonance imaging (MRI) segmentation is a complex issue. This paper proposes a new method for estimating the right number of segments and automatic segmentation of human normal and abnormal MR brain images. The purpose of automatic diagnosis of the segments is to find the number of divided image areas of an image according to its entropy and with correctly diagnose of the segment of an image also increased the precision of segmentation. Regarding the fact that guessing the number of image segments and the center of segments automatically requires algorithm test many states in order to solve this problem and to have a high accuracy, we used a combination of the genetic algorithm and the fuzzy c-means (FCM) method. In this method, it has been tried to change the FCM method as a fitness function for combination of it in genetic algorithm to do the image segmentation more accurately. Our experiment shows that the proposed method has a significant improvement in the accuracy of image segmentation in comparison to similar methods. Omid Jamshidi and Abdol Hamid Pilevar Copyright © 2013 Omid Jamshidi and Abdol Hamid Pilevar. All rights reserved.