A new preprocessing procedure in the analysis of cardiac RR interval time series is described. It uses the singular spectrum analysis (SSA) and the Monte Carlo SSA (MCSSA) test. A novel feature of this preprocessing procedure is the ability to identify the noise component present in the series with a given probability and to separate the time series into a trend, signal, and noise. The MCSSA test involves testing whether the modes obtained from SSA can be generated by a noise process leading to separation of the noise modes from the signal. The procedure described here does not discard or modify any sample in the record but merely separates the time series into a trend, signal, and noise, allowing for further analysis of these components. The procedure is not limited to the length of the record and could be applied to nonstationary data. The basis functions used in SSA are data adaptive in that they are not chosen a priori but instead are dependent on the data set used, increasing flexibility to the analysis. The procedure is illustrated using the RR interval time series of a healthy, congestive heart failure, and atrial fibrillation subject.

R. A. Thuraisingham

Use of SSA and MCSSA in the Analysis of Cardiac RR Time Series

Arsenic contamination of ground water has become a global problem affecting specially, south-east Asian countries like Bangladesh and eastern parts of India. It also affects South America and some parts of the US. Different organs of the physiological system are affected due to contamination of inorganic arsenic in water. Animal studies with different chelators are not very conclusive as far as the multi/differential organ effect(s) of arsenic is concerned. Our docking study establishes the molecular rationale of blood test for early detection of arsenic toxicity; as arsenic has a high affinity to albumin, a plasma protein and actin, a structural protein of all cells including Red Blood Cells. This study also shows that there is a little possibility of male reproductive organs toxicity by different forms of inorganic arsenic; however, female reproductive system is very much susceptible to sodium-arsenite. Through comparative analysis regarding the chelating effectiveness among the available arsenic chelator drugs, meso-2,3 dimercaptosuccinic acid (DMSA) and in some cases lipoic acid is the most preferred choice of drug for removing of arsenic deposits. This computational method actually reinforces the clinical finding regarding DMSA as the most preferred drug in removal of arsenic deposits from majority of the human tissues.

Durjoy Majumder

Sayan Mukherjee

Molecular Docking Assessment of Efficacy of Different Clinically Used Arsenic Chelator Drugs

An elastic continuum mathematical model was implemented to study collective C8161 melanoma cell migration during a &#x201c;scratch wound&#x201d; assay, in control and under the influence of the proinflammatory cytokine tumour necrosis factor-alpha (TNF-&#x3b1;). The model has four constants: force that results from lamellipod formation (F), adhesion constant between cells and extracellular matrix (ECM) (b), cell layer elasticity modulus (k), and growth rate (&#x3c1;). A nonlinear regression routine was used to obtain the parameters of the model with data from an experiment made with C8161 melanoma cells, with and without TNF-&#x3b1;. Coefficient of determination for both situations was <svg style="vertical-align:-0.20474pt;width:65.1875px;" id="M1" height="16.1" version="1.1" viewBox="0 0 65.1875 16.1" width="65.1875" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg">
	
		
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</svg>, respectively. The parameters values obtained were similar to the ones found in the literature. However, the adhesion constant value decreased with the introduction of TNF-&#x3b1;, which is not in accordance with expected since the presence of TNF-&#x3b1; is associated with an increased expression of integrins that would promote an enhanced adhesion among cells. The model was used in a study relating to the adhesion constant and cell migration, and the results suggested that cell migration decreases with higher adhesion, which is also not in accordance with expected. These differences would not occur if it was considered that TNF-&#x3b1; increases the elasticity modulus of the cell layer.

Julia Vianna Gallinaro

Claudia Mirian de Godoy Marques

Fernando Mendes de Azevedo

Daniela Ota Hisayasu Suzuki

Mathematical Modeling of Melanoma Cell Migration with an Elastic Continuum Model for the Evaluation of the Influence of Tumor Necrosis Factor-Alpha on Migration

Cytochrome bc1 (EC 1.10.2.2, bc1) is an essential component of the cellular respiratory chain, which catalyzes electron transfer from quinol to cytochrome c and concomitantly the translocation of protons across the membrane. It has been identified as a promising target in malaria parasites. The structure-based pharmacophore modelling and molecular dynamic simulation approach have been employed to identify novel inhibitors of cytochrome bc1. The best structure-based pharmacophore hypothesis (Hypo1) consists of one hydrogen bond acceptor (HBA), one general hydrophobic (HY), and two hydrophobic aromatic features (HYAr). Further, hydrogen interactions and hydrophobic interactions of known potent inhibitors with cytochrome bc1 were compared with Hypo1, which showed that the Hypo1 has good predictive ability. The validated Hypo1 was used to screen the chemical databases. The hits obtained were subsequently subjected to the molecular docking analysis to identify false-positive hits. Moreover, the molecular docking results were further validated by molecular dynamics simulations. Binding-free energy analysis using MM-GBSA method reveals that the van der Waals interactions and the electrostatic energy provide the basis for favorable absolute free energy of the complex. The five virtual hits were identified as possible candidates for the designing of potent cytochrome bc1 inhibitors.

Rahul P. Gangwal

Gaurao V. Dhoke

Mangesh V. Damre

Kanchan Khandelwal

Abhay T. Sangamwar

Structure-Based Virtual Screening and Molecular Dynamic Simulation Studies to Identify Novel Cytochrome bc1 Inhibitors as Antimalarial Agents

Nuclear receptors (NRs) are important biological macromolecular transcription factors that are implicated in multiple biological pathways and may interact with other xenobiotics that are endocrine disruptors present in the environment. Examples of important NRs include the androgen receptor (AR), estrogen receptors (ER), and the pregnane X receptor (PXR). In this study we have utilized the Ligand Activity by Surface Similarity Order (LASSO) method, a ligand-based virtual screening strategy to derive structural (surface/shape) molecular features used to generate predictive models of biomolecular activity for AR, ER, and PXR. For PXR, twenty-five models were built using between 8 to 128 agonists and tested using 3000, 8000, and 24,000 drug-like decoys including PXR inactive compounds <svg style="vertical-align:-2.3205pt;width:70.650002px;" id="M1" height="15.0875" version="1.1" viewBox="0 0 70.650002 15.0875" width="70.650002" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg">
	
		
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</svg>. Preliminary studies with AR and ER using LASSO suggested the utility of this approach with 2-fold enrichment factors at 20&#x25;. We found that models with 64&#x2013;128 PXR actives provided enrichment factors of 10-fold (10&#x25; actives in the top 1&#x25; of compounds screened). The LASSO models for AR and ER have been deployed and are freely available online, and they represent a ligand-based prediction method for putative NR activity of compounds in this database.

Sean Ekins

Michael-R. Goldsmith

Aniko Simon

Zsolt Zsoldos

Orr Ravitz

Antony J. Williams

LASSO-ing Potential Nuclear Receptor Agonists and Antagonists: A New Computational Method for Database Screening

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&#x2019;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&#x2013;31&#x2009;G basis set. HyperChem, Gaussian 98&#x2009;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

Zinab Rastgoo

QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer&#x2019;s Disease

Activators of PPAR&#x3b3;, 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 PPAR&#x3b3; and its interactions with potential ligands maintain the importance of PPAR&#x3b3; 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 PPAR&#x3b3; 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 PPAR&#x3b3; at SER273 by ligands is reviewed as a new strategy to identify novel drug candidates.

Vaibhav A. Dixit

Prasad V. Bharatam

SAR and Computer-Aided Drug Design Approaches in the Discovery of Peroxisome Proliferator-Activated Receptor &#x3b3; Activators: A Perspective

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 &#x2212;7.13&#x2009;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

Naheed Akhtar

Molecular Docking Study on the Interaction of Riboflavin (Vitamin <svg style="vertical-align:-3.27605pt" height="15.25" version="1.1" viewBox="0 0 16.450001 15.25" width="16.450001" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,11.112)"><path id="x42" d="M372 352v-2q176 -27 176 -159q0 -99 -95 -151q-73 -40 -196 -40h-221v28q65 5 78.5 19t13.5 76v404q0 63 -12 77t-72 18v28h257q102 0 150 -34q26 -18 41 -48.5t15 -65.5q0 -111 -135 -150zM213 362h47q80 0 117.5 32t37.5 96q0 56 -33 92t-100 36q-41 0 -56 -10&#xA;q-13 -8 -13 -50v-196zM213 328v-203q0 -54 17 -72.5t66 -18.5q67 1 110.5 37t43.5 110q0 147 -192 147h-45z" /></g><g transform="matrix(.012,-0,0,-.012,10.062,15.187)"><path id="x32" d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z" /></g></svg>) and Cyanocobalamin (Vitamin <svg style="vertical-align:-3.27605pt" height="15.25" version="1.1" viewBox="0 0 22.1625 15.25" width="22.1625" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,11.112)"><use xlink:href="#x42"/></g><g transform="matrix(.012,-0,0,-.012,10.062,15.187)"><path id="x31" d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" /></g><g transform="matrix(.012,-0,0,-.012,15.774,15.187)"><use xlink:href="#x32"/></g></svg>) Coenzymes

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

Abdol Hamid Pilevar

Automatic Segmentation of Medical Images Using Fuzzy c-Means and the Genetic Algorithm

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Journal of Computational Medicine