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International Journal of Computational Biology and Drug Design

Didier Devaurs, Malvina Papanastasiou, Dinler A Antunes, Jayvee R Abella, Mark Moll, Daniel Ricklin, John D Lambris, Lydia E Kavraki
Hydrogen/deuterium exchange detected by mass spectrometry (HDXMS) provides valuable information on protein structure and dynamics. Although HDX-MS data is often interpreted using crystal structures, it was suggested that conformational ensembles produced by molecular dynamics simulations yield more accurate interpretations. In this paper, we analyse the complement protein C3d by performing an HDX-MS experiment, and evaluate several interpretation methodologies using an existing prediction model to derive HDX-MS data from protein structure...
2018: International Journal of Computational Biology and Drug Design
Yao Wang, Rui Wang, Victor X Jin
The TCF7L2 transcription factor (TF) is a member of Wnt signalling pathway, and may influence transcription of several genes by binding to distinct regulatory regions. Genome-wide studies have identified thousands of TCF7L2 binding sites and have revealed some associated TF partners. However, there is still a large uncharted region in the hierarchical regulatory network for TCF7L2 and the partner TFs in MCF7 cells. We analysed ChIP-seq data by searching for motifs in the enriched peak region based on TF-specific position weight matrix (PWM)...
2016: International Journal of Computational Biology and Drug Design
Yanhui Liang, Fusheng Wang, Darren Treanor, Derek Magee, Nick Roberts, George Teodoro, Yangyang Zhu, Jun Kong
Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable to 3D pathology analytical imaging, with an application to whole slide images of sequential liver slices for 3D vessel structure analysis. The analysis workflow consists of image registration, segmentation, vessel cross-section association, interpolation, and volumetric rendering...
2016: International Journal of Computational Biology and Drug Design
Mohit M Jain, Nirmala Kumari, Geeta Rai
LXR (encoded by NR1H2 and 3) and FXR (known as bile acid receptor) encoded by NR1H4 (nuclear receptor subfamily 1, group H and member 4) are nuclear receptors in humans and are important regulators of bile acid production, cholesterol, fatty acid and glucose homeostasis hence responsible for liver detoxification. Several strategies for drug design with numerous ligands for this target have failed owing to the inability of the ligand to access the target/receptor or their early metabolisation. In this work, we have evaluated FXR and LXR structure bound with agonist and compared the binding energy affinity of active ligands present in live green-real veggies with reference drugs (ligands) present in the market...
2015: International Journal of Computational Biology and Drug Design
Tayebeh Farhadi, Navid Nezafat, Younes Ghasemi
Vibrio cholera, a gram-negative bacterium, has been categorised into clinical and environmental species. Phylogenetic studies have been performed to investigate the relationships of the V. cholerae populations in worldwide. In this study, phylogenetic relationship between V. cholerae isolates from Iran and other regions of the world was determined, based on three housekeeping genes analysis. Results for Iranian strains showed that congruency of asd and hlyA phylogenetic trees were remarkably higher than recA tree...
2015: International Journal of Computational Biology and Drug Design
Mohit M Jain, Nirmala Kumari, Geeta Rai
Calcitonin gene-related peptide (CGRP) is involved in triggering migraine. Many strategies for antimigraine drug designing have been employed using various CGRP antagonist/ligands but most of them have failed due to their inability to reach target CGRP receptor as they get metabolised before conferring their pharmacological action and they are also toxic to the liver. In the present study, we evaluated the binding of our active ligands present in real veggies with the CGRP receptor crystal structure and compared their binding energy and affinity with other reference anti-migraine drugs/ligands present in the market...
2015: International Journal of Computational Biology and Drug Design
Madhulata Kumari, Subhash Chandra
Machine learning techniques have been widely used in drug discovery and development in the areas of cheminformatics. Aspartyl aminopeptidase (M18AAP) of Plasmodium falciparum is crucial for survival of malaria parasite. We have created predictive models using weka and evaluated their performance based on various statistical parameters. Random Forest based model was found to be the most specificity (97.94%), with best accuracy (97.3%), MCC (0.306) as well as ROC (86.1%). The accuracy and MCC of these models indicated that they could be used to classify huge dataset of unknown compounds to predict their antimalarial compounds to develop effective drugs...
2015: International Journal of Computational Biology and Drug Design
Shravan Kumar Gunda, Sofia Florence Kongaleti, Mahmood Shaik
Natural flavonoid derivatives against cancer for selective KB cell lines (oral human epidermoid carcinoma) are analysed to determine the relationship between biological activities and structural properties of these molecules. Molecular alignment was performed for 88 natural flavonoid derivatives; out of these 88 molecules, 69 molecules were taken into training set and rest of the 19 molecules were used in test set prediction. We describe our elucidation of their structure activity relation (SAR) using three-dimensional quantitative structure activity relationship (3D-QSAR) models...
2015: International Journal of Computational Biology and Drug Design
Kh Dhanachandra Singh, Palani Kirubakaran, Selvaraman Nagamani, Muthusamy Karthikeyan
The main goal of this study is to understand the molecular-level interactions of neuraminidase inhibitor. The molecular docking, molecular dynamics and binding energy calculation analyses were carried out and the results revealed that the 150-cavitiy in the active site may play an important role in binding of drugs. Free energy calculations revealed that electrostatic interaction is more favourable for Oseltamivir interaction with H1N1 and van der Waals interaction is more favourable for H5N1, whereas Zanamivir favours the electrostatic interaction in both the strains (H1N1 and H5N1)...
2015: International Journal of Computational Biology and Drug Design
Ramkrishna Mitra, Zhongming Zhao
Transcription factors (TFs) and microRNAs (miRNAs), the two main gene regulators in the biological system, control the gene expression at the transcriptional and post-transcriptional level, respectively. However, little is known regarding whether the miRNATF co-regulatory mechanisms, predicted by several studies, truly reflect the molecular interactions in cellular systems. To tackle this important issue, we developed an integrative framework by utilising four independent miRNA and matched mRNA expression profiling datasets to identify reproducible regulations, and demonstrated this approach in non-small cell lung cancer (NSCLC)...
2014: International Journal of Computational Biology and Drug Design
Timothy G Lilburn, Hong Cai, Jianying Gu, Zhan Zhou, Yufeng Wang
The heat shock response is a general mechanism by which organisms deal with physical insults such as sudden changes in temperature, osmotic and oxidative stresses, and exposure to toxic substances. Plasmodium falciparum is exposed to drastic temperature changes as a part of its life cycle and maintains an extensive repertoire of heat shock response-related proteins. As these proteins serve to maintain the parasite in the face of anti-malarial drugs as well, better understanding of the heat shock-related systems in the malaria parasite will lead to therapeutic approaches that frustrate these systems, leading to more effective use of anti-malarials...
2014: International Journal of Computational Biology and Drug Design
Maryam Pourkamali Anaraki, Mehdi Sadeghi
Availability of complete human genome is a crucial factor for genetic studies to explore possible association between the genome and complex diseases. Haplotype, as a set of single nucleotide polymorphisms (SNPs) on a single chromosome, is believed to contain promising data for disease association studies, detecting natural positive selection and recombination hotspots. Various computational methods for haplotype reconstruction from aligned fragment of SNPs have already been proposed. This study presents a novel approach to obtain paternal and maternal haplotypes form the SNP fragments on minimum error correction (MEC) model...
2014: International Journal of Computational Biology and Drug Design
Vo Hong Thanh, Roberto Zunino
Stochastic modelling and simulation is a well-known approach for predicting the behaviour of biochemical systems. Its main applications lie in those systems wherein the inherently random fluctuations of some species are significant, as often is the case whenever just a few macromolecules have a large effect on the rest of the system. The Gillespie's stochastic simulation algorithm (SSA) is a standard method to properly realise the stochastic nature of reactions. In this paper we propose an improvement to SSA based on the Huffman tree, a binary tree which is used to define an optimal data compression algorithm...
2014: International Journal of Computational Biology and Drug Design
Monika Singh, Harish Dureja, A K Madan
In present study, adjacent path eccentric distance sum indices proposed in Part-I of the manuscript were successfully utilised for the development of models for cycloxygenase-2 (COX-2) inhibitory activity. Values of diverse molecular descriptors (MDs) for each of 38 indomethacin analogues involved in the dataset were computed. A total of 55 diverse MDs were ultimately shortlisted for further analysis. The suitable models were developed using decision tree (DT), random forest (RF) and moving average analysis (MAA)...
2014: International Journal of Computational Biology and Drug Design
Monika Singh, P V Bharatam, A K Madan
In the present study, three detour matrix-based topological indices (TIs) termed as adjacent path eccentric distance sum indices 1-3 (denoted by (A)ξ(1)(PDS), (A)ξ(2)(PDS) and (A)ξ(3)(PDS)) as well as their topochemical versions (denoted by (A)ξ(1c)(PDS), (A)ξ(2c)(PDS) and (A)ξ(3c)(PDS)) have been conceptualised. Values of the proposed TIs were computed for all possible cyclic and acyclic structures containing three, four, five vertices using an in-house computer programme. Proposed TIs were evaluated for discriminating power, degeneracy, intercorrelation and sensitivity towards branching as well relative position of substituent(s) in cyclic structures...
2014: International Journal of Computational Biology and Drug Design
Shravan Kumar Gunda, Sandeep Kumar Mulukala Narasimha, Mahmood Shaik
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on 3D-QSAR (3D-quantitative structure activity relationship) studies were carried out on 97 flavonoid derivatives as potent P56(lck) protein tyrosine kinase inhibitors. The best prediction was obtained with CoMFA standard model (q² = 0.838, r² = 0.948) using steric, electrostatic along with CoMSIA standard model (q² = 0.714, r² = 0.921) using steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields...
2014: International Journal of Computational Biology and Drug Design
S Buhl, B Neumann, S C Schäfer, A L Severing
This paper presents a method of separating cells that are connected to each other forming clusters. The difference to many other publications covering similar topics is that the cell types we are dealing with form clusters of highly varying morphology. An advantage of our method is that it can be universally used for different cell types. The segmentation method is based on a growth simulation starting from the nuclei areas. To start the evaluation, the cells need to be made visible with a histological stain, in our case with the May-Grünwald solution...
2014: International Journal of Computational Biology and Drug Design
Jakob L Andersen, Christoph Flamm, Daniel Merkle, Peter F Stadler
The chemical universe of molecules reachable from a set of start compounds by iterative application of a finite number of reactions is usually so vast, that sophisticated and efficient exploration strategies are required to cope with the combinatorial complexity. A stringent analysis of (bio)chemical reaction networks, as approximations of these complex chemical spaces, forms the foundation for the understanding of functional relations in Chemistry and Biology. Graphs and graph rewriting are natural models for molecules and reactions...
2014: International Journal of Computational Biology and Drug Design
Wei Chen, Yong-Mei Cheng, Shao-Wu Zhang, Quan Pan
Microbes play an important role on human health, however, little is known on microbes in the past decades for the limitation of culture-based techniques. Recently, with the development of next-generation sequencing (NGS) technologies, it is now possible to sequence millions of sequences directly from environments samples, and thus it supplies us a sight to probe the hidden world of microbial communities and detect the associations between microbes and diseases. In the present work, we proposed a supervised learning-based method to mine the relationship between microbes and periodontitis with 16S rRNA sequences...
2014: International Journal of Computational Biology and Drug Design
Xinjun Zhang, Dharanesh Gangaiah, Robert S Munson, Stanley M Spinola, Yunlong Liu
High throughput bacterial RNA-Seq experiments can generate extremely high and imbalanced sequencing coverage. Over- or under-estimation of gene expression levels will hinder accurate gene differential expression analysis. Here we evaluated strategies to identify expression differences of genes with high coverage in bacterial transcriptome data using either raw sequence reads or unique reads with duplicate fragments removed. In addition, we proposed a generalised linear model (GLM) based approach to identify imbalance in read coverage based on sequence compositions...
2014: International Journal of Computational Biology and Drug Design
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