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Interdisciplinary Sciences, Computational Life Sciences

Nuno M F S A Cerqueira, Pedro A Fernandes, Maria João Ramos
Visualization can be a motivating way of teaching students about the microscopic world. This can become even more exciting if the information is based on accurate computational results rather than on crude approximations that eventually might create unreal alternative perceptions. Here, we report on a VMD plug-in, named vmdMagazine, which can turn computational simulations into stunning high-impact video presentations, suitable for classes/lectures and even conferences. The software will help students/audience to understand atoms and molecules better and learn to like them...
August 9, 2017: Interdisciplinary Sciences, Computational Life Sciences
Devender Arora, Ritu Chaudhary, Ajeet Singh
Cancer is a public health concern which is spreading throughout the world. Different approaches have been employed to combat this disease. System biology approach has been used to understand the molecular mechanisms of drugs targeting cancer cell's receptor which have opened-up a window to develop effective drugs for it. We have demonstrated biomolecular interaction studies using the rational drug design of indole[2,1-a]isoquinoline derivative as a potent inhibitor against identified cancerous protein PIK3CA -a catalytic sub-unit of PI3K family protein-and compared its affinity with FDA approved drugs for receptors such as dactolisib, idelalisib, and several others such afatinib, avastin, ceritinib and crizotinib, etc...
July 26, 2017: Interdisciplinary Sciences, Computational Life Sciences
Chi-Kan Chen
BACKGROUND: The identification of genetic regulatory networks (GRNs) provides insights into complex cellular processes. A class of recurrent neural networks (RNNs) captures the dynamics of GRN. Algorithms combining the RNN and machine learning schemes were proposed to reconstruct small-scale GRNs using gene expression time series. RESULTS: We present new GRN reconstruction methods with neural networks. The RNN is extended to a class of recurrent multilayer perceptrons (RMLPs) with latent nodes...
July 26, 2017: Interdisciplinary Sciences, Computational Life Sciences
George Kadakasseril Varghese, Rini Abraham, Nisha N Chandran, Solomon Habtemariam
Hypercholesterolemia is one of the major risk factors for the development and progression of atherosclerosis. Hence, inhibitors of cholesterol absorption have been investigated for decades as a strategy to prevent and treat cardiovascular diseases associated with hypercholesterolemia. Cholesterol esterase (CEase) in pancreatic juice plays a vital role in the hydrolysis of dietary cholesterol esters to cholesterol and fatty acids. Since inhibition of CEase might lead to a reduction of cholesterol absorption, an attempt is made in this study to identify lead molecules of Garcinia mangostana by the in silico approach...
July 24, 2017: Interdisciplinary Sciences, Computational Life Sciences
Pallavi Gaur, Anoop Chaturvedi
BACKGROUND: The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Recent progress in the field of exosome research and more particularly regarding exosomal miRNAs has led much bioinformatic-based research to come into existence. The information on clustering pattern and candidate motifs in miRNAs of exosomal origin would help in analyzing existing, as well as newly discovered miRNAs within exosomes...
July 22, 2017: Interdisciplinary Sciences, Computational Life Sciences
Vemulawada Chakrapani, Kiran D Rasal, Sunil Kumar, Shibani D Mohapatra, Jitendra K Sundaray, Pallipuram Jayasankar, Hirak K Barman
Immune response mediated by toll-like receptor 22 (TLR22), only found in teleost/amphibians, is triggered by double-stranded RNA binding to its LRR (leucine-rich repeats) ecto-domain. Accumulated evidences suggested that missense mutations in TLR genes affect its function. However, information on mutation linked pathogen recognition for TLR22 was lacking. The present study was commenced for predicting the effect of non-synonymous single-nucleotide polymorphisms (nsSNPs) on the pathogen recognizable LRR domain of TLR22 of farmed carp, Labeo rohita...
June 28, 2017: Interdisciplinary Sciences, Computational Life Sciences
Bahram Baghban Kohnehrouz, Meysam Bastami, Shahnoush Nayeri
microRNAs (miRNAs) are a newly discovered class of non-coding small RNAs roughly 22 nucleotides long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation, apoptosis and stress responses. The identification of miRNAs and their targets is an important need to understand their roles in the development and physiology of sweet onion (Allium cepa). In this research, several computational approaches were combined to make concise prediction of the potential miRNAs and their targets...
June 28, 2017: Interdisciplinary Sciences, Computational Life Sciences
Li-Hua Dong, Xiao-Rong Cao
Influenza virus is a major causative agent of respiratory viral infections, and RNA polymerase catalyzes its replication and transcription activities in infected cell nuclei. Since it is highly conserved in all virus strains, RNA polymerase becomes a key target of anti-influenza virus agents. Although experimental studies have revealed the good inhibitory activity of endonuclease inhibitors to RNA polymerase, the mechanism is still unclear. In this study, the docking and molecular dynamics simulations have been performed to explore the interaction of three kinds of endonuclease inhibitors with the subunit (PAN) of RNA polymerase...
June 19, 2017: Interdisciplinary Sciences, Computational Life Sciences
Hemant Arya, Safiulla Basha Syed, Sorokhaibam Sureshkumar Singh, Dinakar R Ampasala, Mohane Selvaraj Coumar
Understanding the molecular mode of action of natural product is a key step for developing drugs from them. In this regard, this study is aimed to understand the molecular-level interactions of chemical constituents of Clerodendrum colebrookianum Walp., with anti-hypertensive drug targets using computational approaches. The plant has ethno-medicinal importance for the treatment of hypertension and reported to show activity against anti-hypertensive drug targets-Rho-associated coiled-coil protein kinase (ROCK), angiotensin-converting enzyme, and phosphodiesterase 5 (PDE5)...
June 16, 2017: Interdisciplinary Sciences, Computational Life Sciences
Lu Xin, Hai Yu, Qiyang Hong, Xingjian Bi, Xiao Zhang, Zhiqing Zhang, Zhibo Kong, Qingbing Zheng, Ying Gu, Qinjian Zhao, Jun Zhang, Shaowei Li, Ningshao Xia
Structural information pertaining to antigen-antibody interactions is fundamental in immunology, and benefits structure-based vaccine design. Modeling of antigen-antibody immune complexes from co-crystal structures or molecular docking simulations provides an extensive profile of the epitope at the interface; however, the key amino acids involved in the interaction must be further clarified, often through the use of experimental mutagenesis and subsequent binding assays. Here, we describe an in silico mutagenesis method to identify key sites at antigen-antibody interfaces, using significant increase in pH-dependency energy among saturated point mutations...
May 30, 2017: Interdisciplinary Sciences, Computational Life Sciences
Prashant Mohanpuria, Naveen Duhan, Navraj Kaur Sarao, Manvir Kaur, Mandip Kaur
MicroRNAs (miRNAs) are a large family of 19-25 nucleotides, regulatory, non-coding RNA molecules that control gene expression by cleaving or inhibiting the translation of target gene transcripts in animals and plants. Despite the important functions of miRNAs related to regulation of plant growth and development processes, metabolism, and abiotic and biotic stresses, little is known about the disease-related miRNA. Here, we present a new pipeline for miRNA analysis using expressed sequence tags (ESTs)-based bioinformatics approach in Kinnow mandarin, a commercially important citrus fruit crop...
May 22, 2017: Interdisciplinary Sciences, Computational Life Sciences
Yanqing Niu, Wen Zhang
MOTIVATION: Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. METHODS: In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Serena Indelicato, David Bongiorno, Valentina Calabrese, Ugo Perricone, Anna Maria Almerico, Leopoldo Ceraulo, Daniela Piazzese, Marco Tutone
Surfactants are an interesting class of compounds characterized by the segregation of polar and apolar domains in the same molecule. This peculiarity makes possible a whole series of microscopic and macroscopic effects. Among their features, their ability to segregate particles (fluids or entire domains) and to reduce the surface/interfacial tension is the utmost important. The interest in the chemistry of surfactants never weakened; instead, waves of increasing interest have occurred every time a new field of application of these molecules has been discovered...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Marek Danielewski, Henryk Leszczyński, Anna Szafrańska
Ternary diffusion models lead to strongly coupled systems of PDEs. We choose the smallest diffusion coefficient as a small parameter in a power series expansion whose components fulfill relatively simple equations. Although this series is divergent, one can use its finite sums to derive feasible numerical approximations, e.g. finite difference methods (FDMs).
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Pu Wang, Ruiquan Ge, Xuan Xiao, Yunpeng Cai, Guoqing Wang, Fengfeng Zhou
Disease diagnosis is one of the major data mining questions by the clinicians. The current diagnosis models usually have a strong assumption that one patient has only one disease, i.e. a single-label data mining problem. But the patients, especially when at the late stages, may have more than one disease and require a multi-label diagnosis. The multi-label data mining is much more difficult than a single-label one, and very few algorithms have been developed for this situation. Deep learning is a data mining algorithm with highly dense inner structure and has achieved many successful applications in the other areas...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Emiliene Berinyuy, Mahmoud E S Soliman
Inhibition of HIV-1 target cell entry, by targeting gp120, has been identified as a promising approach for the identification and development of prophylactic and salvage HIV infection inhibitors. A small molecule compound 18A is an important chemotype in the development of novel and diverse viral cell entry inhibitors, as it inhibits a wide variety of HIV strains by disrupting allosteric structuring on gp120. This study combines residue energy contribution (REC) pharmacophore mapping of 18A and in silico molecular docking in a virtual screening campaign to identify novel and diverse antagonists of gp120...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Lalitha Simon, Abdelli Imane, K K Srinivasan, Lokesh Pathak, I Daoud
In silico molecular modeling studies were carried out on some newly synthesized flavanoid analogues. Search for potential targets for these compounds was performed using pharmacophore-mapping algorithm employing inverse screening of some representative compounds to a large set of pharmacophore models constructed from human target proteins. Further, molecular docking studies were carried out to assess binding affinity of these compounds to proteins mediating tumor growth. In vitro anticancer studies were carried out on colon cancer cell lines (HCT116) to assess validity of this approach for target identification of the new compounds...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Priyanka Narad, Abhishek Kumar, Amlan Chakraborty, Pranav Patni, Abhishek Sengupta, Gulshan Wadhwa, K C Upadhyaya
Transcription factors are trans-acting proteins that interact with specific nucleotide sequences known as transcription factor binding site (TFBS), and these interactions are implicated in regulation of the gene expression. Regulation of transcriptional activation of a gene often involves multiple interactions of transcription factors with various sequence elements. Identification of these sequence elements is the first step in understanding the underlying molecular mechanism(s) that regulate the gene expression...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Nagendra Kumar Singh
microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
Zhijun Liao, Xinrui Wang, Dexin Lin, Quan Zou
Human DEP domain containing 7 (DEPDC7) gene was originally found expressing high in liver tissue and low in most other tissues, but its function was largely unknown. In this study, we construct an RNA interference (RNAi) recombinant lentiviral vector particle targeting DEPDC7 in order to knockdown its gene expression in human hepatocellular carcinoma cell line HepG2. We screened three RNAi sequences targeting DEPDC7 and a scramble sequence by the aid of short hairpin RNAs (shRNA) design tools. Then, these sequences were separately cloned into the pLV-H1-EF1α-puro vector to construct four lentiviral vectors (pshRNA-DEPDC7-NC, pshRNA-DEPDC7-RNAi1, pshRNA-DEPDC7-RNAi2 and pshRNA-DEPDC7-RNAi3)...
September 2017: Interdisciplinary Sciences, Computational Life Sciences
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