Int. J. Bioinform. Res. Appl.最新文献_第4页

Application of machine learning techniques towards classification of drug molecules specific to peptide deformylase against Helicobacter pylori 机器学习技术在抗幽门螺杆菌肽脱甲酰基酶特异性药物分子分类中的应用

Int. J. Bioinform. Res. Appl. Pub Date : 2019-07-07 DOI: 10.1504/IJBRA.2019.10022509

S. Patil, Shivakumar B. Madagi

{"title":"Application of machine learning techniques towards classification of drug molecules specific to peptide deformylase against Helicobacter pylori","authors":"S. Patil, Shivakumar B. Madagi","doi":"10.1504/IJBRA.2019.10022509","DOIUrl":"https://doi.org/10.1504/IJBRA.2019.10022509","url":null,"abstract":"It is crucial to adapt to the current computational drug discovery pipeline to develop novel drug molecules to combat the gastric disorders caused by Helicobacter pylori. Virtual screening techniques can be used as a preliminary screening tool to identify the relevant compounds which may have drug-like properties. These drug-like molecules can be further screened to test their bioactivity against a particular protein target. In this context, we apply different machine learning techniques to generate models to predict the pIC50 value of drug molecules. Molecular descriptors were produced for the drug data set. Initial models were developed for the data set with a large number of descriptors. Later, feature reduction techniques were applied to yield feature descriptors with the best six variables using three algorithms: principal component analysis, random forest and genetic algorithm. Consequently, machine learning techniques were applied to the reduced data set to develop predictive models. Nai ve Bayes algorithm achieved better accuracy of 84.42% compared with other algorithms. The results were validated on the test set using 10-fold cross validation. The methodology can be applied to predict the bioactivity of drug molecules. The procedure can be further implemented to identify novel drug molecules against pathogenic H. pylori by blocking its functionalities. The computational process also helps reduce the timeline of drug discovery process.","PeriodicalId":434900,"journal":{"name":"Int. J. Bioinform. Res. Appl.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134126797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction of discrete descriptions of biological shapes through curvilinear image meshing 通过曲线图像网格构建生物形状的离散描述

Int. J. Bioinform. Res. Appl. Pub Date : 2019-07-07 DOI: 10.1504/IJBRA.2019.101204

Jing Xu, Andrey N. Chernikov

引用次数: 0

Genetic algorithm based clustering for gene-gene interaction in episodic memory 基于遗传算法的情景记忆基因-基因相互作用聚类

Int. J. Bioinform. Res. Appl. Pub Date : 2019-07-07 DOI: 10.1504/IJBRA.2019.101208

Sudhakar Tripathi, R. Mishra, A. Sharma

引用次数: 0

Efficient formulation of the rejection-based algorithm for biochemical reactions with delays 具有时滞的生化反应的基于拒绝的有效算法

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021065

Vo Hong Thanh, R. Zunino, C. Priami

引用次数: 0

Bioinformatics resources and approaches for the interaction of Oryza sativa and Magnaporthe oryzae pathosystem 水稻与稻瘟病系统相互作用的生物信息学资源与方法

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021064

V. Sharma, V. Singh, Pramod Katara

引用次数: 0

Exploring new features of α-amylases from different source organisms by an in silico approach 利用计算机方法探索不同来源生物α-淀粉酶的新特征

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021066

J. Harati, S. R. Siadat, Saeed Kaboli, S. M. Motevalli, Ardeshir Hesampour

{"title":"Exploring new features of α-amylases from different source organisms by an in silico approach","authors":"J. Harati, S. R. Siadat, Saeed Kaboli, S. M. Motevalli, Ardeshir Hesampour","doi":"10.1504/IJBRA.2019.10021066","DOIUrl":"https://doi.org/10.1504/IJBRA.2019.10021066","url":null,"abstract":"A total of 78 full-length protein sequences of α-amylase from different source organisms were subjected to phylogenetic analysis, multiple sequence alignment (MSA), motif search and physiochemical properties. The phylogenetic tree was built using the maximum likelihood method in molecular evolutionary genetics analysis (MEGA) software and was pointed out in two major clusters. One of the clusters included plants and animals, whereas the other one contained fungi, archaea and bacteria. Furthermore, Firmicutes and Proteobacteria are bacterial phylum that placed in the same evolutionary cluster with plants and animals. The deviations from expected clusters were explained by motif analysis. MSA declared three conserved sequence blocks, 505-527, 725-745 and 1010-1030, that were present in all studied species. Moreover, it provided information about highly conserved residues at which three glycine and one aspartic acid residues were conserved. Motif analysis with multiple EM for the motif elicitation server revealed that Motif 4 'HDTGSTQRHWPFPSDHVMQGYAYILTHPGIPCIFYDHFFDW', Motif 6 'EGAGGPSTAFDFTTKGILQEAVKGELWRLRDPQGKPPGMIGWWPERAVTF' and Motif 11 'EQIVKLIAIRKRNGIHSRSSIRILEAEGDLYVAMIDEK VCMKIG' were present only in plants. Pearson correlation analysis to clarify relationships among different physiochemical properties showed a direct correlation between average hydropathy (GRAVY) and the aliphatic index and a reverse correlation between GRAVY and pI and instability indexes.","PeriodicalId":434900,"journal":{"name":"Int. J. Bioinform. Res. Appl.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126570867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cell-level 3D reconstruction and quantification of the Drosophila wing imaginal disc 果蝇翅膀影像盘的细胞级三维重建与定量

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021069

D. Breen, Liyuan Sui, Linge Bai, F. Jülicher, Christian Dahmann

引用次数: 1

Computational protein design of bacteriocins based on structural scaffold of aureocin A53 基于金黄色葡萄球菌蛋白A53结构支架的细菌素计算蛋白设计

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021067

S. Talluri

引用次数: 7

Molecular docking and in vitro study of Syzygium cumini-derived natural compounds on receptor tyrosine kinases pathway components 小茴香衍生天然化合物与受体酪氨酸激酶途径组分的分子对接及体外研究

Int. J. Bioinform. Res. Appl. Pub Date : 2019-05-06 DOI: 10.1504/IJBRA.2019.10021068

Pushpendra Singh, F. Bast, Satej Bhushan, Richa Mehra, P. Kamboj

{"title":"Molecular docking and in vitro study of Syzygium cumini-derived natural compounds on receptor tyrosine kinases pathway components","authors":"Pushpendra Singh, F. Bast, Satej Bhushan, Richa Mehra, P. Kamboj","doi":"10.1504/IJBRA.2019.10021068","DOIUrl":"https://doi.org/10.1504/IJBRA.2019.10021068","url":null,"abstract":"Syzygium cumini (S. cumini) is used for a variety of biological activities such as anti-inflammatory, anti-diabetic and anti-oxidant; currently, it has been reported for DNA protecting activity against radiation damage. Receptor tyrosine kinases (RTKs) are identified as critical regulators of various cellular processes including cell proliferation, metabolism and apoptosis. These receptors have recently gained attention as an attractive target for cancer treatment. The present research was aimed to screen S. cumini-derived natural compounds against RTKs pathway components using molecular docking. Furthermore, in vitro anti-proliferative 3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and anti-oxidative (nitro blue tetrazolium and H2CDFD) activities of leaf extract of S. cumini are also reported. Selected natural compounds were docked with X-ray crystal structure of RTKs signalling proteins using grid-based ligand docking with energetics Maestro 9.6. In the present investigation, our result highlighted that myricetin, kaempferol, delphinidin chloride, ellagic acid, rutin, petunidin, gossypol and mirtillin generated a good dock score with all selected proteins. Protein-ligand interactions accentuated that several bonds such as lipophilic, hydrogen bonding, π-π stacking and cation-π interactions represent a ruling contribution at the active site. Moreover, reduction in cell viability with leaf extract of S. cumini treatment at concentrations of 5-80 µg/ml after 48 h in MCF-7 cells was observed. Leaf extract of S. cumini significantly reduced the Reactive oxygen species (ROS) generation in MCF-7 cells after 48 h. These results indicate the anti-cancer potential of S. cumini. Thus, isolation and purification of anti-cancerous compounds are suggested to explore more possibilities in the field.","PeriodicalId":434900,"journal":{"name":"Int. J. Bioinform. Res. Appl.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130080293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification of breast cancer based on thermal image using support vector machine 基于热图像的支持向量机乳腺癌分类

Int. J. Bioinform. Res. Appl. Pub Date : 2019-02-27 DOI: 10.1504/IJBRA.2019.097997

S. Aarthy, S. Prabu

引用次数: 5