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https://read.qxmd.com/read/30704472/comparison-of-different-functional-prediction-scores-using-a-gene-based-permutation-model-for-identifying-cancer-driver-genes
#1
Alice Djotsa Nono, Ken Chen, Xiaoming Liu
BACKGROUND: Identifying cancer driver genes (CDG) is a crucial step in cancer genomic toward the advancement of precision medicine. However, driver gene discovery is a very challenging task because we are not only dealing with huge amount of data; but we are also faced with the complexity of the disease including the heterogeneity of background somatic mutation rate in each cancer patient. It is generally accepted that CDG harbor variants conferring growth advantage in the malignant cell and they are positively selected, which are critical to cancer development; whereas, non-driver genes harbor random mutations with no functional consequence on cancer...
January 31, 2019: BMC Medical Genomics
https://read.qxmd.com/read/30686258/cinnamaldehyde-analogs-docking-based-optimization-cox-2-inhibitory-in-vivo-and-in-vitro-studies
#2
Vaishali M Patil, Preeti Anand, Monika Bhardwaj, Neeraj Masand
The research work aims to investigate Schiff bases of Cinnamaldehyde as biologically potent analogs. In the past decade CADD has emerged as a rational approach in drug development so with the help molecular docking approach we planned to perform virtual screening of the designed data set of Schiff bases. This will be helpful to put some light on the drug receptor interactions required for anti-inflammatory activity. For carrying out virtual screening of the developed Schiff base data set, AutoDock 4.0 was used...
January 25, 2019: Current Drug Discovery Technologies
https://read.qxmd.com/read/30671673/leveraging-linkage-evidence-to-identify-low-frequency-and-rare-variants-on-16p13-associated-with-blood-pressure-using-topmed-whole-genome-sequencing-data
#3
Karen Y He, Xiaoyin Li, Tanika N Kelly, Jingjing Liang, Brian E Cade, Themistocles L Assimes, Lewis C Becker, Amber L Beitelshees, Adam P Bress, Yen-Pei Christy Chang, Yii-Der Ida Chen, Paul S de Vries, Ervin R Fox, Nora Franceschini, Anna Furniss, Yan Gao, Xiuqing Guo, Jeffrey Haessler, Shih-Jen Hwang, Marguerite Ryan Irvin, Rita R Kalyani, Ching-Ti Liu, Chunyu Liu, Lisa Warsinger Martin, May E Montasser, Paul M Muntner, Stanford Mwasongwe, Walter Palmas, Alex P Reiner, Daichi Shimbo, Jennifer A Smith, Beverly M Snively, Lisa R Yanek, Eric Boerwinkle, Adolfo Correa, L Adrienne Cupples, Jiang He, Sharon L R Kardia, Charles Kooperberg, Rasika A Mathias, Braxton D Mitchell, Bruce M Psaty, Ramachandran S Vasan, D C Rao, Stephen S Rich, Jerome I Rotter, James G Wilson, Aravinda Chakravarti, Alanna C Morrison, Daniel Levy, Donna K Arnett, Susan Redline, Xiaofeng Zhu
In this study, we investigated low-frequency and rare variants associated with blood pressure (BP) by focusing on a linkage region on chromosome 16p13. We used whole genome sequencing (WGS) data obtained through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program on 395 Cleveland Family Study (CFS) European Americans (CFS-EA). By analyzing functional coding variants and non-coding rare variants with CADD score > 10 residing within the chromosomal region in families with linkage evidence, we observed 25 genes with nominal statistical evidence (burden or SKAT p < 0...
January 22, 2019: Human Genetics
https://read.qxmd.com/read/30663568/combating-diseases-with-computational-strategies-used-for-drug-design-and-discovery
#4
Farahnaz Rezaei Makhouri, Jahan B Ghasemi
Computer-aided drug discovery (CADD) tools have provided an effective way in the drug discovery pipeline for expediting of this long process and economizing the cost of research and development. Because of the dramatic increase in the availability of human proteins as drug targets and small molecule information due to the advances in bioinformatics, cheminformatics, genomics, proteomics, and structural information, the applicability of in silico drug discovery has been extended. Computational approaches have been used at almost all stages in the drug discovery pipeline including target identification and validation, lead discovery and optimization, and pharmacokinetic and toxicity profiles prediction...
January 21, 2019: Current Topics in Medicinal Chemistry
https://read.qxmd.com/read/30659543/modern-computational-strategies-for-designing-drugs-to-curb-human-diseases-a-prospect
#5
Khalid Bashir, Ashiq Hussain Bhatt, Shajrul Amin, Rabia Hamid, Suhail Anees, Syed Anjum, Bilal Ahmed Reshi, Muhammad Afzal Zargar, Showkat Ahmed Ganie, Akbar Masood
Drug discovery is an exhaustive and time consuming process involving numerous stages like target identification, validation, lead optimization, preclinical trials, clinical trials and finally post marketing vigilance for drug safety. The application of computer aided drug designing (CADD) is an indispensable approach for developing safe and effective drugs. Previous methods based on combinatorial chemistry (CC) and high throughput screening (HTS) consumed a lot of time as well as expenditure. CADD based approaches including pharmacophore modeling (PM), molecular docking (MD), inverse docking, chemical similarity (CS), quantitative structure-activity relationship (QSAR), virtual screening (VS) and molecular dynamics simulations have been quite productive in predicting the therapeutic outcome of candidate drugs/compounds besides saving precious time...
January 19, 2019: Current Topics in Medicinal Chemistry
https://read.qxmd.com/read/30626175/the-26th-annual-nucleic-acids-research-database-issue-and-molecular-biology-database-collection
#6
Daniel J Rigden, Xosé M Fernández
The 2019 Nucleic Acids Research (NAR) Database Issue contains 168 papers spanning molecular biology. Among them, 64 are new and another 92 are updates describing resources that appeared in the Issue previously. The remaining 12 are updates on databases most recently published elsewhere. This Issue contains two Breakthrough articles, on the Virtual Metabolic Human (VMH) database which links human and gut microbiota metabolism with diet and disease, and Vibrism DB, a database of mouse brain anatomy and gene (co-)expression with sophisticated visualization and session sharing...
January 8, 2019: Nucleic Acids Research
https://read.qxmd.com/read/30623477/eshafts-integrated-and-graphical-drug-design-software-based-on-3d-molecular-similarity
#7
Gaoqi He, Yiping Song, Wenhao Wei, Xia Wang, Xingjian Lu, Honglin Li
With the development of computer technology, computer-aided drug design (CADD) has become an important means for drug research and development, and its representative method is virtual screening. Various virtual screening platforms have emerged in an endless stream and play great roles in the field of drug discovery. With the increasing number of compound molecules, virtual screening platforms face two challenges: low fluency and low visibility of software operations. In this article, we present an integrated and graphical drug design software eSHAFTS based on three-dimensional (3D) molecular similarity to overcome these shortcomings...
March 5, 2019: Journal of Computational Chemistry
https://read.qxmd.com/read/30582441/whole-exome-sequencing-reveals-the-major-genetic-contributors-to-non-syndromic-tetralogy-of-fallot
#8
Donna J Page, Matthieu J Miossec, Simon G Williams, Richard M Monaghan, Elisavet Fotiou, Heather Cordell, Louise Sutcliffe, Ana Topf, Mathieu Bourgey, Guillaume Bourque, Robert Eveleigh, Sally L Dunwoodie, David S Winlaw, Shoumo Bhattacharya, Jeroen Breckpot, Koenraad Devriendt, Marc Gewillig, J David Brook, Kerry Jane Setchfield, Frances Bu'Lock, John J o'sullivan, Graham Stuart, Connie R Bezzina, Barbara Jm Mulder, Alex V Postma, James R Bentham, Martin Baron, Sanjeev S Bhaskar, Graeme C Black, William G Newman, Kathryn E Hentges, G Mark Lathrop, Mauro Santibanez Koref, Bernard Keavney
RATIONALE: Familial recurrence studies provide strong evidence for a genetic component to the predisposition to sporadic, non-syndromic Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease (CHD) phenotype. Rare genetic variants have been identified as important contributors to the risk of CHD, but relatively small numbers of TOF cases have been studied to date. OBJECTIVE: We used whole exome sequencing (WES) to assess the prevalence of unique, deleterious variants in the largest cohort of non-syndromic TOF patients reported to date...
November 28, 2018: Circulation Research
https://read.qxmd.com/read/30546860/yatcm-yet-another-traditional-chinese-medicine-database-for-drug-discovery
#9
Baiqing Li, Chunfeng Ma, Xiaoyong Zhao, Zhigang Hu, Tengfei Du, Xuanming Xu, Zhonghua Wang, Jianping Lin
Traditional Chinese Medicine (TCM) has a long history of widespread clinical applications, especially in East Asia, and is becoming frequently used in Western countries. However, owing to extreme complicacy in both chemical ingredients and mechanism of action, a deep understanding of TCM is still difficult. To accelerate the modernization and popularization of TCM, a single comprehensive database is required, containing a wealth of TCM-related information and equipped with complete analytical tools. Here we present YaTCM (Yet another Traditional Chinese Medicine database), a free web-based toolkit, which provides comprehensive TCM information and is furnished with analysis tools...
2018: Computational and Structural Biotechnology Journal
https://read.qxmd.com/read/30541027/a-robust-pipeline-with-high-replication-rate-for-detection-of-somatic-variants-in-the-adaptive-immune-system-as-a-source-of-common-genetic-variation-in-autoimmune-disease
#10
Lies Van Horebeek, Kelly Hilven, Klara Mallants, Annemarie Van Nieuwenhuijze, Tiina Kelkka, Paula Savola, Satu Mustjoki, Susan M Schlenner, Adrian Liston, Bénédicte Dubois, An Goris
The role of somatic variants in diseases beyond cancer is increasingly being recognized, with potential roles in autoinflammatory and autoimmune diseases. However, as mutation rates and allele fractions are lower, studies in these diseases are substantially less tolerant of false positives and bio-informatics algorithms require high replication rates. We developed a pipeline combining two variant callers, MuTect2 and VarScan2, with technical filtering and prioritization. Our pipeline detects somatic variants with allele fractions as low as 0...
December 12, 2018: Human Molecular Genetics
https://read.qxmd.com/read/30535305/popviz-a-webserver-for-visualizing-minor-allele-frequencies-and-damage-prediction-scores-of-human-genetic-variations
#11
Peng Zhang, Benedetta Bigio, Franck Rapaport, Shen-Ying Zhang, Jean-Laurent Casanova, Laurent Abel, Bertrand Boisson, Yuval Itan
Summary: Next-generation sequencing (NGS) generates large amounts of genomic data and reveals about 20 000 genetic coding variants per individual studied. Several mutation damage prediction scores are available to prioritize variants, but there is currently no application to help investigators to determine the relevance of the candidate genes and variants quickly and visually from population genetics data and deleteriousness scores. Here, we present PopViz, a user-friendly, rapid, interactive, mobile-compatible webserver providing a gene-centric visualization of the variants of any human gene, with (i) population-specific minor allele frequencies from the gnomAD population genetic database; (ii) mutation damage prediction scores from CADD, EIGEN and LINSIGHT and (iii) amino-acid positions and protein domains...
December 15, 2018: Bioinformatics
https://read.qxmd.com/read/30500556/computational-studies-on-n-phenyl-pyrrole-derivatives-as-mmpl3-inhibitors-in-mycobacterium-tuberculosis
#12
RamaKrishna Munnaluri, Saikiran Reddy Peddi, Sree Kanth Sivan, Vijjulatha Manga
The fight against tuberculosis (TB) is a time immemorial one and the emergence of new drug resistant strains of Mycobacterium tuberculosis keeps throwing new challenges to the scientific community immersed in finding mechanisms to control this dreaded disease. Computer aided drug designing (CADD) is one of the several approaches that can assist in identifying the potent actives against Mycobacterium. In this work, a series of 109 known Mycobacterial membrane proteins large 3 (MmpL3) inhibitors were pooled and atom based 3D QSAR analysis was performed to understand the structural features essential for inhibitory activity against the MmpL3, known to be a key player in transporting substances critical for cell wall integrity of Mycobacterium...
November 19, 2018: Computational Biology and Chemistry
https://read.qxmd.com/read/30488731/advances-with-support-vector-machines-for-novel-drug-discovery
#13
Vinicius Gonçalves Maltarollo, Thales Kronenberger, Gabriel Zarzana Espinoza, Patricia Rufino Oliveira, Kathia Maria Honorio
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learning techniques. SVMs and their variations offer numerous drug discovery applications, which range from the classification of substances (as active or inactive) to the construction of regression models and the ranking/virtual screening of databased compounds. Areas covered: Herein, the authors consider some of the applications of SVMs in medicinal chemistry, illustrating their main advantages and disadvantages, as well as trends in their utilization, via the available published literature...
November 29, 2018: Expert Opinion on Drug Discovery
https://read.qxmd.com/read/30417777/cancer-biology-aspects-of-computational-methods-applications-in-drug-discovery
#14
Shang-Tao Chien, Ajay Kumar, Shifa Pandey, Chung-Kun Yen, Shao-Yu Wang, Zhi-Hong Wen, Aman Chandra Kaushik, Yow-Ling Shiue, Cheng-Tang Pan
BACKGROUND: Cancer is one of the most debilitating diseases in the world. Even though advances in molecular and cellular biology have contributed to the decline of mortality associated with cancer, the procedure of drug discovery and development of cancer is time-consuming and expensive. However, with computer-aided drug discovery (CADD) techniques, pharmaceutical firms can save production costs and reduce the time of introducing effective anticancer drugs to the market. CADD strategies like structure-based, ligand-based, and combined structure-based and ligand-based approaches also have the advantage of identifying target sites and discovering active compounds with high affinity for the target sites...
November 11, 2018: Current Pharmaceutical Design
https://read.qxmd.com/read/30403855/ezcadd-a-rapid-2d-3d-visualization-enabled-web-modeling-environment-for-democratizing-computer-aided-drug-design
#15
Aoxiang Tao, Yuying Huang, Yasuhiro Shinohara, Matthew L Caylor, Srinath Pashikanti, Dong Xu
As abundant and user-friendly as computer-aided drug design (CADD) software may seem, there is still a large underserved population of biomedical researchers around the world, particularly those with no computational training and limited research funding. To address this important need and help scientists overcome barriers that impede them from leveraging CADD in their drug discovery work, we have developed ezCADD, a web-based CADD modeling environment that manifests four simple design concepts: easy, quick, user-friendly, and 2D/3D visualization-enabled...
November 16, 2018: Journal of Chemical Information and Modeling
https://read.qxmd.com/read/30401457/fut2-variants-confer-susceptibility-to-familial-otitis-media
#16
Regie Lyn P Santos-Cortez, Charlotte M Chiong, Daniel N Frank, Allen F Ryan, Arnaud P J Giese, Tori Bootpetch Roberts, Kathleen A Daly, Matthew J Steritz, Wasyl Szeremeta, Melquiadesa Pedro, Harold Pine, Talitha Karisse L Yarza, Melissa A Scholes, Erasmo Gonzalo D V Llanes, Saira Yousaf, Norman Friedman, Ma Leah C Tantoco, Todd M Wine, Patrick John Labra, Jeanne Benoit, Amanda G Ruiz, Rhodieleen Anne R de la Cruz, Christopher Greenlee, Ayesha Yousaf, Jonathan Cardwell, Rachelle Marie A Nonato, Dylan Ray, Kimberly Mae C Ong, Edward So, Charles E Robertson, Jordyn Dinwiddie, Sheryl Mae Lagrana-Villagracia, Samuel P Gubbels, Rehan S Shaikh, Stephen P Cass, Elisabet Einarsdottir, Nanette R Lee, David A Schwartz, Teresa Luisa I Gloria-Cruz, Michael J Bamshad, Ivana V Yang, Juha Kere, Generoso T Abes, Jeremy D Prager, Saima Riazuddin, Abner L Chan, Patricia J Yoon, Deborah A Nickerson, Eva Maria Cutiongco-de la Paz, Sven-Olrik Streubel, Maria Rina T Reyes-Quintos, Herman A Jenkins, Petri Mattila, Kenny H Chan, Karen L Mohlke, Suzanne M Leal, Lena Hafrén, Tasnee Chonmaitree, Michele M Sale, Zubair M Ahmed
Non-secretor status due to homozygosity for the common FUT2 variant c.461G>A (p.Trp154∗ ) is associated with either risk for autoimmune diseases or protection against viral diarrhea and HIV. We determined the role of FUT2 in otitis media susceptibility by obtaining DNA samples from 609 multi-ethnic families and simplex case subjects with otitis media. Exome and Sanger sequencing, linkage analysis, and Fisher exact and transmission disequilibrium tests (TDT) were performed. The common FUT2 c.604C>T (p...
November 1, 2018: American Journal of Human Genetics
https://read.qxmd.com/read/30371827/cadd-predicting-the-deleteriousness-of-variants-throughout-the-human-genome
#17
Philipp Rentzsch, Daniela Witten, Gregory M Cooper, Jay Shendure, Martin Kircher
Combined Annotation-Dependent Depletion (CADD) is a widely used measure of variant deleteriousness that can effectively prioritize causal variants in genetic analyses, particularly highly penetrant contributors to severe Mendelian disorders. CADD is an integrative annotation built from more than 60 genomic features, and can score human single nucleotide variants and short insertion and deletions anywhere in the reference assembly. CADD uses a machine learning model trained on a binary distinction between simulated de novo variants and variants that have arisen and become fixed in human populations since the split between humans and chimpanzees; the former are free of selective pressure and may thus include both neutral and deleterious alleles, while the latter are overwhelmingly neutral (or, at most, weakly deleterious) by virtue of having survived millions of years of purifying selection...
October 29, 2018: Nucleic Acids Research
https://read.qxmd.com/read/30371760/gcdb-a-glaucomatous-chemogenomics-database-for-in-silico-drug-discovery
#18
Yu Wei, Jinlong Li, Baiqing Li, Chunfeng Ma, Xuanming Xu, Xu Wang, Aqin Liu, Tengfei Du, Zhonghua Wang, Zhangyong Hong, Jianping Lin
Glaucoma is a group of neurodegenerative diseases that can cause irreversible blindness. The current medications, which mainly reduce intraocular pressure to slow the progression of disease, may have local and systemic side effects. Recently, medications with possible neuroprotective effects have attracted much attention. To assist in the identification of new glaucoma drugs, we created a glaucomatous chemogenomics database (GCDB; http://cadd.pharmacy.nankai.edu.cn/gcdb/home) in which various glaucoma-related chemogenomics data records are assembled, including 275 genes, 105 proteins, 83 approved or clinical trial drugs, 90 206 chemicals associated with 213 093 records of reported bioactivities from 22 324 corresponding bioassays and 5630 references...
January 1, 2018: Database: the Journal of Biological Databases and Curation
https://read.qxmd.com/read/30338293/plasticity-related-gene-3-lppr1-and-age-at-diagnosis-of-parkinson-disease
#19
Zachary D Wallen, Honglei Chen, Erin M Hill-Burns, Stewart A Factor, Cyrus P Zabetian, Haydeh Payami
Objective: To identify modifiers of age at diagnosis of Parkinson disease (PD). Methods: Genome-wide association study (GWAS) included 1,950 individuals with PD from the NeuroGenetics Research Consortium (NGRC) study. Replication was conducted in the Parkinson's, Genes and Environment study, including 209 prevalent (PAGEP ) and 517 incident (PAGEI ) PD cases. Cox regression was used to test association with age at diagnosis. Individuals without neurologic disease were used to rule out confounding...
October 2018: Neurology. Genetics
https://read.qxmd.com/read/30329012/farppi-a-webserver-for-accurate-prediction-of-protein-ligand-binding-structures-for-small-molecule-ppi-inhibitors-by-mm-pb-gb-sa-methods
#20
Zhe Wang, Xuwen Wang, Youyong Li, Tailong Lei, Ercheng Wang, Dan Li, Yu Kang, Feng Zhu, Tingjun Hou
Summary: Protein-protein interactions (PPIs) have been regarded as an attractive emerging class of therapeutic targets for the development of new treatments. Computational approaches, especially molecular docking, have been extensively employed to predict the binding structures of PPI-inhibitors or discover novel small molecule PPI inhibitors. However, due to the relatively 'undruggable' features of PPI interfaces, accurate predictions of the binding structures for ligands towards PPI targets are quite challenging for most docking algorithms...
October 17, 2018: Bioinformatics
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