检索结果-内蒙古大学图书馆

structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries

引用

BRIEFINGS IN BIOINFORMATICS 2021年第6期22卷 bbab113-bbab113页

作者： Masoudi-Sobhanzadeh, Yosef Salemi, Aysan Pourseif, Mohammad M. Jafari, Behzad Omidi, Yadollah Masoudi-Nejad, Ali Nova Southeastern Univ Coll Pharm Ft Lauderdale FL 33314 USA Tabriz Univ Med Sci TUOMS Res Ctr Pharmaceut Nanotechnol RCPN Tabriz Iran TUOMS RCPN Tabriz Iran Urmia Univ Med Sci Sch Pharm Med Chem Dept Orumiyeh Iran

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.

关键词： COVID-19 drug repurposing emerging diseases SARS-CoV-2 structure-based methods

来源：评论

学校读者我要写书评

暂无评论

Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors

引用

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN 2006年第12期20卷 789-802页

作者： Kortagere, Sandhya Welsh, William J. UMDNJ Robert Wood Johnson Med Sch Dept Pharmacol Piscataway NJ 08854 USA UMDNJ Inst Informat Piscataway NJ 08854 USA

G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor's three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid structure based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially;this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of similar to 300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs.

关键词： GPCRs virtual screening structure-based methods Shape Signatures dopamine receptors scoring functions

来源：评论

学校读者我要写书评

暂无评论

Comparison of structure-based and threading-based approaches to protein functional annotation

引用

PROTEINS-structure FUNCTION AND BIOINFORMATICS 2010年第1期78卷 118-134页

作者： Brylinski, Michal Skolnick, Jeffrey Georgia Inst Technol Ctr Study Syst Biol Sch Biol Atlanta GA 30318 USA

To exploit the vast amount of sequence information provided by the Genomic revolution, the biological function of these sequences must be identified. As a practical matter, this is often accomplished by functional inference. Purely sequence-based approaches, particularly in the "twilight zone" of low sequence similarity levels, are complicated by many factors. For proteins, structure-based techniques aim to overcome these problems;however, most require high-quality crystal structures and suffer from complex and equivocal relations between protein fold and function. In this study, in extensive benchmarking, we consider a number of aspects of structure-based functional annotation: binding pocket detection, molecular function assignment and ligand-based virtual screening. We demonstrate that protein threading driven by a strong sequence profile component greatly improves the quality of purely structure-based functional annotation in the "twilight zone." By detecting evolutionarily related proteins, it considerably reduces the high false positive rate of function inference derived on the basis of global structure similarity alone. Combined evolution/structure-based function assignment emerges as a powerful technique that can make a significant contribution to comprehensive proteome annotation.

关键词： binding pocket detection gene ontology molecular function protein function annotation protein threading sequence-based methods structure-based methods virtual screening

来源：评论

学校读者我要写书评

暂无评论

Computational modeling in glioblastoma: from the prediction of blood-brain barrier permeability to the simulation of tumor behavior

引用

FUTURE MEDICINAL CHEMISTRY 2018年第1期10卷 121-131页

作者： Miranda, Ana Cova, Tania Sousa, Joao Vitorino, Carla Pais, Alberto Univ Coimbra Fac Pharm Pharmaceut Technol Dept Polo Ciencias Saude P-3000548 Coimbra Portugal Univ Coimbra Fac Med Ctr Neurosci & Cell Biol CNC Pharmacometr Grp Rua LargaPolo 11st Floor P-3004504 Coimbra Portugal Univ Coimbra Dept Chem Coimbra Chem Ctr Rua Larga P-3004535 Coimbra Portugal

The integrated in silico-in vitro-in vivo approaches have fostered the development of new treatment strategies for glioblastoma patients and improved diagnosis, establishing the bridge between biochemical research and clinical practice. These approaches have provided new insights on the identification of bioactive compounds and on the complex mechanisms underlying the interactions among glioblastoma cells, and the tumor microenvironment. This review focuses on the key advances pertaining to computational modeling in glioblastoma, including predictive data on drug permeability across the blood-brain barrier, tumor growth and treatment responses. structure-and ligand-based methods have been widely adopted, enabling the study of dynamic and evolutionary aspects of glioblastoma. Their potential applications as predictive tools and the advantages over other well-known methodologies are outlined. Challenges regarding in silico approaches for predicting tumor properties are also discussed.

关键词： blood-brain barrier cancer treatment computational modeling glioblastoma ligand-based methods structure-based methods

来源：评论

学校读者我要写书评

暂无评论

Role of Computational methods in Pharmaceutical Sciences

Role of Computational Methods in Pharmaceutical Sciences

引用

作者： Sandhya Kortagere Markus LillJohn Kerrigan

Over the past two decades computational methods have eased up the financial and experimental burden of early drug discovery process. The in silico methods have provided support in terms of databases, data mining of large genomes, network analysis, systems biology on the bioinformatics front and structure–activity relationship, similarity analysis, docking, and pharmacophore methods for lead design and optimization. This review highlights some of the applications of bioinformatics and chemoinformatics methods that have enriched the field of drug discovery. In addition, the review also provided insights into the use of free energy perturbation methods for efficiently computing binding energy. These in silico methods are complementary and can be easily integrated into the traditional in vitro and in vivo methods to test pharmacological hypothesis. less

关键词： Protein structure Prediction Virtual Screening Data Mining Bioinformatics Systems biology Chemoinformatics Protein–protein interactions Drug design Protein networks Docking and scoring Homology models ADME/Tox Ligand-based methods structure-based methods PK–PD modeling

来源：评论

学校读者我要写书评

暂无评论

Virtual Screening in Drug Design

Virtual Screening in Drug Design

引用

作者： Markus Lill

Virtual screening has become a standard tool in drug discovery to identify novel lead compounds that target a biomolecule of interest. I present several concepts in ligand-based and structure-based virtual screening and discuss some of the current shortcomings and new developments. I also highlight approaches that combine concepts from structure- and ligand-based design. less

关键词： Virtual Screening Machine Learning Similarity Protein flexibility Drug design Docking and scoring Ligand-based methods structure-based methods Shape matching

来源：评论

学校读者我要写书评

暂无评论

Finding and Characterizing Repeats in Plant Genomes

Finding and Characterizing Repeats in Plant Genomes

引用

作者： Jacques Nicolas Sébastien Tempel Anna-Sophie Fiston-Lavier Emira Cherif

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of the available software that can help biologists to scan automatically for these repeats in sequence data or check hypothetical models intended to characterize their structures. Since transposable elements (TEs) are a major source of repeats in plants, many methods have been used or developed for this broad class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided two sections on this topic (for the analysis of genomes or directly of sequenced reads), as well as a selection of the main existing software. It may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of an efficient search for repeats and more complex patterns. We first introduce the key concepts of the art of indexing and mapping or querying sequences. We end the chapter with the more prospective issue of building models of repeat families. We present the Machine Learning approach first, seeking to build predictors automatically for some families of ET, from a set of sequences known to belong to this family. A second approach, the linguistic (or syntactic) approach, allows biologists to describe themselves and check the validity of models of their favorite repeat family. less

关键词： Machine Learning Mapping Transposon Repeats Indexing Pattern matching structure-based methods Homology-based Algorithmics on words

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：