語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Current trends in computational mode...
~
Kar, Supratik.
FindBook
Google Book
Amazon
博客來
Current trends in computational modeling for drug discovery
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Current trends in computational modeling for drug discovery/ edited by Supratik Kar, Jerzy Leszczynski.
其他作者:
Kar, Supratik.
出版者:
Cham :Springer International Publishing : : 2023.,
面頁冊數:
xv, 301 p. :ill. (some col.), digital ;24 cm.
內容註:
SBDD and its challenges -- In silico discovery of class IIb HDAC inhibitors: The state of art -- Role of computational modelling in drug discovery for Alzheimer's disease -- Computational Modeling in the Development of Antiviral Agents -- Targeted computational approaches to identify potential inhibitors for Nipah virus -- Role of Computational Modelling in Drug Discovery for HIV -- Recent insight of the emerging severe fever with thrombocytopenia syndrome virus: drug discovery, therapeutic options, and limitations -- Computational toxicological aspects in drug design and discovery, screening adverse effects -- Read-Across and RASAR tools from the DTC Laboratory -- Databases for Drug Discovery and Development.
Contained By:
Springer Nature eBook
標題:
Drug development - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-031-33871-7
ISBN:
9783031338717
Current trends in computational modeling for drug discovery
Current trends in computational modeling for drug discovery
[electronic resource] /edited by Supratik Kar, Jerzy Leszczynski. - Cham :Springer International Publishing :2023. - xv, 301 p. :ill. (some col.), digital ;24 cm. - Challenges and advances in computational chemistry and physics,v. 352542-4483 ;. - Challenges and advances in computational chemistry and physics ;v. 35..
SBDD and its challenges -- In silico discovery of class IIb HDAC inhibitors: The state of art -- Role of computational modelling in drug discovery for Alzheimer's disease -- Computational Modeling in the Development of Antiviral Agents -- Targeted computational approaches to identify potential inhibitors for Nipah virus -- Role of Computational Modelling in Drug Discovery for HIV -- Recent insight of the emerging severe fever with thrombocytopenia syndrome virus: drug discovery, therapeutic options, and limitations -- Computational toxicological aspects in drug design and discovery, screening adverse effects -- Read-Across and RASAR tools from the DTC Laboratory -- Databases for Drug Discovery and Development.
This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques, theories, protocols, databases, and tools employed in computer-aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure-Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer's disease (AD), antiviral agents, anti-human immunodeficiency virus (HIV) drugs, and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery, screening adverse effects, and existing or future in silico tools are highlighted, while a novel in silico tool, RASAR, which can be a major technique for small to big datasets when not much experimental data are present, is presented. The book also introduces the reader to the major drug databases covering drug molecules, chemicals, therapeutic targets, metabolomics, and peptides, which are great resources for drug discovery employing drug repurposing, high throughput, and virtual screening. This volume is a great tool for graduates, researchers, academics, and industrial scientists working in the fields of cheminformatics, bioinformatics, computational biology, and chemistry.
ISBN: 9783031338717
Standard No.: 10.1007/978-3-031-33871-7doiSubjects--Topical Terms:
1965635
Drug development
--Data processing.
LC Class. No.: RM301.25
Dewey Class. No.: 615.190113
Current trends in computational modeling for drug discovery
LDR
:03291nmm a2200337 a 4500
001
2331999
003
DE-He213
005
20230630144358.0
006
m d
007
cr nn 008maaau
008
240402s2023 sz s 0 eng d
020
$a
9783031338717
$q
(electronic bk.)
020
$a
9783031338700
$q
(paper)
024
7
$a
10.1007/978-3-031-33871-7
$2
doi
035
$a
978-3-031-33871-7
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
RM301.25
072
7
$a
PNRP
$2
bicssc
072
7
$a
SCI013050
$2
bisacsh
072
7
$a
PNRP
$2
thema
082
0 4
$a
615.190113
$2
23
090
$a
RM301.25
$b
.C976 2023
245
0 0
$a
Current trends in computational modeling for drug discovery
$h
[electronic resource] /
$c
edited by Supratik Kar, Jerzy Leszczynski.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2023.
300
$a
xv, 301 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Challenges and advances in computational chemistry and physics,
$x
2542-4483 ;
$v
v. 35
505
0
$a
SBDD and its challenges -- In silico discovery of class IIb HDAC inhibitors: The state of art -- Role of computational modelling in drug discovery for Alzheimer's disease -- Computational Modeling in the Development of Antiviral Agents -- Targeted computational approaches to identify potential inhibitors for Nipah virus -- Role of Computational Modelling in Drug Discovery for HIV -- Recent insight of the emerging severe fever with thrombocytopenia syndrome virus: drug discovery, therapeutic options, and limitations -- Computational toxicological aspects in drug design and discovery, screening adverse effects -- Read-Across and RASAR tools from the DTC Laboratory -- Databases for Drug Discovery and Development.
520
$a
This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The different chapters deal with the classical and most advanced techniques, theories, protocols, databases, and tools employed in computer-aided drug design (CADD) covering diverse therapeutic classes. Multiple components of Structure-Based Drug Discovery (SBDD) along with its workflow and associated challenges are presented while potential leads for Alzheimer's disease (AD), antiviral agents, anti-human immunodeficiency virus (HIV) drugs, and leads for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) disease are discussed in detail. Computational toxicological aspects in drug design and discovery, screening adverse effects, and existing or future in silico tools are highlighted, while a novel in silico tool, RASAR, which can be a major technique for small to big datasets when not much experimental data are present, is presented. The book also introduces the reader to the major drug databases covering drug molecules, chemicals, therapeutic targets, metabolomics, and peptides, which are great resources for drug discovery employing drug repurposing, high throughput, and virtual screening. This volume is a great tool for graduates, researchers, academics, and industrial scientists working in the fields of cheminformatics, bioinformatics, computational biology, and chemistry.
650
0
$a
Drug development
$x
Data processing.
$3
1965635
650
0
$a
Drug development
$x
Computer simulation.
$3
768310
650
1 4
$a
Structure-Based Drug Design.
$3
3538435
650
2 4
$a
Molecular Modelling.
$3
3661500
650
2 4
$a
Computational Chemistry.
$3
3595554
650
2 4
$a
Medicinal Chemistry.
$3
892420
650
2 4
$a
Pharmacology.
$3
634543
700
1
$a
Kar, Supratik.
$3
2145303
700
1
$a
Leszczynski, Jerzy.
$3
1067151
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Challenges and advances in computational chemistry and physics ;
$v
v. 35.
$3
3661499
856
4 0
$u
https://doi.org/10.1007/978-3-031-33871-7
950
$a
Chemistry and Materials Science (SpringerNature-11644)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9458204
電子資源
11.線上閱覽_V
電子書
EB RM301.25
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入