Titlebook: Current Trends in Computational Modeling for Drug Discovery; Supratik Kar,Jerzy Leszczynski Book 2023 The Editor(s) (if applicable) and Th

口语

书目名称Current Trends in Computational Modeling for Drug Discovery影响因子(影响力)




书目名称Current Trends in Computational Modeling for Drug Discovery影响因子(影响力)学科排名




书目名称Current Trends in Computational Modeling for Drug Discovery网络公开度




书目名称Current Trends in Computational Modeling for Drug Discovery网络公开度学科排名




书目名称Current Trends in Computational Modeling for Drug Discovery被引频次




书目名称Current Trends in Computational Modeling for Drug Discovery被引频次学科排名




书目名称Current Trends in Computational Modeling for Drug Discovery年度引用




书目名称Current Trends in Computational Modeling for Drug Discovery年度引用学科排名




书目名称Current Trends in Computational Modeling for Drug Discovery读者反馈




书目名称Current Trends in Computational Modeling for Drug Discovery读者反馈学科排名

Delude

https://doi.org/10.1007/978-3-658-10567-9y the long process of drug design and discovery, and to optimize the selection of preferable features present in a new pharmaceutical. In this new vision, a more holistic approach can apply multiple methodologies and not only the screening of the adverse effects.

Filibuster

Computational Toxicological Aspects in Drug Design and Discovery, Screening Adverse Effects,y the long process of drug design and discovery, and to optimize the selection of preferable features present in a new pharmaceutical. In this new vision, a more holistic approach can apply multiple methodologies and not only the screening of the adverse effects.

Enervate

魅力

预示

预示

https://doi.org/10.1007/978-3-658-10567-9ter, we provide an overview of computational SBDD workflow, and the various challenges associated with it. We also discuss strategies that could be adopted to tackle the challenges by making the best use of available information.

伪书

constitute

SBDD and Its Challenges,ter, we provide an overview of computational SBDD workflow, and the various challenges associated with it. We also discuss strategies that could be adopted to tackle the challenges by making the best use of available information.

abstemious

In Silico Discovery of Class IIb HDAC Inhibitors: The State of Art,in silico studies including the virtual screening approaches have been implemented to design HDAC6 and HDAC10 inhibitors. In addition, the interactions of class IIb HDACs with their inhibitors are also highlighted extensively to get a detail insight. This chapter offers understanding for designing newer class IIb HDAC inhibitors in future.