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Recent Advances Of The Fragment Molecular Orbital Method Enhanced Performance And Applicability Yuji Mochizuki

  • SKU: BELL-50318604
Recent Advances Of The Fragment Molecular Orbital Method Enhanced Performance And Applicability Yuji Mochizuki
$ 31.00 $ 45.00 (-31%)

4.0

6 reviews

Recent Advances Of The Fragment Molecular Orbital Method Enhanced Performance And Applicability Yuji Mochizuki instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 24.59 MB
Pages: 605
Author: Yuji Mochizuki, Shigenori Tanaka, Kaori Fukuzawa
ISBN: 9789811592348, 9811592349
Language: English
Year: 2021

Product desciption

Recent Advances Of The Fragment Molecular Orbital Method Enhanced Performance And Applicability Yuji Mochizuki by Yuji Mochizuki, Shigenori Tanaka, Kaori Fukuzawa 9789811592348, 9811592349 instant download after payment.

This book covers recent advances of the fragment molecular orbital (FMO) method, consisting of 5 parts and a total of 30 chapters written by FMO experts. The FMO method is a promising way to calculate large-scale molecular systems such as proteins in a quantum mechanical framework. The highly efficient parallelism deserves being considered the principal advantage of FMO calculations. Additionally, the FMO method can be employed as an analysis tool by using the inter-fragment (pairwise) interaction energies, among others, and this feature has been utilized well in biophysical and pharmaceutical chemistry. In recent years, the methodological developments of FMO have been remarkable, and both reliability and applicability have been enhanced, in particular, for non-bio problems. The current trend of the parallel computing facility is of the many-core type, and adaptation to modern computer environments has been explored as well. In this book, a historical review of FMO and comparison to other methods are provided in Part I (two chapters) and major FMO programs (GAMESS-US, ABINIT-MP, PAICS and OpenFMO) are described in Part II (four chapters). dedicated to pharmaceutical activities (twelve chapters). A variety of new applications with methodological breakthroughs are introduced in Part IV (six chapters). Finally, computer and information science-oriented topics including massively parallel computation and machine learning are addressed in Part V (six chapters). Many color figures and illustrations are included. Readers can refer to this book in its entirety as a practical textbook of the FMO method or read only the chapters of greatest interest to them.

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