Editorial: High Performance Computing in Drug Discovery

2016 ◽  
Vol 17 (14) ◽  
pp. 1578-1579
Author(s):  
Horacio Pérez-Sánchez ◽  
Sandra Gesing ◽  
Ivan Merelli
2020 ◽  
Vol 15 (9) ◽  
pp. 981-985
Author(s):  
Savíns Puertas-Martín ◽  
Antonio J. Banegas-Luna ◽  
María Paredes-Ramos ◽  
Juana L. Redondo ◽  
Pilar M. Ortigosa ◽  
...  

ChemInform ◽  
2008 ◽  
Vol 39 (29) ◽  
Author(s):  
Drew Bullard ◽  
Alberto Gobbi ◽  
Matthew A. Lardy ◽  
Charles Perkins ◽  
Zach Little

2016 ◽  
Vol 3 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Tingting Liu ◽  
Dong Lu ◽  
Hao Zhang ◽  
Mingyue Zheng ◽  
Huaiyu Yang ◽  
...  

Abstract In recent decades, high-performance computing (HPC) technologies and supercomputers in China have significantly advanced, resulting in remarkable achievements. Computational drug discovery and design, which is based on HPC and combines pharmaceutical chemistry and computational biology, has become a critical approach in drug research and development and is financially supported by the Chinese government. This approach has yielded a series of new algorithms in drug design, as well as new software and databases. This review mainly focuses on the application of HPC to the fields of drug discovery and molecular simulation at the Chinese Academy of Sciences, including virtual drug screening, molecular dynamics simulation, and protein folding. In addition, the potential future application of HPC in precision medicine is briefly discussed.


2008 ◽  
Vol 48 (4) ◽  
pp. 811-816 ◽  
Author(s):  
Drew Bullard ◽  
Alberto Gobbi ◽  
Matthew A. Lardy ◽  
Charles Perkins ◽  
Zach Little

MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon

Recent events in the high-performance computing industry have concerned scientists and the general public regarding a crisis or a lack of leadership in the field. That concern is understandable considering the industry's history from 1993 to 1996. Cray Research, the historic leader in supercomputing technology, was unable to survive financially as an independent company and was acquired by Silicon Graphics. Two ambitious new companies that introduced new technologies in the late 1980s and early 1990s—Thinking Machines and Kendall Square Research—were commercial failures and went out of business. And Intel, which introduced its Paragon supercomputer in 1994, discontinued production only two years later.During the same time frame, scientists who had finished the laborious task of writing scientific codes to run on vector parallel supercomputers learned that those codes would have to be rewritten if they were to run on the next-generation, highly parallel architecture. Scientists who are not yet involved in high-performance computing are understandably hesitant about committing their time and energy to such an apparently unstable enterprise.However, beneath the commercial chaos of the last several years, a technological revolution has been occurring. The good news is that the revolution is over, leading to five to ten years of predictable stability, steady improvements in system performance, and increased productivity for scientific applications. It is time for scientists who were sitting on the fence to jump in and reap the benefits of the new technology.


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