https://doi.org/10.7490/f1000research.1112285.1
Slides
NOT PEER REVIEWED
Download
metrics
VIEWS
399
 
downloads
368
CITE
How to cite these slides:
Miao Y. Gaussian accelerated Molecular Dynamics (GaMD): unconstrained enhanced simulations for drug discovery [version 1; not peer reviewed]. F1000Research 2016, 5:1324 (slides) (https://doi.org/10.7490/f1000research.1112285.1)
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

Gaussian accelerated Molecular Dynamics (GaMD): unconstrained enhanced simulations for drug discovery

Author Affiliations
  • Metrics
  • 399 Views
  • 368 Downloads
Browse by related subjects
Published 10 Jun 2016

Gaussian accelerated Molecular Dynamics (GaMD): unconstrained enhanced simulations for drug discovery

[version 1; not peer reviewed]

Author Affiliations
1 Howard Hughes Medical Institute, UCSD, USA
Presented at
2016 Workshop on Free Energy Methods in Drug Design: Targeting Cancer
Abstract
Competing Interests

No competing interests were disclosed

Keywords
Gaussian Accelerated Molecular Dynamics, Enhanced Sampling, Free Energy, Drug Binding.
Comments
0 Comments
 
Sign In
If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password.

The email address should be the one you originally registered with F1000.

Email address not valid, please try again

You registered with F1000 via Google, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Google account password, please click here.

You registered with F1000 via Facebook, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Facebook account password, please click here.

Code not correct, please try again
Email us for further assistance.
Server error, please try again.