This Virtual Special Issue will highlight the development and application of new Machine Learning-based methods for designing Coarse-Grained models of molecules, including large macromolecules. Submit your manuscript by March 15, 2025.

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Computer simulations, particularly molecular dynamics (MD) simulations, are effective tools for studying microscopic and dynamic details of complex systems in physicochemical and biological processes. Recent advancements in computer hardware and algorithms have significantly improved the efficiency of molecular dynamics methods, expanding their applicability to the treatment of large macromolecular assemblies as well as the understanding of intricate mechanisms of biomolecular processes.

Low resolution ‘Coarse-Grained’ models help address challenges to large system size and sampling issues by dramatically reducing the number of particles in a system. While a number of Machine Learning-Coarse Grained methods have shown proficiency in dealing with complex organic and biomolecules, others are still in their early stages of development.

If you are a researcher working on the development and application of new Machine Learning-based methods for designing Coarse-Grained models of molecules, Journal of Chemical Information and Modeling (JCIM) invites you to submit your manuscript to this upcoming Virtual Special Issue: Enhancing Coarse-Grained Models through Machine Learning. The deadline for submissions is March 15, 2025.

Learn more about the scope of this Virtual Special Issue from our journal Editors:

Organizing Editors

Dr. Kenneth M. Merz, Jr., Editor-in-Chief, JCIM
Michigan State University, United States (Email)

Dr. Thereza A. Soares, Executive Editor, JCIM
University of São Paulo, Brazil (Email)

Dr. Tarak Karmakar, Guest Editor
Indian Institute of Technology, India (Email)

Submission Information

Submissions are welcome through March 15, 2025.

If your paper is accepted for inclusion in this Virtual Special Issue, your work will be highlighted as a significant contribution to this field. If accepted, publications will go online as soon as possible and be published in the next available issue. Publications on this topic will be gathered into a Virtual Special Issue and widely promoted thereafter.

All articles will be peer reviewed prior to acceptance, to ensure they fit the scope of the Virtual Special Issue and meet the high scientific publishing standards of JCIM.

How to Submit

  • Log in to the ACS Paragon Plus submission site.
  • Choose Journal of Chemical Information and Modeling as your journal.
  • Select your manuscript type.
  • Under the ‘Special Issue Selection’, choose ‘Enhancing Coarse-Grained Models through Machine Learning.’

Please see the journal's Author Guidelines for more information on submission requirements.

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