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Computational Structural Biology: Successes, Future Directions, and Challenges
Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to g...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384756/ https://www.ncbi.nlm.nih.gov/pubmed/30759724 http://dx.doi.org/10.3390/molecules24030637 |
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author | Nussinov, Ruth Tsai, Chung-Jung Shehu, Amarda Jang, Hyunbum |
author_facet | Nussinov, Ruth Tsai, Chung-Jung Shehu, Amarda Jang, Hyunbum |
author_sort | Nussinov, Ruth |
collection | PubMed |
description | Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells’ actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions. |
format | Online Article Text |
id | pubmed-6384756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63847562019-02-23 Computational Structural Biology: Successes, Future Directions, and Challenges Nussinov, Ruth Tsai, Chung-Jung Shehu, Amarda Jang, Hyunbum Molecules Review Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells’ actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions. MDPI 2019-02-12 /pmc/articles/PMC6384756/ /pubmed/30759724 http://dx.doi.org/10.3390/molecules24030637 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Nussinov, Ruth Tsai, Chung-Jung Shehu, Amarda Jang, Hyunbum Computational Structural Biology: Successes, Future Directions, and Challenges |
title | Computational Structural Biology: Successes, Future Directions, and Challenges |
title_full | Computational Structural Biology: Successes, Future Directions, and Challenges |
title_fullStr | Computational Structural Biology: Successes, Future Directions, and Challenges |
title_full_unstemmed | Computational Structural Biology: Successes, Future Directions, and Challenges |
title_short | Computational Structural Biology: Successes, Future Directions, and Challenges |
title_sort | computational structural biology: successes, future directions, and challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384756/ https://www.ncbi.nlm.nih.gov/pubmed/30759724 http://dx.doi.org/10.3390/molecules24030637 |
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