Defining and Exploring Chemical Spaces
Designing functional molecules with desirable properties is often a challenging, multi-objective optimization. For decades, there have been computational approaches to facilitate this process through the simulation of physical processes, the prediction of molecular properties using structure–propert...
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/131238 |
| _version_ | 1826213903906897920 |
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| author | Coley, Connor Wilson |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Coley, Connor Wilson |
| author_sort | Coley, Connor Wilson |
| collection | MIT |
| description | Designing functional molecules with desirable properties is often a challenging, multi-objective optimization. For decades, there have been computational approaches to facilitate this process through the simulation of physical processes, the prediction of molecular properties using structure–property relationships, and the selection or generation of molecular structures. This review provides an overview of some algorithmic approaches to defining and exploring chemical spaces that have the potential to operationalize the process of molecular discovery. We emphasize the potential roles of machine learning and the consideration of synthetic feasibility, which is a prerequisite to ‘closing the loop’. We conclude by summarizing important directions for the future development and evaluation of these methods. |
| first_indexed | 2024-09-23T15:56:41Z |
| format | Article |
| id | mit-1721.1/131238 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:56:41Z |
| publishDate | 2021 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1312382022-10-02T05:14:25Z Defining and Exploring Chemical Spaces Coley, Connor Wilson Massachusetts Institute of Technology. Department of Chemical Engineering Designing functional molecules with desirable properties is often a challenging, multi-objective optimization. For decades, there have been computational approaches to facilitate this process through the simulation of physical processes, the prediction of molecular properties using structure–property relationships, and the selection or generation of molecular structures. This review provides an overview of some algorithmic approaches to defining and exploring chemical spaces that have the potential to operationalize the process of molecular discovery. We emphasize the potential roles of machine learning and the consideration of synthetic feasibility, which is a prerequisite to ‘closing the loop’. We conclude by summarizing important directions for the future development and evaluation of these methods. 2021-09-03T15:28:40Z 2021-09-03T15:28:40Z 2021-02 2020-11 2021-09-03T14:49:31Z Article http://purl.org/eprint/type/JournalArticle 2589-5974 https://hdl.handle.net/1721.1/131238 Coley, Connor W. "Defining and Exploring Chemical Spaces." Trends in Chemistry 3, 2 (February 2021): 133-145. © 2020 Elsevier Inc. en http://dx.doi.org/10.1016/j.trechm.2020.11.004 Trends in Chemistry Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Elsevier |
| spellingShingle | Coley, Connor Wilson Defining and Exploring Chemical Spaces |
| title | Defining and Exploring Chemical Spaces |
| title_full | Defining and Exploring Chemical Spaces |
| title_fullStr | Defining and Exploring Chemical Spaces |
| title_full_unstemmed | Defining and Exploring Chemical Spaces |
| title_short | Defining and Exploring Chemical Spaces |
| title_sort | defining and exploring chemical spaces |
| url | https://hdl.handle.net/1721.1/131238 |
| work_keys_str_mv | AT coleyconnorwilson definingandexploringchemicalspaces |