Defining and Exploring Chemical Spaces
Name
Defining and Exploring - Coley.pdf
Description
Accepted version
Size
1.65 MB
Format
Adobe PDF
Checksum (MD5)
5bb46e14ca1711c2ad99b664e79d4a6b
Author(s)
Coley, Connor Wilson
Date Issued
February 2021
Journal
Trends in Chemistry
Publisher
Elsevier BV
Citation
Coley, Connor W. "Defining and Exploring Chemical Spaces." Trends in Chemistry 3, 2 (February 2021): 133-145. © 2020 Elsevier Inc.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.trechm.2020.11.004
