RRC ID 86063
Author Etezadi F, Ito S, Yasui K, Kado Abdalkader R, Minami I, Uesugi M, Ganesh Pandian N, Nakano H, Nakano A, Packwood DM.
Title Molecular Design for Cardiac Cell Differentiation Using a Small Data Set and Decorated Shape Features.
Journal J Chem Inf Model
Abstract The discovery of small organic compounds for inducing stem cell differentiation is a time- and resource-intensive process. While data science could, in principle, streamline the discovery of these compounds, novel approaches are required due to the difficulty of acquiring training data from large numbers of example compounds. In this paper, we present the design of a new compound for inducing cardiomyocyte differentiation using simple regression models trained with a data set containing only 80 examples. We introduce decorated shape descriptors, an information-rich molecular feature representation that integrates both molecular shape and hydrophilicity information. These models demonstrate improved performance compared to ones using standard molecular descriptors based on shape alone. Model overtraining is diagnosed using a new type of sensitivity analysis. Our new compound is designed using a conservative molecular design strategy, and its effectiveness is confirmed through expression profiles of cardiomyocyte-related marker genes using real-time polymerase chain reaction experiments on human iPS cell lines. This work demonstrates a viable data-driven strategy for designing new compounds for stem cell differentiation protocols and will be useful in situations where training data is limited.
Volume 64(23)
Pages 8824-8837
Published 2024-12-9
DOI 10.1021/acs.jcim.4c01353
PMID 39586080
MeSH Cell Differentiation* / drug effects Drug Design Humans Induced Pluripotent Stem Cells / cytology Induced Pluripotent Stem Cells / metabolism Myocytes, Cardiac* / cytology Myocytes, Cardiac* / metabolism Small Molecule Libraries / chemistry Small Molecule Libraries / pharmacology
Resource
Human and Animal Cells 253G1