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Article

Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines

by
Alejandro Speck-Planche
* and
M. Natália D. S. Cordeiro
LAQV/REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(23), 11453; https://doi.org/10.3390/ijms262311453
Submission received: 3 November 2025 / Revised: 24 November 2025 / Accepted: 25 November 2025 / Published: 26 November 2025
(This article belongs to the Special Issue In Silico Approaches to Drug Design and Discovery)

Abstract

Colorectal cancer is one of the most dangerous neoplastic diseases in terms of both mortality and incidence. Thus, anti-colorectal cancer agents are urgently needed. Computational approaches have great potential to accelerate the phenotypic discovery of versatile anticancer agents. Here, by combining perturbation-theory machine learning (PTML) modeling with the fragment-based topological design (FBTD) approach, we provide key computational evidence on the computer-aided de novo design and prediction of new molecules virtually exhibiting multi-cell inhibitory activity against different colorectal cancer cell lines. The PTML model created in this study achieved sensitivity and specificity values exceeding 80% in training and test sets. The FBTD approach was employed to physicochemically and structurally interpret the PTML model. These interpretations enabled the rational design of six new drug-like molecules, which were predicted as active against multiple colorectal cancer cell lines by both our PTML model and a CLC-Pred 2.0 webserver, with the latter being a well-established virtual screening tool for early anticancer discovery. This work confirms the potential of the joint use of PTML and FBTD as a unified computational methodology for early phenotypic anticancer drug discovery.
Keywords: PTML; topological indices; multilayer perceptron; fragment; fragment-based topological design; colorectal cancer PTML; topological indices; multilayer perceptron; fragment; fragment-based topological design; colorectal cancer

Share and Cite

MDPI and ACS Style

Speck-Planche, A.; Cordeiro, M.N.D.S. Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines. Int. J. Mol. Sci. 2025, 26, 11453. https://doi.org/10.3390/ijms262311453

AMA Style

Speck-Planche A, Cordeiro MNDS. Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines. International Journal of Molecular Sciences. 2025; 26(23):11453. https://doi.org/10.3390/ijms262311453

Chicago/Turabian Style

Speck-Planche, Alejandro, and M. Natália D. S. Cordeiro. 2025. "Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines" International Journal of Molecular Sciences 26, no. 23: 11453. https://doi.org/10.3390/ijms262311453

APA Style

Speck-Planche, A., & Cordeiro, M. N. D. S. (2025). Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines. International Journal of Molecular Sciences, 26(23), 11453. https://doi.org/10.3390/ijms262311453

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