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

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

SUBMITTER: Speck-Planche A 

PROVIDER: S-EPMC12692404 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature