Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977 (2026) IUPAC-induced computational approaches for identifying boosters of small biomolecule functionality: A case study of human tyrosyl-DNA phosphodiesterase 1 (TDP1) inhibitors. Computers in Biology and Medicine, 204.

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Abstract

This paper introduces several proof-of-concept (PoC) computational methods intended to offer biochemical researchers straightforward, time- and cost-effective strategies to accelerate their work. While Machine Learning (ML) models were developed, the study's central purpose was to explore approaches for the identification of desirable functional groups/fragments in small biomolecules regarding a specific functionality, which, in this case, was human tyrosyl-DNA phosphodiesterase 1 (TDP1) inhibition. This was achieved primarily by tokenising IUPAC names to generate features. Additionally, the applicability of the CID_SID ML model for predicting TDP1 activity was developed and explored. Since these computational approaches were not experimentally validated due to a lack of appropriate laboratory facilities, they are presented as open proposals for further laboratory investigation.

Item Type:	Article
Keywords:	scikit-learn, PubChem, HTS, bioassay, CID_SID ML model
Subjects:	Computing > Intelligent systems Medicine and health
Date Deposited:	17 Sep 2025
URI:	https://repository.uwl.ac.uk/id/eprint/14074

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