Hydrogen bond descriptors of hydroxamic acids for use in drug design: A 2DQSPR Approach using kNN

Hydroxamic acids, functionally –NOH.C=O, are associated with diverse biological activities, including antibacterial, antifungal, and antitumor properties. Hydrogen bonding is an important property in drug and xenobiotic interactions with biota, and numerous attempts have been made to quantify it for use in quantitative structure-activity relationships. This study aimed to investigate the lipophilicity and hydrogen bond strengths of hydroxamic acids and develop quantitative structure-property relationship (QSPR) models to predict theseproperties. Lipophilicity of five hydroxamic acids was experimentally determined using the shake flask method between octanol-water and chloroform-water systems. k-nearest neighbor quantitative structure-property relationship (kNN-QSPR) models were developed using Vlife MDS 3.0 software to predict hydrogen bond donor and acceptor strengths for a dataset of 29 hydroxamic acids. The observed lipophilicities of hydroxamic acids ranged from 2.337 to 2.829. The measured hydrogen bond donor (εα) and hydrogen bond acceptor () strengths ranged from 0.560 to 1.644 and 1.35 to 5.080, respectively. Statistically, the SWkNN (Stepwise variable selection k-nearest neighbor) QSPR model for hydrogen bond donor strength was comparatively better than the other two (i.e., simulated annealing k-nearest neighbor, SAkNN-QSPR, and genetic algorithm k-nearest neighbor, GAkNN-QSPR) with respect to internal (q2=0.7062) and external (pred_r2=0.5767) model validation. The SAkNN-QSPR model obtained for hydrogen bond acceptor strength was statistically better than the other two (i.e., SWkNN QSPR and GAkNN QSPR) with internal and predictivity with q2 of 0.6864 and external predictivity with a pred_r2 of 0.5238. The developed kNN QSPR models revealed that molecular descriptors such as electronegativity count (EH), SA most hydrophobic, molecular weight, volume, and quadrupole1 were favorable for the hydrogen bond strength of the hydroxamic acid moiety.

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Publication Details

Journal
International Journal of Biological and Chemical Sciences
Published
2025-08-22
DOI
https://doi.org/10.4314/ijbcs.v19i2.30
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Hydrogen bond descriptors of hydroxamic acids for use in drug design: A 2DQSPR Approach using kNN

Jena Diwan, Ram Prakash Rajwade
International Journal of Biological and Chemical Sciences
Computational Drug Discovery Methods
article

Hydrogen bond descriptors of hydroxamic acids for use in drug design: A 2DQSPR Approach using kNN

Jena Diwan, Ram Prakash Rajwade
article en

Abstract

Hydroxamic acids, functionally –NOH.C=O, are associated with diverse biological activities, including antibacterial, antifungal, and antitumor properties. Hydrogen bonding is an important property in drug and xenobiotic interactions with biota, and numerous attempts have been made to quantify it for use in quantitative structure-activity relationships. This study aimed to investigate the lipophilicity and hydrogen bond strengths of hydroxamic acids and develop quantitative structure-property relationship (QSPR) models to predict theseproperties. Lipophilicity of five hydroxamic acids was experimentally determined using the shake flask method between octanol-water and chloroform-water systems. k-nearest neighbor quantitative structure-property relationship (kNN-QSPR) models were developed using Vlife MDS 3.0 software to predict hydrogen bond donor and acceptor strengths for a dataset of 29 hydroxamic acids. The observed lipophilicities of hydroxamic acids ranged from 2.337 to 2.829. The measured hydrogen bond donor (εα) and hydrogen bond acceptor () strengths ranged from 0.560 to 1.644 and 1.35 to 5.080, respectively. Statistically, the SWkNN (Stepwise variable selection k-nearest neighbor) QSPR model for hydrogen bond donor strength was comparatively better than the other two (i.e., simulated annealing k-nearest neighbor, SAkNN-QSPR, and genetic algorithm k-nearest neighbor, GAkNN-QSPR) with respect to internal (q2=0.7062) and external (pred_r2=0.5767) model validation. The SAkNN-QSPR model obtained for hydrogen bond acceptor strength was statistically better than the other two (i.e., SWkNN QSPR and GAkNN QSPR) with internal and predictivity with q2 of 0.6864 and external predictivity with a pred_r2 of 0.5238. The developed kNN QSPR models revealed that molecular descriptors such as electronegativity count (EH), SA most hydrophobic, molecular weight, volume, and quadrupole1 were favorable for the hydrogen bond strength of the hydroxamic acid moiety.

International Journal of Biological and Chemical SciencesVol. 19(2)
Openalex Percentile: Top 73%
Computational Drug Discovery Methods
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