Exploring different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors

ABSTRACT

Histone deacetylase 3 (HDAC3), a Zn²⁺-dependent class I HDACs, contributes to numerous disorders such as neurodegenerative disorders, diabetes, cardiovascular disease, kidney disease and several types of cancers. Therefore, the development of novel and selective HDAC3 inhibitors might be promising to combat such diseases. Here, different classification-based molecular modelling studies such as Bayesian classification, recursive partitioning (RP), SARpy and linear discriminant analysis (LDA) were conducted on a set of HDAC3 inhibitors to pinpoint essential structural requirements contributing to HDAC3 inhibition followed by molecular docking study and molecular dynamics (MD) simulation analyses. The current study revealed the importance of hydroxamate function for Zn²⁺ chelation as well as hydrogen bonding interaction with Tyr298 residue. The importance of hydroxamate function for higher HDAC3 inhibition was noticed in the case of Bayesian classification, recursive partitioning and SARpy models. Also, the importance of substituted thiazole ring was revealed, whereas the presence of linear alkyl groups with carboxylic acid function, any type of ester function, benzodiazepine moiety and methoxy group in the molecular structure can be detrimental to HDAC3 inhibition. Therefore, this study can aid in the design and discovery of effective novel HDAC3 inhibitors in the future.

KEYWORDS:

• HDAC3 inhibitor
• recursive partitioning
• Bayesian classification
• SARpy
• LDA
• molecular docking

Acknowledgements

RJ is thankful to the AICTE for providing a scholarship. SB is thankful to the Swami Vivekananda Merit-cum-Means (SVMCM) scholarship, Govt. of West Bengal, India, for awarding the fellowship. BG is thankful to the Department of Health Research, India (File No. 11013_33_2021-GIA HR), Govt. of India and Council of Scientific and Industrial Research (CSIR-37(1722)/19/EMR-II), Govt. of India, for providing research grants. The authors are thankful to the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India and the Department of Pharmacy, BITS-Pilani Hyderabad Campus, Shamirpet, Hyderabad, India, for proving the necessary research Facilities.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2024.2350504.

Additional information

Funding

The work was supported by the All India Council for Technical Education and Council of Scientific and Industrial Research, India [CSIR-37(1722)/19/EMR-II]; Department of Health Research, India [11013_33_2021-GIA HR].