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Structure-Based Design of Potential Anti-schistosomiasis Agent Targeting SmHDAC8: An In Silico Approach Utilizing QSAR, MD Simulation and ADMET Prediction

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Abstract

Due to the increasing emergences of drug resistance, there is a need to discover new drugs that can target Schistosoma mansoni histone deacetylase 8 (SmHDAC8) and effectively combat Schistosomiasis. In view of this, an in-silico approach was employed to identify potential inhibitors by evaluating the binding energy and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties of SmHDAC8 inhibitors. Employing density functional theory (DFT) calculations with the B3LYP/6-311G* as basis set, the optimal configuration of SmHDAC8 inhibitors was established, and a quantitative structure activity relationship (QSAR) model was constructed utilizing a combined genetic function approximation and multilinear regression (GFA-MLR) methodology. The selected model demonstrated strong statistical parameters, including R2 of 0.896, \({\text{R}}_{{{\text{adj}}}}^{2}\) of 0.877, \({\text{Q}}_{{{\text{cv}}}}^{2}\) of 0.863, \({\text{R}}_{{{\text{test}}}}^{2}\) of 0.662, and \({\text{cR}}_{{\text{p}}}^{2}\) of 0.747, confirming its reliability. Molecular docking screening was then utilized to position the derivatives into the active site of the SmHDAC8 target (PDB ID: 4BZ8). This analysis revealed Compound 26 as a highly promising lead candidate, displaying a MolDock score of − 137.103 kcal/mol. Four novel compounds were designed, showing improved binding affinities (− 151.376 to − 154.777 kcal/mol) and predicted activities (6.928 – 7.060) compared to the lead compound and standard drug, PZQ. Further validation was conducted through molecular dynamics (MD) simulations on compound 26d, confirming the stability and integrity of the docked complex. Additionally, an assessment of drug-likeness and ADMET properties indicated favorable pharmacokinetic profiles for the designed analogs, with no violations of Lipinski's rule of five. These newly designed derivatives hold promise as novel agents for the treatment of Schistosomiasis.

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Data Availability

All data generated or analyzed during this study are included in this published article.

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Acknowledgements

The authors acknowledge the Ahmadu Bello University, Zaria-Nigeria for providing the soft wares adopted in this research and all the members of the Chemistry department for their kind advice and encouragement.

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Authors and Affiliations

  1. Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria

    Saudatu Chinade Ja’afaru, Adamu Uzairu, Muhammed Sani Sallau, George Iloegbulam Ndukwe, Muhammad Tukur Ibrahim & Ammar Usman Danazumi

  2. Department of Chemistry, Aliko Dangote University of Science and Technology, Wudil, Kano, Nigeria

    Saudatu Chinade Ja’afaru

  3. Department of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland

    Ammar Usman Danazumi

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  1. Saudatu Chinade Ja’afaru
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  2. Adamu Uzairu
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Contributions

SCJ: designed, performed the study, interpreted the results and wrote the manuscript. AU: interpreted the results and edited the manuscript, MSS: interpreted the results and edited the manuscript, GIN: interpreted the results and edited the manuscript, MTI: interpreted the results and edited the manuscript, AUD: molecular dynamic simulations and interpretation of results.

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Correspondence to Saudatu Chinade Ja’afaru.

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Ja’afaru, S.C., Uzairu, A., Sallau, M.S. et al. Structure-Based Design of Potential Anti-schistosomiasis Agent Targeting SmHDAC8: An In Silico Approach Utilizing QSAR, MD Simulation and ADMET Prediction. Chemistry Africa 7, 725–745 (2024). https://doi.org/10.1007/s42250-023-00777-2

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