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All Journal Journal of Pharmascience Journal of Pharmaceutical Sciences and Community
Bonifacius Ivan Wiranata
Pharmaceutical Sciences Department, Faculty of Pharmacy, Widya Mandala Catholic University, Surabaya, Indonesia

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Integrative Study on the Binding Energy Calculation: Molecular Docking and Molecular Mechanics with Generalized Born Surface Area Targeting Acetylcholinesterase Ignasius Widya Parahita Putranto; Bonifacius Ivan Wiranata; Enade Perdana Istyastono; Florentinus Dika Octa Riswanto
Journal of Pharmascience Vol. 13 No. 1 (2026): Jurnal Pharmascience
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jps.v13i1.24094

Abstract

Alzheimer's disease (AD) imposes a significant global financial burden. Previous studies have reported that acetylcholinesterase (AChE) activity is strongly associated with AD, making it a key target in therapeutic research. Molecular docking and computational techniques are increasingly used to study these associations, yet a surge in publications has led to a departure from strictly designed paradigms. This study evaluates the accuracy of the Gibbs free energy of binding (ΔG) from molecular docking scores, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), and local Vina scores. The Spearman rank test was applied to compare ΔG predictions and the in vitro results from our previous study. The correlation coefficient for molecular docking was -0.491, the MM/GBSA correlation coefficient calculated at the best molecular docking pose was -0.309, the MM/GBSA correlation coefficient calculated at the last 5 nanoseconds (ns) snapshots was 0.164, and the correlation coefficient of the Vina local score calculated at the last 5 ns snapshots was 0.273. Our findings indicate that the ΔG prediction from the Vina local score for the last 5 ns shows the strongest correlation with in vitro results.
Employing Ensemble Protein-Ligand Interaction Fingerprints to Mimic Induced-Fit Theory in Structure-Based Virtual Screening Targeting Dipeptidyl Peptidase IV Enade Perdana Istyastono; Bonifacius Ivan Wiranata; Florentinus D.O. Riswanto; Fransiska Kurniawan; Tasia Amelia; Nunung Yuniarti; Eko Adi Prasetyanto
Journal of Pharmaceutical Sciences and Community Vol. 23 No. 1 (2026)
Publisher : Sanata Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/jpsc.v23i1.1070

Abstract

We have successfully employed PyPLIF HIPPOS in retrospective Structure-Based Virtual Screening (SBVS) campaigns targeting some G-protein coupled receptors (GPCRs), which could pinpoint the molecular determinants of the protein-ligand bindings and increase the quality of the SBVS protocols. We were then tempted to append with molecular dynamics simulations using YASARA-Structure to mimic the induced-fit theory in the construction of SBVS protocols targeting dipeptidyl peptidase IV (DPP4). The protocol was retrospectively validated by employing the DPP4 ligands and decoys provided by the Directory of Useful Decoys: Enhanced (DUDE). The best SBVS protocol from this research has the balanced accuracy (BA) value of 0.836, which could be used further in prospective screening campaigns. 
Co-Authors Eko Adi Prasetyanto Enade Perdana Istyastono Enade Perdana Istyastono Florentinus D.O. Riswanto Florentinus Dika Octa Riswanto Fransiska Kurniawan Ignasius Widya Parahita Putranto Nunung Yuniarti Tasia Amelia