QSAR-Guided In Silico Design of Piperazinylanthranilamide Factor Xa Inhibitors: Applicability-Domain Assessment, ADMET Profiling, Molecular Docking, Molecular Dynamics, and MM/GBSA
5 affiliations
- 1University of Health Sciences in Bydgoszcz, Jagiellońska 4 Str., 85-067 Bydgoszcz, Poland
- 2Department of Toxicology and Bromatology, Faculty of Pharmacy, L. Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, A. Jurasza 2 Street, 85-089 Bydgoszcz, Poland
- 3Doctoral School of Medical and Health Sciences, Ludwik Rydygier Collegium Medicum, Nicolaus Copernicus University in Toruń, Jagiellońska 13-15 Str., 85-067 Bydgoszcz, Poland
- 4Department of Pharmaceutical Chemistry and Biomaterials, Faculty of Pharmacy, Medical University of Warsaw, 1 Banacha Str., 02-093 Warsaw, Poland
- 5Department of Organic and Physical Chemistry, Medical University of Warsaw, 1 Banacha Str., 02-097 Warsaw, Poland
Abstract
An integrated computational workflow was developed to prioritize piperazinylanthranilamide factor Xa (FXa) inhibitor candidates. Twenty literature compounds were geometry-optimized and described using alvaDesc to construct a constrained additive multivariate adaptive regression splines model. Internal validation and an assessment of the applicability domain guided the evaluation of 20 prospective analogs. Ten selected analogs and two same-series references were docked to FXa, with apixaban as the crystallographic comparator. Thirteen initial 100 ns molecular dynamics simulations were supplemented by two independent runs for each of PAX-M09, PAX-M15, and PAX-M18. Binding energetics were assessed using molecular mechanics/generalized Born surface area (MM/GBSA), alongside in silico developability profiling. The model achieved R2 = 0.904 and an internal leave-one-out Q2 of 0.846. PAX-M09 was the strongest strict in-domain prediction, whereas PAX-M15 was borderline. Apixaban redocking yielded a root-mean-square deviation (RMSD) of 0.953 Å. Although PAX-M17 and PAX-M19 ranked highest in docking, subsequent analyses prioritized PAX-M15, PAX-M09, and PAX-M18. PAX-M15 showed the most consistent positional behavior across replicates and consistently favorable run-specific MM/GBSA estimates (−68.76, −70.11, and −69.42 kcal/mol). PAX-M09 and PAX-M18 showed greater between-run heterogeneity. Solubility, metabolic, and toxicity liabilities remained important. The results support experimental investigation of the three candidates without changing their applicability-domain classifications or establishing superior experimental potency.
Related
- Unrevealed oligoresveratrols from Shorea parvifolia root bark as xanthine oxidase inhibitors: isolation, in vitro bioassay, quantum studies and structure-based computational profiling
- Integrative proximity labeling and multiomic profiling uncover domain-specific interactomes and molecular vulnerabilities of oncogenic PI3K
- Does Short Molecular Dynamics Rescoring Improve the Ranking of p38α Inhibitors over Docking? A Replicate Benchmark
- Using the housekeeping gene cpn60 as a marker for microbial community profiling and viability assessment
- integrating single-cell transcriptomics and chromatin accessibility profiling to decipher the molecular landscape of Hepatocellular carcinoma
BibTeX
@article{gordon2026qsarguided,
title = {{QSAR-Guided In Silico Design of Piperazinylanthranilamide Factor Xa Inhibitors: Applicability-Domain Assessment, ADMET Profiling, Molecular Docking, Molecular Dynamics, and MM/GBSA}},
author = {Paweł Gordon and Michał Janiak and Marcin Gackowski and Monika Zielińska-Pisklak and Łukasz Szeleszczuk},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27209204},
url = {https://www.mdpi.com/1422-0067/27/20/9204},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - QSAR-Guided In Silico Design of Piperazinylanthranilamide Factor Xa Inhibitors: Applicability-Domain Assessment, ADMET Profiling, Molecular Docking, Molecular Dynamics, and MM/GBSA
AU - Paweł Gordon
AU - Michał Janiak
AU - Marcin Gackowski
AU - Monika Zielińska-Pisklak
AU - Łukasz Szeleszczuk
PY - 2026
DA - 2026/10/16
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27209204
UR - https://www.mdpi.com/1422-0067/27/20/9204
AB - An integrated computational workflow was developed to prioritize piperazinylanthranilamide factor Xa (FXa) inhibitor candidates. Twenty literature compounds were geometry-optimized and described using alvaDesc to construct a constrained additive multivariate adaptive regression splines model. Internal validation and an assessment of the applicability domain guided the evaluation of 20 prospective analogs. Ten selected analogs and two same-series references were docked to FXa, with apixaban as the crystallographic comparator. Thirteen initial 100 ns molecular dynamics simulations were supplemented by two independent runs for each of PAX-M09, PAX-M15, and PAX-M18. Binding energetics were assessed using molecular mechanics/generalized Born surface area (MM/GBSA), alongside in silico developability profiling. The model achieved R2 = 0.904 and an internal leave-one-out Q2 of 0.846. PAX-M09 was the strongest strict in-domain prediction, whereas PAX-M15 was borderline. Apixaban redocking yielded a root-mean-square deviation (RMSD) of 0.953 Å. Although PAX-M17 and PAX-M19 ranked highest in docking, subsequent analyses prioritized PAX-M15, PAX-M09, and PAX-M18. PAX-M15 showed the most consistent positional behavior across replicates and consistently favorable run-specific MM/GBSA estimates (−68.76, −70.11, and −69.42 kcal/mol). PAX-M09 and PAX-M18 showed greater between-run heterogeneity. Solubility, metabolic, and toxicity liabilities remained important. The results support experimental investigation of the three candidates without changing their applicability-domain classifications or establishing superior experimental potency.
SN - 1422-0067
ER -