Prediction of the mechanisms of hepatotropic action of maloben using molecular docking

Introduction. Non-alcoholic (metabolic dysfunction-associated) fatty liver disease (NAFLD) encompasses a spectrum of common pathological conditions associated with systemic metabolic dysfunction. The development of new effective and safe pharmacological therapies for NAFLD and its comorbid conditions remains an ongoing challenge. The malonic acid derivative maloben (sodium 4,4’-(propanediamido)dibenzoate) is currently undergoing phase II clinical trials for NAFLD; however, its molecular mechanism of action requires further investigation and clarification. Aim. The aim of this study was to investigate the potential mechanisms of action of maloben using molecular docking. Materials and methods. Molecular docking of maloben structures protonated at physiological pH was performed using the Schrödinger Suite with the Glide XP scoring function. The target molecules included proteins with established roles in the pathogenesis of NAFLD, including Kelch-like ECH-associated protein 1 (KEAP-1), the glucagon-like peptide 1 receptor (GLP-1R), the farnesoid X receptor (FXR), peroxisome proliferator-activated receptor γ (PPAR-γ), and thyroid hormone receptors (THR) β and α. Docking results were evaluated and interpreted based on the calculated binding energy values for the selected targets. Results and discussion. Molecular docking generated binding maps of maloben structures with the selected targets and identified the lowest binding energy values for two of them: PPAR-γ (−8.425 kcal/mol) and FXR (−8.369 kcal/mol). Accordingly, the selective PPAR-γ agonist pioglitazone, the PPAR-α/γ/δ agonist bezafibrate, and the FXR agonist cilofexor were chosen as comparator ligands for further analysis. Based on the docking results, these compounds exhibited lower binding energies (−11.177 kcal/mol, −10.907 kcal/mol, and −15.870 kcal/mol, respectively) than maloben; however, the latter may have an advantage with respect to several physicochemical predictors of pharmacokinetics. Maloben has a molecular weight of 340.29 Da and octanol/water partition coefficient (logD) and apparent aqueous solubility (logS) values of 1.763 and 4.58, respectively, which are favorable for intestinal absorption and membrane permeability. Conclusion. The results indicate that the hepatotropic and metabolic effects of maloben may be mediated by its interaction with PPAR-γ and/or FXR. Several physicochemical predictors suggest that maloben may exhibit a favorable pharmacokinetic profile following oral administration.

Authors

Institutions

Publication Details

Journal
Drug development & registration
Published
2026-11-06
DOI
https://doi.org/10.33380/2305-2066-2026-15-4-2370
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Prediction of the mechanisms of hepatotropic action of maloben using molecular docking

I. A. Titovich, Sergey V. Okovityi, Приходько Вероника Александровна, Artur V. Sauts
1 links
Drug development & registration
Computational Drug Discovery Methods
article

Prediction of the mechanisms of hepatotropic action of maloben using molecular docking

I. A. Titovich, Sergey V. Okovityi, Приходько Вероника Александровна, Artur V. Sauts
article en

Abstract

Introduction. Non-alcoholic (metabolic dysfunction-associated) fatty liver disease (NAFLD) encompasses a spectrum of common pathological conditions associated with systemic metabolic dysfunction. The development of new effective and safe pharmacological therapies for NAFLD and its comorbid conditions remains an ongoing challenge. The malonic acid derivative maloben (sodium 4,4’-(propanediamido)dibenzoate) is currently undergoing phase II clinical trials for NAFLD; however, its molecular mechanism of action requires further investigation and clarification. Aim. The aim of this study was to investigate the potential mechanisms of action of maloben using molecular docking. Materials and methods. Molecular docking of maloben structures protonated at physiological pH was performed using the Schrödinger Suite with the Glide XP scoring function. The target molecules included proteins with established roles in the pathogenesis of NAFLD, including Kelch-like ECH-associated protein 1 (KEAP-1), the glucagon-like peptide 1 receptor (GLP-1R), the farnesoid X receptor (FXR), peroxisome proliferator-activated receptor γ (PPAR-γ), and thyroid hormone receptors (THR) β and α. Docking results were evaluated and interpreted based on the calculated binding energy values for the selected targets. Results and discussion. Molecular docking generated binding maps of maloben structures with the selected targets and identified the lowest binding energy values for two of them: PPAR-γ (−8.425 kcal/mol) and FXR (−8.369 kcal/mol). Accordingly, the selective PPAR-γ agonist pioglitazone, the PPAR-α/γ/δ agonist bezafibrate, and the FXR agonist cilofexor were chosen as comparator ligands for further analysis. Based on the docking results, these compounds exhibited lower binding energies (−11.177 kcal/mol, −10.907 kcal/mol, and −15.870 kcal/mol, respectively) than maloben; however, the latter may have an advantage with respect to several physicochemical predictors of pharmacokinetics. Maloben has a molecular weight of 340.29 Da and octanol/water partition coefficient (logD) and apparent aqueous solubility (logS) values of 1.763 and 4.58, respectively, which are favorable for intestinal absorption and membrane permeability. Conclusion. The results indicate that the hepatotropic and metabolic effects of maloben may be mediated by its interaction with PPAR-γ and/or FXR. Several physicochemical predictors suggest that maloben may exhibit a favorable pharmacokinetic profile following oral administration.

Drug development & registration
Saint Petersburg University of Management and Economics (RU)
Good health and well-being
Openalex Percentile: Top 20%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon