Aug 2026· In Silico Pharmacology· Vol 14· 0 citations· 35 references
Medicine
TL;DR
A cost-effective computational workflow for prioritizing ENR inhibitors is demonstrated, providing a foundation for the development of novel antimalarial agents and highlighting Cd3 and Cd5 as the most promising candidates for further development.
Caspase-1 is a crucial inflammatory cysteine protease that facilitates the maturation of pro-inflammatory cytokines such as interleukin-1β and interleukin-18, making it a significant therapeutic target for inflammatory diseases. However, existing caspase-1 inhibitors often face challenges like toxicity and suboptimal drug-like properties, underscoring the need for new inhibitors. This study employed an integrated computational strategy, combining quantitative structure–activity relationship (QSAR) modeling and application of this validated model to a large natural product database followed by molecular docking, rigorous binding free energy analysis and extended molecular dynamics simulations. Initially, a dataset of 185 caspase-1 inhibitors with experimentally reported pKi values (ranging from 4.05 to 9.24) was used to construct a QSAR model using Partial Least Squares (PLS) regression. The PLS-based QSAR model was developed with 18 descriptors out of 5799 calculated descriptors for each compound and 10 latent variables, demonstrating strong statistical performance with R2 values of 0.870 and 0.838 for the training and test sets, respectively, and leave-one-out cross-validation coefficient Q2LOO and 5-fold cross-validation (Q25-fold) values of 0.819 and 0.814, respectively. Y-randomization tests further confirmed the model’s robustness, as the randomized models exhibited significantly lower statistical parameters than the original model. The validated QSAR model was applied to 276,518 natural products in the LOTUS database. Subsequent molecular docking, Molecular Mechanics/General Born Surface Area (MM/GBSA) scoring, and Pan-Assay INterference Compounds (PAINS) and Chemical Frequent Hitter (ChemFH) filtering identified 14 candidate compounds, which were further evaluated using 300 ns molecular dynamics simulations. Among these, four natural products (LTS0162325, LTS0221286, LTS0016840, and LTS0070407) showed the most stable binding behavior and maintained persistent interactions with key catalytic and substrate-binding residues of caspase-1 in a mimicked physiological condition. Overall, this study highlights natural diterpenoids and coumarin glycosides as promising scaffolds for caspase-1 inhibition and demonstrates that integrating QSAR modeling with structure-based approaches provides an efficient strategy for discovering potential anti-inflammatory drug candidates.
Yusuf Şeflekçi, Alper Yılmaz, Abdulilah Ece· Molecules· 0 citations
The main protease (MPro) of coronaviruses (CoVs) is an essential enzyme involved in viral replication and represents an attractive target for antiviral drug discovery. Based on the similar binding pocket residues within the MPro of different CoVs, this study aimed to identify potential inhibitors of SARS-CoV-2 MPro from PDB ID 6M2N using integrated computational approaches. Interaction-based pharmacophore modeling, virtual screening, molecular docking, MM-GBSA binding energy calculation, and molecular dynamics simulation (MDS) were performed using BIOVIA Discovery Studio. The validated pharmacophore model was utilized to screen the ZINC database, followed by docking and 100 ns MDS analyses of the top-ranked compounds. The pharmacophore model 01 demonstrated favorable predictive performance (AUC = 0.781). Virtual screening identified 483 compounds, from which 15 compounds were selected for docking studies. Among them, ZINC95473654 (Lig-1), ZINC95473725 (Lig-2), and ZINC08792368 (Lig-3) exhibited strong binding affinity toward MPro. Lig-1 demonstrated the best docking score and binding free energy, along with stable interactions with key catalytic residues HIS41, CYS145, and GLU166. MDS analyses further confirmed that Lig-1, Lig-2 and Lig-3 maintained stable conformations. The hydrogen bond distance monitoring and post MDS-MM-GBSA results suggest Lig-1 followed by Lig-3 as an inhibitor for MPro and persistent intermolecular interactions throughout the 100 ns simulation period. The findings suggest that Lig-1, followed by Lig-3, may serve as promising computational lead compounds targeting SARS-CoV-2 MPro, representing promising candidates for further experimental validation.
Mohd Yasir Khan, Farah Maarfi, A. Shah et al.· International Journal of Mol...· 0 citations
Cancer remains a major global health challenge, highlighting the need for novel therapeutic agents with improved selectivity and efficacy. Histone deacetylase (HDAC) inhibition represents an important epigenetic strategy in anticancer drug discovery because it can influence gene expression, cell-cycle regulation, and tumor cell survival. In this computational study, fifteen 4-oxoquinazolin-3(4
H
)-yl-
N
-hydroxybenzamide derivatives were evaluated as potential HDAC8-targeting compounds using an integrated
in silico
workflow. Molecular docking was performed against HDAC8 using the crystal structure deposited under Protein Data Bank (PDB) ID 1T69, with suberoylanilide hydroxamic acid (SAHA) used as the reference inhibitor.
The investigated derivatives showed favorable accommodation within the HDAC8 catalytic pocket, with predicted interaction patterns involving zinc coordination, hydrogen bonding, and π-related interactions with key active-site residues. Several derivatives showed favorable predicted docking scores and interaction profiles relative to SAHA, suggesting that the designed quinazolinone–hydroxamate scaffold may be suitable for further prioritization. Prime molecular mechanics generalized Born surface area (MM-GBSA) analysis identified selected derivatives with comparatively favorable calculated binding free-energy contributions, particularly through van der Waals, electrostatic, and lipophilic interactions.
In silico
absorption, distribution, metabolism, and excretion (ADME) prediction indicated that most derivatives possessed acceptable drug-like and pharmacokinetic descriptors, including physicochemical properties, predicted oral absorption, and limited central nervous system (CNS) activity. Density functional theory (DFT) analysis provided supportive electronic-level information by identifying molecular regions that may contribute to hydrogen bonding and zinc coordination. A 100 ns molecular dynamics simulation of the HDAC8–derivative 15 complex suggested the short-timescale persistence of one representative predicted binding pose under the selected simulation conditions.
Overall, this study identifies selected 4-oxoquinazoline hydroxamic acid derivatives as preliminary computational leads for further experimental validation as potential HDAC8-targeting compounds.
D. Saleem, M. Mahdi, Ayad Mohammed Rasheed· Pharmacia· 0 citations
Plasmodium falciparum Calcium-Dependent Protein Kinase 4 (PfCDPK4) is a validated target for malaria transmission-blocking interventions, as its inhibition disrupts male gametocyte exflagellation. Hexahydroquinolines (HHQs) have emerged as promising gametocytocidal agents. This study aimed to design novel HHQs as potential PfCDPK4 inhibitors with good binding affinity, favourable pharmacokinetics, and structural stability. A library of 20,000 novel HHQ analogs was generated using genetic algorithm-driven de novo molecular design in AlvaBuilder and systematically filtered through a pipeline comprising machine-learning-based bioactivity prediction, PAINS removal, pharmacophore modeling, ADMET screening, and structure-based virtual screening. Top-ranking compounds underwent bioisosteric optimization and were evaluated using 300 ns molecular dynamics simulations and density functional theory (DFT) calculations. Comparative in silico validation against known inhibitor Bumped Kinase Inhibitor-1 (BKI-1) and the co-crystallized ligand DXR as controls demonstrated that four HHQ analogs exhibited comparable binding affinities and stable interactions with key residues within the ATP-binding pocket. Favourable ADMET profiles, dynamic stability, and supportive electronic properties further reinforced their inhibition potential. These findings provide biologically meaningful computational evidence supporting HHQ scaffolds as potential PfCDPK4 inhibitors and demonstrate the utility of integrated bioinformatics approaches for malaria transmission-blocking drug discovery. Further experimental validation is required to confirm the inhibitory activities of the identified hexahydroquinoline compounds.
G. Oduselu, D. Bodun, O. Ajani et al.· Bioinformatics and Biology I...· 0 citations
The MGC803 cell line is a human gastric cancer model frequently used in cancer research. In this context, a combined in silico approach including 3D-QSAR modeling, ADMET analysis, network pharmacology, docking, molecular dynamics and ligand transport evaluations, was applied to design new antiproliferative molecules. A robust 3D-QSAR model with high predictive capacity (R² and Q²) was developed and used to design new compounds (PR1–PR4). After an ADMET screening, the putative biological targets of the non-toxic compounds were predicted using PharmMapper. A network pharmacology analysis identified several hub genes, of which HSP90AA1 had the highest degree value. Given its central role in stabilizing multiple oncogenic proteins involved in gastric cancer progression, as well as its suitability for structure-based studies, HSP90AA1 was selected for molecular docking and molecular dynamics simulations. In addition, molecular docking was performed on HSP90AA1 protein (1YET) in complex with the designed molecules (PR1-PR4), and their predicted binding behaviors were compared to both the most active molecule (M34) and the reference drug, geldanamycin. These results demonstrate a high predicted binding affinity and remarkable interaction profiles within the active site of the HSP90AA1. To further evaluate the dynamic stability of these complexes, we performed molecular dynamics simulations over a 100 ns period, thus confirming stable attachment modes and durable contact networks. The MM-PBSA approach demonstrated favorable binding free energies between the chosen PR4 ligand and the 1YET protein (-26.47 ± 2.89 kcal/mol). Finally, the ligand transport study showed that the PR4 ligand easily crosses tunnels 1 and 2 with optimal theoretical transport dynamics compared to the reference drug, geldanamycin (GA). This comprehensive computational method underlines the diverse potential of the examined molecules, identifying the most promising candidates for subsequent experimental validation against gastric cancer.
L. Naanaai, Abdellah El Aissouq, Yassine El Allouche et al.· Beni-Suef University Journal...· 0 citations
An integrated computational strategy involving pharmacophore mapping, molecular docking, molecular dynamics simulations, and density functional theory (DFT) analysis was employed to identify potential SaFtsZ inhibitors, highlighting compound 15 as a computationally predicted scaffold for the development of SaFtsZ-targeted antibacterial agents.
Sundarrajan T., Neerugatti Dora Babu, A. K. N. et al.· RSC Advances· 0 citations
