Background: Phytoestrogens share common structural features with human estradiol, which primarily contribute to the proliferation of breast tissue cells by binding Estrogen Receptor (ER) subtypes. The Selective Estrogen Receptor Modulators (SERMs) have many therapeutic implications, including Estrogen Receptor Positive Breast Cancer (ERPBC). Prenylated phytoestrogens have emerged as attractive flavonoid scaffolds for ERβ-selective agonists, with potential for effective utilisation in the development of anti-breast cancer agents. Aim: Exploring prenylated phytoestrogens as selective ERβ agonists for Estrogen Receptor positive breast cancer therapy. Methods: To investigate the SERM modulatory activity of prenyl phytoestrogens, molecular docking, Molecular Mechanics with Generalised Born Surface Area (MM-GBSA) and dynamic simulation approach. Prenylated phytoestrogens were retrieved from pubchem database and screened against ERα and ERβ. The pharmacokinetic parameters like Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) predictions were done to analyse drug likeness, human oral absorption and toxicity. Results: In total, 215 prenylated phytoestrogens were retrieved from pubchem database by similarity searching, and six of them, namely, Gamma Mangostin, GancaoninL, Licocoumarone, 2,3-Dehydrokievitone and Xanthohumol, showed binding towards ERβ with a significant docking score comparable with that of the standard ERβ selective agonist genistein. Molecular dynamics studies indicated the stability of the top-scoring compound Gancaonin L, and the required mode of binding is significant. MM-GBSA implies good affinity of these compounds with ERβ. On in silico ADME prediction using Qikprop, all the compounds showed good human oral absorption, poor blood-brain barrier permeability and less toxicity. Conclusion: The present study highlights that the prenylated phytoestrogens may act as selective ERβ modulators based on their favourable in silico ADME profiles, high affinity, and specific binding mode. Further in vitro and in vivo validation will provide additional insights in developing ERβ modulators into potential anti-breast cancer agents. Major Findings: The top-scoring compounds can serve as fundamental scaffolds for further exploration and development of novel SERMs.

Developing novel drugs is a long and difficult process, particularly in oncology, where high attrition rates make clinical trials costly and time-consuming. In response, drug repurposing emerges as an efficient alternative: existing compounds can be used effectively in new therapeutic contexts. Discoidin domain receptor 1 (DDR1), a receptor tyrosine kinase involved in tumor progression, has emerged as a promising target for solid tumor treatment. To identify novel potential DDR1 inhibitors, we applied ESSENCE-Dock, an in-house consensus docking method designed to improve hit enrichment. Using this approach, we performed virtual screening of the DrugBank database, a comprehensive collection of Food and Drug Administration-approved and investigational drugs. To ensure novelty, we performed fingerprint dissimilarity analysis against known DDR1 inhibitors from BindingDB, prioritizing structurally distinct candidates. While several known DDR1 inhibitors ranked among the top-scoring compounds, we prioritized novel, structurally distinct candidates for testing. Biochemical IC50 assays validated three previously unreported DDR1 inhibitors with nanomolar potency, while molecular dynamics simulations confirmed their stable binding within the DDR1 active site. Functional cell-based assays revealed inhibition of DDR1-mediated signaling and cancer cell migration. These findings demonstrate the effectiveness of our consensus-based virtual screening approach in drug repurposing and underscore its potential to streamline oncology drug development.

Introduction: Tuberculosis is a life-threatening infectious disease and a major public health concern. The recent emergence of extensively and totally resistant strains of Mycobacterium tuberculosis has driven the search for new antituberculosis agents with previously unexploited mechanisms of action. The main aim of this study is to develop inhibitors with dual-targeted activity toward M. tuberculosis leucyl-tRNA synthetase (LeuRS) and methionyl-tRNA synthetase (MetRS). Methods: In order to find M. tuberculosis LeuRS and MetRS inhibitors, virtual screening was performed with AutoDock software. The top-scoring compounds were then evaluated in vitro in aminoacylation assay using radioactive [14C]-L-leucine. Results: The low molecular weight inhibitors targeting M. tuberculosis LeuRS were identified among Benzo[b]oxepine-4-carboxylic acid (5-benzyl-thiazol-2-yl)-amide derivatives. Discussion: The most active compound – 7-Methoxy-benzo[b]oxepine-4-carboxylic acid [5-(2- fluoro-benzyl)-thiazol-2-yl]-amide, inhibited mycobacterial LeuRS with IC50 value of 19.7 μM. It was found that this compound inhibits M. tuberculosis MetRS by 96.5% at the concentration of 100 μM. Based on molecular docking results, the compounds from this class bind simultaneously to adenine recognition region and amino acid acceptor region of M. tuberculosis aminoacyl-tRNA synthetases synthetic sites. Conclusion: Benzo[b]oxepine-4-carboxylic acid (5-benzyl-thiazol-2-yl)-amide derivatives can be the basis for chemical optimization and biological investigations.

Human Papilloma Virus type 16 (HPV-16) is highly oncogenic with the E6 and E7 oncogenes playing crucial roles in the pathogenesis of HPV-related cervical carcinogenesis. Targeting these oncoproteins with specific inhibitors offers a promising approach for therapeutic intervention. This study aimed to identify potential inhibitors of the HPV-16 E6 and E7 oncoproteins through an in silico approach, providing a foundation for the development of targeted therapies against HPV associated malignancies. We performed virtual screening on a library of 1000 compounds to identify promising candidates. Subsequent molecular docking studies were conducted to assess the binding affinities of the promising candidates. The top-scoring compounds for oncoproteins were then subjected to molecular dynamics simulations to evaluate their stability and interaction profiles. The virtual screening identified 14 promising candidates followed by docking studies. Among these Galangin was identified as a promising inhibitor for the E6 oncogene, while Neoechinulin showed potential as an inhibitor of the E7 oncogene. Our findings suggest Galangin and Neoechinulin with high potential as therapeutic inhibitors of HPV-16 E6 and E7 oncogenes respectively. These inhibitors could contribute significantly to the development of targeted therapies against HPV associated malignancies. However, further in vitro and in vivo investigations are required to use these phytochemicals as antiviral agents against HPV-16.

Human Papilloma Virus type 16 (HPV-16) is highly oncogenic with the E6 and E7 oncogenes playing crucial roles in the pathogenesis of HPV-related cervical carcinogenesis. Targeting these oncoproteins with specific inhibitors offers a promising approach for therapeutic intervention. This study aimed to identify potential inhibitors of the HPV-16 E6 and E7 oncoproteins through an in silico approach, providing a foundation for the development of targeted therapies against HPV associated malignancies. We performed virtual screening on a library of 1000 compounds to identify promising candidates. Subsequent molecular docking studies were conducted to assess the binding affinities of the promising candidates. The top-scoring compounds for oncoproteins were then subjected to molecular dynamics simulations to evaluate their stability and interaction profiles. The virtual screening identified 14 promising candidates followed by docking studies. Among these Galangin was identified as a promising inhibitor for the E6 oncogene, while Neoechinulin showed potential as an inhibitor of the E7 oncogene. Our findings suggest Galangin and Neoechinulin with high potential as therapeutic inhibitors of HPV-16 E6 and E7 oncogenes respectively. These inhibitors could contribute significantly to the development of targeted therapies against HPV associated malignancies. However, further in vitro and in vivo investigations are required to use these phytochemicals as antiviral agents against HPV-16.

The monkeypox virus (MPXV) has recently faced a global health concern, and it is urgent to discover potential antiviral agents. Carbazole alkaloids, known for their diverse pharmacological activities, have shown promise as antiviral candidates. In this study, we employ a computational approach to explore the inhibitory potential of natural carbazole alkaloid derivatives against key MPXV viral protein, using molecular docking, molecular dynamics (MD) simulation and ADMET profiling. This study involved 156 carbazole alkaloid derivatives. Among them compound 47 showed the best XP docking score −6.017 kcal/mol with the amino acid interactions TYR204, ALA206, ARG177, ARG140 (PDB: 8OIV). We also performed [Formula: see text]-group enumeration and the virtual screening of the enumerated compounds gave the top-scoring compounds S1, S2 and S3, with S1 exhibiting XP docking score −9.249 kcal/mol and the key amino acid interactions are TYR204, SER205, PHE180, ARG177, and ARG140. The crystal ligand of protein and the drug brincidofovir were used as the reference compounds with XP docking score −12.79 kcal/mol and −4.025 kcal/mol and the key interaction amino acids are LYS41, LYS175, ALA206, ARG177, SER205, TYR204, TYR22, PHE180, ASP182, LYS142, ARG140, ARG97. The MD simulation study indicated that S3 had the most stable interactions with ARG177 and ARG140, the amino acids responsible for substrate recognition and positioning of the G1 ribose for methylation. The ADMET tool gave the data on the physiochemical properties of the compounds. The findings of this investigation may aid in the future development of natural alkaloid derivatives that target the MPXV virus.

Nucleotide diphosphate hydrolase type 5 (NUDT5) plays a significant role in the estrogen-signaling pathway and is overexpressed in breast cancer. This study aimed to explore the anti-breast cancer potential of quercetin and its 52 structural analogs by targeting the NUDT5 enzyme using the in silico molecular docking method. Moreover, Molecular Mechanics/General Born Surface Area (MM/GBSA) calculations were performed for compounds with superior binding affinity scores than quercetin. Their drug-likeness, according to Lipinski’s rule of five, water solubility, and Caco-2 permeability were predicted. In addition, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile was determined for the top-scoring compounds from the docking studies and MM/GBSA calculations, as well as for those that complied with the rules of Lipinski and exhibited high permeability. The obtained results showed that all the tested ligands interact with the active site of NUDT5. Their binding energies ranged from −11.24 to −7.36 kcal/mol. The MM/GBSA calculations further supported the binding affinity predictions. ADMET analysis enabled the selection of compounds with favorable pharmacokinetic profiles in comparison to quercetin. Quercetin analogs L1 and L28 were identified as promising anti-breast cancer drug candidates worthy of further experimental evaluation.

Chalcone derivatives, a prominent class of α,β-unsaturated ketones, are well-known for their diverse pharmacological properties including anticancer, antimicrobial, anti-inflammatory, and antioxidant activities. Due to their structural flexibility and ease of synthesis, chalcones have become attractive scaffolds in drug discovery. In the present study, a comprehensive computational investigation was conducted to evaluate a library of chalcone analogues as potential inhibitors of human carbonic anhydrase-I (hCA-I), an enzyme implicated in numerous physiological and pathological processes such as glaucoma, cancer, edema, and epilepsy. Molecular docking simulations were performed using Maestro Schrödinger and Molecular Operating Environment (MOE) to predict the binding affinity and interaction patterns of the chalcone analogues with the active site of hCA-I (PDB ID: 5E2M). The docking scores ranged from -8.036 to -2.732 kcal/mol, indicating strong binding affinity. Notably, several chalcone derivatives exhibited better binding energies than the standard carbonic anhydrase inhibitor, Acetazolamide (AZA), which had a docking score of -6.246 kcal/mol. Compounds 73, 74, 77, and 102 emerged as top candidates based on their high docking scores. To further evaluate their molecular properties, Density Functional Theory (DFT) calculations were conducted using Gaussian09 software. Parameters such as HOMO-LUMO energy gaps and Molecular Electrostatic Potential (MEP) surfaces were analyzed to understand the electronic distribution and chemical reactivity of the ligands. Drug-likeness was also assessed using the Molsoft tool, and favorable scores were observed for most top-scoring compounds, suggesting good pharmacokinetic potential. Additionally, Quantitative Structure–Activity Relationship (QSAR) modeling was carried out to correlate molecular descriptors with biological activity, reinforcing the predictive power of the computational models. Collectively, the results underscore the potential of chalcone analogues as effective hCA-I inhibitors and encourage further experimental validation for therapeutic development.

Parkinson's disease (PD) involves multiple pathological processes in midbrain dopaminergic (mDA) neurons, including protein degradation defects, vesicular trafficking disruption, endolysosomal dysfunction, mitochondrial issues, and oxidative stress. Current PD models often lack complexity and focus on single phenotypes. We used patient-derived SNCA triplication (SNCA-4x) and isogenic control (SNCA-corr) mDA neurons, applying high-content imaging-based morphological profiling to identify and rescue multiple phenotypes. Screening 1,020 compounds, we identified top-scoring compounds that restored healthy profiles in SNCA-4x neurons, increasing Tyrosine hydroxylase (TH) and decreasing α-synuclein (αSyn) levels. Several hits were linked to mitochondrial biology. Tyrphostin A9, a mitochondrial uncoupler, and several of its structural analogues decreased ROS levels, normalized mitochondrial membrane potential, and increased respiration. Western blotting confirmed that Tyrphostin A9 reduces αSyn levels. Our study highlights the neuroprotective potential of mild mitochondrial uncoupling in mDA neurons.

Background: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, highlights the urgent need for effective antiviral agents. The main protease [3-chymotrypsin-like protease (3CLpro)] of SARS-CoV-2 is crucial for viral replication and is a promising target for therapeutic intervention. Objectives: In this study, an in silico approach was employed to identify potential 3CLpro inhibitors from a library of 80 marine-derived natural compounds. Methods: Molecular docking was performed using AutoDock Vina to assess the binding affinity and interaction profiles of the compounds with the active site of 3CLpro. The top-scoring compounds were selected for molecular dynamics simulations using GROMACS to analyze the structural stability and dynamic behavior of the ligand-protease complexes. Results: Several compounds, particularly those from marine fungi and sponges, formed stable interactions with catalytic residues His41 and Cys145, maintaining conformational stability throughout 100 ns of simulation. In silico ADMET assessments were further performed to predict the pharmacokinetic properties of the docked compounds. Overall, molecular dynamics (MD) analysis showed that the dynamic properties of the protein alter significantly when it is in complex with the selected compounds. Conclusions: The findings in this study suggest that Isobutyrolactone II and Aspernolide A, marine natural products, could serve as promising lead compounds for the development of SARS-CoV-2 main protease inhibitors, warranting further experimental validation.

A growing body of knowledge implicates perturbed RNA homeostasis in amyotrophic lateral sclerosis (ALS), a neurodegenerative disease that currently has no cure and few available treatments. Dysregulation of the multifunctional RNA-binding protein TDP-43 is increasingly regarded as a convergent feature of this disease, evidenced at the neuropathological level by the detection of TDP-43 pathology in most patient tissues, and at the genetic level by the identification of disease-associated mutations in its coding gene TARDBP. To characterize the transcriptional landscape induced by TARDBP mutations, we performed whole-transcriptome profiling of motor neurons (MNs) differentiated from two knock-in iPSC lines expressing the ALS-linked TDP-43 variants p.A382T or p.G348C. Our results show that the TARDBP mutations significantly altered the expression profiles of mRNAs and microRNAs of the 14q32 cluster in MNs. Using mutation-induced gene signatures and the Connectivity Map database, we identified compounds predicted to restore gene expression toward wild-type levels. Among top-scoring compounds selected for further investigation, the NEDD8-activating enzyme inhibitor MLN4924 effectively improved cell viability and neuronal activity, highlighting a possible role for protein post-translational modification via NEDDylation in the pathobiology of TDP-43 in ALS.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-12147-8.

Malaria continues to pose a significant public health threat, particularly across African nations, where Plasmodium falciparum accounts for over 90% of global malaria-related deaths. The progression and survival of P. falciparum are heavily reliant on key proteins, including protein kinase 5 (PfPK5), which is essential for the parasite's cell division and survival. Due to its pivotal role, PfPK5 represents a promising target for antimalarial drug development. This study employed cheminformatics approaches to identify potential PfPK5 inhibitors derived from bioactive compounds in Nigerian plants with known antimalarial properties. A total of 196 compounds from 14 plant species were assessed for drug-likeness, and the drug-like candidates were docked into the active site of PfPK5. The binding free energies of the three top-scoring compounds were subsequently evaluated alongside their pharmacokinetic and toxicological properties. Thirteen compounds demonstrated strong binding affinities, with docking scores ranging from -6.075 to -10.072kcal/mol, surpassing the performance of artemisinin, the reference drug, which showed a docking score of -5.613kcal/mol. Among these, marmesin, cryptolepinone, and lecanoric acid exhibited the most favorable interactions, with binding free energies of -48.73, -43.46, and -29.95kcal/mol, respectively, compared to -20.19kcal/mol for artemisinin. Molecular dynamics simulations over 100ns confirmed the stability of these interactions. Furthermore, the identified compounds demonstrated favorable pharmacokinetic and safety profiles. In conclusion, this study identifies marmesin, cryptolepinone, and lecanoric acid as promising candidates for further computational and experimental investigations aimed at developing novel antimalarial therapies targeting PfPK5.

Targeting tryparedoxin-dependent peroxidase (TXNPx) enzyme to identify repurposing drug candidates from FDA-approved drugs and natural products using virtual screening, ADME/Tox and MD simulations

Unravelling selectivity discrepancies of protoporphyrin binding to glutathione transferase: A comparative analysis of molecular dynamic simulated versus implicit solvent-minimized protein models.

The emergence of the C797S mutation in the epidermal growth factor receptor (EGFR) significantly limits the efficacy of covalent inhibitors in treating non-small cell lung cancer (NSCLC). This study aimed to design and evaluate novel allosteric inhibitors targeting the C797S mutant EGFR using advanced in silico methodologies. Utilizing scaffold hopping techniques, a library of compounds was generated based on the known allosteric inhibitor EAI045. Virtual screening identified 44 top-scoring compounds with strong binding affinities for the C797S mutant EGFR. Molecular docking studies evaluated binding interactions, while the MM-GBSA method assessed binding free energies. Additionally, pharmacokinetic properties were analysed using Lipinski's rule of five, and the most promising compound, MK1, underwent molecular dynamics simulations followed by in-vitro assessment. A total of 12 heterocyclic scaffolds were derived from EAI045, and 44 top-scoring compounds were identified through virtual screening and MM-GBSA analysis. MK1 demonstrated the highest docking score and a ΔG_bind of -29.36 kcal/mol, with strong interactions involving residues such as LYS728 and MET793. MD simulations over 100 ns confirmed the stability of the MK1-EGFR complex, with RMSD values stabilizing post-50 ns and RMSF values consistently below 3 Å. In-vitro assays validated MK1's potent anticancer activity, showing significant cytotoxicity against C797S mutant cell lines, with IC50 values lower than the standard comparator. Additional pharmacokinetic profiling indicated MK1 adhered to Lipinski's Rule of Five with no violations, highlighting its drug-like properties. The findings highlight MK1 as a promising candidate for the treatment of NSCLC harbouring the C797S mutation, providing valuable insights for future drug design and development strategies targeting mutant EGFR.

Abstract Colorectal cancer ranks among the leading causes of cancer-related deaths globally. In this study, we identified miR-135b as a differentially expressed microRNA in colorectal cancer through an analysis of datasets from the Gene Expression Omnibus (GEO) database. Target genes associated with miR-135b were subsequently identified, and pathway and functional enrichment analyses were conducted to provide a deeper understanding of the underlying biological processes. We developed a de novo three-dimensional model of miR-135b's tertiary structure, targeting the Dicer cleavage site for small molecule inhibition. Dicer binds to the terminal loop region of the pre-miRNA and cleaves it to produce a double-stranded miRNA duplex. One strand of this duplex, the guide miRNA, is loaded into the RNA-induced silencing complex (RISC), which mediates miRNA-mRNA interactions, leading to post-transcriptional gene silencing. To identify potential inhibitors, molecular docking simulations were conducted using the ChemDiv miRNA-targeted small molecule library (∼20, 000 compounds). The top-scoring compounds were further explored by screening their commercial analogues in the ZINC library via SwissSimilarity. These analogues were docked at the Dicer cleavage site, and optimized docking scores were obtained. The highest scoring compounds were then subjected to all-atom molecular dynamics simulations, followed by post-simulation analysis to evaluate the dynamic interactions between miR-135b and the selected hit ligands. Citation Format: Berat Demir, Lalehan Oktay, Serdar Durdagi. Targeting oncogenic miR-135b in colorectal cancer: Computational modeling and small molecule screening for RNA-based therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6693.

Alzheimer's disease (AD), one of the neurodegenerative disorders, afflicts negatively across the whole world. Due to its complex etiology, no available treatments are disease-altering. This study aimed to explore isolated saponins profiles from Platycodon grandiflorum in the binding pockets of six target proteins of AD using computational and quantum chemistry simulations. Initially, saponin compounds were docked to AD enzymes, such as GSK-3β and synapsin I, II, and III. The subsequent research from MD simulations of the best three docked compounds (polygalacin D2, polygalacin D, and platycodin D) suggested that their profiles match with the binding of standard active drugs like ifenprodil and donepezil to the six enzymes. Moreover, analyzing DFT quantum calculations of top-scoring compounds fully unravels their electronic and quantum properties and potential in anti-AD. The subtle differences between polygalacin D and D2, and platycodin D, were studied at the level of theory DFT/B3LYP, showing that the electron-donating effect of the hydroxy ethyl group in platycodin D rendering this compound of moderate electrophilicity and reactivity. Polygalacin D2 diglucoside substituent in position-2 contributed to its best binding and intermolecular interactions more than polygalacin D and prosapogenin D, which acted as the negative decoy drug.

The accelerating growth of make-on-demand chemical libraries provides unprecedented opportunities to identify starting points for drug discovery with virtual screening. However, these multi-billion-scale libraries are challenging to screen, even for the fastest structure-based docking methods. Here we explore a strategy that combines machine learning and molecular docking to enable rapid virtual screening of databases containing billions of compounds. In our workflow, a classification algorithm is trained to identify top-scoring compounds based on molecular docking of 1 million compounds to the target protein. The conformal prediction framework is then used to make selections from the multi-billion-scale library, reducing the number of compounds to be scored by docking. The CatBoost classifier showed an optimal balance between speed and accuracy and was used to adapt the workflow for screens of ultralarge libraries. Application to a library of 3.5 billion compounds demonstrated that our protocol can reduce the computational cost of structure-based virtual screening by more than 1,000-fold. Experimental testing of predictions identified ligands of G protein-coupled receptors and demonstrated that our approach enables discovery of compounds with multi-target activity tailored for therapeutic effect.

Identification and evaluation of bioactive compounds from Azadirachta indica as potential inhibitors of DENV-2 capsid protein: An integrative study utilizing network pharmacology, molecular docking, molecular dynamics simulations, and machine learning techniques.

Cyclin-dependent kinases 4 and 6 (CDK4/6) are crucial regulators of cell cycle progression and represent important therapeutic targets in breast cancer. This study employs a comprehensive computational approach to identify novel CDK4/6 inhibitors from marine natural products. We utilized structure-based virtual screening of the CMNPD database and MNP library, followed by rigorous filtering based on drug-likeness criteria, PAINS filter, ADME properties, and toxicity profiles. From an initial hit of 9,497 compounds, 2,344 passed drug-likeness and PAINS filters. Further ADME filtering yielded 50 compounds, of which 25 exhibited non-toxic profiles. These 25 candidates underwent consensus molecular docking using seven distinct algorithms: AutoDockTools 4.2, idock, LeDock, Qvina 2, Smina, AutoDock Vina 1.2.0, PLANTS, and rDock. Based on these results, six top-scoring compounds were selected for comprehensive 500 nanosecond all-atom molecular dynamics simulations to evaluate their structural stability and interactions with CDK4/6. Our analysis revealed that compounds CMNPD11585 and CMNPD2744 demonstrated superior stability in their interactions with CDK4/6, exhibiting lower RMSD and RMSF values, more favorable binding free energies, and persistent hydrogen bonding patterns. These compounds also showed lower Solvent Accessible Surface Area values, indicating better compatibility with the CDK4/6 active site. Subsequent in-vitro studies using MTT assays on MCF-7 breast cancer cells confirmed the cytotoxic effects of these compounds, with CMNPD11585 showing the highest potency, followed by CMNPD2744.