Recep Adiyaman
bioinformatics

Issue #26: MetalloDock: Decoding Metalloprotein-Ligand Interactions via Physics-Aware Deep Learning for Metalloprotein Drug Discovery.

January 20, 2026 Daily Intelligence
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MetalloDock: Decoding Metalloprotein-Ligand Interactions via Physics-Aware Deep Learning for Metalloprotein Drug Discovery.

🧬 Abstract

Accurate prediction of metalloprotein-ligand interactions is critical for metalloprotein-targeted drug discovery. Conventional docking tools and existing deep learning (DL) models fail to reliably capture metal-ligand interactions, hampering the discovery of potent metalloprotein inhibitors. Here, we propose MetalloDock, the first DL-based docking framework specially designed for metalloprotein targets. By innovatively integrating an autoregressive spatial decoding engine with a physics-constrained geometric generation paradigm, MetalloDock can precisely reconstruct metal coordination geometries and accurately capture metal-ligand interactions, which enhance both the accuracy of metalloprotein-ligand docking and binding affinity prediction. Extensive evaluations on our custom-built benchmark data set demonstrate that MetalloDock outperforms existing methods, including AlphaFold3, in docking success rate and virtual screening performance for metalloprotein targets. In real-world applications, MetalloDock successfully identified multiple novel hit compounds in a virtual screening campaign targeting the prostate-specific membrane antigen. Additionally, it enabled rational drug design for acidic polymerase endonuclease, leading to the discovery of potent inhibitors. These results highlight the broad applicability of MetalloDock in accelerating metalloprotein-targeted drug discovery and provide a standardized framework for future evaluation of metalloprotein-specific docking algorithms.

Why it matters: Expands the searchable sequence space for novel folds and high-affinity binders.

⭐ Additional Signals

In silico screening of IMPPAT-derived phytochemicals targeting ERG6 and drug resistance-associated proteins in drug-resistant Candida albicans: virtual screening and molecular dynamics using alphafold models.

Pathogenic fungi, particularly Candida albicans, have been escalating clinical problems, notably because of antifungal resistance and symptomatological comorbidity with COVID-19. This research aimed to find phytochemical inhibitors of ergosterol production, specifically targeting ERG6 (C-24 sterol methyltransferase), utilizing chemicals from the IMPPAT database. A total of 14,965 phytochemicals were computationally evaluated against AlphaFold-predicted ERG6 utilizing AutoDock Vina. Fifteen compounds exhibiting robust binding affinities (- 8.2 to - 9.2 kcal/mol) were found, from which four candidates were chosen based on advantageous ADMET profiles. The docking scores for the top four compounds targeting ERG6-Daturataturin A (- 8.8 kcal/mol), Disogluside (- 8.6), Tataramide B (- 8.4), and Floribundasaponin A (- 8.4)-exceeded those of previously identified ERG6 inhibitors D28 (- 8.0), Tomatidine (- 7.9), and H55 (- 6.4). The selected leads were further docked against other proteins associated with drug resistance and cell proliferation, specifically ERG1, ERG11, CLB2, CDR1, and CDR2. Among these, only ERG1 exhibited significant interactions, with Disogluside (- 9.3 kcal/mol), Tataramide B (- 9.9), and Floribundasaponin A (- 9.3) surpassing the reference inhibitor terbinafine (- 8.7 kcal/mol), except for Daturataturin A, which showed a comparable score of - 8.6 kcal/mol. Nevertheless, owing to steric conflicts inside the ERG1 binding sites, molecular dynamics (MD) simulations were conducted exclusively for ERG6-ligand complexes over duration of 100 ns. The RMSD values demonstrated commendable structural stability: Daturataturin A (~ 0.39 nm), Disogluside (~ 0.38 nm), Tataramide B (~ 0.27 nm), and Floribundasaponin A (~ 0.40 nm). Principal Component Analysis (PCA) validated consistent and significant movements for Daturataturin A and Floribundasaponin A, whereas Disogluside and Tataramide B exhibited increased flexibility. MM/PBSA analysis indicated robust binding free energies for Daturataturin A (- 42.26 kcal/mol), Floribundasaponin A (- 37.48 kcal/mol), and Disogluside (- 29.58 kcal/mol), however Tataramide B exhibited a detrimental + 9.81 kcal/mol. These results endorse the promise of phytochemical-derived antifungals and necessitate more experimental verification. The online version contains supplementary material available at 10.1007/s40203-025-00480-9.

Mechanistic Investigation of Astragalus Root in the Management of T2DM-NAFLD Comorbidity: An Integrated Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation, and In Vitro Study

Background: /Objectives: Astragalus root is a classical qi-tonifying traditional Chinese medicine that has demonstrated potential therapeutic efficacy in T2DM and NAFLD. However, the precise mechanisms underlying its effects on the comorbidity of these two disorders remain unclear. This study investigated the molecular mechanisms by which astragalus root ameliorated T2DM-NAFLD comorbidity. Methods: Network pharmacology, molecular docking, molecular dynamics simulation, and in vitro experiments were employed to elucidate the potential roles and mechanisms of astragalus root in the management of T2DM-NAFLD comorbidity. Results: A total of 25 bioactive constituents and 152 corresponding targets associated with astragalus root were identified. PPI network analysis revealed the top ten core candidate targets, among which six possessed suitable crystal structures for molecular docking, including IL-6, AKT1, JUN, TNF, CASP3, and ESR1. KEGG analysis further identified the PI3K-AKT as the most significantly en-riched pathway. Molecular docking of the principal bioactive constituent formononetin from astragalus root with the six core targets was conducted using AutoDock4 software. Molecular dynamics simulations verified the stability of the interactions between for-mononetin and each of the six core target proteins. In vitro experiments demonstrated that formononetin obviously decreased lipid droplet accumulation, downregulated TC and TG levels, suppressed the expression of TNF-α, IL-6, and IL-1β, decreased ROS and MDA levels, and enhanced GSH content and SOD activity. These therapeutical effects were achieved through inhibition of protein expression within the PI3K/AKT/mTOR signaling pathway. Conclusions: This study determined the potential therapeutic targets and underlying mechanisms of formononetin derived from astragalus root in the T2DM-NAFLD management, thereby providing a scientific basis for its clinical application.

Exploring the mechanism of Kemofang in treating idiopathic membranous nephropathy based on LC-MS/MS combined with network pharmacology, molecular docking, and molecular dynamics simulation.

Idiopathic membranous nephropathy (IMN), an autoimmune glomerular disease, arises from in situ immune complex deposition in the glomerular subepithelial spaces, triggering complement activation and podocyte injury. Although the Kemo Formula shows therapeutic potential for IMN, its mechanisms remain unclear. This study employed LC-MS/MS, network pharmacology, molecular docking, and dynamic simulations to elucidate the mechanism of action. LC-MS/MS and the TCMSP database identified 83 bioactive components from 267 chemicals detected in the Kemo Formula. Using PubChem, Swiss Target Prediction, and GeneCards, 827 drug targets and 2581 IMN-related targets were screened, yielding 336 overlapping targets linked to 81 components. Network analysis prioritized 15 key components ( baicalein and quercetin) and 36 core targets (TP53, IL6, and AKT1). Functional enrichment revealed involvement in hormone response, MAPK cascade regulation, and kinase binding with pathways including lipid metabolism, PI3K/Akt, and MAPK signaling. Molecular docking indicated strong binding affinities between the active components and targets, while dynamic simulations predicted the stability of the galangin-AKT1 complex. The Kemo Formula likely mitigates IMN by multi-target modulation, ameliorating lipid dysregulation, suppressing podocyte apoptosis, and attenuating immune-inflammatory and oxidative stress via PI3K/Akt and MAPK pathways. This integrative approach highlights its multicomponent, multitarget therapeutic strategy against IMN, providing a foundation for further mechanistic and clinical exploration.

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Evaluation of the antibacterial and antioxidant potential of the endophytic fungus EFY14 from <i>Cannabis sativa</i> L. leaves through metabolomics and molecular docking.

Endophytic fungi are prolific sources of natural antioxidants and antibacterial agents. This study aims to isolate and identify the endophytic fungus EFY14 from Cannabis sativa L. leaves and to evaluate the antibacterial and antioxidant activities of its culture filtrates. Non-targeted metabolomics was employed to chemically profile the EFY14 crude extract, a potential biological targets were predicted through molecular docking and molecular dynamics simulations. EFY14 was taxonomically identified as belonging to the Chaetomium genus. Its extract contained 20.823 ± 1.449 mg gallic acid equivalent (GAE)/L total phenolic and 0.230 ± 0.007 mg rutin equivalent (RE)/mL total flavonoids, displaying antioxidant and antibacterial activities. Metabolomic profiling identified flavonoids and phenolic compounds, including 4’,7-dihydroxy-8-methylisoflavone, scopoletin, xanthohumol, tricin, sophoraflavanone G, prenyl glucoside, melilotoside and maltol. Molecular docking indicated potential molecular targets for these metabolites. These findings suggest that EFY14 derived endophytic fungi from C. sativa L. may represent a novel source of antioxidant and antibacterial compounds.

In-silico evaluation of <i>Hedychium spicatum</i> phytochemicals as potential COX-2 inhibitors: molecular docking, dynamics simulation, and ADMET analysis.

This study aims to analyze the inhibitory action of the phytochemicals of Hedychium spicatum by computational docking studies, molecular dynamics simulations, and ADMET studies. For this, natural metabolites were taken from the IMPPAT and KNApSAcK databases. The crystallographic structure of the molecular target cyclooxygenase-2 (COX-2) was obtained from the RCSB PDB (PDB ID: 5IKR). Mefenamic acid, a well-known nonsteroidal anti-inflammatory drug (NSAID), was used as the standard for comparative analysis. Computational docking analysis was performed using Schrödinger’s Glide, an option based on scoring functions. MD simulations were performed, followed by statistical analysis that included RMSD, RMSF, RoG, and H-bond analysis. MMGBSA analysis revealed optimal binding affinities ([Formula: see text]) with molecular targets HS6428435 ( cis -Sesquisabinene hydrate), HS519857 (Cubenol), and HS7439 (Carvone), with values of - 37.32, - 32.20, and - 26.31 kcal/mol, respectively. Notably, HS6428435 exhibits a strong binding affinity of - 37.32 kcal/mol, compared to the standard drug, which has a binding affinity of - 35.28 kcal/mol, making it a more favorable alternative. These results indicated that cis -Sesquisabinene hydrate could be one of the potential ligands for the treatment of inflammatory conditions. The druggability of the suggested compounds is confirmed by the in-silico ADMET study. This work will later serve as a foundation for experimental investigations conducted both in vitro and in vivo to confirm the anti-inflammatory capabilities of the same. Supplementary information The online version of this article (10.1007/s40203-025-00537-9) contains supplementary material, which is available to authorized users.

From metabolomics to molecular docking: Unveiling the antioxidant potential of Ecuadorian <i>Hyeronima macrocarpa</i>.

Hyeronima macrocarpa (“motilón”) is an underexplored tropical fruit. This study evaluated the antioxidant properties of its pulp and peel extracts obtained with 80 % acetone, MeOH-acetic acid (19:1), and H₂O-acetic acid (19,1). Total phenolic, flavonoid, anthocyanin, carotenoid, and tocopherol contents were determined, alongside radical scavenging activity (DPPH•), chelating capacity, electrochemical index (EI), and metabolomic profiling by UHPLC-MS. The MeOH-AcH (19,1). 80 % acetone extracts, especially from the peel, exhibited the highest total phenolic content, lowest EC₅₀ and TEC₅₀ values, and the strongest electrochemical responses, indicating superior redox activity. Metabolomic analysis identified abundant flavonols and anthocyanins with catechol or carbonyl groups, which likely explain their enhanced antioxidant efficiency. Molecular docking confirmed high binding affinity of these metabolites toward catalase and superoxide dismutase, reinforcing their biological relevance. These findings highlight the potential of H. macrocarpa extracts as natural antioxidant ingredients for functional foods and nutraceutical formulations.

Exploring the Therapeutic Potential of Oridonin in the Treatment of Laryngeal Cancer: A Comprehensive Strategy Involving Network Pharmacology, Molecular Docking, Dynamic Simulation, and Experimental Verification.

Laryngeal cancer (LC) is one of the most common malignant tumors of the head and neck, with high morbidity and mortality rates worldwide. Oridonin (Ori), a natural tetracyclic diterpenoid, exhibits notable anti-tumor properties. However, its efficacy and underlying mechanism in LC remain to be elucidated. This study employed comprehensive network pharmacology, molecular docking, and molecular dynamic simulation to investigate the molecular targets and mechanisms underlying the anti-LC effects of Ori, followed by in vitro validation of its key mechanisms. A total of 172 potential therapeutic targets of Ori for LC were identified. GO and KEGG analyses indicated that Ori’s anti-LC mechanism primarily involved the PI3K-Akt, Ras, MAPK, and Rap1 signaling pathways. The PPI network and molecular docking analyses revealed that AKT1, EGFR, and MAPK1 are potential core targets of Ori. Additionally, molecular dynamics simulations and bioinformatics analyses further confirmed that these proteins are key candidate targets. In vitro, Ori inhibited the proliferation of LC Hep-2 and TU212 cells, induced apoptosis, arrested the cell cycle at the G1 phase, and suppressed migration and invasion. WB assays further showed that Ori significantly downregulated p-AKT expression in the PI3K/AKT pathway. These findings indicate that Ori represents a promising therapeutic candidate for LC.

Chemical composition, antioxidant properties and cytotoxic potential of <i>Leea macrophylla</i> extracts: insights from molecular docking and pharmacokinetic analysis.

This study investigates the chemical composition, antioxidant properties, and antiproliferative activities of Leea macrophylla extracts, with a focus on their potential therapeutic applications. The total phenolic and flavonoid contents were quantified, and antioxidant activity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and hydroxyl radical scavenging assays. Molecular docking studies were performed using PyRx, and pharmacokinetic properties were assessed through SwissADME. Among the tested extracts, the ethyl acetate fraction (EAF) exhibited significantly higher antioxidant activity, with IC 50 values of 9.07 µg/mL (DPPH) and 13.78 µg/mL (hydroxyl radical), alongside higher phenolic and flavonoid content compared to other fractions. The antiproliferative potential of the extracts and the isolated compound, 3,4-dihydroxybenzoic acid, was evaluated against the MCF-7 breast cancer cell line and the normal HEK-293T cell line using the MTT assay. The EAF showed 47.79% inhibition of MCF-7 cells at 512 µg/mL and 24.82% inhibition of HEK-293T cells at 256 µg/mL after 48 h. The isolated compound, 3,4-dihydroxybenzoic acid, inhibited MCF-7 cells by 21.47% at 512 µg/mL (3.35 mM). Docking analysis identified MAPK as the protein with the highest binding affinity to 3,4-dihydroxybenzoic acid. Molecular docking analysis revealed that among the four target proteins studied, MAPK exhibited the highest binding affinity with 3,4-dihydroxybenzoic acid.

Anti-inflammatory effects of Lonicera macranthoides Hand.-Mazz based on Spectrum-effect relationship, network pharmacology and molecular docking technology.

This study investigated the anti-inflammatory properties of Lonicera macranthoides and its active component isochlorogenic acid C (ILAC) through an integrated approach combining spectrum-effect relationship analysis, network pharmacology, and molecular docking. Five extracts (S1-S5) were evaluated in LPS-stimulated RAW 264.7 macrophages, with S4 demonstrating the strongest inhibition (45.53 ± 0.23%). HPLC fingerprinting identified 12 characteristic peaks, including ILAC and chlorogenic acid. PLS regression analysis revealed these two compounds were most positively correlated with the observed anti-inflammatory activity. Network pharmacology predicted 113 potential anti-inflammatory targets for ILAC, with PPI network analysis identifying 10 core targets (e.g., CASP3, HIF1A, NF-κB1, TLR4). Molecular docking studies suggested ILAC’s potential high binding affinity to these targets (<-5 kcal/mol). Together, these in vitro and in silico analyses indicated that ILAC is a key anti-inflammatory constituent in L. macranthoides, likely acting via multi-target interactions with critical inflammatory mediators. The study provided preliminary molecular-level insights into the traditional use of L. macranthoides for inflammatory conditions and suggested ILAC’s potential as a candidate for further anti-inflammatory research. Further in vivo studies are required to substantiate its therapeutic potential and mechanism of action.

Arugula-derived isothiocyanates as novel agents for a potential regulator of AKR1B10 protein in breast cancer: an integrated transcriptomic and molecular docking approach.

Breast cancer (BC) is a leading cause of cancer-related mortality, with estrogen receptor (ER)-negative subtypes, especially triple-negative BC, comprising one-fifth of global cases. Natural inhibitors, particularly those from cruciferous vegetables like arugula (Eruca sativa), which are rich in bioactive isothiocyanates (ITCs), show potent anticancer effects and cytoprotection when combined with chemotherapy. Sulforaphane (SFN) and its analogue erucin modulate oxidative stress, detoxification, and epigenetic pathways. This study computationally assessed their anti-cancer potential in ER-negative BC using transcriptomic analysis, molecular docking, and ADMET profiling. Microarray data (GSE28813) from SFN-treated ER-negative MCF10A cells were analyzed via GEO2R and GEOExplorer to identify highly upregulated differentially expressed genes (DEGs). Key DEGs included AKR1B10 (logFC = 7.26), AKR1C1 (logFC = 5.10), AKR1C3 (logFC = 4.42), NMRAL1P1 (logFC = 6.42), and HKDC1 (logFC = 6.13). Elevated AKR1B10 is strongly linked to early BC malignancies, positioning it as a diagnostic and therapeutic target. Molecular docking showed SFN’s superior binding affinity to AKR1B10 compared to erucin, with strong interactions at catalytic site residues via hydrogen and hydrophobic bonds. ADMET profiling confirmed SFN’s high intestinal absorption and blood-brain barrier non-permeability. Thus, integrating SFN as a natural AKR1B10 inhibitor into ER-negative BC treatment regimens may enhance early malignancy management and support its development as a nutraceutical adjunct.

Mechanistic insights into DEHP-induced progression of non-small cell lung cancer based on network toxicology and molecular docking.

Di(2-ethylhexyl) phthalate (DEHP), a widely used plasticizer, has been implicated in various health risks, including tumorigenesis. Non-small cell lung cancer (NSCLC), accounting for over 80% of lung cancer cases, remains a leading cause of cancer-related mortality. This study employed network toxicology and molecular docking to explore the molecular mechanisms underlying DEHP’s toxic effects on NSCLC. DEHP and NSCLC targets were retrieved from CTD, SwissTargetPrediction, and GeneCards, yielding 225 overlapping genes. Protein-protein interaction (PPI) network analysis identified five core targets: TP53, JUN, SRC, AKT1, and ESR1. Gene Ontology (GO) and KEGG pathway enrichment analyses revealed significant involvement of the PI3K/AKT signaling pathway and regulation of apoptotic signaling in DEHP-induced NSCLC pathogenesis. Molecular docking confirmed strong binding affinities between DEHP and the core targets, with binding energies ranging from - 4.611 to -7.535 kcal/mol. These findings suggest that DEHP promotes NSCLC progression, metastasis, and chemoresistance through PI3K/AKT signaling and apoptotic pathway dysregulation. This study provides mechanistic insights into DEHP’s role in NSCLC and highlights the need for public health interventions to mitigate DEHP exposure. Further experimental validation is warranted to strengthen these findings and guide the development of targeted therapies.

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The protein structure is the language of life; design is its poetry. — Recep Adiyaman

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