Search Results (420)

Background: Ferrocene-containing compounds have gained attention in medicinal chemistry due to their unique redox and structural properties. This study investigates ferrocene-based analogues of imatinib and nilotinib to define their binding determinants within the ABL1 kinase domain using an integrated in silico approach, in relation to their previously reported cytotoxic activity. Methods: Ligand geometries were optimized at the B3LYP/def2-TZVP level with D3(BJ) dispersion and SMD solvation. Molecular docking against ABL1 (PDB ID: 2HYY) was performed using Glide SP, validated by re-docking and enrichment screening. Docked poses were refined using MM-GBSA (Prime, VSGB 2.1/OPLS4). The most active compounds (9 and 15a), together with the inactive control 15e, were subjected to three independent 500 ns molecular dynamics simulations (Desmond, OPLS4), followed by trajectory analysis including RMSD, RMSF, radius of gyration, SASA, and polar surface area. Results: Compounds 9 and 15a maintained stable binding within the ATP-binding pocket despite lacking the canonical hinge interaction with Met318, indicating hinge-independent binding. Their binding was mainly driven by interactions with Asp381 (DFG motif) and cation–π contacts with Lys271. In contrast, the compound 15e showed unstable binding, increased conformational flexibility, reduced pocket burial, and loss of key stabilizing interactions. Active compounds also preserved stable P-loop dynamics, with Tyr253 engagement suggesting a role in loop stabilization. Compound 9 exhibited the most constrained and reproducible binding mode among all analogues. Conclusions: Ferrocene-based analogues can sustain stable ABL1 binding via non-classical interaction networks independent of hinge recognition. The clear distinction between active compounds and the inactive analogue 15e supports the robustness of the proposed binding mode and provides a structural basis for their reported cytotoxic activity. These findings support further experimental evaluation of ferrocene-containing scaffolds as potential BCR-ABL1 inhibitors. Full article

Health, social, and ethical considerations highlight the need for new male contraceptives. Pimozide is an FDA approved drug known to block T-type calcium channels and which shares structural similarities with mibefradil, a proven antagonist of the CatSper channel. In this study, we examined the effect of pimozide on CatSper, a key target for non-hormonal male contraception. Molecular docking and molecular dynamics simulations were carried out to assess how pimozide binds within the channel pore, and binding energies were estimated using MM-GBSA. To determine its impact on sperm function, we evaluated hyperactivation, the acrosome reaction, and CatSper activity. Our computational analyses indicate that pimozide functions as a pore blocker of the CatSper channel. Experimental findings further support this, showing that pimozide inhibits CatSper activity, and impairs hyperactivation and the acrosome reaction in human spermatozoa. Overall, these results identify pimozide as a novel CatSper antagonist and propose a binding mode, offering a basis for the rational design of reversible, non-hormonal male contraceptives that target the CatSper channel. Full article

Marburg virus (MARV), a highly pathogenic member of the Filoviridae family, causes severe hemorrhagic fever with a high case fatality rate and currently lacks effective therapeutics. The viral entry process, mediated by the interaction between the MARV glycoprotein (GP) and host receptor C-type lectin domain family 4 member M (CLEC4M) (L-SIGN), represents a critical target for early-stage intervention. The active compounds from BindingDB and the decoy from DUDE were used. The RDKit was used for feature engineering. Machine learning models were trained on an initial dataset consisting of 56 active chemicals and 1232 decoys. Among the tested algorithms, the Random Forest model demonstrated superior performance, achieving the highest discriminative ability (AUC = 0.93, MCC = 0.88) on the test set. Virtual screening of 11,032 phytochemicals resulted in 120 predicted actives, of which 42 compounds satisfied drug-likeness criteria. Subsequent molecular docking identified three lead compounds (PubChem IDs: 42608095, 5281601, and 11243993) with moderate-to-promising binding affinities (−6.3 to −6.5 kcal/mol) toward the CLEC4M binding site. ADMET analysis revealed favorable pharmacokinetic and toxicity profiles for the selected lead compounds. DFT calculations of the three compounds highlighted their electronic stability and reactive nature, indicating that PubChem IDs 42608095 and 5281601 possess particularly stable electronic properties conducive to favorable target interactions. Combining machine learning models with molecular docking and Molecular Dynamics (MD) simulations worked well in finding promising phytochemical inhibitors. The MM/GBSA binding free energy calculations further confirmed binding affinities, with values of −10.83 and −11.08 kcal/mol, respectively, suggesting favorable complex stability. These findings provide a pathway for developing new antiviral agents against MARV, pending further experimental validation and optimization. Full article

The present study aimed to design, synthesize, and evaluate a new series of thieno[3,2-d]pyrimidin-4(3H)-one-based Schiff bases as potential antileishmanial agents against Leishmania major (L. major). A series of twenty thieno[3,2-d]pyrimidine Schiff base derivatives were synthesized and characterized using FTIR, NMR, and HRMS techniques. Their antipromastigote activities were evaluated in vitro against L. major, while cytotoxic effects were assessed on HUVECs to determine selectivity indices. The most active compound was further investigated using molecular docking against several L. major proteins. Among the tested compounds, compound 12, bearing a 2-hydroxy-5-bromophenyl moiety, exhibited the most potent activity against L. major promastigotes with an IC₅₀ value of 13.7 µM, along with a favorable selectivity index (SI = 17.5), outperforming the reference drug miltefosine (IC₅₀ = 31 µM and SI = 0.2). Docking studies demonstrated that compound 12 showed the strongest binding affinity toward phosphodiesterase B1, supported by a docking score of −9.042 kcal/mol and an MM-GBSA value of −67.21 kcal/mol. This study highlights thieno[3,2-d]pyrimidin-4(3H)-one as a promising scaffold in the context of in vitro antileishmanial screening and suggests the role of ortho-phenolic substitution in enhancing activity and selectivity. Compound 12 emerges as a promising lead, warranting further optimization and biological evaluation in future studies. Full article

Background/Objectives: Poly (ADP-ribose) polymerase (PARP1) has emerged as a promising therapeutic target in human breast cancer particularly in BRCA1/2 mutation carriers where a synthetic lethal interaction leads to massive tumor cell death upon specific inhibitors’ administration. Current clinically approved PARP inhibitors (Talazoparib and Olaparib) show outstanding therapeutic capabilities but suffer from severe side effects. Most importantly, some of them can cause life-threatening cardiotoxicity through hERG off-target effects. Here, we performed an extensive study to identify lead compounds with improved binding modes and favorable predicted pharmacokinetics using an integrated computational strategy. Methods: An artificial intelligence-driven drug design (AIDDISON™ v2023) workflow was employed to search ultra-large chemical space libraries for active compounds, which were then optimized via computer-aided methods to form a PARP-Tailored Database (PTD). This database was then analyzed through a virtual screening workflow, molecular docking studies, molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, DFT analysis and ADME/Tox predictions using the Schrödinger suite (v2023-2), MobaXterm v25.2, Gaussian 16.0, ProTox-3 and Pred-hERG v5.0 respectively. Results: Three compounds (1a–1c) were identified as promising candidates. Among them 1a appeared to be the most active compound with a favorable docking score (−9.488 kcal/mol) that is not only higher than 1b and 1c but also higher than that of Talazoparib (−6.778 kcal/mol). MD simulations of 1a–1c in the active site revealed an average RMSD of ~2.5–3.6 Å which is better compared to the parent Talazoparib (5.6 Å). Interestingly, on the 250 ns extended MD study, 1a exhibited a slightly reduced RMSD between 2.4 and 3.2 Å, whereas Talazoparib retained higher fluctuations of ~5 Å to 6 Å. MM/GBSA binding energy analysis indicated 1a to have better predicted binding affinity (−67.820 kcal/mol), which is also better than Talazoparib (−63.734 kcal/mol). DFT calculations showed good electronic properties and in silico ADMET studies also indicated 1a to have good drug-likeness and lower predicted hepatotoxicity and cardiotoxicity risk. Conclusions: These findings identify compound 1a as a promising lead, while compounds 1b and 1c remain viable candidates for further optimization. However, experimental validation is critical to confirm the predicted biological activity and safety profiles. Full article

Background/Objectives: Methylxanthines, such as caffeine, exhibit neuroprotective properties in neurodegenerative conditions, partly linked to modulation of monoamine oxidase B (MAO-B) and oxidative stress pathways. This work aimed to design, synthesize and functionally characterize new caffeine-8-methylthioglycolic acid derivatives as selective MAO-B inhibitors with neuroprotective potential. Methods: A QSAR model was built on 94 studies of xanthine derivatives to guide the design of ten new semi- and thiosemicarbazides (Jas1–Jas10), followed by molecular docking to human MAO-B (PDB: 2V5Z) using Glide, GOLD and MM-GBSA binding free energy calculations. The target compounds were synthesized in relatively high yields, structurally confirmed by spectroscopic methods and tested in vitro for hMAO-A/B inhibition, as well as for neurotoxicity and neuroprotection in isolated mouse brain synaptosomes, mitochondria and microsomes under 6-hydroxydopamine (6-OHDA), tert-butyl hydroperoxide (t-BuOOH) and Fe/ascorbate (Fe²⁺/AA)-induced oxidative stress. Results: Docking and MM-GBSA identified Jas6 and Jas7 as the most stable MAO-B binders, with binding free energies approaching those of safinamide. All derivatives inhibited hMAO-A and hMAO-B in the submicromolar range, with Jas2 and Jas6 showing the highest MAO-B selectivity indices. At 100 µM, the series produced mild but significant pro-oxidant and cytotoxic effects when applied alone, yet under oxidative stress all compounds, especially Jas2 and Jas6, markedly preserved synaptosomal and mitochondrial viability, maintained glutathione levels, and reduced malondialdehyde production. Conclusions: The caffeine-based semi- and thiosemicarbazides, particularly Jas2 and Jas6, emerge as promising selective MAO-B inhibitors with pronounced antioxidant and neuroprotective activity, supporting their further optimization as multitarget candidates for neurodegenerative disorders such as Parkinson’s disease. Full article

Beta Secretase (BACE1) is a well-validated target for Alzheimer’s therapies, but there has been attrition in drug development. Herein, we leveraged machine learning (ML), virtual screening and molecular dynamics (MD) to identify novel compounds with potential activity against BACE1. We developed ML algorithms to distinguish active and inactive compounds from public databases. Molecular docking and dynamics were used to explore the inhibition mechanism, thermodynamic stability, and the flap dynamics of the BACE1-ligand complexes. Random Forest Classifier (RF) showed excellent metrics (accuracy: 0.9807; F1 score: 0.9804; specificity 0.9977), compared to other models. Molecular docking with predicted actives revealed compounds BA1, BA2, and BA3 with strong affinity for BACE1. Compound BA2, a cysteinyl sulfoxide derivative, showed good stability (RMSD) during simulations (1.307 ± 0.109 Å) compared to Verubecestat (1.602 ± 0.159 Å). MMGBSA-based binding free energy (ΔG_bind; kcal/mol) showed that BA2 (−33.820 ± 4.254) had comparatively lower energy than Verubecestat (−21.090 ± 6.183). BA2 maintained electrostatic interactions with the catalytic dyad (Asp36 and Asp232) and Thr76 of the flap. BA2 also maintained the flaps in a semi-open conformation (d0: 11.807 ± 0.401 Å) throughout the simulation. Our study clearly demonstrates the utility of ML in prioritization of compounds before molecular docking and MD in early phases of drug discovery. Full article

Background/Objectives: Osteoporosis remains a clinically important metabolic bone disorder with limited bone-forming therapeutic options. SET domain bifurcated protein 1 (SETDB1) is involved in osteogenic epigenetic regulation, but small-molecule discovery guided by SETDB1-associated structural regions remains limited. This study aimed to identify a candidate compound with in silico relevance to a SETDB1-associated ligand-bound pocket and assess its association with early osteogenic readouts. Methods: A computational–experimental workflow was used, including hierarchical molecular docking, MM-GBSA rescoring, ADMET-based prioritization, redocking validation, molecular dynamics simulations, and preliminary in vitro evaluation in MC3T3-E1 cells. Compound 271 (C271) was selected based on structure-based screening results and predicted developability-related properties. Cytocompatibility, alkaline phosphatase (ALP) activity and staining, selected molecular markers, and SETDB1–H3 molecular dynamics behavior were evaluated. Results: Redocking reproduced the reference binding mode, and molecular dynamics simulations indicated that C271 maintained a relatively persistent conformation around the predicted SETDB1-associated pocket. Comparative SETDB1–H3 simulations showed altered H3 dynamics and SETDB1–H3 contact patterns in the C271-containing system. In cell-based assays, C271 showed no appreciable cytotoxicity within the tested concentration range and was associated with increased ALP activity and staining. C271 treatment was accompanied by higher global H3K9me3 and Runx2 levels, whereas SETDB1 protein abundance remained largely unchanged. Conclusions: C271 was identified as a computationally prioritized SETDB1-related candidate compound associated with early osteogenic-associated cellular responses. The evidence supports computational plausibility and cell-level association, but does not establish direct SETDB1 engagement, SETDB1 enzymatic modulation, SETDB1-dependent causality, or late-stage osteogenic maturation/mineralization. Given the single-compound evaluation, further target-engagement, enzymatic, and functional studies are needed. Full article

Background: Diabetes mellitus remains a major public health concern, particularly in sub-Saharan Africa where type 2 diabetes predominates. In West Africa, Uvaria chamae P. Beauv. is traditionally used for diabetes management. This study investigates previously reported metabolites from Uvaria chamae using an integrated in silico approach to explore their potential antidiabetic activity and underlying mechanisms. Methods: A comprehensive literature survey identified 106 phytochemicals from stems, roots, leaves, and seeds. Diabetes-related protein targets were retrieved from the RCSB Protein Data Bank, while ligand structures were obtained from PubChem and the COCONUT database. Molecular docking, MM-GBSA rescoring, induced-fit docking, QSAR, and ADMET analyses were performed to evaluate interaction profiles, predicted activity, and developability. Results: The integrated analysis supports a polypharmacological mixture-based profile with organ-associated trends. Stem- and root-derived flavonoids, particularly isouvaretin and diuvaretin, showed the most consistent profiles for PPARγ-related pathways, while uvarinol was associated with PTP1B. Leaf alkaloids were mainly linked to DPP-4 and digestive enzyme inhibition. These compounds displayed more favorable predicted pharmacokinetic and toxicity profiles compared to acetogenins, which, despite favorable binding energies, were not prioritized as drug-like candidates due to their high lipophilicity, low QED values, and predicted toxicity liabilities, but may contribute to extract-level activity. Conclusion: These findings provide a hypothesis-generating and hierarchical framework for the prioritization of Uvaria chamae metabolites and extracts, supporting further experimental validation through enzymatic, cellular, and gene expression studies. Full article

Background/Objectives: The unprecedented structural and binding data for antibodies to the SARS-CoV-2 virus taken together with the mutations for the spike protein allows for a broad simulation study of antibody–spike protein binding. This provides an understanding of the co-evolution of human immunity and viral immunity escape. Methods: We utilized the YASARA molecular dynamics program to generate initial structures and simulate to equilibration for six SARS-CoV-2 variants and ten different antibodies sampling two different binding regions to the receptor binding domain of the spike (especially for the Class I antibodies in the same part of the spike that attaches to the ACE2 receptor protein) and one to the N-terminal domain of the spike. Starting structures for antibody binding to variant spike protein domains are perturbatively achieved through point mutations and insertions/deletions in the YASARA program. We employed YASARA to measure interfacial hydrogen bound counts between antibodies and variant spike proteins and the HawkDock MMGBSA program to characterize trends in binding energies with mutation for four of the antibodies. We utilized the VMD program to analyze the time course of hydrogen bond populations. Results: As seen in previous studies, interfacial hydrogen bond counts serve as an excellent proxy for binding energies without the large systematic error inherent in the latter. We find that there is generally a decline in antibody binding strength, as measured by interfacial hydrogen bond counts, with viral evolution, but that a modest re-entrance of binding strength is present for most antibodies studied. Generically, the antibody heavy chain binds more strongly to the spike protein, though for approximately half the antibodies the light chain binding strength converges to the heavy chain strength with viral evolution. Conclusions: The key conclusion is that the identified re-entrant immunity, speculatively arising from a balancing of maintenance of ACE2-spike binding while escaping antibodies through mutation, allows for some maintenance and even strengthening of immunity for later viral strains from early infection or vaccination. Full article

The anti-apoptotic Bcl-2 protein family, frequently upregulated in a wide range of cancers, contributes to tumor persistence and therapeutic resistance, making these proteins attractive targets for structure-based inhibitor development. Betulinic acid-derived hybrids represent promising scaffolds for apoptosis-oriented anticancer drug discovery due to their reported antiproliferative and pro-apoptotic properties. In this study, a virtual library of 152 betulinic acid-derived hybrids was screened against Bcl-2 and Bcl-XL. This molecular docking study using AutoDock Vina identified BA–Celastrol and BA–Proanthocyanidin B2 as top-ranked ligands, with docking scores ranging from −13.00 to −8.7 kcal/mol. Both compounds were further analyzed by 100 ns molecular dynamics simulation runs, which revealed system-dependent ligand behavior rather than uniform preservation of the initial docked pose across all complexes. BA–Celastrol showed a more compact internal ligand conformation in the ligand property and RMSF analyses, whereas BA–Proanthocyanidin B2 showed greater intramolecular flexibility and conformational adaptability. Ligand displacement relative to the protein differed between targets, with BA–Proanthocyanidin B2 showing a more retained profile in the Bcl-XL model and BA–Celastrol showing more moderate positional behavior in the Bcl-2 model. MM-GBSA calculations resulted in free energy values ranging from −4.95 to −31.82 kcal/mol, indicating protein-dependent energetic differences across the investigated systems. Based on docking performance, molecular dynamics stability, and energetic data, both hybrids were ranked as computational candidates for further exploration against Bcl-2 family targets. The present findings, although confined to computational analysis, underscore the need for prioritizing betulinic acid-based hybrids for subsequent experimental evaluation. Full article

Traditional doubanjiang was investigated to identify endogenous peptides that may contribute to taste maintenance under salt-reduction conditions. Peptidomics identified 1230 peptides at −10logP ≥ 15. UMPred-FRL predicted 161 potential umami peptides, and molecular docking showed that 141 of these peptides could enter the binding site of the T1R1/T1R3 receptor. The successfully docked sequences were mainly short oligopeptides containing three to five amino acid residues. Based on docking scores, six representative candidate peptides were screened, namely EESP, SCPH, SSSGF, PDTE, SYH, and DYDS. Docking and MM-GBSA analyses suggested that these peptides mainly bound within the VFT cavity of T1R1/T1R3, and the interacting residues were dominated by polar residues such as Ser, Asn, Gln, and His and hydrophobic residues such as Tyr, Ile, Leu, and Val. MM-GBSA further suggested that vdW was the major favorable contributor, while Lipo supported complex stability. The umami thresholds of the six peptides ranged from 0.14 to 1.09 mmol/L. Experimental validation by threshold determination and sensory addition showed that all six peptides significantly increased saltiness, whereas their effects on umami differed. PDTE showed the strongest umami-enhancing effect, while SSSGF, SYH, and SCPH exhibited more pronounced saltiness synergy. These results suggest that the screened peptides do not necessarily amplify umami in complex food systems, but may contribute to taste maintenance under salt-reduction conditions through umami support, saltiness synergy, and taste-structure remodeling. Full article

Background: Thrombotic disorders remain one of the leading causes of global mortality, necessitating the discovery of anticoagulants with broader therapeutic windows and multi-target efficacy. This study aimed to identify FDA-approved drugs capable of simultaneously inhibiting three critical nodes of the coagulation cascade: Factor X (F10), Proteinase-activated receptor 1 (PAR1) and Prothrombin (F2). Methods: High-confidence 3D structures of coagulation cascade proteins were established using AlphaFold2 and validated via MolProbity (Favored regions > 91%). A library of 1657 compounds from the Zinc database was screened using PyRx, followed by rigorous ADMET profiling to evaluate pharmacokinetic viability. The structural integrity and binding kinetics of the top candidate drugs were further analyzed through Molecular Dynamics simulation for 100 ns. Results: Virtual screening and downstream analysis identified 30 multi-target drugs. Avodart and Naldemedine were observed to have superior pharmacokinetic equilibrium. Compared to the other two drugs (Digoxin and Ledipasvir), Avodart and Naldemedine showed high affinity, higher adherence to drug likeness, lower metabolic inhibition risks and lack of acute toxicity, and were therefore the most suitable candidates. The 100 ns MD simulations revealed Avodart and Naldemedine to have the highest level of interaction stability and favorable MM-GBSA energies with Factor X, whereas Ledipasvir and Digoxin exhibited significant structural instability. Conclusions: The study proposes Avodart and Naldemedine as promising candidates for drug repurposing in antithrombotic therapy. This study provides a computational blueprint for the development of next-generation, broad-spectrum anticoagulants. Full article

Background/Objectives: Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge, exacerbated by the emergence of multidrug-resistant strains and limited efficacy of existing therapies. Given the involvement of multiple essential mycobacterial proteins, multitarget drug discovery represents a rational therapeutic strategy. Methods: In this study, an integrated in silico pipeline combining machine learning–based quantitative structure–activity relationship modeling, graph neural network–driven drug–target affinity prediction, molecular docking, molecular dynamics (MD) simulations, and pharmacokinetic–toxicity profiling was employed to identify potential antitubercular leads from natural products. Results: A curated library of over 0.69 million compounds from the COCONUT database was systematically screened against seven essential M. tuberculosis protein targets. Machine learning and heterogeneous graph neural network models effectively captured complex ligand–protein interaction patterns, enabling high-confidence multitarget prioritization. Structure-based docking and MM-GBSA analyses revealed favorable binding affinities, further supported by 100 ns Molecular Dynamics simulations demonstrating stable binding and conformational integrity. In silico ADMET and toxicity predictions identified pharmacokinetically balanced candidates, while density functional theory calculations corroborated favorable electronic properties. Conclusions: Notably, a myricetin-based flavonoid glycoside exhibited consistent multitarget binding and dynamic stability across all targets. Overall, this study underscores the potential of integrated artificial intelligence and structure-based approaches in accelerating natural product-based antitubercular drug discovery and supports further experimental validation of prioritized leads. Full article

This study aimed to identify umami peptides in non-alcoholic beer and clarify their potential contribution to taste reconstruction and aftertaste improvement. Peptides were profiled by RPLC-Q-TOF-MS and screened using machine learning prediction, molecular docking, MM-GBSA analysis, and sensory validation. Under the criteria of −10logP ≥ 15 and ALC ≥ 90.00%, 2081 peptides were identified. Among them, 122 potential umami peptides were predicted, and 117 peptides were successfully docked with the T1R1/T1R3 umami receptor. The docked peptides were mainly short to medium oligopeptides, especially tetrapeptides and pentapeptides, which accounted for 40.17% and 35.90%, respectively. Based on docking score, structural diversity, and peptide length distribution, CTGAA, IDQILG, KDTHP, QRQ, and EITGR were selected as representative candidates. These peptides showed favorable receptor binding, mainly supported by hydrogen bonding, electrostatic interactions, and local hydrophobic contacts. Sensory validation further showed that the 5 peptides improved umami and aftertaste cleanliness to different degrees. Umami intensity increased by 7.58% to 22.73%, while aftertaste cleanliness increased by 5.80% to 17.39%. Among them, CTGAA showed the strongest umami enhancement, and QRQ produced the greatest improvement in aftertaste cleanliness. These results suggest that selected umami peptides may contribute to flavor reconstruction in non-alcoholic beer by enhancing umami perception and improving aftertaste quality. Full article