Search Results (29)

Schiff bases are widely studied for their biological activities, yet structure–activity relationships governing their anticancer potential remain insufficiently understood. In this work, eight structurally diverse imine derivatives (A–H) were evaluated for their cytotoxic, biochemical, and biomolecular interactions in human cancer cells. Their antiproliferative effects were assessed in HeLa, A549, and LS174T cell lines, with MRC-5 fibroblasts used as a non-malignant control. Cytotoxicity screening identified three compounds (A, B, and F) with the highest potency, prompting further mechanistic investigation. Cell cycle analysis revealed G1 arrest and accumulation of sub-G1 populations for all three derivatives, with compound B additionally increasing S-phase content and compound F inducing G2/M arrest. All compounds reduced intracellular ROS levels and caused significant DNA damage at subtoxic concentrations. Western blot analysis demonstrated downregulation of HIF-1α and PDK3, suggesting disruption of hypoxia-associated metabolic signaling. Fluorescence quenching experiments showed strong binding of the active compounds to bovine serum albumin (K_a ≈ 10⁶ M⁻¹), and molecular docking supported stable interactions near tryptophan-adjacent binding regions. Collectively, these findings indicate that selected Schiff bases exert multi-target anticancer activity by modulating oxidative stress, DNA integrity, cell-cycle progression, and metabolic adaptation pathways, warranting further investigation of their therapeutic potential. Full article

Blind docking predicts binding interactions between two molecular entities without prior knowledge of the binding site. This approach is essential because it explores the entire surface of the receptor to identify potential interaction sites. Blind docking widely works for both protein–protein and ligand–protein interaction studies. In protein–protein blind docking, the method aims to predict the correct orientation and interface of two proteins forming a complex. Protein blind docking is particularly valuable in studying transient interactions, protein–protein recognition, signaling pathways, tentative and significant biomolecular assemblies where structural data is limited. Ligand–protein blind docking discovers potential binding pockets across the entire protein surface. It is frequently applied in early-stage drug discovery, especially for novel or poorly characterized targets. The method helps identify allosteric sites or novel binding regions that are not evident from known structures. Overall, blind docking provides a versatile and powerful tool for studying molecular interactions, enabling discovery even in the absence of detailed structural information. In this scenario, we reported a timeline of attempts to improve this kind of computational approach with ML and hybrid approaches to obtain more reliable predictions. We dedicate two main sections to protein–protein and protein-ligand blind docking, presenting the reliability and caveats for each approach and outlining potential future directions. Full article

Protein–protein docking is a cornerstone of computational structural biology, yet its reliability for large, multimeric assemblies remains uncertain. Standard workflows typically include geometry optimization or molecular dynamics equilibration to relieve local strains and improve input quality, but the extent to which these preparatory steps alter docking outcomes has not been systematically evaluated. Here, we address this question using the mitochondrial chaperonin Hsp60, a dynamic double-ring complex essential for protein folding, and MIX, a kinetoplastid-specific protein with unresolved function, as a stress test system. By comparing docking predictions across minimized, equilibrated, and ensemble-refined structures of Hsp60 in three conformational states (apo, ATP-bound, and ATP–Hsp10), we show that structural relaxation profoundly reshapes the docking landscape. Minimization alone often yielded favorable scores but localized binding, while longer MD trajectories exposed alternative sites, including central cavity, equatorial ATP pocket, and apical domain, each consistent with distinct regulatory hypotheses. These findings reveal that docking outcomes are highly sensitive to receptor preparation, especially in complexes undergoing large conformational transitions. More broadly, our study highlights an underappreciated vulnerability of docking pipelines and calls for ensemble-based and dynamics-aware approaches when predicting interactions in large biomolecular machines. Full article

Rhamnose is a natural sugar found in glycoproteins and structural polysaccharides of plants, fungi, and bacteria. Its incorporation into glycoconjugates is mediated by rhamnosyltransferases (RHTs), key enzymes for biomolecular stability and function. While rhamnose biosynthesis has been studied in certain fungal genera, the evolutionary history and distribution of RHTs across the fungal kingdom remain largely unknown. In this study, 351 fungal species were found to encode putative RHTs. Phylogenetic and structural analyses revealed conserved patterns and similarities with previously characterized RHTs. Molecular docking predicted a high affinity of these proteins for UDP-L-rhamnose, and in silico mutagenesis identified key residues potentially involved in substrate binding. Carbohydrate profiling confirmed the presence of rhamnose in the cell walls of multiple fungi, including Aspergillus, Madurella, Metarhizium, and Trichoderma species. Enzymatic assays further supported rhamnose transfer activity. These findings provide the first comprehensive in silico characterization of fungal RHTs, uncovering conserved sequence motifs despite overall diversity, which may be linked to functional adaptation in different fungal lineages. Full article

We report on the synthesis and characterization of a novel fluorenyl-methoxycarbonyl (Fmoc)-containing thioxo-triazole-bearing dipeptide 5, evaluated for potential therapeutic applications. The compound was tested for its antioxidant and antimicrobial properties, demonstrating significant effects in scavenging reactive oxygen species (ROS) and inhibiting microbial growth, particularly when combined with plant extracts from an endemic Peonia species from the Caucasus. Circular dichroism (CD) binding studies with bovine serum albumin (BSA) and calf thymus DNA revealed important interactions, suggesting the dipeptide’s potential in biomedically relevant conditions that involve DNA modulation. Molecular docking and CD spectra deconvolution provided additional insights into the binding mechanisms and structural characteristics of the formed complexes with the biomolecular targets. The Fmoc group enhances the dipeptide’s lipophilicity, which may facilitate its interaction with cellular membranes, supporting efficient drug delivery. A computational evaluation at the ωB97XD/aug-cc-pVDZ level of theory was carried out, confirming the experimental results and revealing a powerful potential of the peptide as an antioxidant, through FMOs, MEP analysis, and antioxidant mechanism assessments. Together, these findings suggest that this dipeptide could be valuable as an antimicrobial and antioxidant agent, with potential applications in pathologies involving oxidative stress, DNA modulation, and microbial infections. Full article

The coordination chemistry, structural characterization, and biomolecular interactions of europium(III) and iron(III) complexes with the pyridoxal-semicarbazone (PLSC) ligand were thoroughly examined using experimental and computational approaches. Single-crystal X-ray diffraction revealed that the europium complex exhibits a nine-coordinate geometry with one protonated and one deprotonated PLSC ligand and nitrato and aqua ligands. In contrast, the iron complex adopts a six-coordinate structure featuring a monoprotonated PLSC, two chlorido, and an aqua ligand. Hirshfeld surface analysis confirmed the significance of intermolecular contacts in stabilizing the crystal lattice. Theoretical geometry optimizations using DFT methods demonstrated excellent agreement with experimental bond lengths and angles, thereby validating the reliability of the chosen computational levels for subsequent quantum chemical analyses. Quantum Theory of Atoms in Molecules (QTAIM) analysis was employed to investigate the nature of metal–ligand interactions, with variations based on the identity of the donor atom and the ligand’s protonation state. The biological potential of the complexes was evaluated through spectrofluorimetric titration and molecular docking. Eu-PLSC displayed stronger binding to human serum albumin (HSA), while Fe-PLSC showed higher affinity for calf thymus DNA (CT-DNA), driven by intercalation. Thermodynamic data confirmed spontaneous and enthalpy-driven interactions. These findings support using PLSC-based metal complexes as promising candidates for future biomedical applications, particularly in drug delivery and DNA targeting. Full article

AlphaFold3, the latest release of AlphaFold developed by Google DeepMind and Isomorphic Labs, was designed to predict protein structures with remarkable accuracy. AlphaFold3 enhances our ability to model not only single protein structures but also complex biomolecular interactions, including protein–protein interactions, protein–ligand docking, and protein-nucleic acid complexes. Herein, we provide a detailed examination of AlphaFold3’s capabilities, emphasizing its applications across diverse biological fields and its effectiveness in complex biological systems. The strengths of the new AI model are also highlighted, including its ability to predict protein structures in dynamic systems, multi-chain assemblies, and complicated biomolecular complexes that were previously challenging to depict. We explore its role in advancing drug discovery, epitope prediction, and the study of disease-related mutations. Despite its significant improvements, the present review also addresses ongoing obstacles, particularly in modeling disordered regions, alternative protein folds, and multi-state conformations. The limitations and future directions of AlphaFold3 are discussed as well, with an emphasis on its potential integration with experimental techniques to further refine predictions. Lastly, the work underscores the transformative contribution of the new model to computational biology, providing new insights into molecular interactions and revolutionizing the fields of accelerated drug design and genomic research. Full article

Algae, despite being labeled as an underexplored biological source of chemical constituents, remain inadequately studied in terms of their metabolism. Metabolomics has emerged as a high-throughput technology to investigate the full metabolic profile of samples that could aid in the understanding and characterization of algae. By delving into their primary composition, particularly polysaccharides and phycobiliproteins, alongside secondary metabolites like polyphenols and pigments, researchers can uncover not only their rheological and nutritional properties but also their diverse biological activities. Given the growing interest in algae in food and related industries, innovative approaches should be explored to enhance the value of their functional components. In this sense, in the context of contemporary in-silico studies, metabolomics should be paired with computational methodologies, to develop novel techniques for studying biomolecular interactions. Molecular docking has emerged, with the function of predicting the atomic-level interaction between small molecules (ligands) and target proteins (proteins). This synergistic approach integrating both technologies could allow us to characterize algal profiles, evaluate their potential for bioactive properties, and better understand their metabolism. This work explores the development of metabolomic and computational strategies targeted toward the functional characterization of algae. By harnessing these technologies, we can unlock new possibilities for using algae in various industrial applications, paving the way for sustainable and innovative solutions in the future. Full article

Drug discovery was initially attributed to coincidence or experimental research. Historically, the traditional approaches were complex, lengthy, and expensive, entailing costly random screening of synthesized compounds or natural products coupled with in vivo validation largely depending on the availability of appropriate animal models. Currently, in silico modeling has become a vital tool for drug discovery and repurposing. Molecular docking and dynamic simulations are being used to find the best match between a ligand and a molecule, an approach that could help predict the biomolecular interactions between the drug and the target host. Beauvericin (BEA) is an emerging mycotoxin produced by the entomopathogenic fungus Beauveria bassiana, being originally studied for its potential use as a pesticide. BEA is now considered a molecule of interest for its possible use in diverse biotechnological applications in the pharmaceutical industry and medicine. In this manuscript, we provide an overview of the repurposing of BEA as a potential therapeutic agent for multiple diseases. Furthermore, considerable emphasis is given to the fundamental role of in silico techniques to (i) further investigate the activity spectrum of BEA, a secondary metabolite, and (ii) elucidate its mode of action. Full article

Protein model refinement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR refinement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/side-chain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-refined structures and found significant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each refinement element and found that the torsional angle potential played a significant role in improving the geometric validation metrics. In addition, we investigated protein–ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational refinement methods could improve biomolecular NMR structural determination. Full article

Background and Objectives: Breast cancer is a significant type of cancer among women worldwide. Studies have reported the anti-carcinogenic activity of Hydrastis Canadensis (Goldenseal) in cancer cell lines. Hydrastis Canadensis could help eliminate toxic substances due to its anti-cancer, anti-inflammatory, and other properties. The design phase includes the identification of potential and effective molecules through modern computational techniques. Objective: This work aims to study Hydrastis Canadensis’s effect in controlling hormone-independent breast cancer through in-silico analysis. Materials and Methods: The preliminary screening of reported phytochemicals includes biomolecular networking. Identifying functionally relevant phytochemicals and the respective target mutations/genes leads to selecting 3D proteins of the desired mutations being considered the target. Interaction studies have been conducted using docking. The kinetic and thermodynamic stability of complexes was studied through molecular dynamic simulation and MM-PBSA/GBSA analysis. Pharmacodynamic and pharmacokinetic features have been predicted. The mechanism-wise screening, functional enrichment, and interactional studies suggest that canadaline and Riboflavin effectively interact with the target proteins. Results: Hydrastis Canadensis has been identified as the effective formulation containing all these constituents. The phytoconstituents; Riboflavin and Canadensis showed good interaction with the targets of hormone-independent breast cancer. The complexes were found to be kinetically and thermodynamically stable. Conclusions: Hydrastis Canadensis has been identified as effective in controlling ‘hormone-independent or basal-like breast cancer’ followed by ‘hormone-dependent breast cancer: Luminal A’ and Luminal B. Full article

In this project, we combine two areas of research, experimental characterization and molecular docking studies of the interaction of positively charged oligopeptides with crucial blood plasma proteins. The investigated peptides are rich in NH₂ groups of amino acid side chains from Dap, Orn, Lys, and Arg residues, which are relevant in protein interaction. The peptides are 9- and 11-mer with the following sequences: (Lys-Dab-Dab-Gly-Orn-Pro-His-Lys-Arg-Lys-Dbt), (Lys-Dab-Ala-Gly-Orn-Pro-His-Lys-Arg), and (Lys-Dab-Dab-Gly-Orn-Pro-Phe(2-F)-Lys-Arg). The net charge of the compound strongly depends on the pH environment and it is an important aspect of protein binding. The studied oligopeptides exhibit therapeutic properties: anti-inflammatory activity and the capacity to diminish reactive oxygen species (ROS). Therefore, the mechanism of potential binding with blood plasma components is the next challenge. The binding interaction has been investigated under pseudo-physiological conditions with the main blood plasma proteins: albumin (BSA), α1-acid glycoprotein (AAG), and γ-globulin fraction (GGF). The biomolecular quenching constant (k_q) and binding constant (K_b) were obtained by fluorescence spectroscopy at various temperatures. Simultaneously, the changes in the secondary structure of proteins were monitored by circular dichroism (CD) and infrared spectroscopy (IR) by quantity analysis. Moreover, molecular docking studies were conducted to estimate the binding affinity, the binding domain, and the chemical nature of these interactions. The results show that the investigated oligopeptides could be mainly transported by albumin, and the binding domain I is the most favored cavity. The BSA and GGF are able to form stable complexes with the studied compounds as opposed to AAG. The binding reactions are spontaneous processes. The highest binding constants were determined for Lys-Dab-Dab-Gly-Orn-Pro-His-Lys-Arg-Lys-Dbt peptide, in which the values of the binding constants K_b to BSA and GGF were 10.1 × 10⁴ dm³mol⁻¹ and 3.39 × 10³ dm³mol⁻¹, respectively. The positively charged surface of peptides participated in salt bridge interaction with proteins; however, hydrogen bonds were also formed. The secondary structure of BSA and GGF after contact with peptides was changed. A reduction in the α-helix structure was observed with an increase in the β-sheet and β-turn and random coil structures. Full article

Novel constructed bioactive mixed-ligand complexes (1b) [Cu^II(L)₂(phen)] and (2b) [Zn^II(L)₂(phen)] {where, L = 2-(4-morpholinobenzylideneamino)phenol), phen = 1,10-phenanthroline} have been structurally analysed by various analytical and spectroscopic techniques, including, magnetic moments, thermogravimetric analysis, and X-ray crystallography. Various analytical and spectral measurements assigned showed that all complexes appear to have an octahedral geometry. Agar gel electrophoresis’s output demonstrated that the Cu(II) complex (1b) had efficient deoxyribonucleic cleavage and complex (2b) demonstrated the partial cleavage accomplished with an oxidation agent, which generates spreadable OH^● through the Fenton type mechanism. The DNA binding constants observed from viscosity, UV–Vis spectral, fluorometric, and electrochemical titrations were in the following sequence: (1b) > (2b) > (HL), which suggests that the complexes (1b–2b) might intercalate DNA, a possibility that is supported by the biothermodynamic measurements. In addition, the observed binding constant results of BSA by electronic absorption and fluorometric titrations indicate that complex (1b) revealed the best binding efficacy as compared to complex (2b) and free ligand. Interestingly, all compounds are found to interact with BSA through a static approach, as further attested by FRET detection. The DFT and molecular docking calculations were also performed to realize the electronic structure, reactivity, and binding capability of all test samples with CT-DNA, BSA, and the SARS-CoV-2 3CL^Pro, which revealed the binding energies were in a range of −8.1 to −8.9, −7.5 to −10.5 and −6.7–−8.8 kcal/mol, respectively. The higher reactivity of the complexes than the free ligand is supported by the FMO theory. Among all the observed data for antioxidant properties against DPPH^᛫, ^᛫OH, O₂^−• and NO^᛫ free radicals, complex (1a) had the best biological efficacy. The antimicrobial and cytotoxic characteristics of all test compounds have been studied by screening against certain selected microorganisms as well as against A549, HepG2, MCF-7, and NHDF cell lines, respectively. The observed findings revealed that the activity enhances coordination as compared to free ligand via Overtone’s and Tweedy’s chelation mechanisms. This is especially encouraging given that in every case, the experimental findings and theoretical detections were in perfect accord. Full article

Electrostatic interactions drive biomolecular interactions and associations. Computational modeling of electrostatics in biomolecular systems, such as protein-ligand, protein–protein, and protein-DNA, has provided atomistic insights into the binding process. In drug discovery, finding biologically plausible ligand-protein target interactions is challenging as current virtual screening and adjuvant techniques such as docking methods do not provide optimal treatment of electrostatic interactions. This study describes a novel electrostatics-driven virtual screening method called ‘ES-Screen’ that performs well across diverse protein target systems. ES-Screen provides a unique treatment of electrostatic interaction energies independent of total electrostatic free energy, typically employed by current software. Importantly, ES-Screen uses initial ligand pose input obtained from a receptor-based pharmacophore, thus independent of molecular docking. ES-Screen integrates individual polar and nonpolar replacement energies, which are the energy costs of replacing the cognate ligand for a target with a query ligand from the screening. This uniquely optimizes thermodynamic stability in electrostatic and nonpolar interactions relative to an experimentally determined stable binding state. ES-Screen also integrates chemometrics through shape and other physicochemical properties to prioritize query ligands with the greatest physicochemical similarities to the cognate ligand. The applicability of ES-Screen is demonstrated with in vitro experiments by identifying novel targets for many drugs. The present version includes a combination of many other descriptor components that, in a future version, will be purely based on electrostatics. Therefore, ES-Screen is a first-in-class unique electrostatics-driven virtual screening method with a unique implementation of replacement electrostatic interaction energies with broad applicability in drug discovery. Full article

The SARS-CoV-2 virus invades and replicates within host cells by “hijacking” biomolecular machinery, gaining control of the microtubule cytoskeleton. After attaching to membrane receptors and entering cells, the SARS-CoV-2 virus co-opts the dynamic intra-cellular cytoskeletal network of microtubules, actin, and the microtubule-organizing center, enabling three factors that lead to clinical pathology: (1) viral load due to intra-cellular trafficking, (2) cell-to-cell spread by filopodia, and (3) immune dysfunction, ranging from hyper-inflammatory cytokine storm to ineffective or absent response. These factors all depend directly on microtubules and the microtubule-organizing center, as do cell functions such as mitosis and immune cell movement. Here we consider how the SARS-CoV-2 virus may “hijack” cytoskeletal functions by docking inside the microtubule-organizing center’s centriole “barrels”, enabling certain interactions between the virus’s positively charged spike (“S”) proteins and negatively charged C-termini of the microtubules that the centriole comprises, somewhat like fingers on a keyboard. This points to the potential benefit of therapies aimed not directly at the virus but at the microtubules and microtubule-organizing center of the host cell on which the virus depends. These therapies could range from anti-microtubule drugs to low-intensity ultrasound (megahertz mechanical vibrations) externally applied to the vagus nerve at the neck and/or to the spleen (since both are involved in mediating inflammatory response). Given that ultrasound imaging machines suitable for vagal/splenic ultrasound are available for clinical trials in every hospital, we recommend an alternative therapeutic approach for COVID-19 based on addressing and normalizing the host cell microtubules and microtubule-organizing centers co-opted by the SARS-CoV-2 virus. Full article