Molecular Docking and Dynamics Simulation Revealed the Potential Inhibitory Activity of New Drugs against Human Topoisomerase I Receptor

POCOP-Ni(II) pincer compounds derived from phloroglucinol. Cytotoxic and antioxidant evaluation

POCOP-Ni(II) pincer compounds have primarily been explored as catalysts, but their potential biological activity has been scarcely studied. To address this gap, we evaluated the anticancer and antioxidant potential of four POCOP-Ni(II) complexes derived from phloroglucinol. A comprehensive supramolecular analysis, based on single-crystal X-ray diffraction (DRX) structures, was conducted using Hirshfeld surfaces and non-covalent interaction analysis. The cytotoxicity of all complexes was systematically assessed against various cancerous cell lines, as well as a non-cancerous cell line (COS-7). The results revealed that complexes 1b and 1c exhibited remarkable antiproliferative activity, with IC50 values ranging from 2.43 to 7.85 μM against cancerous cell lines U251, K562, HCT-15, MCF-7, and SK-LU-1. To further elucidate their mechanism of action, a competitive fluorescence displacement assay with ethidium bromide (EB) suggested that these complexes possess the ability to intercalate with DNA. This multifaceted investigation not only enhances our understanding of the biological potential of POCOP-Ni complexes but also provides valuable insights into their structural features and interactions, paving the way for future exploration in both catalytic and therapeutic domains.

Unveiling the Anticancer Potential: Computational Exploration of Nitrogenated Derivatives of (+)-Pancratistatin as Topoisomerase I Inhibitors

Cancer poses a substantial global health challenge, driving the need for innovative therapeutic solutions that offer improved effectiveness and fewer side effects. Topoisomerase I (Topo I) has emerged as a validated molecular target in the pursuit of developing anticancer drugs due to its critical role in DNA replication and transcription. (+)-Pancratistatin (PST), a naturally occurring compound found in various Amaryllidaceae plants, exhibits promising anticancer properties by inhibiting Topo I activity. However, its clinical utility is hindered by issues related to limited chemical availability and aqueous solubility. To address these challenges, molecular modelling techniques, including virtual screening, molecular docking, molecular mechanics with generalised born and surface area solvation (MM-GBSA) calculations, and molecular dynamics simulations were utilised to evaluate the binding interactions and energetics of PST analogues with Topo I, comparing them with the well-known Topo I inhibitor, Camptothecin. Among the compounds screened for this study, nitrogenated analogues emerged as the most encouraging drug candidates, exhibiting improved binding affinities, favourable interactions with the active site of Topo I, and stability of the protein-ligand complex. Structural analysis pinpointed key molecular determinants responsible for the heightened potency of nitrogenated analogues, shedding light on essential structural modifications for increased activity. Moreover, in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions highlighted favourable drug-like properties and reduced toxicity profiles for the most prominent nitrogenated analogues, further supporting their potential as effective anticancer agents. In summary, this screening study underscores the significance of nitrogenation in augmenting the anticancer efficacy of PST analogues targeting Topo I. The identified lead compounds exhibit significant potential for subsequent experimental validation and optimisation, thus facilitating the development of novel and efficacious anticancer therapeutics with enhanced pharmacological profiles.

Improving the thermostability of Pseudoalteromonas Porphyrae κ-carrageenase by rational design and MD simulation

The industrial applications of the κ-carrageenases have been restricted by their poor thermostability. In this study, based on the folding free energy change (ΔΔG) and the flexibility analysis using molecular dynamics (MD) simulation for the alkaline κ-carrageenase KCgCD from Pseudoalteromonas porphyrae (WT), the mutant S190R was identified with improved thermostability. After incubation at 50 °C for 30 min, the residual activity of S190R was 63.7%, 25.7% higher than that of WT. The Tm values determined by differential scanning calorimetry were 66.2 °C and 64.4 °C for S190R and WT, respectively. The optimal temperature of S190R was 10 °C higher than that of WT. The κ-carrageenan hydrolysates produced by S190R showed higher xanthine oxidase inhibitory activity compared with the untreated κ-carrageenan. MD simulation analysis of S190R showed that the residues (V186-M194 and P196-G197) in F5 and the key residue R150 in F3 displayed the decreased flexibility, and residues of T169-N173 near the catalytic center displayed the increased flexibility. These changed flexibilities might be the reasons for the improved thermostability of mutant S190R. This study provides a useful rational design strategy of combination of ΔΔG calculation and MD simulation to improve the κ-carrageenase's thermostability for its better industrial applications.

Molecular Dynamics Investigations of Human DNA-Topoisomerase I Interacting with Novel Dewar Valence Photo-Adducts: Insights into Inhibitory Activity

Chronic exposure to ultraviolet (UV) radiation is known to induce the formation of DNA photo-adducts, including cyclobutane pyrimidine dimers (CPDs) and Dewar valence derivatives (DVs). While CPDs usually occur at higher frequency than DVs, recent studies have shown that the latter display superior selectivity and significant stability in interaction with the human DNA/topoisomerase 1 complex (TOP1). With the aim to deeply investigate the mechanism of interaction of DVs with TOP1, we report here four all-atom molecular dynamic simulations spanning one microsecond. These simulations are focused on the stability and conformational changes of two DNA/TOP1-DV complexes in solution, the data being compared with the biomimetic thymine dimer counterparts. Results from root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) analyses unequivocally confirmed increased stability of the DNA/TOP1-DV complexes throughout the simulation duration. Detailed interaction analyses, uncovering the presence of salt bridges, hydrogen bonds, water-mediated interactions, and hydrophobic interactions, as well as pinpointing the non-covalent interactions within the complexes, enabled the identification of specific TOP1 residues involved in the interactions over time and suggested a potential TOP1 inhibition mechanism in action.

MD-Ligand-Receptor: A High-Performance Computing Tool for Characterizing Ligand-Receptor Binding Interactions in Molecular Dynamics Trajectories

Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand-receptor binding interactions (lrbi) to be studied. In this study, we present MD-ligand-receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand-receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand-receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations.