Journal of Biomolecular Structure & Dynamics最新文献

Hyperuricemia is mainly caused by insufficient renal urate excretion. Urate transporter 1 (URAT1), an organic anion transporter, is the main protein responsible for urate reabsorption. In this study, we utilized artificial intelligence-based AlphaFold2 program to construct URAT1 structural model. After molecular docking and conformational evaluation, four e-pharmacophoric models were constructed based on the complex structures of probenecid-URAT1, benzbromarone-URAT1, lesinurad-URAT1, and verinurad-URAT1. Combining pharmacophore modeling, molecular docking, MM/GBSA calculation and ADME prediction, 25 flavonoids were selected from the natural products database containing 10,968 molecules. Then, a model of HEK-293T cells overexpressing URAT1 was constructed, and the inhibitory activity to URAT1 of 25 flavonoids was evaluated by measuring their effect on cellular uptake of 6-carboxyfluorescein (6-CFL). Fisetin, baicalein, and acacetin showed the best activity with IC₅₀ values of 12.77, 26.71, and 57.30 µM, respectively. Finally, the structure-activity relationship of these three flavonoids was analyzed by molecular docking and molecular dynamics simulations. The results showed that the carbonyl group on C-4 and hydroxyl group on C-7, C-4', and C-5' in flavonoids were conducive for URAT1 inhibitory effects. This study facilitates the application of flavonoids in the development of URAT1 inhibitors.

Leucine is the native known ligand of Sestrin2 (Sesn2) and its interaction with Sesn2 is particularly important, as it influences the activity of mTOR in aging and its associated pathologies. It is important to find out how leucine interacts with Sesn2 and how mutations in the binding pocket of leucine affect the binding of leucine. Therefore, this study was committed to investigating the impact of non-synonymous mutations by incorporating a broad spectrum of simulation techniques, from molecular dynamics to free energy calculations. Our study was designed to model the atomic-scale interactions between leucine and mutant forms of Sesn2. Our results demonstrated that the interaction paradigm for the mutants has been altered thus showing a significant decline in the hydrogen bonding network. Moreover, these mutations compromised the dynamic stability by altering the conformational flexibility, sampling time, and leucine-induced structural constraints that consequently caused variation in the binding and structural stability. Molecular dynamics-based flexibility analysis revealed that the regions 217-339 and 371-380 demonstrated a higher fluctuation. Noteworthy, these regions correspond to a linker (217-339) and a loop (371-380) that cover the leucine binding cavity that is critical for the 'latch' mechanism in the N-terminal, which is essential for leucine binding. Further validation of reduced binding and modified internal motions caused by the mutants was obtained through binding free energy calculations, principal components analysis (PCA), and free energy landscape (FEL) analysis. By unraveling the molecular intricacies of Sesn2-leucine interactions and their mutations, we hope to pave the way for innovative strategies to combat the inevitable tide of aging and its associated diseases.

Stroke-related numbness and weakness (SRNW) are resultant disabilities following a stroke episode and may present with muscle weakness, numbness, tightness, spasticity, and pain in up to 85% of patients. Huangqi Guizhi Wuwu Decoction (HGWD) has been widely investigated to manage the sensorimotor deficiencies at the herb and formula level. However, detailed molecular mechanisms of its constituents are presently lacking. This project employed computational molecular modelling and docking methods to identify candidate compounds of HGWD which may serve as effective modulators of target proteins involved in SRNW. Estrogen Receptor 1 was identified as a promising target for HGWD compounds, while the herbal compound fumarine, a constituent of Jujubae Fructus, was predicted to exhibit high binding affinity and favourable ligand-receptor interactions with ESR1. There is currently a lack of scientific evidence for specific atomic-level interactions between ESR1 and this compound. Therefore, molecular docking and molecular dynamics simulations were used to elucidate the interaction mechanisms of fumarine with ESR1; and the molecular-level structural and functional consequences of ligand binding. Ligand-receptor contact analysis and free energy decomposition calculations identified Glu419 and Leu38 as stable hydrogen bond partners, while favourable contributions to the binding free energy include in Met421 (-10.74 kJ/mol) and Leu525 (-10.02 kJ/mol). This work provides the basis for further studies on discovering lead compounds which modulate the activity of ESR1.

Breast cancer is among the most prevalent causes of death in women worldwide. About 70-75% of these cancers are hormone-dependent, expressing estrogen receptors (ERs), mainly ER-α, making it an essential target for managing breast cancer. Potentilla genus has been traditionally used worldwide for its diverse biological activities, including antidiabetic, anti-inflammatory, antioxidant, etc. In the present study, phytochemicals isolated from various species of the Potentilla species were evaluated for their in silico ER-α inhibitory activity through molecular docking, molecular dynamic simulation, Density Functional Theory calculations and free energy calculations. Four hundred seventy-one molecules were used through ligand preparation and docked inside the generated grid on ER-α protein cavity and the standard drug tamoxifen. Fourteen molecules have shown better dock (-14.42 to -12.57 kcal/mol) scores than tamoxifen (-10.71 kcal/mol). Most of the molecules belong to the category of flavonoid glycosides. Molecules with good binding free energy (-78.81 to -12.94 kcal/mol) indicate stability inside the binding pocket. Further, based on dock score, pharmacokinetic parameters, and binding free energy, two hit molecules, 1 and 2, were selected for their molecular dynamic simulation, MM/PBSA and DFT calculations for assessing their stability and structural dynamics inside the binding cavity as well as their reactivity. Through MD simulation analysis, it was evaluated that Compound 1 could distort the protein to a greater extent. In contrast, compound 2 was stable throughout the simulation time of 150 ns and can be further explored in vitro and in vivo studies as ER-α inhibitors in breast cancer.

DNA methyltransferase (DNMTs) are essential epigenetic modifiers that play a critical role in gene regulation. These enzymes add a methyl group to cytosine's 5'-carbon, specifically within CpG dinucleotides, using S-adenosyl-L-methionine. Abnormal overexpression of DNMTs can alter the gene expression patterns and contribute to cancer development in the human body. Therefore, the inhibition of DNMT is a promising therapeutic approach to cancer treatment. This study was aimed to identify potential nutraceutical inhibitors from the Sri Lanka Flora database using computational methods, which provided an atomic-level description of the drug binding site and examined the interactions between nutraceuticals and amino acids of the DNMT enzyme. A series of nutraceuticals from Sri Lanka-oriented plants were selected and evaluated to assess their inhibitory effects on DNMT using absorption, distribution, metabolism, excretion and toxicity analysis, virtual screening, molecular docking, molecular dynamics simulation and trajectory analysis. Azacitidine, a DNMT inhibitor approved by the US Food and Drug Administration, was selected as a reference inhibitor. The complexes with more negative binding energies were selected and further assessed for their potency. Seven molecules were identified from 200 nutraceuticals, demonstrating significantly negative binding energies against the DNMT enzyme. Various trajectory analyses were conducted to investigate the stability of the DNMT enzyme. The results indicated that petchicine (NP#0003), ouregidione (NP#0011) and azacitidine increased the stability of the DNMT enzyme. Consequently, these two nutraceuticals showed inhibitory efficacies similar to azacitidine, making them potential candidates for therapeutic interventions targeting DNMT enzyme-related cancers. Additional bioassay testing is recommended to confirm the efficacies of these nutraceuticals and explore their applicability in clinical treatments.

Abnormal expression of PRDX has been found to play a significant role in the growth of colorectal cancer and other types of tumors. Despite the identification of several PRDX1 inhibitory compounds in recent years, none of them have been utilized in clinical treatments. Therefore, we conducted a virtual screening of 210,331 small molecules from the SPECS library using PRDX1 and multiple methods. From this screening, we identified 13 compounds with the highest scores from the molecular docking analysis. To further validate the accuracy of our pharmacophore model, we constructed a structure-based pharmacophore model and analyzed the receiver operating characteristic curve (ROC curve). Through this process, we selected nine compounds using skeleton jumping and virtual screening based on the highest pharmacophore model scores. Subsequently, we examined the ADMET properties of these nine compounds to assess their drug-forming potential, resulting in three compounds with the best drug properties. Finally, we assessed the binding stability of these three candidate molecules to proteins using molecular dynamics and MM-PBSA calculations. After a comprehensive evaluation, we found that compounds 6 and 9 formed stable complexes with PRDX1 proteins and could potentially serve as competitive inhibitors of PRDX1 substrates.

Dengue fever, a major global health challenge, affects nearly half the world's population and lacks effective treatments or vaccines. Addressing this, our study focused on natural compounds that potentially inhibit the dengue virus's RNA-dependent RNA polymerase (RdRp), a crucial target in the viral replication cycle. Utilizing the MTiOpenScreen webserver, we screened 1226 natural compounds from the NP-lib database. This screening identified four promising compounds ZINC000059779788, ZINC0000044404209, ZINC0000253504517 and ZINC0000253499146), each demonstrating high negative binding energies between -10.4 and -9.9 kcal/mol, indicative of strong potential as RdRp inhibitors. These compounds underwent rigorous validation through re-docking and a detailed 100 ns molecular dynamics (MD) simulation. This analysis affirmed the dynamic stability of the protein-ligand complexes, a critical factor in the effectiveness of potential drug candidates. Additionally, we conducted essential dynamics and free energy landscape calculations to understand the structural transitions in the RdRp protein upon ligand binding, providing valuable insights into the mechanism of inhibition. Our findings present these natural molecules as promising therapeutic agents against the dengue virus. By targeting the allosteric site of RdRp, these compounds offer a novel approach to hinder the viral replication process. This research significantly contributes to the search for effective anti-dengue treatments, positioning natural compounds as potential key players in dengue virus control strategies.

Approximately 90% of malignancies have been shown to have human telomerase activity, establishing it as a viable therapeutic target. The crystal structure of telomerase was determined recently. However, the tertiary structure of the non-conserved flexible linker region remains unresolved. This study aims to predict the full-length tertiary structure of the human telomerase reverse transcriptase (hTERT). Two strategies were employed to determine the full-length structure of hTERT (1132 amino acids); iterative threading and a conjoined model generated from machine learning and energy functions. After energy minimization, Ramachandran Plot analysis, and simulation; the conjoined model was considered of better quality and stability. The linker region of the conjoined depicted two helices from approximately 275-284 and 201-211 amino acids respectively in contrast to the iterative threading model which has a single helix. Moreover, the region was observed to undergo major structural changes throughout the simulation. These changes signify its flexibility which might be due to the region having a significant number of glycine and proline and could enhance the clamping movement.

Cognitive functions are lost due to the rapid hydrolysis of acetylcholine including Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE). Marine algae-derived compounds were reported for their neuroprotective activities and hence they can be utilised for treating neurodegenerative ailments like Alzheimer's Disease and Parkinson's Disease which are due to the loss of cognitive functions. Major attention is currently paid to seaweeds due to their health benefits and high nutritional values. Sea weeds are of a rich sense of natural bioactive compounds which antioxidants, pharmaceutical compounds, flavonoids and alkaloids. They also contain a high amount of vitamins A, D, E, C and Ca, K, Mg and Fe. Regular consumption of a marine algae-based diet may boost immunities. In searching for natural cholinesterase inhibitors, the present study is focussed on some marine bioactive compounds reported from brown, red and green algae. Molecular docking studies have been carried out along with molecular dynamics simulations studies and binding energy calculations resulting in three best bioactive compounds when AChE is used as the target. The results are compared with cocrystal studies. Two best compounds, namely, Diphlorethohydroxycarmalol and Phlorofucofuroeckol from the brown seaweeds are identified as the potential lead compounds for neurodegenerative diseases, Alzheimer's and Parkinson's.

The opportunistic bacterium Acinetobacter baumannii, which belongs to ESKAPE group of pathogenic bacteria, is leading cause of infections associated with gram-negative bacteria. Acinetobacter baumannii causes severe diseases, such as VAP (ventilator-associated pneumonia), meningitis, and UTI (urinary tract infections) among the nosocomial infections contracted in hospitals. The high infection rate and growing resistance to the vast array of antibiotics makes it paramount to look for new therapeutic strategies against this pathogen. The most promising therapeutic targets are the proteins involved in the synthesis of peptidoglycan which is chief component of bacterial cell wall, MurE is one of those enzymes and is responsible for the addition of one unit of meso-diaminopimelic acid (meso-A2pm) to the nucleotide precursor, UDPMurNAc-L-Ala-D-Glu, and aids in the formation of crosslinker pentapeptide chain. The three-dimensional structure of MurE was modelled using homology modelling technique and then vHTS was performed using this model against Approved Drug Library on DrugRep server using AutoDock Vina. Out of 500 drug molecules, two were selected based on estimated binding affinity, interaction pattern, interacting residues, etc. The selected drug molecules are DB12887 (Tazemetostat) and DB13879 (Glecaprevir). Then, MD simulations were performed on native MurE and its complexes with ligands to examine their dynamical behaviour, stability, integrity, compactness, and folding properties. The protein-ligand complexes were then subjected to binding free energy calculations using the MM/PBSA-based binding free energy analysis and the values are -109.788 ± 8.03 and -152.753 ± 11.98 kcal for MurE-DB12887 and MurE-DB13879 complex, respectively. All the analysis performed on MD trajectories for the complexes of these ligands with protein provided plenty of dependable evidences to consider these molecules for inhibition of MurE enzyme from A. baumannii.