Dynamic Cross-correlation Research Articles

The binding pattern of ferric iron and iron-binding protein in Botrytis cinerea

Iron-binding protein (Ibp) has protective effect on pathogen exposed to H2O2 in defense response of plants. Ibp in Botrytis cinerea (BcIbp) is related to its virulence. Bcibp mutation lead to virulence deficiencies in B. cinerea. BcIbp is involved in the Fe3+ homeostasis regulation. Recognition the binding site and binding pattern of ferric iron and iron-binding protein in B. cinerea are vital to understand its function. In this study, molecular dynamics (MD) simulations, gaussian accelerated molecular dynamics (GaMD) simulations, dynamic cross correlation analysis and quantum chemical energy calculation were used to explore binding pattern of ferric iron. MD results showed that the C-terminal region had little effect on the stability of residues in the Fe3+-binding pocket. Energy calculations suggested the most likely coordination pattern for ferric iron in iron-binding protein. These results will help to understand the binding of ferric iron to iron-binding protein and provide new ideas for regulating the virulence of B. cinerea.

Quercetin derivatives as potential inhibitors of Nipah virus phosphoprotein through in silico drug design approaches

The Nipah virus (NiV) is a pathogenic infection presenting a substantial risk to both human and animal communities. Despite its virulence, there are currently no available drugs or vaccines for NiV. To fight against this challenge, we applied a multi-step in silico drug design strategy, including PASS prediction, molecular docking, absorption, distribution, metabolism and excretion (ADMET) analysis, molecular dynamics simulations, frontier molecular orbitals calculations, dynamic cross-correlation matrix (DCCM), and principal component analysis (PCA). To find out the potential drug candidate against NiV target protein, more than 100 derivatives were taken from the PubChem database. After that, the Pa (probability “to be active"), and Pi (probability “to be inactive") calculation was conducted. Based on the maximum probability “to be active score (Pa), the top nine compounds were studied against NiV. Our findings suggest that the quercetin derivatives exhibit promising binding affinities with the Nipah virus phosphoprotein, particularly compounds 03 (−7.8 kcal/mol), 22 (−6.9 kcal/mol), and 89 (−7.3 kcal/mol). The molecular dynamics simulations over the 100 had confirmed excellent stability and ADMET profiles has reported that all the mentioned ligands are free from Hepatotoxicity, and AMES toxicity, suggesting them as promising candidates for anti-NiV drugs. Based on the results of molecular dynamics simulations, it was observed that the reported drug candidates 03, 22, and 89 exhibited a high degree of stability in forming protein-ligand complexes. These complexes showed only minor fluctuations in RMSF over the 100 ns simulation period. The utilization of frontier molecular orbitals aided in the understanding of the electronic structure behavior, providing strong evidence for their suitability. The study indicates that certain quercetin derivatives, such as 03, 22, and 89, show promise as potentially effective antiviral drug candidates against NiV. Future research should focus on experimental testing of these compounds to develop new antiviral drugs against NiV.

The two-step strategy for enhancing the specific activity and thermostability of alginate lyase AlyG2 with mechanism for improved thermostability

To overcome the trade-off challenge encountered in the engineering of alginate lyase AlyG2 from Seonamhaeicola algicola Gy8T and to expand its potential industrial applications, we devised a two-step strategy encompassing activity enhancement followed by thermal stability engineering. To enhance the specific activity of efficient AlyG2, we strategically substituted residues with bulky steric hindrance proximal to the active pocket with glycine or alanine. This led to the generation of three promising positive mutants, with particular emphasis on the T91S mutant, exhibiting a 1.91-fold specific activity compared to the wild type. To mitigate the poor thermal stability of T91S, mutants with negative ΔΔG values in the thermal flexibility region were screened out. Notably, the S72Ya mutant not only displayed 17.96 % further increase in specific activity but also exhibited improved stability compared to T91S, manifesting as a remarkable 30.97 % increase in relative activity following a 1-hour incubation at 42 °C. Furthermore, enhanced kinetic stability was observed. To gain deeper insights into the mechanism underlying the enhanced thermostability of the S72Ya mutant, we conducted molecular dynamics simulations, principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. The results unveiled a reduction in the flexibility of the surface loop, a stronger correlation dynamic and a narrower motion subspace in S72Ya system, along with the formation of more stable hydrogen bonds. Collectively, our findings suggest amino acids substitutions resulting in smaller side chains proximate to the active site can positively impact enzyme activity, while reducing the flexibility of surface loops emerges as a pivotal factor in conferring thermal stability. These insights offer valuable guidance and a framework for the engineering of other enzyme types.

Investigating natural plant products as potential inhibitors to disrupt NS1 β-roll domain polymerisation in DENV2: a detailed computational chemistry approach

ABSTRACT The aim of this investigation is to design a novel drug, screened through various computational methods, that harnesses the historical evidence of plant products inhibiting viral infections. The beta-roll domain of Flavivirus NS1, crucial for its stability, membrane interaction and viral RNA replication, underscores its significance in disease pathogenesis, being the sole non-structural protein detected in the sera of DENV-infected patients. Our goal is to develop optimised compounds that disrupt NS1 β-roll domain polymerisation, mitigating hydrophobic core formation, to effectively inhibit DENV2 cytopathic infection by leveraging natural interference with viral replication. We created 10 plant-based ligand libraries and applied scaffold hopping and bioisosteric replacement to improve them. Computational methodologies, including virtual screening, molecular dynamics simulation, contact matrix and dynamic cross correlation matrix, were employed for analysing the dynamics of the protein with the association of ligand. ADMET analysis of ligand 126 revealed a favourable ADME profile with no observed toxicity properties. Calculations of pKd, pKi and pIC50 values indicated a heightened affinity of the ligand for the receptor protein, suggesting enhanced inhibitory action and a reduced dissociation rate. These encouraging findings suggest a greater potency of the drug, warranting further in vitro testing for validation.

Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis.

Halide methyltransferases (HMTs) provide an effective way to regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine and reactive electrophiles, such as methyl iodide (MeI) and methyl toluene sulfonate (MeOTs). As compared with MeI, the cost-effective unnatural substrate MeOTs can be accessed directly from cheap and abundant alcohols, but shows only limited reactivity in SAM production. In this study, we developed a dynamic cross-correlation network analysis (DCCNA) strategy for quickly identifying hot spots influencing the catalytic efficiency of the enzyme, and applied it to the evolution of HMT from Paraburkholderia xenovorans. Finally, the optimal mutant, M4 (V55T/C125S/L127T/L129P), exhibited remarkable improvement, with a specific activity of 4.08 U/mg towards MeOTs, representing an 82-fold increase as compared to the wild-type (WT) enzyme. Notably, M4 also demonstrated a positive impact on the catalytic ability with other methyl donors. The structural mechanism behind the enhanced enzyme activity was uncovered by molecular dynamics simulations. Our work not only contributes a promising biocatalyst for the regeneration of SAM, but also offers a strategy for efficient enzyme engineering.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches.

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

Discovery of small molecule entry inhibitors targeting the linoleic acid binding pocket of SARS-CoV-2 spike protein

Spike glycoprotein has a significant role in the entry of SARS-CoV-2 to host cells, which makes it a potential drug target. Continued accumulation of non-synonymous mutations in the receptor binding domain of spike protein poses great challenges in identifying antiviral drugs targeting this protein. This study aims to identify potential entry inhibitors of SARS-CoV-2 using virtual screening and molecular dynamics (MD) simulations from three distinct chemical libraries including Pandemic Response Box, Drugbank and DrugCentral, comprising 6971 small molecules. The molecules were screened against a binding pocket identified in the receptor-binding domain (RBD) region of the spike protein which is known as the linoleic acid binding pocket, a highly conserved motif among several SARS-CoV-2 variants. Through virtual screening and binding free energy calculations, we identified four top-scoring compounds, MMV1579787 ([2-Oxo-2-[2-(3-phenoxyphenyl)ethylamino]ethyl]phosphonic acid), Tretinoin, MMV1633963 ((2E,4E)-5-[3-(3,5-dichlorophenoxy)phenyl]penta-2,4-dienoic acid) and Polydatin, which were previously reported to have antibacterial, antifungal or antiviral properties. These molecules showed stable binding on MD simulations over 100 ns and maintained stable interactions with TYR365, PHE338, PHE342, PHE377, TYR369, PHE374 and LEU368 of the spike protein RBD that are found to be conserved among SARS-CoV-2 variants. Our findings were further validated with free energy landscape, principal component analysis and dynamic cross-correlation analysis. Our in silico analysis of binding mode and MD simulation analyses suggest that the identified compounds may impede viral entrance by interacting with the linoleic acid binding site of the spike protein of SARS-CoV-2 regardless of its variants, and they thus demand for further in vitro and in vivo research. Communicated by Ramaswamy H. Sarma

Structural dynamics and anti-biofilm screening of novel imidazole derivative to explore their anti-biofilm inhibition mechanism against Pseudomonas Aeruginosa

The biofilm formation is still prevalent mechanism of developing the drug resistance in the Pseudomonas aeruginosa, gram-negative bacteria, known for its major role in nosocomial, ventilator-associated pneumonia (VAP), lung infections and catheter-associated urinary tract infections. As best of our knowledge, current study first time reports the most potent inhibitors of LasR, a transcriptional activator of biofilm and virulence regulating genes in, Pseudomonas aeruginosa LasR, utilizing newly functionalized imidazoles (5a-d), synthesized via 1,3-dipolar cycloaddition using click approach. The synthesized ligands were characterized through Mass Spectrometry and 1H NMR. The binding potency and mode of biding of ligands. Quantum Mechanical(QM) methods were utilized to investigate the electronic basis, HOMO/LUMO and dipole moment of the geometry of the ligands for their binding potency. Dynamics cross correlation matrix (DCCMs) and protein surface analysis were further utilized to explore the structural dynamics of the protein. Free energy of binding of ligands and protein were further estimated using Molecular Mechanical Energies with the Poisson–Boltzmann surface area (MMPBSA) method. Molecular Docking studies revealed significant negative binding energies (5a − 10.33, 5b −10.09, 5c − 10.11, and 5d −8.33 KJ/mol). HOMO/LUMO and potential energy surface map estimation showed the ligands(5a) with lower energy gaps and larger dipole moments had relatively larger binding potency. The significant change in the structural dynamics of LasR protein due to complex formation with newlyfunctionalized imidazoles ligands. Hydrogen bond surface analysis followed by MMPBSA calculations of free energy of binding further complemented the Molecular docking revelations showing the specifically ligand (5a) having the relatively higher energy of binding(-65.22kj/mol). Communicated by Ramaswamy H. Sarma

The effect of phosphorylation on the conformational dynamics and allostery of the association of death-associated protein kinase with calmodulin

Protein phosphorylation plays an important role in the signal transduction and is capable of regulation of cell activity. The death-associated protein kinase 1 (DAPK1), as a Ser/Thr kinase, interacts with calmodulin (CaM) to regulate apoptotic and autophagic signaling. Autophosphorylation of DAPK1 at Ser308 located at the autoregulatory domain (ARD) blocks CaM binding and inhibits kinase catalytic activity. However, the mechanism underlying the influence of Ser308 phosphorylation (pS308) on the DAPK1 activity remains unclear. Here, we performed multiple, microsecond length molecular dynamics (MD) simulations, the molecular mechanics generalized Born/surface area (MM-GBSA) binding free energy calculations, principal component analysis, and dynamic cross-correlation analysis to unravel the conformational dynamics and allostery of the DAPK1 − CaM interaction triggered by the pS308 at the ARD. MD simulations showed that pS308 affected the conformational stability of the DAPK1 − CaM complex. Further energetic and structural exploration revealed that pS308 weakened the association of the phosphorylated DAPK1 to CaM, which lowered the susceptibility of DAPK1 to be activated by CaM. This result can provide mechanistic insights into the molecular underpinning through which the DAPK1 kinase activity is modulated by the auto-phosphorylation. Communicated by Ramaswamy H. Sarma

Insights to Design New Drugs against Human African Trypanosomiasis Targeting Rhodesain using Covalent Docking, Molecular Dynamics Simulations, and MM-PBSA Calculations.

Neglected tropical diseases (NTDs) are parasitic and bacterial diseases that affect approximately 149 countries, mainly the poor population without basic sanitation. Among these, African Human Trypanosomiasis (HAT), known as sleeping sickness, shows alarming data, with treatment based on suramin and pentamidine in the initial phase and melarsoprol and eflornithine in the chronic phase. Thus, to discover new drugs, several studies point to rhodesain as a promising drug target due to the function of protein degradation and intracellular transport of proteins between the insect and host cells and is present in all cycle phases of the parasite. Here, based on the previous studies by Nascimento et al. (2021) that show the main rhodesain inhibitors development in the last decade, molecular docking and dynamics were applied in these inhibitors datasets to reveal crucial information that can be into drug design. Thus, conventional and covalent docking was employed and highlighted the presence of Michael acceptors in the ligands in a peptidomimetics scaffold, and interaction with Gly19, Gly23, Gly65, Asp161, and Trp184 is essential to the inhibiting activity. Also, our findings using MD simulations and MM-PBSA calculations confirmed Gly19, Gly23, Gly65, Asp161, and Trp184, showing high binding energy (ΔGbind between -72.782 to -124.477 kJ.mol-1). In addition, Van der Waals interactions have a better contribution (-140,930 to -96,988 kJ.mol-1) than electrostatic forces (-43,270 to -6,854 kJ.mol-1), indicating Van der Waals interactions are the leading forces in forming and maintaining ligand-rhodesain complexes. Furthermore, the Dynamic Cross-Correlation Maps (DCCM) show more correlated movements for all complexes than the free rhodesain and strong interactions in the regions of the aforementioned residues. Principal Component Analysis (PCA) demonstrates complex stability corroborating with RMSF and RMSD. This study can provide valuable insights that can guide researchers worldwide to discover a new promising drug against HAT.

Comparison of Free-Breathing 3D Phase-Resolved Functional Lung (PREFUL) MRI With Dynamic 19F Ventilation MRI in Patients With Obstructive Lung Disease and Healthy Volunteers.

Non-contrast-enhanced 1H magnetic resonance imaging (MRI) with full lung coverage shows promise for assessment of regional lung ventilation but a comparison with direct ventilation measurement using 19F MRI is lacking. To compare ventilation parameters calculated using 3D phase-resolved functional lung (PREFUL) MRI with 19F MRI. Prospective. Fifteen patients with asthma, 14 patients with chronic obstructive lung disease, and 13 healthy volunteers. A 3D gradient-echo pulse sequence with golden-angle increment and stack-of-stars encoding at 1.5 T. All participants underwent 3D PREFUL MRI and 19F MRI. For 3D PREFUL, static regional ventilation (RVent) and dynamic flow-volume cross-correlation metric (FVL-CM) were calculated. For both parameters, ventilation defect percentage (VDP) values and ventilation defect (VD) maps (including a combination of both parameters [VDPCombined]) were determined. For 19F MRI, images from eight consecutive breaths under volume-controlled inhalation of perfluoropropane were acquired. Time-to-fill (TTF) and wash-in (WI) parameters were extracted. For all 19F parameters, a VD map was generated and the corresponding VDP values were calculated. For all parameters, the relationship between the two techniques was assessed using a Spearman correlation (r). Differences between VDP values were compared using Bland-Altman analysis. For regional comparison of VD maps, spatial overlap and Sørensen-Dice coefficients were computed. 3D PREFUL VDP values were significantly correlated to VDP measures by 19F (r range: 0.59-0.70). For VDPRVent, no significant bias was observed with VDP of the third and fourth breath (bias range = -6.8:7.7%, P range = 0.25:0.30). For VDPFVL-CM, no significant bias was found with VDP values of fourth-eighth breaths (bias range = -2.0:12.5%, P range = 0.12:0.75). The overall spatial overlap of all VD maps increased with each breath, ranging from 61% to 81%, stabilizing at the fourth breath. 3D PREFUL MRI parameters showed moderate to strong correlation with 19F MRI. Depending on the 3D PREFUL VD map, the best regional agreement was found to 19F VD maps of third-fifth breath. 3 TECHNICAL EFFICACY: Stage 2.

Molecular dynamics simulation analysis of structural dynamic cross correlation induced by odorant hydrogen-bonding in mouse eugenol ol- factory receptor.

Structural fluctuations and dynamic cross-correlations in the mouse eugenol olfactory receptor (Olfr73) were studied by molecular dynamics (MD) simulation to characterize the dynamic response of the protein upon ligand binding. The initial structure was generated by the artificial intelligence tool AlphaFold2 due to the current lack of experimental data. We focused on the hydrogen (H) bond of the odorant eugenol to Ser113, Asn207, and Tyr260 of the receptor protein, the importance of which has been suggested by previous experimental studies. The H-bond was not observed in docking simulations, but in subsequent MD simulations the H-bond to Ser113 was formed in 2-4 ns. The lifetime of the H-bond was in the range of 1-20 ns. On the trajectory with the most stable (20 ns) H-bond, the structural fluctuation of the α-carbon atoms of the receptor main chain was studied by calculating the root mean square fluctuations, the dynamic cross-correlation map, and the time-dependent dynamic cross-correlation. The analysis suggested a correlation transfer pathway Ser113 → Phe182 → (Leu259 or Tyr260) → Tyr291 induced by the ligand binding with a time scale of 4-6 ns.

An Efficient Dynamic Auto-Regressive CCA for Time Series Imputation With Irregular Sampling

System dynamics are inevitable in industrial processes due to factors such as ambient disturbances and controller tuning. Accurate modeling of these dynamics are of key importance for subsequent process analysis and anomaly detection, and dynamic latent variable methods are widely adopted since they retain good interpretability. However, only dynamic cross-correlations are modeled in existing methods, leaving a large portion of quality information unexploited. In this work, an efficient dynamic auto-regressive canonical correlation analysis (EDACCA) method is proposed with a modified auto-regressive exogenous model to extract dynamics in both auto-correlations and cross-correlations. The flexibility and efficiency of EDACCA are improved with the design of weighting parameters and the economic singular value decomposition. EDACCA is further adapted for multi-step ahead (MS) prediction and missing data imputation. Two industrial processes are employed to evaluate the prediction performance and imputation performance of EDACCA. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Different sampling rates are usually set for process and quality variables in industrial processes, which leads to less quality samples. Meanwhile, system dynamics are not fully exploited for dynamic predictive modeling in most existing algorithms. The focus of this study is to develop a customized data imputation method for different data volume of process and quality data. An efficient dynamic auto-regressive canonical correlation analysis (EDACCA) is designed to extract temporal relations between process and quality variables, which is also adapted for multi-step-ahead prediction purpose. An EDACCA based data imputation method is also proposed to impute incomplete data caused by irregular sampling rates.

Insights into the chirality-dependent recognition of Danshensu Bingpian Zhi stereoisomers with PPARγ.

Peroxisome proliferator-activated receptor γ (PPARγ), a nuclear receptor involved in metabolic processes, inflammation, and energy balance, represents a promising therapeutic target for cardiovascular diseases. Danshensu Bingpian Zhi (DBZ), a chiral compound derived from traditional Chinese medicine, exhibits potential as a PPARγ agonist. Using an ensemble-based docking approach, molecular dynamics (MD) simulations, and the molecular mechanics generalized born surface area (MM/GBSA) methods, we explored the binding modes and energetics of DBZ stereoisomers with the PPARγ ligand-binding domain (LBD). The results indicated that the right-handed stereoisomer (DBZR) binds like a full agonist, while the left-handed stereoisomer (DBZS) binds as a partial agonist with stronger binding energies (ΔGbind), indicating a robust interaction with PPARγ. Both the stereoisomers stabilize the β-sheet region of PPARγ-LBD, potentially protecting Ser245 from phosphorylation by Cdk5, a process implicated in atherosclerosis. Principal component analysis (PCA) and dynamic cross-correlation matrices (DCCM) revealed the complex structural dynamics within the Ω loop, β-sheet, and AF-2 region of PPARγ-LBD upon ligand binding, which may contribute to the unique binding mode and efficacy of DBZS. These findings provide insights into the molecular recognition of PPARγ-LBD by DBZ stereoisomers and their impact on the conformational dynamics of PPARγ, highlighting the therapeutic potential of DBZ and the significance of chirality in drug design.

Accelerated molecular dynamics study of the interaction mechanism between small molecule inhibitors and phosphoglycerate mutase 1.

In 2020, cancer-related deaths reached 9.96 million globally, of which China accounted for 3 million, ranking first in the world. Phosphoglycerate mutase 1 (PGAM1) is a key metabolic enzyme in glycolysis, catalysing the conversion of 3-phosphoglycerate to 2-phosphoglycerate. Based on the excellent anticancer activity of PGMI-004A and HKB99, new small molecules with an anthraquinone core were synthesised to inhibit tumour growth. Developing small molecules with an anthraquinone core targeting PGAM1 may be an effective strategy for treating cancer. In this study, accelerated molecular dynamics (aMD) simulation, dynamic cross-correlation map (DCCM) calculation, principal component analysis (PCA) and free energy landscape (FEL) analysis were used to analyse conformational changes of PGAM1 caused by binding of inhibitors 8KX, 9HU and HKB. DCCM calculations and PCA showed that inhibitor binding significantly affected the kinetic behaviour of PGAM1 and conformational rearrangement of PGAM1. The binding ability and mechanism of 8KX, 9HU and HKB to PGAM1 were studied using the molecular mechanics generalised Born surface area (MM-GBSA) method. The results showed that compared with 8KX, the binding ability of 9HU and HKB to PGAM1 was enhanced by sulphonamide reversal and aminocarboxyl trifluoromethyl substitution. There were several hydrophobic interactions between inhibitors and PGAM1, providing significant contributions for inhibitor binding. Calculation of residue-based free energy decomposition revealed that F22, R90, Y92, L95, V112, W115, R116, V121, P123, P124, R191 and M206 were key residues of the PGAM1-inhibitor interaction and could be used as effective targets for designing drugs that inhibit the activity of PGAM1.

In silico computational prediction of Saussurea pulchella compounds with inhibitory effects on plasmepsin X in Plasmodiumfalciparum

Malaria poses serious problems in countries located in tropical and subtropical regions worldwide. Plasmodium falciparum is responsible for approximately 90 % of malaria-related deaths worldwide. Therefore, alternative treatments are required to effectively reduce the number of malaria cases. Therefore, the objective of this study was to explore alternative malaria treatments by identifying compounds targeting P. falciparum plasmepsin X and characterizing the interactions under various temperatures. Molecular docking was used to evaluate interactions between polyphenolic compounds from Saussurea pulchella and plasmepsin X, followed by stability analyses using molecular dynamics (MD) simulations. Selected compounds were analyzed for biological activity, reactivity, and toxicity. RMSD (root mean square deviation), RMSF (root mean square fluctuation), Rg (radius of gyration), SASA (solvent-accessible surface area), and H-bonds were evaluated. Furthermore, MM-PBSA (molecular mechanics Poisson–Boltzmann surface area), PCA (principal component analysis), and DCCM (dynamic cross-correlation matrix) were use to evaluate effects of various temperatures. Pinoresinol 4-glucoside had a binding energy of 10.006 kcal/mol and was predicted to be nontoxic. MD simulations of pinoresinol 4-glucoside were conducted at different temperatures (298 K, 300 K, 305 K, 310 K, and 320 K) over a trajectory of 150 ns, revealing a strong binding energy using the MM-PBSA method. Our findings suggest that pinoresinol 4-glucoside is an alternative treatment for malaria and should be further evaluated at the laboratory and clinical levels.

Investigation of the new substitution glycine to alanine within the Kringle-2 domain of reteplase: a molecular dynamics study.

Recombinant plasminogen activator (r-PA) consists of the Kringle-2 and protease domains of human tissue-type plasminogen. It is used clinically to treat coronary artery thrombosis and acute myocardial infarction. However, the expression and production of reteplase (r-PA) are limited due to its susceptibility to proteolysis during manufacturing processes. Therefore, efforts have been made to address this limitation. To enhance the conformational stability of r-PA and increase its resistance to proteolysis, we used Gly 6 Ala substitutions in the Kringle-2 domain through in silico . We created an in silico mutant collection with eight structures, incorporating four designated mutations (R103S, G39A, G53A, and G55A). Using MODELLER software and homology modeling, we developed three-dimensional structures for two Kringle-2 and tissue plasminogen activator protease domains, including the wild noncleavable form (R103S) and mutants with all four designated mutations. We assessed protein stability using a dynamic cross-correlation matrix by extracting global properties such as Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) from trajectory files. The findings revealed that a single glycine-alanine substitution (G39A) enhanced the conformational stability of r-PA, as evidenced by improvements in RMSD, RMSF, radius of gyration, surface accessibility, hydrogen bond formation, eigenvector projection, and density analysis. The conformational stability of r-PA conferred by glycine replacement with alanine may decrease the propensity for proteolysis in protease - rich environments across various recombinant systems and potentially enhance its production and expression levels.

Insights into novel inhibitors intending HCMV protease a computational molecular modelling investigation for antiviral drug repurposing

Human cytomegalovirus (HCMV) is an important opportunistic pathogen that is the most significant viral cause of congenital birth abnormalities and is responsible for a high morbidity and death rate in immunocompromised patients. HCMV's rising severity and the limitations of current vaccines in preventing infection highlight the urgent need for effective antiviral drugs. This study aimed to identify small compounds using extensive & appropriate in-silico drug design techniques, including molecular docking, Post-docking MM-GBSA, ADMET, MD simulation, PCA, and DCCM were employed in this study capable of binding to the viral protease and inhibiting its activity, thereby preventing proteolytic processing during capsid maturation. 3516 compounds from life chemical were used in molecular docking, and the top four compounds having high binding affinity and promising ADMET properties with life chemicals ID: F3407-0101 (CID: 49667672), F6559-3323 (CID: 121022124), F6456-1266 (CID: 71810903), and F3411-7969 (CID: 50785034). MD simulation was also used to assess the stability of the protein-ligand complex structure. Finally, after MD simulation, principal component analysis (PCA), and dynamic cross-correlation matrix (DCCM) analysis were performed using trajectories, and we can suggest the best drug candidate which is CID: 50785034 (N-(3-fluoro-4-methylphenyl)-2-({7-oxo-8-[(oxolan-2-yl) methyl]-5-thia-1,8,10,11-tetraazatricyclo [7.3.0.0^ {2,6}] dodeca-2(6),3,9,11-tetraen-12-yl}sulfanyl)acetamide), another two compounds CID: 121022124, and CID: 71810903 which comes after CID: 50785034. All three compounds may have the potential to be developed as a therapy option for HCMV infection.

Salt-bridge mediated conformational dynamics in the figure-of-eight knotted ketol acid reductoisomerase (KARI).

The utility of knotted proteins in biological activities has been ambiguous since their discovery. From their evolutionary significance to their functionality in stabilizing the native protein structure, a unilateral conclusion hasn't been achieved yet. While most studies have been performed to understand the stabilizing effect of the knotted fold on the protein chain, more ideas are yet to emerge regarding the interactions in stabilizing the knot. Using classical molecular dynamics (MD) simulations, we have explored the dynamics of the figure-of-eight knotted domain present in ketol acid reductoisomerase (KARI). Our main focus was on the presence of a salt bridge network evident within the knotted region and its role in shaping the conformational dynamics of the knotted chain. Through the potential of mean forces (PMFs) calculation, we have also marked the specific salt bridges that are pivotal in stabilizing the knotted structure. The correlated motions have been further monitored with the help of principal component analysis (PCA) and dynamic cross-correlation maps (DCCM). Furthermore, mutation of the specific salt bridges led to a change in their conformational stability, vindicating their importance.

Static and dynamic diffuse wave inspection of delaminations in carbon fiber reinforced composites

This paper aims to realize a self-reference delamination inspection in CFRPs with diffuse ultrasonic waves. The static experiments are first conducted on samples with a machined defect of 0.5 mm in height which simulates an opening state delamination. The diffusivity decreases with delamination diameter (pristine, 6 mm, 12 mm) at a constant depth and increases with delamination depth (0.25 mm, 0.75 mm) at a given diameter. However, no clear pattern can be found for the dissipation coefficient because of the intrinsic absorption and manufacturing uncertainties. Both coefficients are insensitive to the delamination height under loading. In contrast, the corresponding maximum cross-correlation coefficient from coda wave interferometry shows a variation of 2.4–7 % in different samples. A sharp transition can be found due to the clapping effect when the delamination is fully closed. After then, the static loading is replaced by acoustic stressing pulse from PZT in a closed delamination sample. The low frequency pulse induced reverberation field is sampled by a high frequency diffuse wave semi-synchronously, which mimics a cyclic and low amplitude loading during service. All the dynamic cross-correlation coefficient curves present an ascending trend during voltage ramp-up due to the viscoelastic effect, no matter in the intact zone or delamination zone. When the voltage threshold of 250 V is reached, the clapping effect can be triggered. A descending trend has been found not only when the excitation is right above but also near the delamination. This can be applied as an indicator of the delamination existence regionally without scanning. Such nonlinear measurement system can be expanded to passive imaging and other deficiency inspection in CFRPs with less demanding facilities.