RMSD Research Articles

Determination of Novel SARS-CoV-2 Inhibitors by Combination of Machine Learning and Molecular Modeling Methods.

Within the scope of the project, this study aimed to find novel inhibitors by combining computational methods. In order to design inhibitors, it was aimed to produce molecules similar to the RdRp inhibitor drug Favipiravir by using the deep learning method. For this purpose, a Trained Neural Network (TNN) was used to produce 75 molecules similar to Favipiravir by using Simplified Molecular Input Line Entry System (SMILES) representations. The binding properties of molecules to Viral RNA-dependent RNA polymerase (RdRp) were studied by using molecular docking studies. To confirm the accuracy of this method, compounds were also tested against 3CL protease (3CLpro), which is another important enzyme for the progression of SARS-CoV-2. Compounds having better binding energies and RMSD values than favipiravir were searched with similarity analysis on the ChEMBL drug database in order to find similar structures with RdRp and 3CLpro inhibitory activities. A similarity search found new 200 potential RdRp and 3CLpro inhibitors structurally similar to produced molecules, and these compounds were again evaluated for their receptor interactions with molecular docking studies. Compounds showed better interaction with RdRp protease than 3CLpro. This result presented that artificial intelligence correctly produced structures similar to favipiravir that act more specifically as RdRp inhibitors. In addition, Lipinski's rules were applied to the molecules that showed the best interaction with RdRp, and 7 compounds were determined to be potential drug candidates. Among these compounds, a Molecular Dynamic simulation study was applied for ChEMBL ID:1193133 to better understand the existence and duration of the compound in the receptor site. The results confirmed that the ChEMBL ID:1193133 compound showed good Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), hydrogen bonding, and remaining time in the active site; therefore, it was considered that it could be active against the virus. This compound was also tested for antiviral activity, and it was determined that it did not delay viral infection, although it was cytotoxic between 5mg/mL-1.25mg/mL concentrations. However, if other compounds could be tested, it might provide a chance to obtain activity, and compounds should also be tested against the enzymes as well as the other types of viruses.

In silico analysis of molecular mimicry between human aquaporin 3, Aspergillus fumigatus aquaporin and aquaporins from allergic sources

Conduct an in-silico assessment of potential molecular mimicry between human aquaporins, A. fumigatus, and diverse allergenic sources. Amino acid sequences of human AQP3 and A. fumigatus aquaporin were compared through multiple alignments with 25 aquaporins from diverse allergenic sources. Phylogenetic analysis and homology-based modeling were executed, and the ElliPro server predicted conserved antigenic regions on 3D structures. Global identity among studied aquaporins was 32.6%, with a specific conserved local region at 71.4%. Five monophyletic clades (A-E) were formed, and Group B displayed the highest identity (95%), including 6 mammalian aquaporins, notably AQP3. A. fumigatus aquaporin exhibited the highest identity with Malassezia sympodialis (35%). Three linear and three discontinuous epitopes were identified in both human and A. fumigatus aquaporins. The Root Mean Square Deviation (RMSD) from overlapping aquaporin structures was 1.006. Identification of potential linear and conformational epitopes on human AQP3 suggests likely molecular mimicry with A. fumigatus aquaporins. High identity in a specific antigenic region indicates potential autoreactivity and a probable antigenic site involved in cross-reactivity. Validation through in vitro and in vivo studies is essential for further understanding and confirmation.

Identification of Novel EGFR Inhibitors for the Targeted Therapy of Colorectal Cancer Using Pharmacophore Modelling, Docking, Molecular Dynamic Simulation and Biological Activity Prediction.

Colorectal cancer (CRC) is considered the second deadliest cancer in the world. One of the reasons for the occurrence of this cancer is the deregulation of the Epidermal Growth Factor Receptor (EGFR), which plays a critical role in regulating cell division, persistence, differentiation, and migration. The overexpression of the EGFR protein leads to its dysregulation and causes CRC. Hence, this work aims to identify and validate novel EGFR inhibitors for the treatment of colorectal cancer employing various computer aided techniques such as pharmacophore modeling, docking, molecular dynamic simulation and Quantitative Structure-Activity Relationship (QSAR) analysis. In this work, a shared-featured ligand-based pharmacophore model was generated using the known inhibitors of EGFR. The best model was validated and screened against ZincPharmer and Maybridge databases, and 143 hits were obtained. Pharmacokinetic and toxicological properties of these hits were studied, and the acceptable ligands were docked against EGFR. The best five protein-ligand complexes with binding energy less than -5 kcal/mol were selected. The molecular dynamic simulation studies of these complexes were conducted for 100 nanoseconds (ns), and the results were analyzed. The biological activity of this ligand was calculated using QSAR analysis. The best complex with Root Mean Square Deviation (RMSD) 3.429 Å and Radius of Gyration (RoG) 20.181 Å was selected. The Root Mean Square Fluctuations (RMSF) results were also found to be satisfactory. The biological activity of this ligand was found to be 1.38 μM. This work hereby proposes the ligand 2-((1,6-dimethyl-4-oxo-1,4-dihydropyridin-3-yl)oxy)-N- (1H-indol-4-yl)acetamide as a potential EGFR inhibitor for the treatment of colorectal cancer. The wet lab analysis must be conducted, however, to confirm this hypothesis.

RNA threading with secondary structure and sequence profile.

RNA threading aims to identify remote homologies for template-based modeling of RNA 3D structure. Existing RNA alignment methods primarily rely on secondary structure alignment. They are often time- and memory-consuming, limiting large-scale applications. In addition, the accuracy is far from satisfactory. Using RNA secondary structure and sequence profile, we developed a novel RNA threading algorithm, named RNAthreader. To enhance the alignment process and minimize memory usage, a novel approach has been introduced to simplify RNA secondary structures into compact diagrams. RNAthreader employs a two-step methodology. Initially, integer programming and dynamic programming are combined to create an initial alignment for the simplified diagram. Subsequently, the final alignment is obtained using dynamic programming, taking into account the initial alignment derived from the previous step. The benchmark test on 80 RNAs illustrates that RNAthreader generates more accurate alignments than other methods, especially for RNAs with pseudoknots. Another benchmark, involving 30 RNAs from the RNA-Puzzles experiments, exhibits that the models constructed using RNAthreader templates have a lower average RMSD than those created by alternative methods. Remarkably, RNAthreader takes less than two hours to complete alignments with ∼5000 RNAs, which is 3-40 times faster than other methods. These compelling results suggest that RNAthreader is a promising algorithm for RNA template detection. https://yanglab.qd.sdu.edu.cn/RNAthreader.

Artificial neural network model for water consumption prediction in dairy farms

This work presents a model based on artificial neural network (ANN) applied to predict water consumption in Brazilian dairy farms. Inputs were simple process data such as number of lactating cows, milk productivity, type of management, among others, with low computational cost and satisfactory data prediction. Data used for ANN training was acquired during two years from 31 farms in semi-confined dairy production. The analysis of the results was based on the following statistical models’ indicators: R2 (Coefficient of determination), BIAS (trend coefficient), MAE (mean absolute error), RMSE (Root-mean-square deviation), NRMSE (percentage of the mean of the observations) and RAE (Relative absolute error). After performing the ANN training, the results showed good accuracy to predict water consumption in Brazilian dairy farms, with an average absolute error of 28.4% being obtained. On the other hand, considering the dataset used for ANN validation, an average absolute error of 48% was obtained.

Exploring the mechanism of interaction between TBG and halogenated thiophenols: Insights from fluorescence analysis and molecular simulation

Thyroxine-binding globulin (TBG) plays a vital role in regulating metabolism, growth, organ differentiation, and energy homeostasis, exerting significant effects in various key metabolic pathways. Halogenated thiophenols (HTPs) exhibit high toxicity and harmfulness to organisms, and numerous studies have demonstrated their thyroid-disrupting effects. To understand the mechanism of action of HTPs on TBG, a combination of competitive binding experiments, multiple fluorescence spectroscopy techniques, molecular docking, and molecular simulations was employed to investigate the binding mechanism and identify the binding site. The competition binding assay between HTPs and ANS confirmed the competition of HTPs with thyroid hormone T4 for the active site of TBG, resulting in changes in the TBG microenvironment upon the binding of HTPs to the active site. Key amino acid residues involved in the binding process of HTPs and TBG were further investigated through residue energy decomposition. The distribution of high-energy contributing residues was determined. Analysis of root-mean-square deviation (RMSD) demonstrated the stability of the HTPs-TBG complex. These findings confirm the toxic mechanism of HTPs in thyroid disruption, providing a fundamental reference for accurately assessing the ecological risk of pollutants and human health. Providing mechanistic insights into how HTPS causes thyroid diseases.

SISRE of BDS-3 MEO: Evolution as well as Comparison between D1 and B-CNAV (B-CNAV1, B-CNAV2) Navigation Messages

The signal-in-space range error (SISRE) has a direct impact on the performance of global navigation satellite systems (GNSSs). It is an important indicator of navigation satellite space server performance. The new B-CNAV navigation messages (B-CNAV1 and B-CNAV2) are broadcast on the satellites of the Beidou Global Navigation Satellite System (BDS-3), and they are different from D1 navigation messages in satellite orbit parameters. The orbit accuracy of B-CNAV navigation messages lacks analyses and comparisons with D1. The accuracy and stability of the new hydrogen and rubidium clocks on BDS-3 satellites need annual analyses of long time series, which will affect the service quality of this system. Based on precise ephemeris products from the Center for Orbit Determination in Europe (COD), the orbit error, clock error, and SISRE of 24 medium Earth orbit (MEO) satellite D1 and B-CNAV navigation messages of BDS-3 were computed, analyzed, and compared. Their annual evolution processes for the entire year of 2022 were studied. Thanks to the use of inter-satellite links (ISLs) adopted by BDS-3 MEO satellites, the ages of the ephemeris are accurate and the percent of ages of data, ephemerides (AODEs), and ages of data and clocks (AODCs) shorter than 12 h were 99.95% and 99.96%, respectively. In addition, the broadcast orbit performance was also improved by ISLs. The root mean square (RMS) values of the BDS-3 MEO broadcast ephemeris orbit error were 0.067 m, 0.273 m, and 0.297 m in the radial, cross, and along directions, respectively. Moreover, the 3D RMS value was 0.450 m. Thanks to the use of new orbit parameters in the B-CNAV navigation messages of BDS-3 MEO, its satellite orbit accuracy was obviously better than that of D1 in the radial direction. Its improved accuracy can reach up to about 1.2 cm, and the percentage of its accuracy improvement was about 19.06%. With respect to clock errors, the timescale differences between the two clock products were eliminated to assess the accuracy of broadcasting ephemeris clock errors. A standard deviation value of 0.256 m shows good performances as a result of the use of the two new types of atomic clocks, although the RMS value was 0.541 m due to a nonzero mean bias. Overall, the accuracy of atomic clocks was good. For the new hydrogen and rubidium atomic clocks, their RMS and standard deviation were 0.563 m and 0.231 m and 0.519 m and 0.281 m, respectively. The stability of the former was better than that of the latter. However, due to the nonzero mean bias the latter was better than the former in accuracy. The RMS value of the SISRE of BDS-3 MEO’s broadcast ephemeris was 0.556 m, and the value was 0.920 m when it had a 95% confidence level. In contrast, after deducting the influence of the clock error, the value of SISRE_ORB was 0.092 m. Since the satellite clock error was substantially larger than the orbit radial error, the SISRE was mainly affected by the clock error, and their annual evolutions were consistent. Because of the improvement to the B-CNAV’s navigation message with respect to orbit radial accuracy, SISRE_ORB has improved in accuracy. Compared to D1, it had a significant effect on improving the accuracy of SISRE_ORB, and the percentage of the accuracy improvement was 8.40%.

Monitoring of crack repair in concrete using spherical smart aggregates based on electromechanical impedance (EMI) technique

Cracks will inevitably occur in concrete structures or members during the construction process and service life due to aging, environmental factors, external loads, etc. To improve the strength and stability of the cracked concrete structures, many methods have been proposed to repair the cracks. However, the monitoring of the repairing process and repair quality has not been fully studied. The previous studies have proved that the spherical smart aggregates (SSAs) based on the electromechanical impedance (EMI) technique have outperformed the traditional smart aggregates (SAs) based on the EMI technique in structural health monitoring of civil structures, however, SSAs have not been applied to the monitoring of the concrete crack repair. In this work, the monitoring of the concrete crack repair using the SSAs based on the EMI technique was explored. A total of eight concrete specimens were prepared, and cracks in the concrete specimens were simulated by manually cutting under laboratory conditions. According to the principle of grouting method, two repair agents including cement paste and cement mortar were used to repair the cracks. The impedance signals of 28 d were measured, and three quantitative indicators, namely root mean square deviation, mean absolute percentage deviation, and correlation coefficient deviation were used to evaluate the quality of the concrete repair effect. The results indicate that the SSAs show excellent sensitivity and stability over the traditional SAs. In addition, the normalized values of the quantitative indicators were analyzed to distinguish the types of repair agents. A mathematical expression of exponential function was also proposed by fitting the experimental data to quantitatively evaluate and predict the repair effect of concrete cracks. Further, the influences of temperature, humidity, crack depth and width on the experimental results were analyzed and discussed. The numerical simulation was also presented to validate the reasonability of the experimental results.

Design, antitumor, and anti‐Ras activity of propynyl‐substituted harmine bases

AbstractModifications at the harmine (HAM) 9‐N position demonstrated effective antitumor activity in previous studies. However, the difficult preparation, low yield and poor stability of derivatives limited their applications. A partial activity priming was carried out by converting the 9‐position substituted propargyl group of HAM to propynyl group. Molecular docking simulations of compound 9i with DYRK1A kinase showed that it was able to embed itself into the active pocket of the DYRK1A protein and formed hydrogen bonds with multiple active amino acid residues at a low binding energy. The results of molecular dynamics simulations showed that the RMSD (root mean square deviation) fluctuations of the complex were more gentle, and the trends of the changes in Rg (radius of gyration) and SASA (solvent accessible surface area) were lower, indicating that the DYRK1A protein was less disturbed and the structure of the complex was more compact and stable. The cytotoxicity assay indicated that compound 9i displayed good antiproliferative activity against human cancer cells MGC‐803, HepG2, and PANC‐1. In addition, 9i was able to reduce the ratio of polynomials induced by the Ras overexpression model of Caenorhabditis elegans, which showed anti‐Ras activity, and the RT‐qPCR results suggested that its anti‐Ras ability was not achieved by directly inhibiting the expression of the let‐60/Ras genes, and that 9i was able to upregulate the expression of SOD‐3 activation of oxidative stress, which means that it may be useful as a pro‐oxidant for the treatment of cancers caused by Ras over‐activation.

In Silico Assessment of Chemical Constituents of Zingiber officinale Rosc. For Anti-diabetic Activity: Molecular Docking with α-Glucosidase Receptor

Diabetes Mellitus (DM) is a disease in which blood sugar (glucose) levels are elevated because the body cannot release or utilize insulin adequately. Rhizome of Zingiber officinale Rosc. (ginger) has been reported to possess anti-diabetic properties. This study aimed to provide information on the chemical components of ginger that have potential in silico antidiabetic activity against the α-glucosidase receptor. Twenty chemical components of ginger (quercetin, catechin, humulene, β-sesquiphellandrene, camphene, farnesene, β-sitosterol, stigmasterol, curcumin, 6-gingerol, 8-gingerol, 10-gingerol, 6-shogaol, 8-shogaol, 10-shogaol, 6-paradol, 8-paradol, 10-paradol, methyl-6-gingerol, and methyl-8-gingerol) were used as ligands. An in silico study was conducted using the molecular docking technique with the AutoDock Vina software, which was then displayed using PyMOL and Biovia Discovery Studio. The grid box settings obtained in this study were as follows: center_x = -20.209, center_y = -6.763, center_z = 9.393, size_x = 12, size_y = 10, size_z = 12, and spacing (angstrom) = 1. The results indicated that the native ligand acarbose exhibited a binding energy of -6.9 kcal/mol. In contrast, four test ligands, quercetin (-7.3 kcal/mol), catechin (-7.1 kcal/mol), curcumin (-7.0 kcal/mol), and 6-gingerol (-7.0 kcal/mol) - demonstrated lower binding energies than acarbose, suggesting more stable conformations and more potent pharmacological effects. Lipinski analysis revealed that these four test ligands met all five Lipinski rule criteria. The study calculated the Root Mean Square Deviation (RMSD) value for the Docking of acarbose with the α-glucosidase macromolecule, resulting in a value of 0.384 Å. Interaction analysis conducted using Biovia Discovery Studio software revealed various interaction types, including hydrogen bonding, hydrophobic, electrostatic, and unfavorable interactions. In conclusion, this study provides valuable insights into potential therapeutic compounds derived from ginger and offers a foundation for further research and development in pharmaceutical and medicinal chemistry.

Exploring the impact of taurine on the biochemical properties of urate oxidase: response surface methodology and molecular dynamics simulation

This paper investigates the impact of taurine as an additive on the structural and functional stability of urate oxidase. First, the effect of the processing parameters for the stabilization of Urate Oxidase (UOX) using taurine was examined using the response surface methodology (RSM) and the central composite design (CCD) model. Also, the study examines thermodynamic and kinetic parameters as well as structural changes of urate oxidase with and without taurine. Fluorescence intensity changes indicated static quenching during taurine binding. The obtained result indicates that taurine has the ability to preserve the native structural conformation of UOX. Furthermore, molecular dynamics simulation is conducted in order to get insights into the alterations in the structure of urate oxidase in the absence and presence of taurine under optimal conditions. The molecular dynamics simulation section investigated the formation of hydrogen bonds (H-bonds) between different components as well as analysis of root mean square deviation (RMSD), root mean square fluctuations (RMSF) and secondary structure. Lower Cα-RMSD and RMSF values indicate greater stabilization of the taurine-treated UOX structure compared to the free enzyme. The results of molecular docking indicate that the binding of taurine to the UOX enzyme through hydrophobic interactions is associated with a negative value for the Gibbs free energy.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy.

Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

Integrating network pharmacology and animal experimental validation to investigate the action mechanism of oleanolic acid in obesity

BackgroundObesity, a condition associated with the development of widespread cardiovascular disease, metabolic disorders, and other health complications, has emerged as a significant global health issue. Oleanolic acid (OA), a pentacyclic triterpenoid compound that is widely distributed in various natural plants, has demonstrated potential anti-inflammatory and anti-atherosclerotic properties. However, the mechanism by which OA fights obesity has not been well studied.MethodNetwork pharmacology was utilized to search for potential targets and pathways of OA against obesity. Molecular docking and molecular dynamics simulations were utilized to validate the interaction of OA with core targets, and an animal model of obesity induced by high-fat eating was then employed to confirm the most central of these targets.ResultsThe network pharmacology study thoroughly examined 42 important OA targets for the treatment of obesity. The key biological processes (BP), cellular components (CC), and molecular functions (MF) of OA for anti-obesity were identified using GO enrichment analysis, including intracellular receptor signaling, intracellular steroid hormone receptor signaling, chromatin, nucleoplasm, receptor complex, endoplasmic reticulum membrane, and RNA polymerase II transcription Factor Activity. The KEGG/DAVID database enrichment study found that metabolic pathways, PPAR signaling pathways, cancer pathways/PPAR signaling pathways, insulin resistance, and ovarian steroidogenesis all play essential roles in the treatment of obesity and OA. The protein-protein interaction (PPI) network was used to screen nine main targets: PPARG, PPARA, MAPK3, NR3C1, PTGS2, CYP19A1, CNR1, HSD11B1, and AGTR1. Using molecular docking technology, the possible binding mechanism and degree of binding between OA and each important target were validated, demonstrating that OA has a good binding potential with each target. The molecular dynamics simulation’s Root Mean Square Deviation (RMSD), and Radius of Gyration (Rg) further demonstrated that OA has strong binding stability with each target. Additional animal studies confirmed the significance of the core target PPARG and the core pathway PPAR signaling pathway in OA anti-obesity.ConclusionOverall, our study utilized a multifaceted approach to investigate the value and mechanisms of OA in treating obesity, thereby providing a novel foundation for the identification and development of natural drug treatments.

Structure-based virtual screening and molecular dynamics studies to explore potential natural inhibitors against 3C protease of foot-and-mouth disease virus.

Foot-and-mouth disease (FMD) is a highly infectious animal disease caused by foot-and-mouth disease virus (FMDV) and primarily infects cloven-hoofed animals such as cattle, sheep, goats, and pigs. It has become a significant health concern in global livestock industries because of diverse serotypes, high mutation rates, and contagious nature. There is no specific antiviral treatment available for FMD. Hence, based on the importance of 3C protease in FMDV viral replication and pathogenesis, we have employed a structure-based virtual screening method by targeting 3C protease with a natural compounds dataset (n = 69,040) from the InterBioScreen database. Virtual screening results identified five potential compounds, STOCK1N-62634, STOCK1N-96109, STOCK1N-94672, STOCK1N-89819, and STOCK1N-80570, with a binding affinity of -9.576 kcal/mol, -8.1 kcal/mol, -7.744 kcal/mol, -7.647 kcal/mol, and - 7.778 kcal/mol, respectively. The compounds were further validated through physiochemical properties and density functional theory (DFT). Subsequently, the comparative 300-ns MD simulation of all five complexes exhibited overall structural stability from various MD analyses such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), H-bonds, principal component analysis (PCA), and free energy landscape (FEL). Furthermore, MM-PBSA calculation suggests that all five compounds, particularly STOCK1N-62634, STOCK1N-96109, and STOCK1N-94672, can be considered as potential inhibitors because of their strong binding affinity toward 3C protease. Thus, we hope that these identified compounds can be studied extensively to develop natural therapeutics for the better management of FMD.

Rice Height Estimation with Multi-Baseline PolInSAR Data and Optimal Detection Baseline Combination Analysis

Rice is a primary food source, and height is a crucial parameter affecting its growth status. Consequently, high-precision, real-time monitoring of quantitative changes in crop height are required for improved crop production. Polarimetric interferometric SAR (PolInSAR) has both polarization and interferometric observation capabilities. Due to the short height of crops and rapid growth changes, the large spatial and short temporal baselines of PolInSAR data are essential for effective crop height inversion; however, relevant satellite-borne SAR and airborne SAR data are currently limited. This study presents a PolInSAR rice height inversion algorithm that uses the oriented volume over ground (OVoG) mode with PolInSAR 0-time and controllable spatial baseline data from a LAMP microwave anechoic chamber. Exploiting the advantages of microwave anechoic chamber measurement data, which includes continuous frequency bands, multiple baselines, and varied incidence angles, the influences of incident angles, baseline length, number of baselines, and baseline combinations are assessed. The highest accuracy rice plant height inversion has a root mean square deviation (RMSE) of 0.1093 m and is achieved with an incidence angle of 35–55°, baseline length of 0.25°, and three to four baselines. Furthermore, an imaging geometric equivalence analysis provides reliable foundation data to guide research into new earth observation SAR systems. The results indicate that, under simulated observations from the GF3 satellite at an altitude of 755 km, the optimal spatial baseline ranges for various frequency bands are as follows: L-band: 10.93–42.59 km; S-band: 4.10–15.97 km; C-band: 2.48–9.64 km; X-band: 1.36–5.32 km; Ku-band: 0.87–3.40 km. Notably, the measurement modes corresponding to the C, X, and Ku bands are ultimately identified as the most suitable for PolInSAR rice height inversion.

Computational Design of Novel Griseofulvin Derivatives Demonstrating Potential Antibacterial Activity: Insights from Molecular Docking and Molecular Dynamics Simulation.

In response to the urgent demand for innovative antibiotics, theoretical investigations have been employed to design novel analogs. Because griseofulvin is a potential antibacterial agent, we have designed novel derivatives of griseofulvin to enhance its antibacterial efficacy and to evaluate their interactions with bacterial targets using in silico analysis. The results of this study reveal that the newly designed derivatives displayed the most robust binding affinities towards PBP2, tyrosine phosphatase, and FtsZ proteins. Additionally, molecular dynamics (MD) simulations underscored the notable stability of these derivatives when engaged with the FtsZ protein, as evidenced by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA). Importantly, this observation aligns with expectations, considering that griseofulvin primarily targets microtubules in eukaryotic cells, and FtsZ functions as the prokaryotic counterpart to microtubules. These findings collectively suggest the promising potential of griseofulvin and its designed derivatives as effective antibacterial agents, particularly concerning their interaction with the FtsZ protein. This research contributes to the ongoing exploration of novel antibiotics and may serve as a foundation for future drug development efforts.

Unveiling the potential of recently FDA-approved drugs as quorum sensing inhibitors against P. Aeruginosa using high-performance computational techniques

Through cell-to-cell communication, activation of efflux pumps, formation of biofilms, and other mechanisms, pseudomonas aeruginosa’s quorum sensing systems (QSS), notably the lasl/las-r system, contribute a vital role in the development of anti-microbial resistance (AMR). Identifying potential drugs against these targets could have significant implications for combating pseudomonal infections. The current study aims to identify promising recently FDA-approved drugs against lasl/las-r proteins. The ligands were selected from the FDA-approved drug lists of the last 5 years. Out of 202, 78 drugs were checked for interaction with lasl/las-r protein and 4 drugs revealed top binding conformations characterized by favorable energetic profiles within the active site of the las-r protein which were further assigned for 250-ns molecular dynamics (MD) simulation. The MD analysis confirmed the dynamical stability of brexanolone and oteseconazole with las-r protein. The root mean square deviation (RMSD), radius of gyration (Rg) and solvent-accessible surface area (SASA) analysis have indicated less deviation, more compactness of protein and less exposure of protein ligand complex to its surroundings as compared to the reference ligand-protein complex. The hydroxyl group in the oteseconazole whereas hydroxyl and ketone group in the brexanolone were responsible for hydrogen bonds with the active site residue of las r ptotein as indicated by ligand-protein contacts diagram. The binding energies per residue analysis revealed TYR-47 as the most contributing amino acid residue for interaction with oteseconazole and brexanolone. The identified drugs may be potential repurposing candidates against pseudomonal infections through inhibition of las-r protein. Communicated by Ramaswamy H. Sarma

Molecular Dynamics Simulation of Various Bioactive Compounds of Red Betel (Piper crocatum) as Anti-Inflammatory Drug-Like Candidates in Rheumatoid Arthritis Treatment

Joint inflammation and damage can be caused by rheumatoid arthritis (RA), a systemic autoimmune disorder. Long-term RA affects the joints, causing pain, edema, and stiffness. Several studies have revealed that the exact origin of RA is still unidentified, but inherited disorder and external factors may contribute to the inflammatory condition. The incidence of RA is mostly caused by uncontrolled-production of pro-inflammatory cytokines under nuclear factor-kappa B (NF-κB) overexpression condition. The nuclear factor-kappa B plays an important role in inflammatory T cell activation, differentiation, and effector function. Therefore, the inhibition of NF-κB can be a strategy to reduce the adverse effects or incidence of RA. Red betel is a perennial herb native to Indonesia that is widely used by conventional healers. Many reports show that red betel leaf extracts contain several critical bioactive compounds such as Apigenin, Luteolin, Hydroxychavicol, Eugenol, and Chavibetol. This present study aims to evaluate and predict the therapeutic potential of those compounds as medication that reduce inflammation against RA by disturbing and inactivating the NF-κB molecular interaction. The LC-MS chromatography was used to evaluate the chemical contents of red betel leaves. Furthermore, in silico study, the 3D structure of the active compounds of red betel leaves is obtained from PubChem web server, while NF-κB is obtained from Protein Data Bank (PDB) website. Molecular docking was used to screen the potential compounds compared to aspirin as control. As a result, 2 compounds including Apigenin and Luteolin have smaller bond affinity values, −6.3 and −6.0 kcal/mol, respectively compared to aspirin. Based on molecular dynamics (MD) simulation, the root-mean-square deviation (RMSD) value of protein-ligand complexes have the similar pattern over 1000/ps except the NF-κB-Chavibetol complex which has an unstable pattern. On the other hand, the total energy of the protein-ligand complexes have similar average number of −1.69 kJ/mol. The simulation indicates the ligands have constant binding energy to the protein. Furthermore, numerous pharmacokinetic properties of compounds including absorption, distribution, metabolism, excretion and toxicity are exponentially greater than the control drugs. Finally, red betel active compounds can be used as alternative candidates of RA therapy medication. HIGHLIGHTS Rheumatoid arthritis, a systemic autoimmune condition, damages joints. Long-term RA causes joint discomfort, swelling, and stiffness. The identified flavonoids from red betel leaf extract include flavonone, isoflavone, auron, catechin, anthocyanidin, and chalcone. Apigenin, chavibetol, eugenol, hydroxychavicol, and luteolin, the active chemicals found in red betel, have the potential to serve as NF-B inhibitors, making them potentially useful in the treatment of rheumatoid arthritis. GRAPHICAL ABSTRACT

Docking and molecular dynamic simulations of Mithramycin-A and Tolfenamic acid against Sp1 and survivin

Therapeutic targeting of Sp1 transcription factor and survivin, are studied in various cancers due to their consistent overexpression. These markers result in poorer cancer prognoses and their downregulation has been investigated as an effective treatment approach. Mithramycin-A and Tolfenamic acid are two drugs with innate anti-cancer properties and are suggested to be able to target Sp1 through GC/GT DNA binding interference, however in-depth binding and mechanistic studies are lacking. Through docking analysis, we investigated Mithramycin-A and Tolfenamic acid in terms of their specific binding interactions with Sp1 and survivin. Through further molecular dynamics simulations including Root Mean Square (RMS) Fluctuation and RMS Deviation, rGYr, and H-bond analysis, we identified critical residues involved in drug interactions with each protein in question. We show Mithramycin-A as the superior binding candidate to each protein and found that it exhibited stronger binding with Sp1, and then survivin. Subsequent molecular dynamics simulations followed the same trend as initial binding energy calculations and showed crucial amino acids involved in each Mithramycin-A-protein complex. Our findings warrant further investigation into Mithramycin-A and its specific interaction with Sp1 and their downstream targets giving a better understanding of Mithramycin-A and its potential as an effective cancer treatment.

LIGAND-BASED VIRTUAL SCREENING OF FDA-APPROVED DRUGS TO IDENTIFY NEW INHIBITORS AGAINST LACTATE DEHYDROGENASE ENZYME OF MALARIA PARASITES

Objective: The aim of this study is to computationally repurpose FDA-approved drugs as potential inhibitors of the Plasmodium falciparum lactate dehydrogenase (PfLDH) by competing with the cofactor NADH. Methods: In this in silico study, we have virtually screened a library of FDA-approved drugs for structural similarity to the dihydro nicotinamide adenine dinucleotide (NADH). Then, the top hits were further assessed for clinical safety and by application of molecular docking and dynamics simulation. Results: Ligand-based virtual screening reports that the antibiotic Novobiocin has a good similarity to the cofactor NADH with a score of 0.7. Also, molecular docking study indicates that Novobiocin may has the ability to interact with PfLDH enzyme with a docking energy of-8.8 Kcal/mol. However, during molecular dynamics (MD) simulation, the mean ligand proximity root mean square deviation (RMSD) and binding energy for Novobiocin were 4.3 Angstrom and-37.45 Kcal/mol, respectively. These MD simulation parameters are inferior to those recorded for NADH molecule during 50 nanosecond intervals. Conclusion: The antibiotic Novobiocin may serve as a potential lead candidate toward the design of novel antimalarial agents. However, further evaluation of Novobiocin may be recommended to affirm its capacity against PfLDH enzyme.