Displaying publications 441 - 460 of 616 in total

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  1. Fulltext An Efficient Optimization Method for Solving Unsupervised Data Classification Problems
    Shabanzadeh P, Yusof R
    Comput Math Methods Med, 2015;2015:802754.
    PMID: 26336509 DOI: 10.1155/2015/802754
    Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
    Matched MeSH terms: Computer Simulation
  2. A hyperelastic fibre-reinforced continuum model of healing tendons with distributed collagen fibre orientations
    Bajuri MN, Isaksson H, Eliasson P, Thompson MS
    Biomech Model Mechanobiol, 2016 12;15(6):1457-1466.
    PMID: 26951049
    The healing process of ruptured tendons is problematic due to scar tissue formation and deteriorated material properties, and in some cases, it may take nearly a year to complete. Mechanical loading has been shown to positively influence tendon healing; however, the mechanisms remain unclear. Computational mechanobiology methods employed extensively to model bone healing have achieved high fidelity. This study aimed to investigate whether an established hyperelastic fibre-reinforced continuum model introduced by Gasser, Ogden and Holzapfel (GOH) can be used to capture the mechanical behaviour of the Achilles tendon under loading during discrete timepoints of the healing process and to assess the model's sensitivity to its microstructural parameters. Curve fitting of the GOH model against experimental tensile testing data of rat Achilles tendons at four timepoints during the tendon repair was used and achieved excellent fits ([Formula: see text]). A parametric sensitivity study using a three-level central composite design, which is a fractional factorial design method, showed that the collagen-fibre-related parameters in the GOH model-[Formula: see text] and [Formula: see text]-had almost equal influence on the fitting. This study demonstrates that the GOH hyperelastic fibre-reinforced model is capable of describing the mechanical behaviour of healing tendons and that further experiments should focus on establishing the structural and material parameters of collagen fibres in the healing tissue.
    Matched MeSH terms: Computer Simulation
  3. Fulltext The Role of Serotype Interactions and Seasonality in Dengue Model Selection and Control: Insights from a Pattern Matching Approach
    Ten Bosch QA, Singh BK, Hassan MR, Chadee DD, Michael E
    PLoS Negl Trop Dis, 2016 05;10(5):e0004680.
    PMID: 27159023 DOI: 10.1371/journal.pntd.0004680
    The epidemiology of dengue fever is characterized by highly seasonal, multi-annual fluctuations, and the irregular circulation of its four serotypes. It is believed that this behaviour arises from the interplay between environmental drivers and serotype interactions. The exact mechanism, however, is uncertain. Constraining mathematical models to patterns characteristic to dengue epidemiology offers a means for detecting such mechanisms. Here, we used a pattern-oriented modelling (POM) strategy to fit and assess a range of dengue models, driven by combinations of temporary cross protective-immunity, cross-enhancement, and seasonal forcing, on their ability to capture the main characteristics of dengue dynamics. We show that all proposed models reproduce the observed dengue patterns across some part of the parameter space. Which model best supports the dengue dynamics is determined by the level of seasonal forcing. Further, when tertiary and quaternary infections are allowed, the inclusion of temporary cross-immunity alone is strongly supported, but the addition of cross-enhancement markedly reduces the parameter range at which dengue dynamics are produced, irrespective of the strength of seasonal forcing. The implication of these structural uncertainties on predicted vulnerability to control is also discussed. With ever expanding spread of dengue, greater understanding of dengue dynamics and control efforts (e.g. a near-future vaccine introduction) has become critically important. This study highlights the capacity of multi-level pattern-matching modelling approaches to offer an analytic tool for deeper insights into dengue epidemiology and control.
    Matched MeSH terms: Computer Simulation
  4. Fulltext Technical Study of a Standalone Photovoltaic-Wind Energy Based Hybrid Power Supply Systems for Island Electrification in Malaysia
    Samrat NH, Ahmad N, Choudhury IA, Taha Z
    PLoS One, 2015;10(6):e0130678.
    PMID: 26121032 DOI: 10.1371/journal.pone.0130678
    Energy is one of the most important factors in the socioeconomic development of a country. In a developing country like Malaysia, the development of islands is mostly related to the availability of electric power. Power generated by renewable energy sources has recently become one of the most promising solutions for the electrification of islands and remote rural areas. But high dependency on weather conditions and the unpredictable nature of these renewable energy sources are the main drawbacks. To overcome this weakness, different green energy sources and power electronic converters need to be integrated with each other. This study presents a battery storage hybrid standalone photovoltaic-wind energy power supply system. In the proposed standalone hybrid system, a DC-DC buck-boost bidirectional converter controller is used to accumulates the surplus hybrid power in the battery bank and supplies this power to the load during the hybrid power shortage by maintaining the constant dc-link voltage. A three-phase voltage source inverter complex vector control scheme is used to control the load side voltage in terms of the voltage amplitude and frequency. Based on the simulation results obtained from MATLAB/Simulink, it has been found that the overall hybrid framework is capable of working under variable weather and load conditions.
    Matched MeSH terms: Computer Simulation
  5. Fulltext A Unified Framework for Brain Segmentation in MR Images
    Yazdani S, Yusof R, Karimian A, Riazi AH, Bennamoun M
    Comput Math Methods Med, 2015;2015:829893.
    PMID: 26089978 DOI: 10.1155/2015/829893
    Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets.
    Matched MeSH terms: Computer Simulation
  6. Rheological and fractal hydrodynamics of aerobic granules
    Tijani HI, Abdullah N, Yuzir A, Ujang Z
    Bioresour Technol, 2015 Jun;186:276-85.
    PMID: 25836036 DOI: 10.1016/j.biortech.2015.02.107
    The structural and hydrodynamic features for granules were characterized using settling experiments, predefined mathematical simulations and ImageJ-particle analyses. This study describes the rheological characterization of these biologically immobilized aggregates under non-Newtonian flows. The second order dimensional analysis defined as D2=1.795 for native clusters and D2=1.099 for dewatered clusters and a characteristic three-dimensional fractal dimension of 2.46 depicts that these relatively porous and differentially permeable fractals had a structural configuration in close proximity with that described for a compact sphere formed via cluster-cluster aggregation. The three-dimensional fractal dimension calculated via settling-fractal correlation, U∝l(D) to characterize immobilized granules validates the quantitative measurements used for describing its structural integrity and aggregate complexity. These results suggest that scaling relationships based on fractal geometry are vital for quantifying the effects of different laminar conditions on the aggregates' morphology and characteristics such as density, porosity, and projected surface area.
    Matched MeSH terms: Computer Simulation
  7. Predicted effect compartment concentration of thiopental at loss of eyelash reflex
    Lim TA, Inbasegaran K
    Br J Anaesth, 2001 Mar;86(3):422-4.
    PMID: 11573534
    We derived the predicted effect compartment concentration of thiopental, at loss of the eyelash reflex, following three different injection regimens. Sixty patients were given thiopental for induction of anaesthesia. Twenty patients received multiple small boluses, 20 patients received a single bolus and 20 patients received an infusion. Computer simulation was then used to derive the effect compartment concentration. The median concentration was not significantly different between the three groups. EC50, derived after combining all three groups was 11.3 microg ml(-1). The EC05-EC95 range was 6.9-18.3 microg ml(-1), suggesting wide inter-individual variation.
    Matched MeSH terms: Computer Simulation
  8. Fulltext Healthcare knowledge management through building and operationalising healthcare enterprise memory
    Cheah YN, Abidi SS
    Stud Health Technol Inform, 1999;68:726-30.
    PMID: 10724990
    In this paper we suggest that the healthcare enterprise needs to be more conscious of its vast knowledge resources vis-à-vis the exploitation of knowledge management techniques to efficiently manage its knowledge. The development of healthcare enterprise memory is suggested as a solution, together with a novel approach advocating the operationalisation of healthcare enterprise memories leading to the modelling of healthcare processes for strategic planning. As an example, we present a simulation of Service Delivery Time in a hospital's OPD.
    Matched MeSH terms: Computer Simulation
  9. A novel method of deriving the effect compartment equilibrium rate constant for propofol
    Lim TA
    Br J Anaesth, 2003 Nov;91(5):730-2.
    PMID: 14570797
    BACKGROUND: Calculation of the effect compartment concentration (Ce) in non-steady-state conditions requires the equilibrium rate constant, keo. Most studies of propofol derive the keo using EEG measurements. This study investigated an alternative method. Starting from a predicted concentration-time profile, a keo value was included so that the predicted Ce at a specific pharmacodynamic end-point was the same when using three different methods of injection.

    METHODS: Seventy-five patients were given propofol for induction of anaesthesia. Twenty-five patients received a single bolus, 25 patients received an infusion, and 25 patients received a bolus followed by an infusion. Computer simulation was used to derive the central compartment concentration. The keo that brought about the same value for Ce at loss of the eyelash reflex using the three methods of injection was derived.

    RESULTS: Keo was found to be 0.80 min(-1). Mean (SD) Ce at loss of the eyelash reflex was 2.27 (0.69) microg ml(-1).

    CONCLUSIONS: The effect compartment equilibrium rate constant and concentration at loss of the eyelash reflex can be derived without the use of electronic central nervous system monitors.

    Matched MeSH terms: Computer Simulation
  10. Modeling and development of screen-printed impedance biosensor for cytotoxicity studies of lung carcinoma cells
    Mansor AFM, Ibrahim I, Zainuddin AA, Voiculescu I, Nordin AN
    Med Biol Eng Comput, 2018 Jan;56(1):173-181.
    PMID: 29247387 DOI: 10.1007/s11517-017-1756-1
    Electrical cell-substrate impedance sensing (ECIS) is a powerful technique to monitor real-time cell behavior. In this study, an ECIS biosensor formed using two interdigitated electrode structures (IDEs) was used to monitor cell behavior and its response to toxicants. Three different sensors with varied electrode spacing were first modeled using COMSOL Multiphysics and then fabricated and tested. The silver/silver chloride IDEs were fabricated using a screen-printing technique and incorporated with polydimethylsiloxane (PDMS) cell culture wells. To study the effectiveness of the biosensor, A549 lung carcinoma cells were seeded in the culture wells together with collagen as an extracellular matrix (ECM) to promote cell attachment on electrodes. A549 cells were cultured in the chambers and impedance measurements were taken at 12-h intervals for 120 h. Cell index (CI) for both designs were calculated from the impedance measurement and plotted in comparison with the growth profile of the cells in T-flasks. To verify that the ECIS biosensor can also be used to study cell response to toxicants, the A549 cells were also treated with anti-cancer drug, paclitaxel, and its responses were monitored over 5 days. Both simulation and experimental results show better sensitivity for smaller spacing between electrodes. Graphical abstract The fabricated impedance biosensor used screen-printed silver/silver chloride IDEs. Simulation and experimental results show better sensitivity for smaller between electrodes.
    Matched MeSH terms: Computer Simulation
  11. Fulltext The Use of System Dynamics Methodology in Building a COVID-19 Confirmed Case Model
    Mohd Yusoff MI
    Comput Math Methods Med, 2020;2020:9328414.
    PMID: 33224268 DOI: 10.1155/2020/9328414
    Researchers used a hybrid model (a combination of health resource demand model and disease transmission model), Bayesian model, and susceptible-exposed-infectious-removed (SEIR) model to predict health service utilization and deaths and mixed-effect nonlinear regression. Further, they used the mixture model to predict the number of confirmed cases and deaths or to predict when the curve would flatten. In this article, we show, through scenarios developed using system dynamics methodology, besides close to real-world results, the detrimental effects of ignoring social distancing guidelines (in terms of the number of people infected, which decreased as the percentage of noncompliance decreased).
    Matched MeSH terms: Computer Simulation
  12. Synthesis of new indazole based dual inhibitors of α-glucosidase and α-amylase enzymes, their in vitro, in silico and kinetics studies
    Rafique R, Khan KM, Arshia, Kanwal, Chigurupati S, Wadood A, et al.
    Bioorg Chem, 2020 01;94:103195.
    PMID: 31451297 DOI: 10.1016/j.bioorg.2019.103195
    The current study describes the discovery of novel inhibitors of α-glucosidase and α-amylase enzymes. For that purpose, new hybrid analogs of N-hydrazinecarbothioamide substituted indazoles 4-18 were synthesized and fully characterized by EI-MS, FAB-MS, HRFAB-MS, 1H-, and 13C NMR spectroscopic techniques. Stereochemistry of the imine double bond was established by NOESY measurements. All derivatives 4-18 with their intermediates 1-3, were evaluated for in vitro α-glucosidase and α-amylase enzyme inhibition. It is worth mentioning that all synthetic compounds showed good inhibition potential in the range of 1.54 ± 0.02-4.89 ± 0.02 µM for α-glucosidase and for α-amylase 1.42 ± 0.04-4.5 ± 0.18 µM in comparison with the standard acarbose (IC50 value of 1.36 ± 0.01 µM). In silico studies were carried out to rationalize the mode of binding interaction of ligands with the active site of enzymes. Moreover, enzyme inhibitory kinetic characterization was also performed to understand the mechanism of enzyme inhibition.
    Matched MeSH terms: Computer Simulation
  13. Fulltext Quality of Service Class Identifier (QCI) radio resource allocation algorithm for LTE downlink
    Mamman M, Hanapi ZM, Abdullah A, Muhammed A
    PLoS One, 2019;14(1):e0210310.
    PMID: 30682038 DOI: 10.1371/journal.pone.0210310
    The increasing demand for network applications, such as teleconferencing, multimedia messaging and mobile TV, which have diverse requirements, has resulted in the introduction of Long Term Evolution (LTE) by the Third Generation Partnership Project (3GPP). LTE networks implement resource allocation algorithms to distribute radio resource to satisfy the bandwidth and delay requirements of users. However, the scheduling algorithm problem of distributing radio resources to users is not well defined in the LTE standard and thus considerably affects transmission order. Furthermore, the existing radio resource algorithm suffers from performance degradation under prioritised conditions because of the minimum data rate used to determine the transmission order. In this work, a novel downlink resource allocation algorithm that uses quality of service (QoS) requirements and channel conditions to address performance degradation is proposed. The new algorithm is formulated as an optimisation problem where network resources are allocated according to users' priority, whereas the scheduling algorithm decides on the basis of users' channel status to satisfy the demands of QoS. Simulation is used to evaluate the performance of the proposed algorithm, and results demonstrate that it performs better than do all other algorithms according to the measured metrics.
    Matched MeSH terms: Computer Simulation
  14. Fulltext Genomic analyses reveal an absence of contemporary introgressive admixture between fin whales and blue whales, despite known hybrids
    Westbury MV, Petersen B, Lorenzen ED
    PLoS One, 2019;14(9):e0222004.
    PMID: 31553763 DOI: 10.1371/journal.pone.0222004
    Fin whales (Balaenoptera physalus) and blue whales (B. musculus) are the two largest species on Earth and are widely distributed across the world's oceans. Hybrids between these species appear to be relatively widespread and have been reported in both the North Atlantic and North Pacific; they are also relatively common, and have been proposed to occur once in every thousand fin whales. However, despite known hybridization, fin and blue whales are not sibling species. Rather, the closest living relative of fin whales are humpback whales (Megaptera novaeangliae). To improve the quality of fin whale data available for analysis, we assembled and annotated a fin whale nuclear genome using in-silico mate pair libraries and previously published short-read data. Using this assembly and genomic data from a humpback, blue, and bowhead whale, we investigated whether signatures of introgression between the fin and blue whale could be found. We find no signatures of contemporary admixture in the fin and blue whale genomes, although our analyses support ancestral gene flow between the species until 2.4-1.3 Ma. We propose the following explanations for our findings; i) fin/blue whale hybridization does not occur in the populations our samples originate from, ii) contemporary hybrids are a recent phenomenon and the genetic consequences have yet to become widespread across populations, or iii) fin/blue whale hybrids are under large negative selection, preventing them from backcrossing and contributing to the parental gene pools.
    Matched MeSH terms: Computer Simulation
  15. In Silico-Guided Sequence Modification of Epitopes in Cancer Vaccine Development
    Hoo WPY, Siak PY, In LLA
    Methods Mol Biol, 2020;2131:213-228.
    PMID: 32162256 DOI: 10.1007/978-1-0716-0389-5_10
    Discovery of tumor antigenic epitopes is important for cancer vaccine development. Such epitopes can be designed and modified to become more antigenic and immunogenic in order to overcome immunosuppression towards the native tumor antigen. In silico-guided modification of epitope sequences allows predictive discrimination of those that may be potentially immunogenic. Therefore, only candidates predicted with high antigenicity will be selected, constructed, and tested in the lab. Here, we described the employment of in silico tools using a multiparametric approach to assess both potential T-cell epitopes (MHC class I/II binding) and B-cell epitopes (hydrophilicity, surface accessibility, antigenicity, and linear epitope). A scoring and ranking system based on these parameters was developed to shortlist potential mimotope candidates for further development as peptide cancer vaccines.
    Matched MeSH terms: Computer Simulation
  16. Dihydroquinazolin-4(1H)-one derivatives as novel and potential leads for diabetic management
    Babatunde O, Hameed S, Salar U, Chigurupati S, Wadood A, Rehman AU, et al.
    Mol Divers, 2021 Mar 01.
    PMID: 33650031 DOI: 10.1007/s11030-021-10196-5
    A variety of dihydroquinazolin-4(1H)-one derivatives (1-37) were synthesized via "one-pot" three-component reaction scheme by treating aniline and different aromatic aldehydes with isatoic anhydride in the presence of acetic acid. Chemical structures of compounds were deduced by different spectroscopic techniques including EI-MS, HREI-MS, 1H-, and 13C-NMR. Compounds were subjected to α-amylase and α-glucosidase inhibitory activities. A number of derivatives exhibited significant to moderate inhibition potential against α-amylase (IC50 = 23.33 ± 0.02-88.65 ± 0.23 μM) and α-glucosidase (IC50 = 25.01 ± 0.12-89.99 ± 0.09 μM) enzymes, respectively. Results were compared with the standard acarbose (IC50 = 17.08 ± 0.07 μM for α-amylase and IC50 = 17.67 ± 0.09 μM for α-glucosidase). Structure-activity relationship (SAR) was rationalized by analyzing the substituents effects on inhibitory potential. Kinetic studies were implemented to find the mode of inhibition by compounds which revealed competitive inhibition for α-amylase and non-competitive inhibition for α-glucosidase. However, in silico study identified several important binding interactions of ligands (synthetic analogues) with the active site of both enzymes.
    Matched MeSH terms: Computer Simulation
  17. Predicting points of departure for risk assessment based on in vitro cytotoxicity data and physiologically based kinetic (PBK) modeling: The case of kidney toxicity induced by aristolochic acid I
    Abdullah R, Alhusainy W, Woutersen J, Rietjens IM, Punt A
    Food Chem Toxicol, 2016 Jun;92:104-16.
    PMID: 27016491 DOI: 10.1016/j.fct.2016.03.017
    Aristolochic acids are naturally occurring nephrotoxins. This study aims to investigate whether physiologically based kinetic (PBK) model-based reverse dosimetry could convert in vitro concentration-response curves of aristolochic acid I (AAI) to in vivo dose response-curves for nephrotoxicity in rat, mouse and human. To achieve this extrapolation, PBK models were developed for AAI in these different species. Subsequently, concentration-response curves obtained from in vitro cytotoxicity models were translated to in vivo dose-response curves using PBK model-based reverse dosimetry. From the predicted in vivo dose-response curves, points of departure (PODs) for risk assessment could be derived. The PBK models elucidated species differences in the kinetics of AAI with the overall catalytic efficiency for metabolic conversion of AAI to aristolochic acid Ia (AAIa) being 2-fold higher for rat and 64-fold higher for mouse than human. Results show that the predicted PODs generally fall within the range of PODs derived from the available in vivo studies. This study provides proof of principle for a new method to predict a POD for in vivo nephrotoxicity by integrating in vitro toxicity testing with in silico PBK model-based reverse dosimetry.
    Matched MeSH terms: Computer Simulation
  18. Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations
    Wong CK, Bernardo R
    Theor Appl Genet, 2008 Apr;116(6):815-24.
    PMID: 18219476 DOI: 10.1007/s00122-008-0715-5
    Oil palm (Elaeis guineensis Jacq.) requires 19 years per cycle of phenotypic selection. The use of molecular markers may reduce the generation interval and the cost of oil-palm breeding. Our objectives were to compare, by simulation, the response to phenotypic selection, marker-assisted recurrent selection (MARS), and genomewide selection with small population sizes in oil palm, and assess the efficiency of each method in terms of years and cost per unit gain. Markers significantly associated with the trait were used to calculate the marker scores in MARS, whereas all markers were used (without significance tests) to calculate the marker scores in genomewide selection. Responses to phenotypic selection and genomewide selection were consistently greater than the response to MARS. With population sizes of N = 50 or 70, responses to genomewide selection were 4-25% larger than the corresponding responses to phenotypic selection, depending on the heritability and number of quantitative trait loci. Cost per unit gain was 26-57% lower with genomewide selection than with phenotypic selection when markers cost US $1.50 per data point, and 35-65% lower when markers cost $0.15 per data point. With population sizes of N = 50 or 70, time per unit gain was 11-23 years with genomewide selection and 14-25 years with phenotypic selection. We conclude that for a realistic yet relatively small population size of N = 50 in oil palm, genomewide selection is superior to MARS and phenotypic selection in terms of gain per unit cost and time. Our results should be generally applicable to other tree species that are characterized by long generation intervals, high costs of maintaining breeding plantations, and small population sizes in selection programs.
    Matched MeSH terms: Computer Simulation
  19. Fulltext Medicinal Plants in COVID-19: Potential and Limitations
    Lim XY, Teh BP, Tan TYC
    Front Pharmacol, 2021;12:611408.
    PMID: 33841143 DOI: 10.3389/fphar.2021.611408
    Currently, the search to identify treatments and vaccines for novel coronavirus disease (COVID-19) are ongoing. Desperation within the community, especially among the middle-and low-income groups acutely affected by the economic impact of forced lockdowns, has driven increased interest in exploring alternative choices of medicinal plant-based therapeutics. This is evident with the rise in unsubstantiated efficacy claims of these interventions circulating on social media. Based on enquiries received, our team of researchers was given the chance to produce evidence summaries evaluating the potential of complementary interventions in COVID-19 management. Here, we present and discuss the findings of four selected medicinal plants (Nigella sativa, Vernonia amygdalina, Azadirachta indica, Eurycoma longifolia), with reported antiviral, anti-inflammatory, and immunomodulatory effects that might be interesting for further investigation. Our findings showed that only A. indica reported positive antiviral evidence specific to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on preliminary in silico data while all four medicinal plants demonstrated differential anti-inflammatory or immunomodulatory effects. The definitive roles of these medicinal plants in cytokine storms and post-infection complications remains to be further investigated. Quality control and standardisation of medicinal plant-based products also needs to be emphasized. However, given the unprecedented challenges faced, ethnopharmacological research should be given a fair amount of consideration for contribution in this pandemic.
    Matched MeSH terms: Computer Simulation
  20. Vitamin D is a potential inhibitor of COVID-19: In silico molecular docking to the binding site of SARS-CoV-2 endoribonuclease Nsp15
    Shalayel MH, Al-Mazaideh GM, Aladaileh SH, Al-Swailmi FK, Al-Thiabat MG
    Pak J Pharm Sci, 2020 Sep;33(5):2179-2186.
    PMID: 33824127
    Novel coronavirus disease (COVID-19) has become a pandemic threat to public health. Vaccines and targeted therapeutics to prevent infections and stop virus proliferation are currently lacking. Endoribonuclease Nsp15 plays a vital role in the life cycle, including replication and transcription as well as virulence of the virus. Here, we investigated Vitamin D for its in silico potential inhibition of the binding sites of SARS-CoV-2 endoribonuclease Nsp15. In this study, we selected Remdesivir, Chloroquine, Hydroxychloroquine and Vitamin D to study the potential binding affinity with the putative binding sites of endoribonuclease Nsp15 of COVID-19. The docking study was applied to rationalize the possible interactions of the target compounds with the active site of endoribonuclease Nsp 15. Among the results, Vitamin D was found to have the highest potency with strongest interaction in terms of LBE, lowest RMSD, and lowest inhibition intensity Ki than the other standard compounds. The investigation results of endoribonuclease Nsp15 on the PrankWeb server showed that there are three prospective binding sites with the ligands. The singularity of Vitamin D interaction with the three pockets, particularly in the second pocket, may write down Vitamin D as a potential inhibitor of COVID-19 Nsp15 endoribonuclease binding sites and favour addition of Vitamin D in the treatment plan for COVID-19 alone or in combination with the other used drugs in this purpose, which deserves exploration in further in vitro and in vivo studies.
    Matched MeSH terms: Computer Simulation
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