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A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzyme. The tested sets are composed of eight receptor-ligand complexes with high resolution crystal structures downloaded from Protein Data Bank website. Molecular dockings were applied between approved HIV-1 protease inhibitors and the HIV-1 protease using AutoDock Vina, 1-Click Docking, and DOCK6. Then, docking poses of the top-ranked solution was realized using UCSF Chimera. Furthermore, Pearson correlation coefficient (r) and coefficient of determination (r2) between the experimental results and the top scored docking results of each program were calculated using Graphpad prism V9.2. After comparing saquinavir top scored binding poses of each docking program with the crystal structure, various conformational changes were observed. Moreover, according to the relative comparison between the top ranked calculated ?Gbinding values against the experimental results, r2 value of AutoDock Vina, 1-Click Docking, and DOCK6 were 0.65, 0.41, and 0.005, respectively. The outcome of this study shows that the top scored binding free energy could not produce the best pose prediction. In addition, AutoDock Vina results have the highest correlation with the experimental results.

 

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Study the Effect of Adding Aluminum Nanoparticles to a Smart Alloy (Cu-Al-Ni) on Hardness and Porosity
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This work deals with the effect of adding aluminum nanoparticles on the mechanical properties, micro-hardness and porosity of memory-shape alloys (Cu-Al-Ni). These alloys have wide applications in various industrial fields such as (high damping compounds and self-lubricating applications). The samples are manufactured using the powder metallurgy method, which involved pressing in only one direction and sintered in a furnace surrounded by an inert gas. Four percentages (0%, 5%, 10%, and 15%) of aluminum nanoparticles were fabricated, which depended on the weight of aluminum powder (13%) in the sample under study. To find out which phase is responsible for the reliability of the formation of this type of alloy and its porosity, X-ray diffr

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Publication Date
Mon Mar 01 2021
Journal Name
Materials Today: Proccedings
Nanomaterials usage as adsorbents for the pollutants removal from waste water; areview
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Publication Date
Fri Jan 19 2024
Journal Name
Research Journal Of Pharmacy And Technology
Serum Levels of Fetuin-A, Ischemia-modified Albumin (IMA), and Ferritin in Hospitalized patients with severe COVID-19. A Case-control Study
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Objective: To measure the serum levels of Fetuin-A, ischemia-modified albumin (IMA), and ferritin in hospitalized patients with severe COVID-19in Baghdad, Iraq. Moreover, to determine these biomarkers' cut-off valuesthat differentiate between severely ill patients and control subjects. Methods: This case-control study was done from 15 September to the end of December 2021 and involved a review of the files and collectionof blood samples from patients (n=45, group1) hospitalized in COVID-19 treatment centersbecause of severe symptoms compared tohealthy subjects as controls (n=44, group2). Results: Fetuin-A serum levels were not statistically different between patients and controls. In contrast, IMA and ferritin levels were significan

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Publication Date
Sun Apr 30 2017
Journal Name
Journal Of Engineering
Experimental Study on Heat Transfer and Friction Factor Characteristics of Single Layer Graphene Based DI-water Nanofluid in a Circular Tube under Laminar Flow and Different Heat Fluxes as Boundary Conditions
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An experimental study was performed to estimate the forced convection heat transfer performance and the pressure drop of a single layer graphene (GNPs) based DI-water nanofluid in a circular tube under a laminar flow and a uniform heat flux boundary conditions. The viscosity and thermal conductivity of nanofluid at weight concentrations of (0.1 to 1 wt%) were measured. The effects of the velocity of flow, heat flux and nanoparticle weight concentrations on the  enhancement of the heat transfer are examined. The Nusselt number of the GNPs nanofluid was enhanced as the heat flux and the velocity of flow rate  increased, and the maximum Nusselt number  ratio (Nu nanofluid/ Nu base fluid)   and thermal performance factor

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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
The Correlation between the Dimensions of Organizational Silence and the F Function Life an Exploratory Study of the Views of a Sample of Workers in the Health Center / Sulaykh: The Correlation between the Dimensions of Organizational Silence and the F Function Life an Exploratory Study of the Views of a Sample of Workers in the Health Center / Sulaykh
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The research aims to test the effect of the behavioral factors (intangible) represented by an explanatory variable represented by organizational silence and a responsive variable of quality of Function life. The problem was the negative effects of the organizational silence on the morale of the employees and consequently their performance and the quality of function life. To collect the data and information needed to measure the two variables of research conducted in the health center / Sulaikh by taking a sample of (40) employees to test the hypotheses of research through the survey of their views, using statistical tools non parametric using the program. The most important recommendations were the establishment of training workshops fo

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Comparison the effectiveness of using a magnetic field to control theColi phages isolated from rivulet water with water-treatment using magnetic field added iron filings
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The present study aimed to use the magnetic field and nanotechnology in the field of water purification, which slots offering high efficiency to the possibility of removing biological contaminants such as viruses and bacteria rather than the use of chemical and physical transactions such as chlorine and bromine, and ultraviolet light and boiling and sedimentation and distillation, ozone and others that have a direct negative impact on human safety and the environment. Where they were investigating the presence in water samples under study Coli phages using Single agar layer method and then treated samples positive for phages to three types of magnetic field fixed as follows (North Pole - South Pole - Bipolar) and compare the re

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Publication Date
Fri Jun 17 2022
Journal Name
International Journal Of Health Sciences
Molecular detection of biofilm coding genes in Staphylococcus aureus
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In accordance with epidemic COVID-19, the elevated infection rates, disinfectant overuse and antibiotic misuse what led to immune suppression in most of the population in addition to genotypic and phenotypic alterations in the microorganisms, so a great need to reevaluate the genetic determinants that responsible for bacterial community (biofilm) has been raised. A total of 250 clinical specimens were obtained from patients in Baghdad hospitals and streaked on Mannitol salt agar medium. The results revealed that 156 isolates appeared as round yellow colonies, indicating that they were mostly identified as Staphylococcus aureus from 250 specimens. The antibiotic resistance pattern of the isolates for methicillin 37.17% (n=58), Amoxic

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Publication Date
Wed Feb 25 2026
Journal Name
Journalnx
Review Article: Impact of Molecular Biology in Life Science
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To study and understand the mechanism of living systems, and how it works, it is quite important to investigate it at molecular level (like genomic, proteomic) as well as the methodologies, and how to apply and imply it on different branch of sciences and how can use it in developing medical diagnosis, treatments, drugs, and increased it in the future. Additionally it can also be applied in forensic techniques, food production and agriculture, as well as genetic profiling. This can be well understand by interfering and combinations of all branches of life sciences such as chemistry, physics, biotechnology, genetic evolution, and minimize the gap between them, this

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Molecular Detection of Porphyromonas gingivalis in COVID-19 Patients
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Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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