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 enzy

From different hospitals in Baghdad city, 25 clinical isolates of Proteus spp. were collected from different clinical samples, all isolates were identified as Proteus mirabilis by using bacteriological and biochemical assays in addition to Vitek-2 identification system. 15 (60%) isolates were identifying as Proteus mirabilis. The susceptibility of P. mirabilis isolates towards cefotaxime and ceftazidime was (66.6 %), (20%) consecutively; while extended spectrum β-lactamases producing P. mirabilis percentage was (30.7 %). Because blaVEB-1 was documented as an important indicator for increasing risk of extended spectrum beta ßlactamases producing P. mirabilis isolates that began to spread from many geographic area to Far east which inc

This study is the first investigation in Iraq dealing with genotyping of IL-4 −590 (C>T) gene, especially in Iraqi patients with asthma. We studied forty-eight blood samples collected from patients with asthma and compared with age-matched 25 healthy individuals as controls. The polymorphism results of IL-4 −590 (C>T) gene by using amplification refractory mutation system (ARMS-PCR) showed the presence of C and T alleles and three genotypes (CC, CT, and TT). Interestingly the frequency of C allele and CC genotype was higher in patients with asthma in comparison with the same allele and geno

Background: Brush cytology is an accepted technique that gets renewed interest. It is now used as an aid for the diagnosis and observation of possible epithelial changes that could be associated with oral mucosal diseases. This study aimed to evaluate the cytomorphometric changes in gingiva and buccal mucosa of type II diabetics and to assess their relation to oral symptoms and glycemic status. Materials and methods: Cytological Papanicolaou stained smear were prepared from cheek and gingiva of 20 non treated cases, 20 treated diabetics and 20 healthy persons of both sex after measuring their HbA1c and recording their oral symptoms. Hundred unfolded epithelial cells were evaluated qualitatively using MCID software to measure nuclear and cy

KE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9

KE Sharquie, AA Noaimi, AM Oweid, JSSDDS, 2009 - Cited by 2

four coordinated complexes for divalent metal ions : Mn, Fe, Co, Ni, Cu and Cd have been synthesized using bidentate Schiff base ligand type (NN)formed by the condensation of o-phenylenediamine , p- methylbenzadehyde and furfural in methanol. The ligand was reacted with divalent metal chloride forming complexes of the types :[M(L)Cl2] where : MII=Mn, Fe, Ni, Cu, and Cd . These new compounds were characterized by elemental analysis, spectroscopic methods (FT-IR, U.V-Vis, 1HNMR (for ligand only and atomic absorption) , magnetic susceptibility, chloride content along with conductivity measurement. These studies revealed that the geometry for all complexes about central metal ion is tetrahedral.

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca