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Monte Carlo sampling and multivariate adaptive regression splines as tools for QSAR modelling of HIV-1 reverse transcriptase inhibitors
, Article SAR and QSAR in Environmental Research ; Volume 23, Issue 7-8 , Jun , 2012 , Pages 665-682 ; 1062936X (ISSN) ; Mani Varnosfaderani, A ; Asadollahi Baboli, M ; Khalafi Nezhad, A ; Sharif University of Technology
2012
Abstract
The present work focuses on the development of an interpretable quantitative structure-activity relationship (QSAR) model for predicting the anti-HIV activities of 67 thiazolylthiourea derivatives. This set of molecules has been proposed as potent HIV-1 reverse transcriptase inhibitors (RT-INs). The molecules were encoded to a diverse set of molecular descriptors, spanning different physical and chemical properties. Monte Carlo (MC) sampling and multivariate adaptive regression spline (MARS) techniques were used to select the most important descriptors and to predict the activity of the molecules. The most important descriptor was found to be the aspherisity index. The analysis of variance...
Use of artificial neural networks in a QSAR study of Anti-HIV activity for a large group of HEPT derivatives
, Article Journal of Chemical Information and Computer Sciences ; Volume 40, Issue 1 , 2000 , Pages 147-154 ; 00952338 (ISSN) ; Parastar, F ; Sharif University of Technology
American Chemical Society
2000
Abstract
Anti-HIV activity for a set of 107 inhibitors of the HIV-1 reverse transcriptase, derivatives of 1-[2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT), was modeled with the aid of chemometric techniques. The activity of these compounds was estimated by means of multiple linear regression (MLR) and artificial neural network (ANN) techniques and compared with the previous works. The results obtained using the MLR method indicate that the anti-HIV activity of the HEPT derivatives depends on the reverse of standard shadow area on the YZ plane and the ratio of the partial charges of the most positive atom to the most negative atom of the molecule. The best computational neural network model was...
Multiway investigation of interaction between fluorescence labeled DNA strands and unmodified gold nanoparticles
, Article Analytical Chemistry ; Volume 84, Issue 15 , July , 2012 , Pages 6603-6610 ; 00032700 (ISSN) ; Kompany Zareh, M ; Hormozi Nezhad, M. R ; Sharif University of Technology
ACS
2012
Abstract
The single stranded DNA can be adsorbed on the negatively charged surface of gold nanoparticles (AuNPs), but the rigid structure of double stranded DNA prevents it from adsorption. Signal of a tagged single stranded DNA will be quenched by the plasmon effect of the AuNP surface after its adsorption. This phenomenon has been used to study the DNA hybridization and interactions of two complementary 21mer oligonucleotides each tagged with a different fluorescent dye in the presence of 13 nm gold nanoparticles. The DNA strands used in this study belong to the genome of HIV. The obtained rank deficient three-way fluorescence data sets were resolved by both PARAFAC and restricted Tucker3 models....
Classification of anti-HIV compounds using counterpropagation artificial neural networks and decision trees
, Article SAR and QSAR in Environmental Research ; Volume 22, Issue 7-8 , Oct , 2011 , Pages 639-660 ; 1062936X (ISSN) ; Mani Varnosfaderani, A ; Eftekhar Jahromi, P ; Mohsen Mahmoodi, M ; Taherinia, D ; Sharif University of Technology
2011
Abstract
The main aim of the present work was to collect and categorize anti-HIV molecules in order to identify general structure-activity relationships. In this respect, a total of 5580 drugs and drug-like molecules was collected from 256 different articles published between 1992 and 2010. An algorithm called genetic algorithm-pattern search counterpropagation artificial neural networks (GPS-CPANN) was proposed for the classification of compounds. In addition, the CART (classification and regression trees) method was used for construction of decision trees and finding the best molecular descriptors. The results revealed that the developed CPANN models and decision tree can correctly classify the...
Modeling and control of HIV by computational intelligence techniques
, Article IFMBE Proceedings, 30 April 2010 through 2 May 2010, College Park, MD ; Volume 32 IFMBE , April , 2010 , Pages 192-195 ; 16800737 (ISSN) ; 9783642149979 (ISBN) ; Sharif University of Technology
2010
Abstract
The paper aims at proposing a controller through two-layer neural networks (NN) in order to control CD4 amount in HIV + Patients. In the same direction, initially a new mathematical model by using of two-layer neural networks (NN) was designed. Medical information of 300 HIV + Patients who were being treated in the Iranian Research Center for HIV/AIDS (IRCHA), Imam Khomeini Hospital, Tehran, was used to design this model. Highly active antiretroviral therapy (HAART) medical method is a significant method that was used in this study. It is worthy to say that CD4 amount declining leads to immune system deficiency and it is considered as one of AIDS main symptoms. Output of this mathematic...
Neural networks in analytical chemistry
, Article Methods in Molecular Biology ; Volume 458 , 2008 , Pages 81-121 ; 10643745 (ISSN); 9781588297181 (ISBN) ; Sharif University of Technology
2008
Abstract
This chapter covers a part of the spectrum of neural-network uses in analytical chemistry. Different architectures of neural networks are described briefly. The chapter focuses on the development of three-layer artificial neural network for modeling the anti-HIV activity of the HETP derivatives and activity parameters (pIC 50) of heparanase inhibitors. The use of a genetic algorithm-kernel partial least squares algorithm combined with an artificial neural network (GA-KPLS-ANN) is described for predicting the activities of a series of aromatic sulfonamides. The retention behavior of terpenes and volatile organic compounds and predicting the response surface of different detection systems are...
MicroRNAs 29, 150, 155, 223 level and their relation to viral and immunological markers in HIV-1 infected naive patients
, Article Future Virology ; Volume 13, Issue 9 , 2018 , Pages 637-645 ; 17460794 (ISSN) ; Bokharaei Salim, F ; Esghaei, M ; Keyvani, H ; Honardoost, M ; Mostafaei, S ; Ghasemi, A ; Tavakoli, A ; Javanmard, D ; Babaei, F ; Garshasbi, S ; Monavari, S. H ; Sharif University of Technology
Abstract
Aim: The aim of this study was to assess the relationship between microRNAs and viral and immunological markers in HIV-1 infection. Materials & methods: The expression level of miRNAs was evaluated in 60 HIV-1 patients and 20 healthy controls using real-time PCR assays. Results: The results showed that among all miRNAs, miR-29 and miR-150 were significantly downregulated in HIV-1 patients compared with healthy controls, while miR-155 and miR-223 were significantly upregulated compared with healthy controls (p < 0.001 for all comparisons). Conclusion: The mentioned miRNAs seem to influence the clinical progression of HIV-1 infection in naive patients. Moreover, determining the profiles of...
Graphene-based nanomaterials in fighting the most challenging viruses and immunogenic disorders
, Article ACS Biomaterials Science and Engineering ; Volume 8, Issue 1 , 2022 , Pages 54-81 ; 23739878 (ISSN) ; Asadi, M ; Akhavan, O ; Sharif University of Technology
American Chemical Society
2022
Abstract
Viral diseases have long been among the biggest challenges for healthcare systems around the world. The recent Coronavirus Disease 2019 (COVID-19) pandemic is an example of how complicated the situation can get if we are not prepared to combat a viral outbreak in time, which brings up the need for quick and affordable biosensing platforms and vast knowledge of potential antiviral effects and drug/gene delivery opportunities. The same challenges have also existed for nonviral immunogenic disorders. Nanomedicine is considered a novel candidate for effectively overcoming these worldwide challenges. Among the versatile nanomaterials commonly used in biomedical applications, graphene has recently...