Loading...
Search for: ligand-binding
0.004 seconds

    Production of a soluble and functional recombinant apolipoproteinD in the Pichia pastoris expression system

    , Article Protein Expression and Purification ; Volume 121 , 2016 , Pages 157-162 ; 10465928 (ISSN) Armanmehr, S ; Kalhor, H. R ; Tabarraei, A ; Sharif University of Technology
    Academic Press Inc 
    Abstract
    ApolipoproteinD (ApoD) is a human glycoprotein from the lipocalin family. ApoD contains a conserved central motif of an 8-stranded antiparallel β-sheet, which forms a beta-barrel that can be used for transport and storage of diverse hydrophobic ligands. Due to hydrophobic nature of ApoD, it has been difficult to generate a recombinant version of this protein. In the present work, we aimed at the production of ApoD in the robust Pichia pastoris expression system. To this end, the ApoD gene sequence was synthesized and subcloned for expression in the yeast host cells. Following integration of the ApoD gene into the yeast genomic region using homologous recombination, the ApoD recombinant... 

    Drug delivery performance of nanocarriers based on adhesion and interaction for abdominal aortic aneurysm treatment

    , Article International Journal of Pharmaceutics ; Volume 594 , 2021 ; 03785173 (ISSN) Ebrahimi, S ; Vatani, P ; Amani, A ; Shamloo, A ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Targeted drug delivery using nanocarriers (NCs) is one of the novel techniques that has recently been used to improve drug delivery to the Abdominal aortic aneurysm (AAA) disease. The purpose of this study is to evaluate the surface density of NCs (SDNC) adhered via ligand-receptor binding to the inner wall of AAA. For this purpose, fluid–structure interaction (FSI) analysis was first performed for the patient-specific and ideal AAA models. Then, by injecting NCs into the aortic artery, the values of SDNC adhered to and interacted with AAA wall were obtained. Two types of NCs, liposomes, and solid particles in four different diameters, were used to investigate the effect of the diameter and... 

    Margination and adhesion of micro- and nanoparticles in the coronary circulation: A step towards optimised drug carrier design

    , Article Biomechanics and Modeling in Mechanobiology ; Volume 17, Issue 1 , 2018 , Pages 205-221 ; 16177959 (ISSN) Forouzandehmehr, M ; Shamloo, A ; Sharif University of Technology
    Springer Verlag  2018
    Abstract
    Obstruction of left anterior descending artery (LAD) due to the thrombosis or atherosclerotic plaques is the leading cause of death worldwide. Targeted delivery of drugs through micro- and nanoparticles is a very promising approach for developing new strategies in clot-busting or treating restenosis. In this work, we modelled the blood flow characteristics in a patient-specific reconstructed LAD artery by the fluid–solid interaction method and based on physiological boundary conditions. Next, we provided a Lagrangian description of micro- and nanoparticles dynamics in the blood flow considering their Brownian motion and the particle–particle interactions. Our results state that the number of... 

    Binding assessment of two arachidonic-based synthetic derivatives of adrenalin with β-lactoglobulin: Molecular modeling and chemometrics approach

    , Article Biophysical Chemistry ; Volume 207 , 2015 , Pages 97-106 ; 03014622 (ISSN) Gholami, S ; Bordbar, A. K ; Akvan, N ; Parastar, H ; Fani, N ; Gretskaya, N. M ; Bezuglov, V. V ; Haertlé, T ; Sharif University of Technology
    Elsevier  2015
    Abstract
    A computational approach to predict the main binding modes of two adrenalin derivatives, arachidonoyl adrenalin (AA-AD) and arachidonoyl noradrenalin (AA-NOR) with the β-lactoglubuline (BLG) as a nano-milk protein carrier is presented and assessed by comparison to the UV-Vis absorption spectroscopic data using chemometric analysis. Analysis of the spectral data matrices by using the multivariate curve resolution-alternating least squares (MCR-ALS) algorithm led to the pure concentration calculation and spectral profiles resolution of the chemical constituents and the apparent equilibrium constants computation. The negative values of entropy and enthalpy changes for both compound indicated... 

    Effect of physico-chemical properties of nanoparticles on their intracellular uptake

    , Article International Journal of Molecular Sciences ; Volume 21, Issue 21 , 2020 , Pages 1-20 Sabourian, P ; Yazdani, G ; Ashraf, S. S ; Frounchi, M ; Mashayekhan, S ; Kiani, S ; Kakkar, A ; Sharif University of Technology
    MDPI AG  2020
    Abstract
    Cellular internalization of inorganic, lipidic and polymeric nanoparticles is of great significance in the quest to develop effective formulations for the treatment of high morbidity rate diseases. Understanding nanoparticle–cell interactions plays a key role in therapeutic interventions, and it continues to be a topic of great interest to both chemists and biologists. The mechanistic evaluation of cellular uptake is quite complex and is continuously being aided by the design of nanocarriers with desired physico-chemical properties. The progress in biomedicine, including enhancing the rate of uptake by the cells, is being made through the development of structure–property relationships in... 

    Prediction of Protein Ligand Binding Affinity Using Deep Networks

    , M.Sc. Thesis Sharif University of Technology Gholamzadeh Lanjavi, Atena (Author) ; Kalhor, Hamid Reza (Supervisor) ; Motahhari, Abolfazl (Co-Supervisor)
    Abstract
    Protein-ligand binding affinity is extremely important for finding new candidates in drug discovery and computational biochemistry. One of the physical characteristics for protein ligand interactions has been dissociation constant (KD) which can be obtain experimentally. However, there have been tremendous efforts to predict KD using modeling and computational approaches for protein-ligand interactions. In this project, we have exploited Convolutional Neural Network (CNN) model based on KDeep design, PDBBind version 2016 refined set training data, and examining it with KDeep core set test data. In order to modify KDeep,instead of 24 rotations (0, 90, 180 and 270 degrees in selection of two...