Tehran University of Medical Sciences

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In Silico Evaluation of the Interactions Among Two Selected Single Chain Variable Fragments (Scfvs) and Esat-6 Antigen of Mycobacterium Tuberculosis Publisher



Bandehpour M1, 2 ; Ahangarzadeh S1, 2 ; Yarian F1, 2 ; Lari A3 ; Farnia P4
Authors
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Authors Affiliations
  1. 1. Cellular and Molecular Biology Research Center Shahid Beheshti, University of Medical Sciences, Tehran, Iran
  2. 2. Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  3. 3. Systems Biomedicine, Pasteur Institute of Iran, Tehran, Iran
  4. 4. Mycobacteriology Research Centre (MRC), National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: Journal of Theoretical and Computational Chemistry Published:2017


Abstract

Nowadays antibody engineering is an important approach in the design and manufacture of therapeutic and diagnostic antibodies. The study of interactions between antibodies and antigens is the critical step in the design of antibodies with desirable properties. Computational docking is a useful tool for structural characterization of bimolecular interactions. Docking is the process of predicting bound conformations and binding enthalpy of antibody-antigen complexes. In this study, the three-dimensional structures of two ribosome displayed-selected scFv antibodies were constructed by Kotai Antibody Builder. By using ClusPro 2.0 web server, the ESAT-6 antigen (a tuberculosis-specific antigen) structure was docked to both scFv models to obtain the structures of the binding complexes and molecular dynamics (MD) simulations were performed using GROMACS 4.5.3 package. By analyzing of the ESAT-scFv complexes, important amino acids involved in antigen-antibody interactions were identified which were Asn164 in VL3, Ser164 in VL7 and Asn55 in VH7. All three amino acids belonged to the CDRs. In conclusion, results achieved from this bioinformatics study can help in the design and development of novel antibodies with improved affinities for tuberculosis diagnosis. © 2017 World Scientific Publishing Company.
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