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Computational Prediction of Antibody Binding Sites on Tetracycline Antibiotics: Electrostatic Potentials and Average Local Ionization Energies on Molecular Surfaces

Publication Type : Journal Article

Thematic Areas : Center for Computational Engineering and Networking (CEN)

Source : Journal Phys. Chem. A, 113 (4), 756-766, 2009

Url : https://pubmed.ncbi.nlm.nih.gov/19159333/

Campus : Coimbatore

School : School of Engineering

Center : Center for Computational Engineering and Networking, Computational Engineering and Networking

Year : 2009

Abstract : Enzyme linked immunosorbent assay (ELISA) was used for the analysis of tetracycline, chlortetracycline, oxytetracycline, and their transformed compounds in environmental water samples. The antibodies employed in ELISA showed high relative affinity for tetracycline, epitetracycline, chlortetracycline, and epichlortetracycline as compared to anhydrotetracycline, epianhydrotetracycline, and anhydrochlortetracycline. The specificity and crossreactivity of these antibodies are discussed in relation to the electrostatic potentials and average local ionization energies computed on the molecular surfaces of tetracycline antibiotics and their transformed compounds with an objective of identifying common features as well as differences that may be related to the experimentally observed variation in cross-reactivity values. The computations were performed at both the HF/STO-3G and HF/6-31+G* levels using the Gaussian 98 program. The results in this study are based upon molecular electrostatic potentials and local ionization energies computed on isodensity molecular surfaces. The surface electrostatic potentials are characterized in terms of a group of statistically defined quantities, which include the average deviation, the positive, negative, and total variances, positive and negative surface extrema, and a parameter indicating the degree of electrostatic balance.

Cite this Research Publication : Pankaj Kulshrestha, N. Sukumar, Jane S. Murray, Rossman F. Giese and Troy D. Wood, “Computational Prediction of Antibody Binding Sites on Tetracycline Antibiotics: Electrostatic Potentials and Average Local Ionization Energies on Molecular Surfaces” J. Phys. Chem. A, 113 (4), 756-766 (2009) DOI: 10.1021/jp8089165 IF: 2.693

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