Hydrogen bond energy-based comparative analysis of protein-ligand interactions and similarity assessment of protein-DNA complex models

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Malik, F. (2022). Hydrogen bond energy-based comparative analysis of protein-ligand interactions and similarity assessment of protein-DNA complex models. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Hydrogen bonds play a vital role in protein-DNA interactions. In particular, side chain-base hydrogen bonds are crucial to the binding specificity between protein and DNA. Mutations effecting interface hydrogen bonds in protein-DNA complexes have been linked to changes in binding specificity and are implicated in various diseases. However, knowledge about the distribution of hydrogen bond energy (HBE) in protein-DNA complexes as compared to other important biomolecular complexes is unknown. Here, we performed a systematic comparative analysis of hydrogen bond energy (HBE) in three protein-ligand complexes; protein-DNA, protein-protein and protein-peptide. Our results show that while the hydrogen bonds in protein-protein and protein-peptide complexes are predominantly strong, a unique, almost equal distribution of strong and weak hydrogen bonds is observed in protein-DNA complexes. More importantly, more strong hydrogen bonds are observed in the minor grooves of highly specific protein-DNA complexes than multispecific complexes indicating the role of minor groove hydrogen bonds in protein-DNA binding specificity. The knowledge gained from these analyses was applied to develop a novel hydrogen bond energy-based method to assess the similarity between protein-DNA complex models and reference structures, an important step towards computational prediction of complex structures. We show that HBE based method provides more accurate assessment of similarity for models generated by both homology modeling and computational docking methods.

Details
Author

Malik, Fareeha

Title

Hydrogen bond energy-based comparative analysis of protein-ligand interactions and similarity assessment of protein-DNA complex models

Physical Description

1 online resource (127 pages) : PDF

Date

2022

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Hydrogen bonds play a vital role in protein-DNA interactions. In particular, side chain-base hydrogen bonds are crucial to the binding specificity between protein and DNA. Mutations effecting interface hydrogen bonds in protein-DNA complexes have been linked to changes in binding specificity and are implicated in various diseases. However, knowledge about the distribution of hydrogen bond energy (HBE) in protein-DNA complexes as compared to other important biomolecular complexes is unknown. Here, we performed a systematic comparative analysis of hydrogen bond energy (HBE) in three protein-ligand complexes; protein-DNA, protein-protein and protein-peptide. Our results show that while the hydrogen bonds in protein-protein and protein-peptide complexes are predominantly strong, a unique, almost equal distribution of strong and weak hydrogen bonds is observed in protein-DNA complexes. More importantly, more strong hydrogen bonds are observed in the minor grooves of highly specific protein-DNA complexes than multispecific complexes indicating the role of minor groove hydrogen bonds in protein-DNA binding specificity. The knowledge gained from these analyses was applied to develop a novel hydrogen bond energy-based method to assess the similarity between protein-DNA complex models and reference structures, an important step towards computational prediction of complex structures. We show that HBE based method provides more accurate assessment of similarity for models generated by both homology modeling and computational docking methods.

Genre

doctoral dissertations

Subjects--Topics

Bioinformatics
Computer science

Degree

Ph.D.

Keywords

Comparison Of Complexes
Computational Models
Hydrogen Bond
Hydrogen Bond Energy
Protein-Dna Complexes
Protein-Ligand

Subject Area

Bioinformatics

Advisor(s)

Guo, Jun-tao

Committee Members

Weller, Jennifer
Sung, Way
Yan, Shan

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2022.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Malik_uncc_0694D_13064

Permalink

http://hdl.handle.net/20.500.13093/etd:2772