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Abstract The DNA-binding protein from starved cells (Dps) plays a crucial role in maintaining bacterial cell viability during periods of stress. Dps is a nucleoid-associated protein that interacts with DNA to create biomolecular condensates in live bacteria. Purified Dps protein can also rapidly form large complexes when combined with DNA in vitro. However, the mechanism that allows these complexes to nucleate on DNA remains unclear. Here, we examine how DNA topology influences the formation of Dps–DNA complexes. We find that DNA supercoils offer the most preferred template for the nucleation of condensed Dps structures. More generally, bridging contacts between different regions of DNA can facilitate the nucleation of condensed Dps structures. In contrast, Dps shows little affinity for stretched linear DNA before it is relaxed. Once DNA is condensed, Dps forms a stable complex that can form inter-strand contacts with nearby DNA, even without free Dps present in solution. Taken together, our results establish the important role played by bridging contacts between DNA strands in nucleating and stabilizing Dps complexes.
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PDA-Pred: Predicting the binding affinity of protein-DNA complexes using machine learning techniques and structural features
Protein–DNA interactions play an important role in various biological processes such as gene expression, replication, and transcription. Understanding the important features that dictate the binding affinity of protein-DNA complexes and predicting their affinities is important for elucidating their recognition mechanisms. In this work, we have collected the experimental binding free energy (ΔG) for a set of 391 Protein-DNA complexes and derived several structure-based features such as interaction energy, contact potentials, volume and surface area of binding site residues, base step parameters of the DNA and contacts between different types of atoms. Our analysis on relationship between binding affinity and structural features revealed that the important factors mainly depend on the number of DNA strands as well as functional and structural classes of proteins. Specifically, binding site properties such as number of atom contacts between the DNA and protein, volume of protein binding sites and interaction-based features such as interaction energies and contact potentials are important to understand the binding affinity. Further, we developed multiple regression equations for predicting the binding affinity of protein-DNA complexes belonging to different structural and functional classes. Our method showed an average correlation and mean absolute error of 0.78 and 0.98 kcal/mol, respectively, between the experimental and predicted binding affinities on a jack-knife test. We have developed a webserver, PDA-PreD (Protein-DNA Binding affinity predictor), for predicting the affinity of protein-DNA complexes and it is freely available at https://web.iitm.ac.in/bioinfo2/pdapred/
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- Award ID(s):
- 1925643
- PAR ID:
- 10475943
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Methods
- Volume:
- 213
- Issue:
- C
- ISSN:
- 1046-2023
- Page Range / eLocation ID:
- 10 to 17
- Subject(s) / Keyword(s):
- protein-dna interaction binding affinity prediction of interaction
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.ymeth.2023.03.002
