Protein-nucleic acid interactions are involved in various biological processes such as gene expression, replication, transcription, translation, and packaging. Understanding the recognition mechanism of the protein-nucleic acid complexes has been investigated from different perspectives, including the binding affinities of protein-DNA and protein-RNA complexes. Experimentally, protein-nucleic acid interactions are analyzed using X-ray crystallography, Isothermal Titration Calorimetry (ITC), DNA/RNA pull-down assays, DNA/RNA footprinting, and systematic evolution of ligands by exponential enrichment (SELEX). On the other hand, numerous databases and computational tools have been developed to study protein-nucleic acid complexes based on their binding sites, specific interactions between them, and binding affinity. In this chapter, we discuss various databases for protein-nucleic acid complex structures and the tools available to extract features from them. Further, we provide details on databases and prediction methods reported for exploring the binding affinity of protein-nucleic acid complexes along with important structure-based parameters, which govern the binding affinity.
Keywords: Binding affinity; Computational tools; Machine learning; Prediction methods; Protein-DNA complexes; Protein-RNA complexes.
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