Narrow Results

Protein–nucleic acid interactions are inevitable in maintaining the homeostasis of cells. It is important to have a quantitative understanding of these interactions, generally described in terms of the dissociation constant or free energy change of protein–DNA and protein–RNA complexes. These interactions are impaired in the presence of mutations in nucleic acids or their interacting proteins, leading to numerous diseases. Hence, it is important to understand the binding affinity change upon mutation in protein–nucleic acid complexes. Different experimental techniques are available to study the binding affinities, although they are accurate, it is time and labor-intensive. On the other hand, computational techniques are emerging with numerous databases and computational tools to study protein–DNA complexes. In this chapter, we discuss various databases for the binding affinity of complexes and change upon mutation and the tools available to extract different structural and interaction features from the complexes. Further, we provide details on prediction methods reported for predicting the change in binding affinity upon mutation, along with hotspot residue prediction in protein–DNA complexes.

Protein–nucleic acid interactions play a crucial role in maintaining cellular homeostasis. Quantitatively, these interactions are described in terms of the dissociation constant or free energy change observed during protein–nucleic acid complex formation. These interactions are impaired in the presence of mutations affecting the binding affinity of the complexes, in turn leading to numerous diseases. Therefore, understanding how binding affinity changes due to mutations in protein-nucleic acid complexes is vital. While experimental techniques are highly accurate, they are also time-consuming and labor-intensive. On the other hand, computational techniques are emerging as valuable alternatives, with numerous databases and computational tools to study protein–RNA complexes. In this chapter, we discuss various databases that provide information on binding affinities and their changes upon mutation in protein–RNA complexes. Additionally, tools available to extract different structural and interaction features from the complexes are given in detail. Furthermore, we offer insights into prediction methods reported to predict the change in binding affinity upon mutation of protein–RNA complexes. We also cover the existing methods for hotspot residue identification in these complexes.