Chapter 7: Computational resources for understanding the effect of mutations in binding affinities of protein–RNA 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.