@article {152899, title = {The alteration of structural network upon transient association between proteins studied using graph theory.}, journal = {Proteins}, volume = {93}, year = {2025}, month = {2025 Jan}, pages = {217-225}, abstract = {

Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.

}, keywords = {Algorithms, Allosteric Regulation, Databases, Protein, Models, Molecular, Protein Binding, Protein Conformation, Protein Interaction Mapping, Protein Interaction Maps, Proteins}, issn = {1097-0134}, doi = {10.1002/prot.26606}, author = {Prabantu, Vasam Manjveekar and Tandon, Himani and Sandhya, Sankaran and Sowdhamini, Ramanathan and Srinivasan, Narayanaswamy} } @article {118723, title = {Computational tools to study RNA-protein complexes.}, journal = {Front Mol Biosci}, volume = {9}, year = {2022}, month = {2022}, pages = {954926}, abstract = {

RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein-RNA interactions are still poorly derstood in contrast to protein-protein and protein-DNA interactions. This knowledge gap can be attributed to the limited availability of protein-RNA structures along with the experimental difficulties in studying these complexes. Recent progress in computational resources has expanded the number of tools available for studying protein-RNA interactions at various molecular levels. These include tools for predicting interacting residues from primary sequences, modelling of protein-RNA complexes, predicting hotspots in these complexes and insights into derstanding in the dynamics of their interactions. Each of these tools has its strengths and limitations, which makes it significant to select an optimal approach for the question of interest. Here we present a mini review of computational tools to study different aspects of protein-RNA interactions, with focus on overall application, development of the field and the future perspectives.

}, issn = {2296-889X}, doi = {10.3389/fmolb.2022.954926}, author = {Bheemireddy, Sneha and Sandhya, Sankaran and Srinivasan, Narayanaswamy and Sowdhamini, Ramanathan} } @article {5311, title = {Protein sequence design and its applications.}, journal = {Curr Opin Struct Biol}, volume = {37}, year = {2016}, month = {2016 Apr}, pages = {71-80}, abstract = {

Design of proteins has far-reaching potentials in diverse areas that span repurposing of the protein scaffold for reactions and substrates that they were not naturally meant for, to catching a glimpse of the ephemeral proteins that nature might have sampled during evolution. These non-natural proteins, either in synthesized or virtual form have opened the scope for the design of entities that not only rival their natural counterparts but also offer a chance to visualize the protein space continuum that might help to relate proteins and understand their associations. Here, we review the recent advances in protein engineering and design, in multiple areas, with a view to drawing attention to their future potential.

}, issn = {1879-033X}, doi = {10.1016/j.sbi.2015.12.004}, author = {Sandhya, Sankaran and Mudgal, Richa and Kumar, Gayatri and Sowdhamini, Ramanathan and Srinivasan, Narayanaswamy} } @article {901, title = {NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection.}, journal = {Nucleic Acids Res}, volume = {43}, year = {2015}, month = {2015 Jan}, pages = {D300-5}, abstract = {

NrichD (http://proline.biochem.iisc.ernet.in/NRICHD/) is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural {\textquoteright}intermediately related sequences{\textquoteright} is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been {\textquoteright}enriched{\textquoteright} with these artificial intermediary sequences. NrichD database currently contains 3,611,010 artificial sequences that have been generated between 27,882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.

}, keywords = {Computational Biology, Databases, Protein, Internet, Molecular Sequence Annotation, Protein Structure, Tertiary, Sequence Analysis, Protein, Sequence Homology, Amino Acid}, issn = {1362-4962}, doi = {10.1093/nar/gku888}, author = {Mudgal, Richa and Sandhya, Sankaran and Kumar, Gayatri and Sowdhamini, Ramanathan and Chandra, Nagasuma R and Srinivasan, Narayanaswamy} }