Computational prediction of cyclotides from Viola odorata as potential inhibitors against the neuraminidase of Streptococcus pneumoniae.

Cyclotides are naturally occurring peptides characterized by a cyclic cystine knot, which provides them with exceptional structural stability. In addition to their stability, cyclotides exhibit diverse therapeutic activities including antimicrobial, antiviral and antitumor activities, making them promising candidates in drug discovery. Despite their potential, computational studies aimed at identifying cyclotide-based inhibitors for infectious diseases remain limited. To address this gap, this study performed a virtual screening of cyclotides from an Indian medicinal plant Viola odorata to identify potential inhibitors against a bacterial pathogen causing respiratory infections. We compiled a library of 93 cyclotides by retrieving their structures from public domain or predicting them using the AlphaFold server. We then docked these cyclotides against the neuraminidase protein of Streptococcus pneumoniae and analyzed the interacting residues and binding energies to identify the potential inhibitors. The docking based investigation identified five cyclotides namely, kalata S, kalata B1, cycloviolacin O15, vodo L12, and cycloviolacin O36 as potential inhibitors, with maximum binding energy and forming interactions with key residues of the neuraminidase protein. Thereafter, we performed molecular dynamics simulations of the protein-cyclotide complexes, and observed that the cyclotides remained stable within the complex. Notably, this study is the first computational effort to identify potential cyclotide inhibitors against Streptococcus pneumoniae, thereby providing key insights into the development of novel therapeutics for respiratory infections. In future, a more directed approach to characterize the structure and property of these cyclotides, along with further experimental validation could enhance their potential as therapeutic agents for respiratory diseases.