Computational Insights for Interactions between nsP2 and nsP3 of CHIKV and Hormones through DFT Computations and...

The non-structural protein (nsP2 & nsP3) of the Chikungunya virus (CHIKV) is responsible for the transmission of viral infection. The main role of non-structural proteins are involved in the transcription process at an early stage of the infection. In this work, authors have studied the impact of nsP2 and nsP3 of CHIKV on hormones present in the human body using a computational approach. The ten hormones of chemical properties such as 4-Androsterone-2,17-dione, aldosterone, androsterone, corticosterone, cortisol, cortisone, estradiol, estrone, progesterone and testosterone were taken as a potency. From the molecular docking, the binding energy of the complexes is estimated, and cortisone was found to be the highest negative binding energy (-6.57 kcal/mol) with the nsP2 and corticosterone with the nsP3 (-6.47 kcal/mol). This is based on the interactions between hormones and nsP2/nsP3, which are types of noncovalent intermolecular interactions categorized into three types: electrostatic interactions, van der Waals (vdW) interactions, and hydrogen-bonding (H-bonding) interactions. To validate the docking results, additional molecular dynamics simulations and MM-GBSA methods were performed. The change in enthalpy, entropy, and free energy were calculated using MM-GBSA methods. The nsP2 and nsP3 of CHIKV interact strongly with the cortisone and corticosterone with free energy changes of -20.55 & -36.08 kcal/mol, respectively. Methods: The crystal structures of 3TKR and 3GPO proteins of nsP2 and nsP3 were extracted from the RCSB Protein Data Bank. Initially, unnecessary atoms like extra cations or anions and missing explicit hydrogen atoms were removed and added from the native domain of nsP2 and nsP3. The alignment of coordinated in the native domain was performed using Chimera and Notepad⁺⁺ tools. The molecular docking of protein and ligand was performed usingAutoDock tool; it is essential for the prediction of the orientation of the ligand into the cavity of the target protein based on binding affinity. Based on thermodynamic parameters, MD Simulations were employed to calculate the change in binding free energies of various complexes followed by a change in enthalpy and entropy with time. According to MD production, the CPPTAJ and PTRAJ programs were used to analyse the trajectories, such as dynamic stability (RMSD), residual fluctuation (RMSF), compatibility, and hydrogen bonds of the newly formed complexes. After that, the Density Functional Theory (DFT) were used to calculate the electronic properties of selected molecules by Gaussian 16 on applying the B3LYP method with the 6-311G (d, p) basis set.