DOI: 10.5281/zenodo.15862969
title: Conformational dynamics and stability analysis of SARS-CoV-2 Spike glycoprotein

description: We performed a comprehensive structural analysis of the conformational space of several spike (S) protein variants using molecular dynamics (MD) simulations.Specifically, we examined four well-known variants (Delta, BA.1, XBB.1.5, and JN.1) alongside the wild-type (WT) form of SARS-CoV-2. The conformationalstates of each variant were characterized by analyzing their distributions within a selected space of collective variables (CVs), such as inter-domain distances betweenthe receptor-binding domain (RBD) and the N-terminal domain (NTD). Our primary focus was to identify conformational states relevant to potential structuraltransitions and to determine the set of native contacts (NCs) that stabilize these conformations. The results reveal that genetically more distant variants, such asXBB.1.5, BA.1, and JN.1, tend to adopt more compact conformational states compared to the WT. Additionally, these variants exhibit novel NC profiles, character-ized by an increased number of specific contacts distributed among ionic, polar, and nonpolar residues. We further analyzed the impact of specific mutations, includ-ing T478K, N500Y, and Y504H. These mutations not only enhance interactions with the human host receptor but also alter inter-chain stability by introducingadditional NCs compared to the WT. Consequently, these mutations may influence the accessibility of certain protein regions to neutralizing antibodies. Overall,these findings contribute to a deeper understanding of the structural and functional variations among S protein variants.

Trajectories of SARS-CoV-2 Spike Protein from four specific variants (Delta, BA.1, XBB.1.5, and JN.1) are included in this repository. The trajectories were generated by unbiased atomistic molecular dynamics in AMBER for a time of 500 ns (5 replicates of 100 ns). The simulations were performed with structures available in the Protein Data Base: Delta PDB ID: 7W92, BA.1 PDB ID: 7XO5, XBB.1.5 PDB ID: 8VKM, and JN.1 PDB ID: 8Y5J. The trajectories have been stored every 50 ps.

SCRIPTS:



add_chain.py: script to fix the chains in the Spike protein trimmer.

contact_map: Script to calculate contact map of a protein (used with the jupyter notebook, http://pomalab.ippt.pan.pl/GoContactMap/).

contact_frequency.ipynb: jupyter notebook to calculate inter-chain native contacts frecuency.

distance_RBD.tcl: script to calculate distances between 2 RBDs (defined by center of mass of the domains).

distance_NTD.tcl: scrpt to calculate distances between 2 NTDs (defined by center of mass of the domains).

angle.tcl: script to calculate angle values from 2 defined vectors.

Gausian_fitting.py: script to fit and plot the data of distances or angles (CVs). 

calculate_chi2.py: script to calculate the chi2 of the fitting data.

filter_contacts_interaction.py: script to filter the contacts from the list and calculate the type of interaction (ionic, polar, nonpolar, nonspecific).

get_frames_4_contacts.py: script to get the frames that are within the margen of the distribution (defined by mu and sigma).

cat_pdbs.sh: script to concatenate pdbs.


CONTACT MAPS: These files contains all the contact maps from the complete trajestories.



WT_CM.tar.xz

DELTA_CM.tar.xz

BA1_CM.tar.xz

XBB15_CM.tar.xz

JN1_CM.tar.xz


CONTACT MAPS FOR SPECIFIC STATES: These files contains the specific contact maps of indivual states.



WT_states_CM.tar.xz

DELTA_states_CM.tar.xz

BA1_states_CM.tar.xz

XBB15_states_CM.tar.xz

JN1_states_CM.tar.xz