Predicting peptide vaccine candidates against H1N1 influenza virus through theoretical approaches

Abstract

Identification of potential epitopes that might activate the immune system has been facilitated by the employment of algorithms that use experimental data as templates. However, in order to prove the affinity and the map of interactions between the receptor (major histocompatibility complex, MHC, or T-cell receptor) and the potential epitope, further computational studies are required. Docking and molecular dynamics (MDs) simulations have been an effective source of generating structural information at molecular level in immunology. Herein, in order to provide a detailed understanding of the origins of epitope recognition and to select the best peptide candidate to develop an epitope-based vaccine, docking and MDs simulations in combination with MMGBSA free energy calculations and per-residue free energy decomposition were performed, taking as starting complexes those formed between four designed epitopes (P1-P4) from hemagglutinin (HA) of the H1N1 influenza virus and MHC-II anchored in POPC membrane. Our results revealed that the energetic contributions of individual amino acids within the pMHC-II complexes are mainly dictated by van der Waals interactions and the nonpolar part of solvation energy, whereas the electrostatic interactions corresponding to hydrogen bonds and salt bridges determine the binding specificity, being the most favorable interactions formed between p4 and MHC-II. Then, P1-P4 epitopes were synthesized and tested experimentally to compare theoretical and experimental results. Experimental results show that P4 elicited the highest strong humoral immune response to HA of the H1N1 and may induce antibodies that are cross-reactive to other influenza subtypes, suggesting that it could be a good candidate for the development of a peptide-based vaccine.

Molecular Dynamics Assisted Mechanistic Study of Isoniazid-Resistance against Mycobacterium tuberculosis InhA

“…The rmsd pattern provides sufficient information about time when the system reached equilibrium. However, as suggested by Bello et al ., the effective binding free energies can also provide information about system convergences to support rmsd based convergence [ 40 ]. Fig 3 shows that all six systems shows fluctuation in average effective binding energy before 60ns.…”

APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations

“…Additional work would need to be done with molecular docking tools to keep track of what conformations have already been produced at a particular point. Another method that could be used is molecular dynamics, which simulate the interactions between atoms through time [17,18,19]. However, besides the fact that this method requires a bound pMHC conformation to begin with, molecular dynamics is computationally demanding in that it requires massive amounts of computational resources to explore physiologically relevant timescales [20].…”

Exploring the biotransformation of N-(2-hydroxyphenyl)-2-propylpentanamide (an aryl valproic acid derivative) by CYP2C11, using in silico predictions and in vitro studies

“…To verify the robustness and stability of the CYP2C11/HO‐AAVPA complex, long MD simulations were performed for complexes anchored into a POPC membrane (Figure 8a) considering the physiological environment for this system. [ 49,50 ] To evaluate whether the systems reached the equilibrium stages, some structural properties during the MD simulation were monitored, such as the root‐mean‐square deviation (RMSD) of the backbone atoms with respect to the initial structure and the area per lipid. Figure 8b shows that the CYP2C11/HO‐AAVPA complex exhibits a very high area per lipid value at the beginning of the simulation and then decreases towards a converged area per lipid on the order of 60–70 ns, obtaining an area per lipid value of 56.57 ± 0.70 for CYP2C11/HO‐AAVPA.…”