MHCBI: a pipeline for calculating peptide-MHC binding energy using semi-empirical quantum mechanical methods with explicit/implicit solvent models.

Experimentally estimating peptide-major histocompatibility complex (pMHC) binding affinity has been quite challenging due to the many receptors and the many potential ligands implicated in it. We have thus proposed a straightforward computational methodology considering the different mechanisms involved in pMHC binding to facilitate studying such receptor-ligand interactions. We have developed a pipeline using semi-empirical quantum mechanical methods for calculating pMHC class I and II molecules' binding energy (BE). This pipeline can systematize the methodology for calculating pMHC system BE, enabling the rational design of T-cell epitopes to be used as pharmaceuticals and vaccines.

Towards the understanding of the activity of G9a inhibitors: an activity landscape and molecular modeling approach.

In this work, we analyze the structure-activity relationships (SAR) of epigenetic inhibitors (lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined activity landscape, molecular docking and molecular dynamics approach. The study was based on a set of 251 G9a inhibitors with reported experimental activity. The activity landscape analysis rapidly led to the identification of activity cliffs, scaffolds hops and other active an inactive molecules with distinct SAR. Structure-based analysis of activity cliffs, scaffold hops and other selected active and inactive G9a inhibitors by means of docking followed by molecular dynamics simulations led to the identification of interactions with key residues involved in activity against G9a, for instance with ASP 1083, LEU 1086, ASP 1088, TYR 1154 and PHE 1158. The outcome of this work is expected to further advance the development of G9a inhibitors.

Quantum chemical analysis of MHC-peptide interactions for vaccine design.

The development of an adequate immune response against pathogens is mediated by molecular interactions between different cell types. Among them, binding of antigenic peptides to the Major Histocompatibility Complex (MHC) molecule expressed on the membrane of antigen presenting cells (APCs), and their subsequent recognition by the T cell receptor have been demonstrated to be crucial for developing an adequate immune response. The present review compiles computational quantum chemistry studies about the electrostatic potential variations induced on the MHC binding region by peptide's amino acids, carried out with the aim of describing MHC-peptide binding interactions. The global idea is that the electrostatic potential can be represented in terms of a series expansion (charge, dipole, quadrupole, hexadecapole, etc.) whose three first terms provide a good local approximation to the molecular electrostatic 'landscape' and to the variations induced on such landscape by targeted modifications on the residues of the antigenic peptide. Studies carried out in four MHC class II human allele molecules, which are the most representative alleles of their corresponding haplotypes, showed that each of these molecules have conserved as well as specific electrostatic characteristics, which can be correlated at a good extent with the peptide binding profiles reported experimentally for these molecules. The information provided by such characteristics would help increase our knowledge about antigen binding and presentation, and could ultimately contribute to developing a logical and rational methodology for designing chemically synthesized, multi-antigenic, subunit-based vaccines, through the application of quantum chemistry methods.