By
the splendid advance in computation power realized with the
Fugaku supercomputer, it has become possible to perform ab initio
fragment molecular orbital (FMO) calculations for thousands of dynamic
structures of protein–ligand complexes in a parallel way. We
thus carried out electron-correlated FMO calculations for a complex
of the 3C-like (3CL) main protease (Mpro) of the new coronavirus
(SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations
sampled by classical molecular dynamics (MD) simulation in hydrated
conditions. Along with a statistical evaluation of the interfragment
interaction energies (IFIEs) between the N3 ligand and the surrounding
amino-acid residues for 1000 dynamic structure samples, in this study
we applied a novel approach based on principal component analysis
(PCA) and singular value decomposition (SVD) to the analysis of IFIE
data in order to extract the dynamically cooperative interactions
between the ligand and the residues. We found that the relative importance
of each residue is modified via the structural fluctuations and that
the ligand is bound in the pharmacophore in a dynamic manner through
collective interactions formed by multiple residues, thus providing
new insight into structure-based drug discovery.
By the splendid advance in computation power realized with Fugaku supercomputer, it has become
possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of
dynamical structures of a protein-ligand complex in a parallelized way. We have thus carried out the
electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the
new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled
by classical molecular dynamics (MD) simulation in hydrated condition. Along with a statistical
evaluation of inter-fragment interaction energies (IFIEs) between the N3 ligand and surrounding
amino-acid residues for a thousand of dynamical structure samples, we have applied in this study a
novel approach based on the principal component analysis (PCA) and the singular value
decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative
interactions between the ligand and residues. We have found that the relative importance of each
residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore
in a dynamical manner through collective interactions formed by multiple residues, thus providing a
new insight into structure-based drug discovery
By the splendid advance in computation power realized with Fugaku supercomputer, it has become
possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of
dynamical structures of a protein-ligand complex in a parallelized way. We have thus carried out the
electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the
new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled
by classical molecular dynamics (MD) simulation in hydrated condition. Along with a statistical
evaluation of inter-fragment interaction energies (IFIEs) between the N3 ligand and surrounding
amino-acid residues for a thousand of dynamical structure samples, we have applied in this study a
novel approach based on the principal component analysis (PCA) and the singular value
decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative
interactions between the ligand and residues. We have found that the relative importance of each
residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore
in a dynamical manner through collective interactions formed by multiple residues, thus providing a
new insight into structure-based drug discovery
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