Exploring the Spike-hACE 2 Residue–Residue Interaction in Human Coronaviruses SARS-CoV-2, SARS-CoV, and HCoV-NL63

Abstract

Coronaviruses (CoVs) have been responsible for three major outbreaks since the beginning of the 21st century, and the emergence of the recent COVID-19 pandemic has resulted in considerable efforts to design new therapies against coronaviruses. Thus, it is crucial to understand the structural features of their major proteins related to the virus–host interaction. Several studies have shown that from the seven known CoV human pathogens, three of them use the human Angiotensin-Converting Enzyme 2 (hACE-2) to mediate their host’s cell entry: SARS-CoV-2, SARS-CoV, and HCoV-NL63. Therefore, we employed quantum biochemistry techniques within the density function theory (DFT) framework and the molecular fragmentation with conjugate caps (MFCC) approach to analyze the interactions between the hACE-2 and the spike protein-RBD of the three CoVs in order to map the hot-spot residues that form the recognition surface for these complexes and define the similarities and differences in the interaction scenario. The total interaction energy evaluated showed a good agreement with the experimental binding affinity order: SARS-2 > SARS > NL63. A detailed investigation revealed the energetically most relevant regions of hACE-2 and the spike protein for each complex, as well as the key residue–residue interactions. Our results provide valuable information to deeply understand the structural behavior and binding site characteristics that could help to develop antiviral therapeutics that inhibit protein–protein interactions between CoVs S protein and hACE-2.

Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2

“…This is a valuable strategy in drug design because it allows the identification of druggable sites. For the completeness of the analysis, not only residues located at the interface but all residues within 8.0 Å from the interface of the proteins were analyzed ( Silva et al, 2020 ; Lima Neto et al, 2022 ). A schematic representation of the proteins is shown in Figure 2 .…”

“…Among these schemes, MFCC has been widely employed to calculate the interaction energy between protein amino acids and ligands, as well as in protein–protein complexes, allowing the investigation of a large number of amino acid residues in a protein possible with a small computational cost and high accuracy ( Lima Neto et al, 2015 ; Lima Neto et al, 2018 ; Bezerra et al, 2019 ; Albuquerque et al, 2021 ; Tavares et al, 2021 ). Recently, the MFCC scheme was used to study the interaction between the hACE-2 and Spike proteins of SARS-CoV-1, SARS-CoV-2, and hCoV-NL63 ( Lima Neto et al, 2022 ), the SARS-CoV-2 Mpro with synthetic peptides ( Amaral et al, 2022 ), and the human leukocyte antigen (HLA-A2) in complex with tumor-associated antigens based on glycoprotein gp100 ( Pereira et al, 2021 ).…”

Unravelling Insights into the Evolution and Management of SARS-CoV-2

“…Despite these mutations, the Omicron RBD binds to the human ACE2 (hACE2) receptor with a similar affinity as the prototype RBD, possibly due to compensatory mutations [85]. Key residues identified, including Q493, Q498, N501, F486, K417, and F456, are crucial for tight binding to hACE2 [86]. In the Omicron variant, mutated residues R493, S496, and R498 formed new interactions with ACE2, compensating for the reduced ACE2 binding affinity, leading to similar biochemical ACE2 binding affinities for Delta and Omicron [87,88].…”

Machine‐learning assisted scheduling optimization and its application in quantum chemical calculations

“…The QM models can be used only for reasonably modest system sizes (i.e., tens of atoms), while the fragment‐based approaches 15–31 or linear scaling strategies, 32–47 which a good load‐balancing scheme can benefit, are used to increase the reach of QM methods largely. For instance, there are many outstanding studies on analyzing the interactions, recognition of SARS‐CoV‐2 spike protein in QM level using fragment molecular orbital (FMO) approach 48–52 and molecular fractionation with conjugate caps (MFCC) approaches 53,54 …”

“…For instance, there are many outstanding studies on analyzing the interactions, recognition of SARS-CoV-2 spike protein in QM level using fragment molecular orbital (FMO) approach [48][49][50][51][52] and molecular fractionation with conjugate caps (MFCC) approaches. 53,54 As we have already entered the exascale super-computing era, 55 high-performance computing (HPC) is becoming progressively more important in bio-pharmaceutical systems, and achieving an even load balance is a key issue in practical computations. [56][57][58][59] By Amdahl's law, 60 the theoretical speedup of the whole task execution increases when the resources are increased.…”