&lt;b&gt;Development of an automated fragment molecular orbital (FMO) calculation protocol toward construction of quantum mechanical &lt;/b&gt;&lt;b&gt;calculation database for large biomolecules &lt;/b&gt;

Watanabe, Chiduru; Watanabe, Hirofumi; Okiyama, Yoshio; Takaya, Daisuke; Fukuzawa, Kaori; Tanaka, Shigenori; Honma, Teruki

doi:10.1273/cbij.19.5

“…The amino acid residues that are the key to the molecular recognition of three SARS S-proteins and ACE2/B38 Fab antibody were revealed by FMO-based interaction energy analysis with ab initio electron- We plan to release all the FMO data in this study on the public database, FMODB 59,60 , so that all researchers can access it and utilize it for designing effective antibody-drugs. Also, our group has recently performed over 336 FMO calculations for the COVID-19-related proteins such as S-protein, main protease, RNA dependent RNA 65 , based on the representative PDB structures selected in the PDB Japan database in line with this global fight effort against the coronavirus epidemic.…”

Section: Resultsmentioning

confidence: 99%

Molecular Recognition of SARS-CoV-2 Spike Glycoprotein: Quantum Chemical Hot Spot and Epitope Analyses

Watanabe

¹

,

Okiyama²,

Tanaka³

et al. 2020

Preprint

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<div>Due to the COVID-19 pandemic, researchers have attempted to identify complex structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S-protein) with angiotensin-converting enzyme 2 (ACE2) or a blocking antibody. However, the molecular recognition mechanism - critical information for drug and antibody design - has not been fully clarified at the amino acid residue level. Elucidating such a microscopic mechanism in detail requires a more accurate molecular interpretation that includes quantum mechanics to quantitatively evaluate hydrogen bonds, XH/π interactions (X = N, O, and C), and salt bridges. In this study, we applied the fragment molecular orbital (FMO) method to characterize the SARS-CoV-2 S-protein binding interactions with not only ACE2 but also the B38 Fab antibody involved in ACE2-inhibitory binding. By analyzing FMO-based interaction energies along a wide range of binding inter-faces carefully, we identified amino acid residues critical for molecular recognition between S-protein and ACE2 or B38 Fab antibody. Importantly, hydrophobic residues that attribute to weak interactions such as CH-O and XH/π interactions, as well as polar residues that construct conspicuous hydrogen bonds, play important roles in molecular recognition and binding ability. Moreover, through these FMO-based analyses, we also clarified novel hot spots and epitopes that had been overlooked in previous studies by structural and molecular mechanical approaches. Altogether, these hot spots/epitopes identified between S-protein and ACE2/B38 Fab antibody may provide useful information for future anti-body design and small or medium drug design against the SARS-CoV-2. </div><div><br></div>

show abstract

“…We plan to release all the FMO data in this study on the public database, FMODB 59,60 , so that all researchers can access it and utilize it for designing effective antibodydrugs. Also, our group has recently performed over 336 FMO calculations for the COVID-19-related proteins such as S-protein, main protease, RNA dependent RNA 65 , based on the representative PDB structures selected in the PDB Japan database in line with this global fight effort against the coronavirus epidemic.…”

Section: Resultsmentioning

confidence: 99%

Molecular Recognition of SARS-CoV-2 Spike Glycoprotein: Quantum Chemical Hot Spot and Epitope Analyses

Watanabe

¹

,

Okiyama²,

Tanaka³

et al. 2020

Preprint

Self Cite

0

View full text Add to dashboard Cite

<div>Due to the COVID-19 pandemic, researchers have attempted to identify complex structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S-protein) with angiotensin-converting enzyme 2 (ACE2) or a blocking antibody. However, the molecular recognition mechanism - critical information for drug and antibody design - has not been fully clarified at the amino acid residue level. Elucidating such a microscopic mechanism in detail requires a more accurate molecular interpretation that includes quantum mechanics to quantitatively evaluate hydrogen bonds, XH/π interactions (X = N, O, and C), and salt bridges. In this study, we applied the fragment molecular orbital (FMO) method to characterize the SARS-CoV-2 S-protein binding interactions with not only ACE2 but also the B38 Fab antibody involved in ACE2-inhibitory binding. By analyzing FMO-based interaction energies along a wide range of binding inter-faces carefully, we identified amino acid residues critical for molecular recognition between S-protein and ACE2 or B38 Fab antibody. Importantly, hydrophobic residues that attribute to weak interactions such as CH-O and XH/π interactions, as well as polar residues that construct conspicuous hydrogen bonds, play important roles in molecular recognition and binding ability. Moreover, through these FMO-based analyses, we also clarified novel hot spots and epitopes that had been overlooked in previous studies by structural and molecular mechanical approaches. Altogether, these hot spots/epitopes identified between S-protein and ACE2/B38 Fab antibody may provide useful information for future anti-body design and small or medium drug design against the SARS-CoV-2. </div><div><br></div>

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“…Other types of analyses, useful as support to drug design, include those reported by FMODB [ 104 ] [The database of quantum mechanical data based on the fragment molecular orbital (FMO) method, https://drugdesign.riken.jp/FMODB/covid-19.php ]. These involve FMO calculations on PDB structures for several SARS-CoV-2 proteins.…”

Section: Structural Bioinformatics Tools and Resources To Support Thementioning

confidence: 99%

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

Waman¹,

Sen²,

Váradi³

et al. 2020

Briefings in Bioinformatics

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SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor–antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

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<b>Development of an automated fragment molecular orbital (FMO) calculation protocol toward construction of quantum mechanical </b><b>calculation database for large biomolecules </b>

Cited by 43 publications

References 42 publications

Molecular Recognition of SARS-CoV-2 Spike Glycoprotein: Quantum Chemical Hot Spot and Epitope Analyses

Molecular Recognition of SARS-CoV-2 Spike Glycoprotein: Quantum Chemical Hot Spot and Epitope Analyses

Molecular Recognition of SARS-CoV-2 Spike Glycoprotein: Quantum Chemical Hot Spot and Epitope Analyses

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

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