Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital method Article Swipe
Daisuke Takaya
,
Shinichi Ohno
,
T Miyagishi
,
Shinya Tanaka
,
Koji Okuwaki
,
Chiduru Watanabe
,
Koichiro Kato
,
Yu‐Shi Tian
,
Kaori Fukuzawa
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1038/s41597-024-03999-2
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1038/s41597-024-03999-2
The function of a biomacromolecule is not only determined by its three-dimensional structure but also by its electronic state. Quantum chemical calculations are promising non-empirical methods available for determining the electronic state of a given structure. In this study, we used the fragment molecular orbital (FMO) method, which applies to biopolymers such as proteins, to provide physicochemical property values on representative structures in the SCOP2 database of protein families, a subset of the Protein Data Bank. Our dataset was constructed by over 5,000 protein structures, including over 200 million inter-fragment interaction energies (IFIEs) and their energy components obtained by pair interaction energy decomposition analysis (PIEDA) using FMO-MP2/6-31 G*. Moreover, three basis sets, 6-31 G*, 6-31 G**, and cc-pVDZ, were used for the FMO calculations of each structure, making it possible to compare the energies obtained with different basis functions for the same fragment pair. The total data size is approximately 6.7 GB. Our dataset will be useful for functional analyses and machine learning based on the physicochemical property values of proteins.
Related Topics
Concepts
Fragment molecular orbital
Fragment (logic)
Protein Data Bank
Electronic structure
Quantum chemical
Basis (linear algebra)
Function (biology)
Property (philosophy)
Chemistry
Protein structure
Computational chemistry
Biological system
Statistical physics
Computer science
Physics
Molecular orbital
Molecule
Algorithm
Mathematics
Quantum mechanics
Biology
Geometry
Genetics
Epistemology
Biochemistry
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41597-024-03999-2
- OA Status
- gold
- Cited By
- 1
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403688206
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403688206Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41597-024-03999-2Digital Object Identifier
- Title
-
Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital methodWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-10-23Full publication date if available
- Authors
-
Daisuke Takaya, Shinichi Ohno, T Miyagishi, Shinya Tanaka, Koji Okuwaki, Chiduru Watanabe, Koichiro Kato, Yu‐Shi Tian, Kaori FukuzawaList of authors in order
- Landing page
-
https://doi.org/10.1038/s41597-024-03999-2Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1038/s41597-024-03999-2Direct OA link when available
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Fragment molecular orbital, Fragment (logic), Protein Data Bank, Electronic structure, Quantum chemical, Basis (linear algebra), Function (biology), Property (philosophy), Chemistry, Protein structure, Computational chemistry, Biological system, Statistical physics, Computer science, Physics, Molecular orbital, Molecule, Algorithm, Mathematics, Quantum mechanics, Biology, Geometry, Genetics, Epistemology, Biochemistry, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.compare | 132 |
| abstract_inverted_index.dataset | 78, 154 |
| abstract_inverted_index.machine | 162 |
| abstract_inverted_index.method, | 47 |
| abstract_inverted_index.methods | 26 |
| abstract_inverted_index.million | 89 |
| abstract_inverted_index.orbital | 45 |
| abstract_inverted_index.protein | 68, 84 |
| abstract_inverted_index.provide | 56 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analyses | 160 |
| abstract_inverted_index.analysis | 104 |
| abstract_inverted_index.cc-pVDZ, | 118 |
| abstract_inverted_index.chemical | 21 |
| abstract_inverted_index.database | 66 |
| abstract_inverted_index.energies | 92, 134 |
| abstract_inverted_index.fragment | 43, 143 |
| abstract_inverted_index.function | 2 |
| abstract_inverted_index.learning | 163 |
| abstract_inverted_index.obtained | 98, 135 |
| abstract_inverted_index.possible | 130 |
| abstract_inverted_index.property | 58, 168 |
| abstract_inverted_index.Moreover, | 109 |
| abstract_inverted_index.available | 27 |
| abstract_inverted_index.different | 137 |
| abstract_inverted_index.families, | 69 |
| abstract_inverted_index.functions | 139 |
| abstract_inverted_index.including | 86 |
| abstract_inverted_index.molecular | 44 |
| abstract_inverted_index.promising | 24 |
| abstract_inverted_index.proteins, | 54 |
| abstract_inverted_index.proteins. | 171 |
| abstract_inverted_index.structure | 13 |
| abstract_inverted_index.components | 97 |
| abstract_inverted_index.determined | 9 |
| abstract_inverted_index.electronic | 18, 31 |
| abstract_inverted_index.functional | 159 |
| abstract_inverted_index.structure, | 127 |
| abstract_inverted_index.structure. | 36 |
| abstract_inverted_index.structures | 62 |
| abstract_inverted_index.biopolymers | 51 |
| abstract_inverted_index.constructed | 80 |
| abstract_inverted_index.determining | 29 |
| abstract_inverted_index.interaction | 91, 101 |
| abstract_inverted_index.structures, | 85 |
| abstract_inverted_index.FMO-MP2/6-31 | 107 |
| abstract_inverted_index.calculations | 22, 124 |
| abstract_inverted_index.approximately | 150 |
| abstract_inverted_index.decomposition | 103 |
| abstract_inverted_index.non-empirical | 25 |
| abstract_inverted_index.inter-fragment | 90 |
| abstract_inverted_index.representative | 61 |
| abstract_inverted_index.physicochemical | 57, 167 |
| abstract_inverted_index.biomacromolecule | 5 |
| abstract_inverted_index.three-dimensional | 12 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5063060714 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I98285908 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8500000238418579 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.48138481 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |