{"dcterms:modified":"2023-07-19","dcterms:creator":"DR-NTU (Data)","@type":"ore:ResourceMap","@id":"https://researchdata.ntu.edu.sg/api/datasets/export?exporter=OAI_ORE&persistentId=doi:10.21979/N9/16CFBW","ore:describes":{"title":"Replication Data for: Hypergraph based persistent cohomology (HPC) for molecular representations in drug design","dateOfDeposit":"2021-04-02","subject":["Computer and Information Science","Mathematical Sciences","Medicine, Health and Life Sciences"],"kindOfData":"Code","relatedDatasets":"The PDBbind databases were obtained from <a href=\"http://pdbbind.org.cn\"> http://pdbbind.org.cn</a>.The codes implemented for the hypergraph persistent cohomology and HPC-GBT models can be found in <a href=\"http://github.com/LiuXiangMath/Hypergraph-based-Persistent-Cohomology\"> http://github.com/LiuXiangMath/Hypergraph-based-Persistent-Cohomology</a>.","citation:depositor":"Xia, Kelin","publication":{"publicationCitation":"Liu, X., Wang, X., Wu, J., & Xia, K. (2021). Hypergraph-based persistent cohomology (HPC) for molecular representations in drug design. Briefings in Bioinformatics.","publicationIDType":"doi","publicationIDNumber":"10.1093/bib/bbaa411","publicationURL":"https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbaa411/6105940"},"citation:keyword":{"citation:keywordValue":"molecular descriptor, machine learning, hypergraph-based persistent cohomology, drug design"},"citation:datasetContact":{"citation:datasetContactName":"Xia, Kelin","citation:datasetContactAffiliation":"Nanyang Technological University"},"citation:dsDescription":{"citation:dsDescriptionValue":"Artificial intelligence (AI) based drug design has demonstrated great potential to fundamentally change the pharmaceutical industries. Currently, a key issue in AI-based drug design is efficient transferable molecular descriptors or fingerprints. Here, we present hypergraph-based molecular topological representation, hypergraph-based (weighted) persistent cohomology (HPC/HWPC) and HPC/HWPC-based molecular fingerprints for machine learning models in drug design. Molecular structures and their atomic interactions are highly complicated and pose great challenges for efficient mathematical representations. We develop the first hypergraph-based topological framework to characterize detailed molecular structures and interactions at atomic level. Inspired by the elegant path complex model, hypergraph-based embedded homology and persistent homology have been proposed recently. Based on them, we construct HPC/HWPC, and use them to generate molecular descriptors for learning models in protein–ligand binding affinity prediction, one of the key step in drug design. Our models are tested on three most commonly-used databases, including PDBbind-v2007, PDBbind-v2013 and PDBbind-v2016, and outperform all existing machine learning models with traditional molecular descriptors. Our HPC/HWPC models have demonstrated great potential in AI-based drug design.","citation:dsDescriptionDate":"2021-4-2"},"author":{"citation:authorName":"Xia, Kelin","citation:authorAffiliation":"Nanyang Technological University","authorIdentifierScheme":"ORCID","authorIdentifier":"0000-0003-4183-0943"},"software":{"citation:softwareName":"Python"},"grantNumber":[{"citation:grantNumberAgency":"Nanyang Technological University","citation:grantNumberValue":"Startup Grant M4081842"},{"citation:grantNumberAgency":"Ministry of Education (MOE)","citation:grantNumberValue":"Academic Research fund Tier 1 RG31/18"},{"citation:grantNumberAgency":"Ministry of Education (MOE)","citation:grantNumberValue":"RG109/19"},{"citation:grantNumberAgency":"Ministry of Education (MOE)","citation:grantNumberValue":"Tier 2 MOE2018-T2-1-033"},{"citation:grantNumberAgency":"Natural Science Foundation of China (NSFC)","citation:grantNumberValue":"11871284"},{"citation:grantNumberAgency":"Natural Science Foundation of China (NSFC)","citation:grantNumberValue":"11971144"}],"@id":"doi:10.21979/N9/16CFBW","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"2.0","schema:name":"Replication Data for: Hypergraph based persistent cohomology (HPC) for molecular representations in drug design","schema:dateModified":"Tue Jul 12 16:42:13 SGT 2022","schema:datePublished":"2021-04-02","schema:license":"http://creativecommons.org/licenses/by-nc/4.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":false},"schema:includedInDataCatalog":"DR-NTU (Data)","ore:aggregates":[{"schema:name":"Hypergraph-based-Persistent-Cohomology-master.zip","dvcore:restricted":false,"schema:version":1,"dvcore:datasetVersionId":3226,"@id":"https://researchdata.ntu.edu.sg/file.xhtml?fileId=62341","schema:sameAs":"https://researchdata.ntu.edu.sg/api/access/datafile/62341","@type":"ore:AggregatedResource","schema:fileFormat":"application/zip","dvcore:filesize":194276146,"dvcore:storageIdentifier":"file://178a4cd9037-bb4dd08f1a50","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"38015fd58aee816e3cc070e48f1fe80d"}}],"schema:hasPart":["https://researchdata.ntu.edu.sg/file.xhtml?fileId=62341"]},"@context":{"author":"http://purl.org/dc/terms/creator","authorIdentifier":"http://purl.org/spar/datacite/AgentIdentifier","authorIdentifierScheme":"http://purl.org/spar/datacite/AgentIdentifierScheme","citation":"https://dataverse.org/schema/citation/","dateOfDeposit":"http://purl.org/dc/terms/dateSubmitted","dcterms":"http://purl.org/dc/terms/","dvcore":"https://dataverse.org/schema/core#","grantNumber":"https://schema.org/sponsor","kindOfData":"http://rdf-vocabulary.ddialliance.org/discovery#kindOfData","ore":"http://www.openarchives.org/ore/terms/","publication":"http://purl.org/dc/terms/isReferencedBy","publicationCitation":"http://purl.org/dc/terms/bibliographicCitation","publicationIDNumber":"http://purl.org/spar/datacite/ResourceIdentifier","publicationIDType":"http://purl.org/spar/datacite/ResourceIdentifierScheme","publicationURL":"https://schema.org/distribution","relatedDatasets":"http://purl.org/dc/terms/relation","schema":"http://schema.org/","software":"https://www.w3.org/TR/prov-o/#wasGeneratedBy","subject":"http://purl.org/dc/terms/subject","title":"http://purl.org/dc/terms/title"}}