{"id":"https://openalex.org/W7163178562","doi":"https://doi.org/10.48550/arxiv.2606.01781","title":"Structure-Guided Adaptive Propagation for Protein-Protein Interaction Site Prediction","display_name":"Structure-Guided Adaptive Propagation for Protein-Protein Interaction Site Prediction","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163178562","doi":"https://doi.org/10.48550/arxiv.2606.01781"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.01781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.01781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004232829","display_name":"Enqiang Zhu","orcid":"https://orcid.org/0000-0002-5245-7905"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Enqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137692373","display_name":"Yizi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yizi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124186822","display_name":"Yilong Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Yilong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137668032","display_name":"Yao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137634706","display_name":"Yu Zhang","orcid":"https://orcid.org/0009-0009-3960-5852"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137658043","display_name":"Baoshan Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Baoshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.4009000062942505,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.4009000062942505,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.3400999903678894,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.06840000301599503,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5351999998092651},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.47290000319480896},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46889999508857727},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39309999346733093},{"id":"https://openalex.org/keywords/equivariant-map","display_name":"Equivariant map","score":0.3677999973297119},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.34360000491142273},{"id":"https://openalex.org/keywords/geometric-networks","display_name":"Geometric networks","score":0.3346000015735626},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.334199994802475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5751000046730042},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5351999998092651},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.47290000319480896},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4287000000476837},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42739999294281006},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C171036898","wikidata":"https://www.wikidata.org/wiki/Q256355","display_name":"Equivariant map","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C49777392","wikidata":"https://www.wikidata.org/wiki/Q5535495","display_name":"Geometric networks","level":3,"score":0.3346000015735626},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C202311505","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28119999170303345},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C90806461","wikidata":"https://www.wikidata.org/wiki/Q1144416","display_name":"Propagation delay","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.01781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.01781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4754078686237335}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,25],"of":[2,52],"protein-protein":[3],"interaction":[4,75],"sites":[5,76],"(PPIS)":[6],"is":[7],"essential":[8],"for":[9,90],"understanding":[10],"cellular":[11],"processes,":[12],"disease":[13],"mechanisms,":[14],"and":[15,49,127,159],"therapeutic":[16],"target":[17],"discovery.":[18],"Graph-based":[19],"deep":[20],"learning":[21],"has":[22],"advanced":[23],"PPIS":[24,91],"by":[26],"incorporating":[27],"residue-level":[28],"structural":[29,48],"context.":[30],"However,":[31],"most":[32],"graph-based":[33],"models":[34],"still":[35],"rely":[36],"on":[37,147],"fixed":[38,97],"propagation":[39,56,88,98,114],"schemes":[40],"that":[41,138,152],"treat":[42],"all":[43],"residues":[44],"similarly,":[45],"despite":[46],"the":[47,59,144],"functional":[50],"heterogeneity":[51],"protein":[53],"interfaces.":[54],"Such":[55],"may":[57],"limit":[58],"ability":[60],"to":[61,65,72,111,121,131],"adapt":[62],"information":[63],"diffusion":[64,129],"local":[66,124],"geometric":[67,103,133,157],"environments,":[68],"making":[69],"it":[70],"difficult":[71],"distinguish":[73],"true":[74],"from":[77,105],"structurally":[78],"similar":[79],"non-interacting":[80],"neighbors.":[81],"We":[82],"present":[83],"SGAP-PPIS,":[84],"a":[85,96],"structure-guided":[86],"adaptive":[87,154],"model":[89],"prediction.":[92],"Rather":[93],"than":[94],"using":[95],"mechanism,":[99],"SGAP-PPIS":[100,139],"leverages":[101],"multi-scale":[102],"states":[104],"an":[106],"equivariant":[107],"graph":[108],"neural":[109],"network":[110],"generate":[112],"residue-wise":[113],"coefficients.":[115],"This":[116],"design":[117],"allows":[118],"each":[119],"residue":[120],"adaptively":[122],"balance":[123],"feature":[125],"preservation":[126],"neighborhood":[128],"according":[130],"its":[132],"microenvironment.":[134],"Experimental":[135],"results":[136],"show":[137,151],"achieves":[140],"competitive":[141],"performance":[142],"among":[143],"state-of-the-art":[145],"methods":[146],"Test\\_60.":[148],"Ablation":[149],"studies":[150],"geometry-conditioned":[153],"propagation,":[155],"scale-aligned":[156],"guidance,":[158],"multi-step":[160],"propagation-state":[161],"representation":[162],"jointly":[163],"drive":[164],"these":[165],"improvements.":[166]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-03T00:00:00"}
