[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-model-predicts-protein-pairs-it-has-never-seen-before":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},3488,"ai-model-predicts-protein-pairs-it-has-never-seen-before","AI Model Predicts Protein Pairs It Has Never Seen Before","A new multimodal framework called MKGR tackles cold-start protein interaction prediction by fusing sequence data with four biomedical knowledge graphs.","A research team has built a system that predicts how proteins interact even when those proteins were absent from training data entirely.\n\nThe model, called MKGR, combines two types of information: region-aware encoding of protein sequences and four separate biomedical knowledge graphs linking proteins to drugs, diseases, miRNA, and lncRNA. Graph attention encoders pull modality-specific embeddings from sparse associations, while a gating module at the pair level decides how much weight to give sequence evidence versus graph evidence for each candidate pair. A bridge reconstruction objective keeps the graph learning grounded by forcing the model to recover shared protein-entity associations. Tests on two benchmark datasets — covering both novel-old and novel-novel cold-start scenarios — showed MKGR outperforming sequence, network, and knowledge-graph baselines across five standard metrics.\n\nThe cold-start problem is a genuine bottleneck in drug discovery. Most protein interaction models lean heavily on network topology, which means they fail the moment a newly characterized protein shows up with no known connections. A model that handles those unknowns better could shorten the gap between identifying a disease mechanism and finding a molecule that disrupts it.\n\nProtein interaction prediction has attracted a wave of deep learning approaches over the past few years, but most gains have come from proteins that are already well-documented. MKGR's value, if it holds up beyond these benchmarks, is in the long tail — the understudied proteins where the biology is murkiest and the clinical stakes are often highest.","[\"ai\",\"biology\",\"drug-discovery\",\"research\"]","2026-07-03T04:00:00.000Z","2026-07-03T07:06:26.398Z","2026-07-03T07:06:29.375Z","published",null,[],"ai",[24,26,27,28],"biology","drug-discovery","research",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.01627",0,{"sections":35},[36,40,45,50,55,60,65,70,75,80,85,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":86,"slug":87,"count":83,"latest_published_at":88},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]