{"doi":"10.17615/c8fk-pz15","title":"GlycoGrip: Cell Surface-Inspired Universal Sensor for Betacoronaviruses","abstract":"Inspired by the role of cell-surface glycoproteins as coreceptors for pathogens, we report the development of GlycoGrip: a glycopolymer-based lateral flow assay for detecting SARS-CoV-2 and its variants. GlycoGrip utilizes glycopolymers for primary capture and antispike antibodies labeled with gold nanoparticles for signal-generating detection. A lock-step integration between experiment and computation has enabled efficient optimization of GlycoGrip test strips which can selectively, sensitively, and rapidly detect SARS-CoV-2 and its variants in biofluids. Employing the power of the glycocalyx in a diagnostic assay has distinct advantages over conventional immunoassays as glycopolymers can bind to antigens in a multivalent capacity and are highly adaptable for mutated strains. As new variants of SARS-CoV-2 are identified, GlycoGrip will serve as a highly reconfigurable biosensor for their detection. Additionally, via extensive ensemble-based docking simulations which incorporate protein and glycan motion, we have elucidated important clues as to how heparan sulfate and other glycocalyx components may bind the spike glycoprotein during SARS-CoV-2 host-cell infection. GlycoGrip is a promising and generalizable alternative to costly, labor-intensive RT-PCR, and we envision it will be broadly useful, including for rural or low-income populations that are historically undertested and under-reported in infection statistics.","journal":"UNC Libraries","year":2022,"id":301611,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9568,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":993073,"name":"C. Simmerling","orcid":null,"position":1,"is_corresponding":false},{"id":993074,"name":"M.A. Rosenfeld","orcid":null,"position":2,"is_corresponding":false},{"id":735868,"name":"Micah Papanikolas","orcid":"0000-0003-2691-5113","position":3,"is_corresponding":false},{"id":993075,"name":"F.L. Kearns","orcid":null,"position":4,"is_corresponding":false},{"id":993076,"name":"R.E. Amaro","orcid":null,"position":5,"is_corresponding":false},{"id":353583,"name":"Ronit Freeman","orcid":"0000-0001-5960-6689","position":6,"is_corresponding":false},{"id":993077,"name":"L. Casalino","orcid":null,"position":7,"is_corresponding":false},{"id":59974,"name":"S.H. Kim","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T00:32:02.193874Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}