{"doi":"10.1016/j.crmeth.2021.100014","title":"Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations","abstract":"Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with the cutting-edge I-TASSER fragment assembly simulations. Large-scale benchmark tests showed that C-I-TASSER can fold more than twice the number of non-homologous proteins than the I-TASSER, which does not use contacts. When applied to a folding experiment on 8,266 unsolved Pfam families, C-I-TASSER successfully folded 4,162 domain families, including 504 folds that are not found in the PDB. Furthermore, it created correct folds for 85% of proteins in the SARS-CoV-2 genome, despite the quick mutation rate of the virus and sparse sequence profiles. The results demonstrated the critical importance of coupling whole-genome and metagenome-based evolutionary information with optimal structure assembly simulations for solving the problem of non-homologous protein structure prediction.","journal":"Cell Reports Methods","year":2021,"id":145232,"datarank":0.9580318979043969,"base_score":6.386879319362645,"endowment":6.386879319362645,"self_citation_contribution":0.9580318979043969,"citation_network_contribution":0.0,"self_endowment_contribution":0.9580318979043969,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":593,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9503,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":121996,"name":"Chengxin Zhang","orcid":"0000-0001-7290-1324","position":1,"is_corresponding":false},{"id":295014,"name":"Yang Li","orcid":"0000-0002-0736-251X","position":2,"is_corresponding":false},{"id":114797,"name":"Robin Pearce","orcid":"0000-0001-6402-734X","position":3,"is_corresponding":false},{"id":615527,"name":"Eric W. Bell","orcid":"0000-0002-3419-4398","position":4,"is_corresponding":false},{"id":287631,"name":"Yang Zhang","orcid":"0000-0002-2739-1916","position":5,"is_corresponding":false},{"id":529892,"name":"Wei Zheng","orcid":"0000-0002-2984-9003","position":0,"is_corresponding":true}],"reference_count":90,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:41:52.374756Z","pmid":"34355210","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":[]}