{"doi":"10.1101/2024.07.21.604487","title":"Mutational landscape and molecular bases of echinocandin resistance in\n                  <i>Saccharomyces cerevisiae</i>","abstract":"One of the front-line drug classes used to treat invasive fungal infections is echinocandins, which target the fungal-specific beta-glucan synthase (Fks). Treatment failure due to resistance often coincides with mutations in three protein regions defined as hotspots. The biophysical bases by which such mutations confer resistance and cross-resistance among echinocandins are largely unknown. Here, we combine molecular docking and molecular dynamics simulations to construct and refine a model of echinocandin binding to Fks1. This structural framework is integrated with deep-mutational scanning to comprehensively assess the impact of mutations across the three hotspots in the model yeast Saccharomyces cerevisiae . We detail the positioning and binding constraints of the three most widely used echinocandins; anidulafungin, caspofungin and micafungin and elucidate several key molecular bases of resistance. Our findings will enable DNA sequence-based predictions of resistance to this important drug family and the improvement of future molecules that could overcome current resistance mutations. <h4>One sentence summary</h4> Disruption of specific interactions between echinocandins and key residues from their target lead to drug-specific resistance.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2024,"id":74,"datarank":0.6054354653460878,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.22069306172685732,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.22069306172685732,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":7,"citers_with_citation_signal":6,"citers_with_endowment":6,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0473,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-07-21","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":514,"name":"Alexandre G. Torbey","orcid":"0009-0002-3645-0276","position":1,"is_corresponding":false},{"id":515,"name":"Mathieu Giguere","orcid":"0009-0003-0089-5051","position":2,"is_corresponding":false},{"id":516,"name":"Alicia Pageau","orcid":"0009-0004-9934-6390","position":3,"is_corresponding":false},{"id":517,"name":"Alexandre K. Dubé","orcid":"0000-0001-8718-9894","position":4,"is_corresponding":false},{"id":518,"name":"Patrick Lagüe","orcid":"0000-0002-5236-4979","position":5,"is_corresponding":false},{"id":519,"name":"Christian R. Landry","orcid":"0000-0003-3028-6866","position":6,"is_corresponding":false},{"id":520,"name":"Mathieu Giguère","orcid":null,"position":7,"is_corresponding":false},{"id":513,"name":"Romain Durand","orcid":"0000-0002-7681-4727","position":0,"is_corresponding":true}],"reference_count":79,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","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":[]}