{"doi":"10.1101/2022.01.18.476733","title":"Resistor: an algorithm for predicting resistance mutations using Pareto optimization over multistate protein design and mutational signatures","abstract":"Abstract Resistance to pharmacological treatments is a major public health challenge. Here we report R esistor —a novel structure- and sequence-based algorithm for drug design providing prospective prediction of resistance mutations. R esistor computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity (Δ K a ) of the (1) drug and (2) endogenous ligand upon a protein’s mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. To validate R esistor , we applied it to kinase inhibitors targeting EGFR and BRAF in lung adenocarcinoma and melanoma. R esistor correctly identified eight clinically significant EGFR resistance mutations, including the “gatekeeper” T790M mutation to erlotinib and gefitinib and five known resistance mutations to osimertinib. Furthermore, R esistor predictions are consistent with sensitivity data on BRAF inhibitors from both retrospective and prospective experiments using the KinCon biosensor technology. R esistor is available in the open-source protein design software OSPREY.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":302497,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9455,"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":634362,"name":"Andreas Feichtner","orcid":"0000-0002-9376-6229","position":1,"is_corresponding":false},{"id":634366,"name":"Eduard Stefan","orcid":"0000-0003-3650-4713","position":2,"is_corresponding":false},{"id":943073,"name":"Teresa Kaserer","orcid":"0000-0003-0372-1885","position":3,"is_corresponding":false},{"id":413197,"name":"Bruce R. Donald","orcid":"0000-0001-6884-4398","position":4,"is_corresponding":false},{"id":943072,"name":"Nathan Guerin","orcid":"0000-0001-8378-7854","position":0,"is_corresponding":true}],"reference_count":82,"raw_metadata":null,"created_at":"2026-07-19T00:32:16.279991Z","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":[]}