{"doi":"10.1021/acs.jcim.2c01516","title":"Predictive Models for Human Cytochrome P450 3A7 Selective Inhibitors and Substrates","abstract":"Inappropriate use of prescription drugs is potentially more harmful in fetuses/neonates than in adults. Cytochrome P450 (CYP) 3A subfamily undergoes developmental changes in expression, such as a transition from CYP3A7 to CYP3A4 shortly after birth, which provides a potential way to distinguish medication effects on fetuses/neonates and adults. The purpose of this study was to build first-in-class predictive models for both inhibitors and substrates of CYP3A7/CYP3A4 using chemical structure analysis. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The performance varied for each CYP3A7/CYP3A4 inhibitor/substrate model depending on the data set type, model type, rebalancing method, and specific feature set. For the active inhibitor/substrate data set, the optimal models achieved AUC-ROC values ranging from 0.77 ± 0.01 to 0.84 ± 0.01. For the selective inhibitor/substrate data set, the optimal models achieved AUC-ROC values ranging from 0.72 ± 0.02 to 0.79 ± 0.04. The predictive power of the optimal models was validated by compounds with known potencies as CYP3A7/CYP3A4 inhibitors or substrates. In addition, we identified structural features significant for CYP3A7/CYP3A4 selective or common inhibitors and substrates. In summary, the top performing models can be further applied as a tool to rapidly evaluate the safety and efficacy of new drugs separately for fetuses/neonates and adults. The significant structural features could guide the design of new therapeutic drugs as well as aid in the optimization of existing medicine for fetuses/neonates.","journal":"Journal of Chemical Information and Modeling","year":2023,"id":357284,"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":13,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9593,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":288995,"name":"Md Kabir","orcid":"0000-0003-1792-2549","position":1,"is_corresponding":false},{"id":460790,"name":"Srilatha Sakamuru","orcid":"0000-0002-9693-1832","position":2,"is_corresponding":false},{"id":288993,"name":"Pranav Shah","orcid":"0000-0003-0076-7159","position":3,"is_corresponding":false},{"id":288996,"name":"Elias Carvalho Padilha","orcid":"0000-0002-3794-9389","position":4,"is_corresponding":false},{"id":468537,"name":"Deborah K. Ngan","orcid":null,"position":5,"is_corresponding":false},{"id":355263,"name":"Menghang Xia","orcid":"0000-0001-7285-8469","position":6,"is_corresponding":false},{"id":239790,"name":"Xin Xu","orcid":"0000-0003-1163-9304","position":7,"is_corresponding":false},{"id":228423,"name":"Anton Simeonov","orcid":"0000-0002-4523-9977","position":8,"is_corresponding":false},{"id":233832,"name":"Ruili Huang","orcid":"0000-0001-8886-8311","position":9,"is_corresponding":false},{"id":467469,"name":"Tuan Xu","orcid":"0000-0001-6430-3500","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T01:13:34.795336Z","pmid":"36719788","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":[]}