{"doi":"10.3390/ijms23158732","title":"Exploring Ligand Binding Domain Dynamics in the NRs Superfamily","abstract":"<jats:p>Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response to substrate, agonist, and antagonist binding, leading to distinct transcription effects. A key feature of NRs is, indeed, their intrinsic dynamics that make them a challenging target in drug discovery. This work aims to provide a meaningful investigation of NR structural variability to outline a dynamic profile for each of them. To do that, we propose a methodology based on the computation and comparison of protein cavities among the crystallographic structures of NR LBDs. First, pockets were detected with the FLAPsite algorithm and then an “all against all” approach was applied by comparing each pair of pockets within the same sub-family on the basis of their similarity score. The analysis concerned all the detectable cavities in NRs, with particular attention paid to the active site pockets. This approach can guide the investigation of NR intrinsic dynamics, the selection of reference structures to be used in drug design and the easy identification of alternative binding sites.</jats:p>","journal":"International Journal of Molecular Sciences","year":2022,"id":595560,"datarank":0.3453877639491069,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.0,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":567535,"name":"Ida Autiero","orcid":"0000-0001-8886-8063","position":1,"is_corresponding":false},{"id":1069589,"name":"Eleonora Gianquinto","orcid":"0000-0003-0996-5936","position":2,"is_corresponding":false},{"id":1525103,"name":"Lydia Siragusa","orcid":"0000-0003-4596-7242","position":3,"is_corresponding":false},{"id":1525105,"name":"Massimo Baroni","orcid":"0000-0003-0866-148X","position":4,"is_corresponding":false},{"id":819888,"name":"Gabriele Cruciani","orcid":"0000-0002-4162-8692","position":5,"is_corresponding":false},{"id":1069601,"name":"Francesca Spyrakis","orcid":"0000-0002-4016-227X","position":6,"is_corresponding":false},{"id":849848,"name":"Giulia D’Arrigo","orcid":"0000-0003-3984-8888","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Exploring Ligand Binding Domain Dynamics in the NRs Superfamily","abstract":"<jats:p>Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response to substrate, agonist, and antagonist binding, leading to distinct transcription effects. A key feature of NRs is, indeed, their intrinsic dynamics that make them a challenging target in drug discovery. This work aims to provide a meaningful investigation of NR structural variability to outline a dynamic profile for each of them. To do that, we propose a methodology based on the computation and comparison of protein cavities among the crystallographic structures of NR LBDs. First, pockets were detected with the FLAPsite algorithm and then an “all against all” approach was applied by comparing each pair of pockets within the same sub-family on the basis of their similarity score. The analysis concerned all the detectable cavities in NRs, with particular attention paid to the active site pockets. This approach can guide the investigation of NR intrinsic dynamics, the selection of reference structures to be used in drug design and the easy identification of alternative binding sites.</jats:p>","is_dataset_classified":null,"base_score":2.302585092994046,"endowment":2.302585092994046,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"35955864","pmcid":"PMC9369052","openalex_id":"https://openalex.org/W4290600387","authors":[],"funders":[{"funder_name":"University of Turin","grant_id":"SPY_RILO_20_01","title":null},{"funder_name":"University of Turin","grant_id":"SPY_RILO_21_01","title":null}],"total_grants":2,"fwci":1.1759,"citation_percentile":0.79545523,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":3},{"year":2025,"count":3},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://www.mdpi.com/1422-0067/23/15/8732/pdf?version=1659952404","host_type":"journal"},{"url":"https://www.mdpi.com/1422-0067/23/15/8732/pdf?version=1659952404","host_type":"publisher"},{"url":"https://www.mdpi.com/1422-0067/23/15/8732/pdf","host_type":"publisher"},{"url":"https://doi.org/10.3390/ijms23158732","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/35955864","host_type":"repository"},{"url":"https://doaj.org/article/bf1f08107f1e42e292518f28c7adcf05","host_type":"repository"},{"url":"https://dx.doi.org/10.3390/ijms23158732","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9369052","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC9369052","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC9369052?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Estrogen and related hormone effects","Computational Drug Discovery Methods","Receptor Mechanisms and Signaling","Binding Sites","Ligands","Protein Domains","Receptors, Cytoplasmic and Nuclear","Transcription Factors"],"mesh_terms":["Protein Domains","Binding Sites","Ligands","Transcription Factors","Receptors, Cytoplasmic and Nuclear"],"keywords":["Computational biology","Structural similarity","Nuclear receptor","Transcription factor","SUPERFAMILY","Binding site","Binding pocket","Structural bioinformatics","Identification (biology)","Drug discovery","Molecular dynamics","Ligand (biochemistry)","Bioinformatics","Computer science","Protein structure","Chemistry","Biology","Genetics","Biochemistry","Receptor","Computational chemistry","Gene","Drug design","Agonists","Antagonists","Flexibility","Nuclear Receptors","Ligand Binding Domain"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"pdb"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T17:38:09.673926Z","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":[]}