{"doi":"10.1021/acs.jctc.4c00905","title":"Enhancing the Assembly Properties of Bottom-Up Coarse-Grained Phospholipids","abstract":"A plethora of key biological events occur at the cellular membrane where the large spatiotemporal scales necessitate dimensionality reduction or coarse-graining approaches over conventional all-atom molecular dynamics simulation. Constructing coarse-grained descriptions of membranes systematically from statistical mechanical principles has largely remained challenging due to the necessity of capturing amphipathic self-assembling behavior in coarse-grained models. We show that bottom-up coarse-grained lipid models can possess metastable morphological behavior and that this potential metastability has ramifications for accurate development and training. We in turn develop a training algorithm which evades metastability issues by linking model training to self-assembling behavior, and demonstrate its robustness via construction of solvent-free coarse-grained models of various phospholipid membranes, including lipid species such as phosphatidylcholines, phosphatidylserines, sphingolipids, and cholesterol. The resulting coarse-grained lipid models are orders of magnitude faster than their atomistic counterparts while retaining structural fidelity and constitute a promising direction for the development of coarse-grained models of realistic cell membranes.","journal":"Journal of Chemical Theory and Computation","year":2024,"id":434481,"datarank":0.45805400520426254,"base_score":2.70805020110221,"endowment":2.70805020110221,"self_citation_contribution":0.40620753016533157,"citation_network_contribution":0.05184647503893098,"self_endowment_contribution":0.40620753016533157,"citer_contribution":0.05184647503893098,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":4,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9465,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":246697,"name":"Gregory A. Voth","orcid":"0000-0002-3267-6748","position":1,"is_corresponding":false},{"id":1055420,"name":"Patrick G. Sahrmann","orcid":"0000-0002-4781-9561","position":0,"is_corresponding":true}],"reference_count":89,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:59:53.957667Z","pmid":"39535391","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":[]}