{"doi":"10.26434/chemrxiv.9897710","title":"Comparison of Umbrella Sampling and Steered Molecular Dynamics Methods for Computing Free Energy Profiles of Aromatic Substrates through Phospholipid Bilayers","abstract":"<jats:p>Understanding the permeation of molecules through lipid membranes is fundamental for predicting the cellular uptake of solutes and drug delivery mechanisms. In molecular simulations the usual approach is to\n compute the free energy (FE) profile of a molecule across a model lipid bilayer, which can then be used to\n estimate the permeability of the molecule. Umbrella sampling (US), which involves carrying out a series of\n biased simulations along a defined reaction coordinate (usually the bilayer normal direction), is a popular\n method for the computation of such FE profiles. However, US can be challenging to implement because\n the results are dependent on the strength of the biasing potential and the spacing of windows along the\n reaction coordinate, which, in practice, are usually optimized by an inefficient trial and error approach. The\n Steered Molecular Dynamics implementation of the Jarzynski Equality (JE-SMD) has been identified as an\n alternative to equilibrium sampling methods for measuring the FE change across a reaction coordinate. In\n the JE-SMD approach, equilibrium FE values are evaluated from the average of rapid non-equilibrium trajectories, thus avoiding the practical issues that come with US. Here, we use three different corrections of the\n JE-SMD method to calculate the FE change for the translocation of two aromatic substrates, phenylalanine\n and toluene, across a lipid bilayer, and compare the accuracy and computational efficiency of these approaches\n to the results obtained using US. We show evidence that when computing the free energy profile, the JE-SMD\n approach suffers from insufficient sampling convergence of the bilayer environment, and is dependent on the\n characteristic of the aromatic substrate itself. We deduce that, despite its drawbacks, US remains the more\n viable approach of the two for computing the FE profile.</jats:p>","journal":null,"year":null,"id":668063,"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":0,"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":[],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Comparison of Umbrella Sampling and Steered Molecular Dynamics Methods for Computing Free Energy Profiles of Aromatic Substrates through Phospholipid Bilayers","abstract":"<jats:p>Understanding the permeation of molecules through lipid membranes is fundamental for predicting the cellular uptake of solutes and drug delivery mechanisms. In molecular simulations the usual approach is to\n compute the free energy (FE) profile of a molecule across a model lipid bilayer, which can then be used to\n estimate the permeability of the molecule. Umbrella sampling (US), which involves carrying out a series of\n biased simulations along a defined reaction coordinate (usually the bilayer normal direction), is a popular\n method for the computation of such FE profiles. However, US can be challenging to implement because\n the results are dependent on the strength of the biasing potential and the spacing of windows along the\n reaction coordinate, which, in practice, are usually optimized by an inefficient trial and error approach. The\n Steered Molecular Dynamics implementation of the Jarzynski Equality (JE-SMD) has been identified as an\n alternative to equilibrium sampling methods for measuring the FE change across a reaction coordinate. In\n the JE-SMD approach, equilibrium FE values are evaluated from the average of rapid non-equilibrium trajectories, thus avoiding the practical issues that come with US. Here, we use three different corrections of the\n JE-SMD method to calculate the FE change for the translocation of two aromatic substrates, phenylalanine\n and toluene, across a lipid bilayer, and compare the accuracy and computational efficiency of these approaches\n to the results obtained using US. We show evidence that when computing the free energy profile, the JE-SMD\n approach suffers from insufficient sampling convergence of the bilayer environment, and is dependent on the\n characteristic of the aromatic substrate itself. We deduce that, despite its drawbacks, US remains the more\n viable approach of the two for computing the FE profile.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19965766","pmcid":null,"openalex_id":"https://openalex.org/W4235218864","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"cc-by-nc-nd","oa_locations":[{"url":"https://doi.org/10.26434/chemrxiv.9897710","host_type":"repository"},{"url":"https://doi.org/10.26434/chemrxiv.9897710","host_type":"repository"},{"url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.9897710.v3","host_type":"publisher"}],"fields_of_study":["Lipid Membrane Structure and Behavior","DNA and Nucleic Acid Chemistry","RNA Interference and Gene Delivery"],"mesh_terms":[],"keywords":["Umbrella sampling","Reaction coordinate","Molecular dynamics","Lipid bilayer","Bilayer","Potential of mean force","Chemistry","Computation","Biological system","Sampling (signal processing)","Computational chemistry","Chemical physics","Membrane","Computer science","Statistical physics","Algorithm","Physics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Affordable and clean energy"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-13T19:58:50.551694Z","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":[]}