Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared
The early characterization of drug membrane permeability is an important step in pharmaceutical developments to limit possible late failures in preclinical studies. This is particularly crucial for therapeutic peptides whose size generally prevents them from passively entering cells. However, a sequ...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | International Journal of Molecular Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1422-0067/24/5/5021 |
| _version_ | 1797615109107875840 |
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| author | Liuba Mazzanti Tâp Ha-Duong |
| author_facet | Liuba Mazzanti Tâp Ha-Duong |
| author_sort | Liuba Mazzanti |
| collection | DOAJ |
| description | The early characterization of drug membrane permeability is an important step in pharmaceutical developments to limit possible late failures in preclinical studies. This is particularly crucial for therapeutic peptides whose size generally prevents them from passively entering cells. However, a sequence-structure-dynamics-permeability relationship for peptides still needs further insight to help efficient therapeutic peptide design. In this perspective, we conducted here a computational study for estimating the permeability coefficient of a benchmark peptide by considering and comparing two different physical models: on the one hand, the inhomogeneous solubility–diffusion model, which requires umbrella–sampling simulations, and on the other hand, a chemical kinetics model which necessitates multiple unconstrained simulations. Notably, we assessed the accuracy of the two approaches in relation to their computational cost. |
| first_indexed | 2024-03-11T07:21:51Z |
| format | Article |
| id | doaj.art-b48b88f6e00849c99852eeb40bbb67c4 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T07:21:51Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-b48b88f6e00849c99852eeb40bbb67c42023-11-17T07:56:43ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-03-01245502110.3390/ijms24055021Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods ComparedLiuba Mazzanti0Tâp Ha-Duong1BioCIS, CNRS, Université Paris-Saclay, 17 Avenue des Sciences, 91400 Orsay, FranceBioCIS, CNRS, Université Paris-Saclay, 17 Avenue des Sciences, 91400 Orsay, FranceThe early characterization of drug membrane permeability is an important step in pharmaceutical developments to limit possible late failures in preclinical studies. This is particularly crucial for therapeutic peptides whose size generally prevents them from passively entering cells. However, a sequence-structure-dynamics-permeability relationship for peptides still needs further insight to help efficient therapeutic peptide design. In this perspective, we conducted here a computational study for estimating the permeability coefficient of a benchmark peptide by considering and comparing two different physical models: on the one hand, the inhomogeneous solubility–diffusion model, which requires umbrella–sampling simulations, and on the other hand, a chemical kinetics model which necessitates multiple unconstrained simulations. Notably, we assessed the accuracy of the two approaches in relation to their computational cost.https://www.mdpi.com/1422-0067/24/5/5021peptide membrane permeabilitymolecular dynamics simulationumbrella samplingMarkov State Modelfree energy profile |
| spellingShingle | Liuba Mazzanti Tâp Ha-Duong Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared International Journal of Molecular Sciences peptide membrane permeability molecular dynamics simulation umbrella sampling Markov State Model free energy profile |
| title | Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared |
| title_full | Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared |
| title_fullStr | Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared |
| title_full_unstemmed | Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared |
| title_short | Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared |
| title_sort | understanding passive membrane permeation of peptides physical models and sampling methods compared |
| topic | peptide membrane permeability molecular dynamics simulation umbrella sampling Markov State Model free energy profile |
| url | https://www.mdpi.com/1422-0067/24/5/5021 |
| work_keys_str_mv | AT liubamazzanti understandingpassivemembranepermeationofpeptidesphysicalmodelsandsamplingmethodscompared AT taphaduong understandingpassivemembranepermeationofpeptidesphysicalmodelsandsamplingmethodscompared |