A membrane permeability database for nonpeptidic macrocycles
Abstract The process of developing new drugs is arduous and costly, particularly for targets classified as “difficult-to-drug.” Macrocycles show a particular ability to modulate difficult-to-drug targets, including protein-protein interactions, while still allowing oral administration. However, the...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04302-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841559877667782656 |
|---|---|
| author | Qiushi Feng Danjo De Chavez Jan Kihlberg Vasanthanathan Poongavanam |
| author_facet | Qiushi Feng Danjo De Chavez Jan Kihlberg Vasanthanathan Poongavanam |
| author_sort | Qiushi Feng |
| collection | DOAJ |
| description | Abstract The process of developing new drugs is arduous and costly, particularly for targets classified as “difficult-to-drug.” Macrocycles show a particular ability to modulate difficult-to-drug targets, including protein-protein interactions, while still allowing oral administration. However, the determination of membrane permeability, critical for reaching intracellular targets and for oral bioavailability, is laborious and expensive. In silico methods are a cost-effective alternative, enabling predictions prior to compound synthesis. Here, we present a comprehensive online database ( https://swemacrocycledb.com/ ), housing 5638 membrane permeability datapoints for 4216 nonpeptidic macrocycles, curated from the literature, patents, and bioactivity repositories. In addition, we present a new descriptor, the “amide ratio” (AR), that quantifies the peptidic nature of macrocyclic compounds, enabling the classification of peptidic, semipeptidic, and nonpeptidic macrocycles. Overall, this resource fills a gap among existing databases, offering valuable insights into the membrane permeability of nonpeptidic and semipeptidic macrocycles, and facilitating predictions for drug discovery projects. |
| format | Article |
| id | doaj-art-4b418909e59e4672912649267d6ab22c |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-4b418909e59e4672912649267d6ab22c2025-01-05T12:08:22ZengNature PortfolioScientific Data2052-44632025-01-0112111110.1038/s41597-024-04302-zA membrane permeability database for nonpeptidic macrocyclesQiushi Feng0Danjo De Chavez1Jan Kihlberg2Vasanthanathan Poongavanam3Department of Chemistry-BMC, Uppsala UniversityDepartment of Chemistry-BMC, Uppsala UniversityDepartment of Chemistry-BMC, Uppsala UniversityDepartment of Chemistry-BMC, Uppsala UniversityAbstract The process of developing new drugs is arduous and costly, particularly for targets classified as “difficult-to-drug.” Macrocycles show a particular ability to modulate difficult-to-drug targets, including protein-protein interactions, while still allowing oral administration. However, the determination of membrane permeability, critical for reaching intracellular targets and for oral bioavailability, is laborious and expensive. In silico methods are a cost-effective alternative, enabling predictions prior to compound synthesis. Here, we present a comprehensive online database ( https://swemacrocycledb.com/ ), housing 5638 membrane permeability datapoints for 4216 nonpeptidic macrocycles, curated from the literature, patents, and bioactivity repositories. In addition, we present a new descriptor, the “amide ratio” (AR), that quantifies the peptidic nature of macrocyclic compounds, enabling the classification of peptidic, semipeptidic, and nonpeptidic macrocycles. Overall, this resource fills a gap among existing databases, offering valuable insights into the membrane permeability of nonpeptidic and semipeptidic macrocycles, and facilitating predictions for drug discovery projects.https://doi.org/10.1038/s41597-024-04302-z |
| spellingShingle | Qiushi Feng Danjo De Chavez Jan Kihlberg Vasanthanathan Poongavanam A membrane permeability database for nonpeptidic macrocycles Scientific Data |
| title | A membrane permeability database for nonpeptidic macrocycles |
| title_full | A membrane permeability database for nonpeptidic macrocycles |
| title_fullStr | A membrane permeability database for nonpeptidic macrocycles |
| title_full_unstemmed | A membrane permeability database for nonpeptidic macrocycles |
| title_short | A membrane permeability database for nonpeptidic macrocycles |
| title_sort | membrane permeability database for nonpeptidic macrocycles |
| url | https://doi.org/10.1038/s41597-024-04302-z |
| work_keys_str_mv | AT qiushifeng amembranepermeabilitydatabasefornonpeptidicmacrocycles AT danjodechavez amembranepermeabilitydatabasefornonpeptidicmacrocycles AT jankihlberg amembranepermeabilitydatabasefornonpeptidicmacrocycles AT vasanthanathanpoongavanam amembranepermeabilitydatabasefornonpeptidicmacrocycles AT qiushifeng membranepermeabilitydatabasefornonpeptidicmacrocycles AT danjodechavez membranepermeabilitydatabasefornonpeptidicmacrocycles AT jankihlberg membranepermeabilitydatabasefornonpeptidicmacrocycles AT vasanthanathanpoongavanam membranepermeabilitydatabasefornonpeptidicmacrocycles |