HT-SuMD : making molecular dynamics simulations suitable for fragment-based screening. A comparative study with NMR
Fragment-based lead discovery (FBLD) is one of the most efficient methods to develop new drugs. We present here a new computational protocol called High-Throughput Supervised Molecular Dynamics (HT-SuMD), which makes it possible to automatically screen up to thousands of fragments, representing therefore a new valuable resource to prioritise fragments in FBLD campaigns. The protocol was applied to Bcl-XL, an oncological protein target involved in the regulation of apoptosis through protein-protein interactions. Initially, HT-SuMD performances were validated against a robust NMR-based screening, using the same set of 100 fragments. These independent results showed a remarkable agreement between the two methods. Then, a virtual screening on a larger library of additional 300 fragments was carried out and the best hits were validated by NMR. Remarkably, all the in silico selected fragments were confirmed as Bcl-XL binders. This represents, to date, the largest computational fragments screening entirely based on MD.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:36 |
|---|---|
| Enthalten in: |
Journal of enzyme inhibition and medicinal chemistry - 36(2021), 1 vom: 15. Dez., Seite 1-14 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Ferrari, Francesca [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Bcl-X Protein |
|---|
| Anmerkungen: |
Date Completed 17.05.2021 Date Revised 12.11.2023 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.1080/14756366.2020.1838499 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM316838861 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM316838861 | ||
| 003 | DE-627 | ||
| 005 | 20231225161940.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1080/14756366.2020.1838499 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1056.xml |
| 035 | |a (DE-627)NLM316838861 | ||
| 035 | |a (NLM)33115279 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Ferrari, Francesca |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a HT-SuMD |b making molecular dynamics simulations suitable for fragment-based screening. A comparative study with NMR |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 17.05.2021 | ||
| 500 | |a Date Revised 12.11.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Fragment-based lead discovery (FBLD) is one of the most efficient methods to develop new drugs. We present here a new computational protocol called High-Throughput Supervised Molecular Dynamics (HT-SuMD), which makes it possible to automatically screen up to thousands of fragments, representing therefore a new valuable resource to prioritise fragments in FBLD campaigns. The protocol was applied to Bcl-XL, an oncological protein target involved in the regulation of apoptosis through protein-protein interactions. Initially, HT-SuMD performances were validated against a robust NMR-based screening, using the same set of 100 fragments. These independent results showed a remarkable agreement between the two methods. Then, a virtual screening on a larger library of additional 300 fragments was carried out and the best hits were validated by NMR. Remarkably, all the in silico selected fragments were confirmed as Bcl-XL binders. This represents, to date, the largest computational fragments screening entirely based on MD | ||
| 650 | 4 | |a Comparative Study | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Bcl-XL | |
| 650 | 4 | |a FBLD | |
| 650 | 4 | |a MD | |
| 650 | 4 | |a NMR | |
| 650 | 4 | |a SuMD | |
| 650 | 7 | |a Small Molecule Libraries |2 NLM | |
| 650 | 7 | |a bcl-X Protein |2 NLM | |
| 700 | 1 | |a Bissaro, Maicol |e verfasserin |4 aut | |
| 700 | 1 | |a Fabbian, Simone |e verfasserin |4 aut | |
| 700 | 1 | |a De Almeida Roger, Jessica |e verfasserin |4 aut | |
| 700 | 1 | |a Mammi, Stefano |e verfasserin |4 aut | |
| 700 | 1 | |a Moro, Stefano |e verfasserin |4 aut | |
| 700 | 1 | |a Bellanda, Massimo |e verfasserin |4 aut | |
| 700 | 1 | |a Sturlese, Mattia |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of enzyme inhibition and medicinal chemistry |d 2002 |g 36(2021), 1 vom: 15. Dez., Seite 1-14 |w (DE-627)NLM121560376 |x 1475-6374 |7 nnns |
| 773 | 1 | 8 | |g volume:36 |g year:2021 |g number:1 |g day:15 |g month:12 |g pages:1-14 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1080/14756366.2020.1838499 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 36 |j 2021 |e 1 |b 15 |c 12 |h 1-14 | ||