Computational design of PD-L1 small molecule inhibitors for cancer therapy
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG..
Drug repurposing opens new avenues in cancer therapy. Drug repurposing, or finding new uses for existing drugs, can substantially reduce drug discovery time and costs. Cheminformatics, genetics, and systems biology advances enable repositioning drugs. Clinical usage of PD-1/PD-L1 blocking has been approved because of its efficacy in improving prognosis in select groups. The PD-1/PD-L1 axis was considered to represent a mechanism for tumour evasion of host tumour antigen-specific T-cell immunity in early preclinical research. The expression of PD-L1 in cancer cells causes T lymphocytes to become exhausted by transmitting a co-inhibitory signal. A better understanding of how PD-L1 is regulated in cancer cells could lead to new therapeutic options. In this view, the study was aimed to repurpose the existing FDA-approved drugs as a potential PD-L1 inhibitor through e-Pharmacophore modelling, molecular docking and dynamic simulation. e-Pharmacophore screening retrieved 324 FDA-approved medications with the fitness score ≥ 1. The top 10-docked FDA candidates were compared with IN-35 (Clinical trial candidate) for its interaction pattern with critical amino acid residues. Mirabegron and Indacaterol exhibited a greater affinity for PD-L1 with docking scores of - 9.213 kcal mol-1 and - 8.023 kcal mol-1, respectively. Mirabegron retain interactions at all three major hotspots in the PD-L1 dimer interface similar to IN-35. MM-GBSA analyses indicated that Mirabegron uses less energy to create a more stable complex and retains all of the inhibitor's positive interactions found in clinical trial ligand IN-35. Molecular dynamics simulation analysis of the Mirabegron complex showed a similar pattern of deviation in correlation with IN-35, and it retains the interaction with the active key amino acids throughout the simulation time. Our present study has shown Mirabegron as a powerful inhibitor of PD-L1 expression in cancer cells using a drug-repurposing screen.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:27 |
|---|---|
| Enthalten in: |
Molecular diversity - 27(2023), 4 vom: 25. Aug., Seite 1633-1644 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Chandrasekaran, Jaikanth [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Amino Acids |
|---|
| Anmerkungen: |
Date Completed 23.10.2023 Date Revised 23.10.2023 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1007/s11030-022-10516-3 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM345249208 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM345249208 | ||
| 003 | DE-627 | ||
| 005 | 20231226024631.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s11030-022-10516-3 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1150.xml |
| 035 | |a (DE-627)NLM345249208 | ||
| 035 | |a (NLM)36006501 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Chandrasekaran, Jaikanth |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Computational design of PD-L1 small molecule inhibitors for cancer therapy |
| 264 | 1 | |c 2023 | |
| 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 23.10.2023 | ||
| 500 | |a Date Revised 23.10.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG. | ||
| 520 | |a Drug repurposing opens new avenues in cancer therapy. Drug repurposing, or finding new uses for existing drugs, can substantially reduce drug discovery time and costs. Cheminformatics, genetics, and systems biology advances enable repositioning drugs. Clinical usage of PD-1/PD-L1 blocking has been approved because of its efficacy in improving prognosis in select groups. The PD-1/PD-L1 axis was considered to represent a mechanism for tumour evasion of host tumour antigen-specific T-cell immunity in early preclinical research. The expression of PD-L1 in cancer cells causes T lymphocytes to become exhausted by transmitting a co-inhibitory signal. A better understanding of how PD-L1 is regulated in cancer cells could lead to new therapeutic options. In this view, the study was aimed to repurpose the existing FDA-approved drugs as a potential PD-L1 inhibitor through e-Pharmacophore modelling, molecular docking and dynamic simulation. e-Pharmacophore screening retrieved 324 FDA-approved medications with the fitness score ≥ 1. The top 10-docked FDA candidates were compared with IN-35 (Clinical trial candidate) for its interaction pattern with critical amino acid residues. Mirabegron and Indacaterol exhibited a greater affinity for PD-L1 with docking scores of - 9.213 kcal mol-1 and - 8.023 kcal mol-1, respectively. Mirabegron retain interactions at all three major hotspots in the PD-L1 dimer interface similar to IN-35. MM-GBSA analyses indicated that Mirabegron uses less energy to create a more stable complex and retains all of the inhibitor's positive interactions found in clinical trial ligand IN-35. Molecular dynamics simulation analysis of the Mirabegron complex showed a similar pattern of deviation in correlation with IN-35, and it retains the interaction with the active key amino acids throughout the simulation time. Our present study has shown Mirabegron as a powerful inhibitor of PD-L1 expression in cancer cells using a drug-repurposing screen | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a Docking | |
| 650 | 4 | |a Dynamic simulation | |
| 650 | 4 | |a PD-1/PD-L1 | |
| 650 | 4 | |a Repurposing | |
| 650 | 4 | |a e-Pharmacophore | |
| 650 | 7 | |a mirabegron |2 NLM | |
| 650 | 7 | |a MVR3JL3B2V |2 NLM | |
| 650 | 7 | |a Immune Checkpoint Inhibitors |2 NLM | |
| 650 | 7 | |a B7-H1 Antigen |2 NLM | |
| 650 | 7 | |a Programmed Cell Death 1 Receptor |2 NLM | |
| 650 | 7 | |a Amino Acids |2 NLM | |
| 700 | 1 | |a Elumalai, Senthilkumar |e verfasserin |4 aut | |
| 700 | 1 | |a Murugesan, Vidya |e verfasserin |4 aut | |
| 700 | 1 | |a Kunjiappan, Selvaraj |e verfasserin |4 aut | |
| 700 | 1 | |a Pavadai, Parasuraman |e verfasserin |4 aut | |
| 700 | 1 | |a Theivendren, Panneerselvam |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Molecular diversity |d 1997 |g 27(2023), 4 vom: 25. Aug., Seite 1633-1644 |w (DE-627)NLM091914590 |x 1573-501X |7 nnns |
| 773 | 1 | 8 | |g volume:27 |g year:2023 |g number:4 |g day:25 |g month:08 |g pages:1633-1644 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1007/s11030-022-10516-3 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 27 |j 2023 |e 4 |b 25 |c 08 |h 1633-1644 | ||