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A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negative breast cancer

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Abstract

Immunotherapies are promising therapeutic options for the management of triple-negative breast cancer because of its high mutation rate and genomic instability. Of note, the blockade of the immune checkpoint protein PD-1 and its ligand PD-L1 has been proven to be an efficient and potent strategy to combat triple-negative breast cancer. To date, various anti-PD-1/anti-PD-L1 antibodies have been approved. However, the intrinsic constraints of these therapeutic antibodies significantly limit their application, making small molecules a potentially significant option for PD-1/PD-L1 inhibition. In light of this, the current study aims to use a high-throughput virtual screening technique to identify potential repurposed candidates as PD-L1 inhibitors. Thus, the present study explored binding efficiency of 2509 FDA-approved compounds retrieved from the drug bank database against PD-L1 protein. The binding affinity of the compounds was determined using the glide XP docking programme. Furthermore, prime-MM/GBSA, DFT calculations, and RF score were used to precisely re-score the binding free energy of the docked complexes. In addition, the ADME and toxicity profiles for the lead compounds were also examined to address PK/PD characteristics. Altogether, the screening process identified three molecules, namely DB01238, DB06016 and DB01167 as potential therapeutics for the PD-L1 protein. To conclude, a molecular dynamic simulation of 100 ns was run to characterise the stability and inhibitory action of the three lead compounds. The results from the simulation study confirm the robust structural and thermodynamic stability of DB01238 than other investigated molecules. Thus, our findings hypothesize that DB01238 could serve as potential PD-L1 inhibitor in the near future for triple-negative breast cancer patients.

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Data availability

All data to support the conclusions have been either provided or are otherwise publicly available.

Abbreviations

PD-1:

Programmed cell death 1

PD-L1:

Programmed cell death ligand 1

BMS:

Bristol-Myers Squibb

TME:

Tumour micro environment

TIL:

Tumour infiltrating lymphocytes

TMB:

Tumour mutation burden

ADME:

Absorption, distribution, metabolism and excretion

DFT:

Density functional theory

FMO:

Frontier molecular orbitals

PF/PD:

Pharmacokinetics/pharmacodynamics

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

FEL:

Free energy landscape

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Acknowledgements

The authors thank the management of Vellore Institute of Technology for providing the facilities to carry out this research work.

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  1. Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    HemaNandini Rajendran Krishnamoorthy & Ramanathan Karuppasamy

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HRK performed the computational work, analysed the data and prepared tables and figures. RK conceived this study and is responsible for the overall design, interpretation, manuscript preparation and communication. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Ramanathan Karuppasamy.

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Krishnamoorthy, H.R., Karuppasamy, R. A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negative breast cancer. Med Oncol 40, 312 (2023). https://doi.org/10.1007/s12032-023-02183-7

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