Structure-based small inhibitors search combined with molecular dynamics driven energies for human programmed cell death-1 (PD-1) protein

References

• Ahmadzadeh, M., Johnson, L. A., Heemskerk, B., Wunderlich, J. R., Dudley, M. E., White, D. E., & Rosenberg, S. A. (2009). Tumor antigen–specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood, 114(8), 1537–1544. https://doi.org/10.1182/blood-2008-12-195792
   PubMed Web of Science ®Google Scholar
• Almahmoud, S., & Zhong, H. A. (2019). Molecular modeling studies on the binding mode of the PD-1/PD-L1 complex inhibitors. International Journal of Molecular Sciences, 20(18), 4654. https://doi.org/10.3390/ijms20184654
   PubMed Web of Science ®Google Scholar
• Altona, C., & t., Sundaralingam, M. (1972). Conformational analysis of the sugar ring in nucleosides and nucleotides. New description using the concept of pseudorotation. Journal of the American Chemical Society, 94(23), 8205–8212. https://doi.org/10.1021/ja00778a043
   PubMed Web of Science ®Google Scholar
• Andrews, P. (1986). Functional groups, drug-receptor interactions and drug design. Trends in Pharmacological Sciences, 7, 148–151. https://doi.org/10.1016/0165-6147(86)90292-0
   Web of Science ®Google Scholar
• Brunton, L. L., Chabner, B., & Knollmann, B. C. (2018). Goodman & Gilman’s the pharmacological basis of therapeutics. McGraw-Hill Education.
   Google Scholar
• Case, D. A., Belfon, K., Ben-Shalom, I., Brozell, S. R., Cerutti, D., Cheatham, T., Cruzeiro, V. W. D., Darden, T. A., Duke, R. E., Giambasu, G., Gilson, M. K., Gohlke, H., Goetz, A. W., Harris, R., Izadi, S., Izmailov, S. A., Kasavajhala, K., Kovalenko, A., Krasny, R., Kurtzman, T. … Giambasu, G. (2020). Amber 2020.
   Google Scholar
• Community, B. O. (2018). Blender - a 3D modelling and rendering package. Retrieved from http://www.blender.org
   Google Scholar
• Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(1), 1–13. https://doi.org/10.1038/srep42717
   PubMed Web of Science ®Google Scholar
• Darden, T., York, D., & Pedersen, L. (1993). Particle mesh Ewald: An N⋅ log (N) method for Ewald sums in large systems. The Journal of Chemical Physics, 98(12), 10089–10092. https://doi.org/10.1063/1.464397
   Web of Science ®Google Scholar
• Ferrara, R., Mezquita, L., Texier, M., Lahmar, J., Audigier-Valette, C., Tessonnier, L., Mazieres, J., Zalcman, G., Brosseau, S., Le Moulec, S., Leroy, L., Duchemann, B., Lefebvre, C., Veillon, R., Westeel, V., Koscielny, S., Champiat, S., Ferté, C., Planchard, D., … Caramella, C. (2018). Hyperprogressive disease in patients with advanced non–small cell lung cancer treated with PD-1/PD-L1 inhibitors or with single-agent chemotherapy. JAMA Oncology, 4(11), 1543–1552. https://doi.org/10.1001/jamaoncol.2018.3676
   PubMed Web of Science ®Google Scholar
• Fife, B. T., & Bluestone, J. A. (2008). Control of peripheral T‐cell tolerance and autoimmunity via the CTLA‐4 and PD‐1 pathways. Immunological Reviews, 224(1), 166–182. https://doi.org/10.1111/j.1600-065X.2008.00662.x
   PubMedGoogle Scholar
• Gambichler, T., Reuther, J., Scheel, C. H., & Becker, J. C. (2020). On the use of immune checkpoint inhibitors in patients with viral infections including COVID-19. Journal for ImmunoTherapy of Cancer, 8(2), e001145. https://doi.org/10.1136/jitc-2020-001145
   PubMed Web of Science ®Google Scholar
• Grywalska, E., Pasiarski, M., Góźdź, S., & Roliński, J. (2018). Immune-checkpoint inhibitors for combating T-cell dysfunction in cancer. OncoTargets and Therapy, 11, 6505–6524. https://doi.org/10.2147/OTT.S150817
   PubMed Web of Science ®Google Scholar
• Halim, S. A., Jabeen, S., Khan, A., & Al-Harrasi, A. (2021). Rational design of novel inhibitors of α-glucosidase: An application of quantitative structure activity relationship and structure-based virtual screening. Pharmaceuticals, 14(5), 482. https://doi.org/10.3390/ph14050482
   Web of Science ®Google Scholar
• Halim, S. A., Sikandari, A. G., Khan, A., Wadood, A., Fatmi, M. Q., Csuk, R., & Al-Harrasi, A. (2021). Structure-based virtual screening of tumor necrosis factor-α inhibitors by cheminformatics approaches and bio-molecular simulation. Biomolecules, 11(2), 329. https://doi.org/10.3390/biom11020329
   PubMed Web of Science ®Google Scholar
• Halim, S. A., Waqas, M., Khan, A., & Al-Harrasi, A. (2021). In silico prediction of novel inhibitors of SARS-CoV-2 main protease through structure-based virtual screening and molecular dynamic simulation. Pharmaceuticals, 14(9), 896. https://doi.org/10.3390/ph14090896
   Web of Science ®Google Scholar
• Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
   PubMedGoogle Scholar
• Keir, M. E., Butte, M. J., Freeman, G. J., & Sharpe, A. H. (2008). PD-1 and its ligands in tolerance and immunity. Annual Review of Immunology, 26, 677–704. https://doi.org/10.1146/annurev.immunol.26.021607.090331
   PubMed Web of Science ®Google Scholar
• Keizer, R. J., Huitema, A. D., Schellens, J. H., & Beijnen, J. H. (2010). Clinical pharmacokinetics of therapeutic monoclonal antibodies. Clinical Pharmacokinetics, 49(8), 493–507.
   PubMed Web of Science ®Google Scholar
• Khair, D. O., Bax, H. J., Mele, S., Crescioli, S., Pellizzari, G., Khiabany, A., Nakamura, M., Harris, R. J., French, E., Hoffmann, R. M., Williams, I. P., Cheung, A., Thair, B., Beales, C. T., Touizer, E., Signell, A. W., Tasnova, N. L., Spicer, J. F., Josephs, D. H., … Karagiannis, S. N. (2019). Combining immune checkpoint inhibitors: Established and emerging targets and strategies to improve outcomes in melanoma. Frontiers in Immunology, 10, 453. https://doi.org/10.3389/fimmu.2019.00453
   PubMed Web of Science ®Google Scholar
• Krause, M. E., & Sahin, E. (2019). Chemical and physical instabilities in manufacturing and storage of therapeutic proteins. Current Opinion in Biotechnology, 60, 159–167. https://doi.org/10.1016/j.copbio.2019.01.014
   PubMed Web of Science ®Google Scholar
• Kräutler, V., van Gunsteren, W. F., & Hünenberger, P. H. (2001). A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. Journal of Computational Chemistry, 22(5), 501–508. https://doi.org/10.1002/1096-987X(20010415)22:5<501::AID-JCC1021>3.0.CO;2-V
   Web of Science ®Google Scholar
• Kruger, S., Ilmer, M., Kobold, S., Cadilha, B. L., Endres, S., Ormanns, S., Schuebbe, G., Renz, B. W., D’Haese, J. G., Schloesser, H., Heinemann, V., Subklewe, M., Boeck, S., Werner, J., & von Bergwelt-Baildon, M. (2019). Advances in cancer immunotherapy 2019–latest trends. Journal of Experimental & Clinical Cancer Research, 38(1), 1–11. https://doi.org/10.1186/s13046-019-1266-0
   PubMedGoogle Scholar
• Kuol, N., Stojanovska, L., Nurgali, K., & Apostolopoulos, V. (2018). PD-1/PD-L1 in disease. Immunotherapy, 10(2), 149–160. https://doi.org/10.2217/imt-2017-0120
   PubMed Web of Science ®Google Scholar
• Li, K., & Tian, H. (2019). Development of small-molecule immune checkpoint inhibitors of PD-1/PD-L1 as a new therapeutic strategy for tumour immunotherapy. Journal of Drug Targeting, 27(3), 244–256. https://doi.org/10.1080/1061186X.2018.1440400
   PubMed Web of Science ®Google Scholar
• Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1-3), 3–25. https://doi.org/10.1016/S0169-409X(96)00423-1
   Web of Science ®Google Scholar
• Lippert, T., & Rarey, M. (2009). Fast automated placement of polar hydrogen atoms in protein-ligand complexes. Journal of Cheminformatics, 1(1), 1–12. https://doi.org/10.1186/1758-2946-1-13
   PubMedGoogle Scholar
• Lipson, E. J., & Drake, C. G. (2011). Ipilimumab: An anti-CTLA-4 antibody for metastatic melanoma. Clinical Cancer Research, 17(22), 6958–6962. https://doi.org/10.1158/1078-0432.CCR-11-1595
   PubMed Web of Science ®Google Scholar
• Liu, H., Guo, L., Zhang, J., Zhou, Y., Zhou, J., Yao, J., Wu, H., Yao, S., Chen, B., Chai, Y., & Chai, Y. (2019). Glycosylation-independent binding of monoclonal antibody toripalimab to FG loop of PD-1 for tumor immune checkpoint therapy. MAbs, 11, 681–690.
   PubMed Web of Science ®Google Scholar
• Makuku, R., Khalili, N., Razi, S., Keshavarz-Fathi, M., & Rezaei, N. (2021). Current and future perspectives of PD-1/PDL-1 blockade in cancer immunotherapy. Journal of Immunology Research, 2021, 1–15. https://doi.org/10.1155/2021/6661406
   Web of Science ®Google Scholar
• Miller III, B. R., McGee, Jr, T. D., Swails, J. M., Homeyer, N., Gohlke, H., & Roitberg, A. E. (2012). MMPBSA. py: An efficient program for end-state free energy calculations. Journal of Chemical Theory and Computation, 8(9), 3314–3321. https://doi.org/10.1021/ct300418h
   PubMed Web of Science ®Google Scholar
• Minchinton, A. I., & Tannock, I. F. (2006). Drug penetration in solid tumours. Nature Reviews. Cancer, 6(8), 583–592. https://doi.org/10.1038/nrc1893
   PubMed Web of Science ®Google Scholar
• Muegge, I. (2003). Selection criteria for drug‐like compounds. Medicinal Research Reviews, 23(3), 302–321. https://doi.org/10.1002/med.10041
   PubMed Web of Science ®Google Scholar
• Onufriev, A., Bashford, D., & Case, D. A. (2004). Exploring protein native states and large‐scale conformational changes with a modified generalized born model. Proteins, 55(2), 383–394. https://doi.org/10.1002/prot.20033
   PubMed Web of Science ®Google Scholar
• Origin(Pro). (2021). Version 2021. OriginLab Corporation, Northampton, MA, USA.
   Google Scholar
• Pathania, S., & Singh, P. K. (2021). Analyzing FDA-approved drugs for compliance of pharmacokinetic principles: should there be a critical screening parameter in drug designing protocols? Expert Opinion on Drug Metabolism & Toxicology, 17(4), 351–354. https://doi.org/10.1080/17425255.2021.1865309
   PubMed Web of Science ®Google Scholar
• Poels, K., van Leent, M. M. T., Boutros, C., Tissot, H., Roy, S., Meerwaldt, A. E., Toner, Y. C. A., Reiche, M. E., Kusters, P. J. H., Malinova, T., Huveneers, S., Kaufman, A. E., Mani, V., Fayad, Z. A., de Winther, M. P. J., Marabelle, A., Mulder, W. J. M., Robert, C., Seijkens, T. T. P., & Lutgens, E. (2020). Immune checkpoint inhibitor therapy aggravates T cell–driven plaque inflammation in atherosclerosis. JACC. CardioOncology, 2(4), 599–610. https://doi.org/10.1016/j.jaccao.2020.08.007
   PubMedGoogle Scholar
• Powles, T., Eder, J. P., Fine, G. D., Braiteh, F. S., Loriot, Y., Cruz, C., Bellmunt, J., Burris, H. A., Petrylak, D. P., Teng, S-l., Shen, X., Boyd, Z., Hegde, P. S., Chen, D. S., & Vogelzang, N. J. (2014). MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer. Nature, 515(7528), 558–562. https://doi.org/10.1038/nature13904
   PubMed Web of Science ®Google Scholar
• Press, W. H., Flannery, B. P., Teukolsky, S. A., Vetterling, W. T., & Kramer, P. B. (1987). Numerical recipes: The art of scientific computing. Physics Today, 40(10), 120–122. https://doi.org/10.1063/1.2820230
   Google Scholar
• Roe, D. R., & Cheatham III, T. E. (2013). PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. Journal of Chemical Theory and Computation, 9(7), 3084–3095. https://doi.org/10.1021/ct400341p
   PubMed Web of Science ®Google Scholar
• Sakuishi, K., Apetoh, L., Sullivan, J. M., Blazar, B. R., Kuchroo, V. K., & Anderson, A. C. (2010). Targeting Tim-3 and PD-1 pathways to reverse T cell exhaustion and restore anti-tumor immunity. Journal of Experimental Medicine, 207(10), 2187–2194. https://doi.org/10.1084/jem.20100643
   PubMed Web of Science ®Google Scholar
• Schrodinger, L. L. C. (2015). The PyMOL Molecular Graphics System, Version 1.8.
   Google Scholar
• Sengupta, A., Li, Z., Song, L. F., Li, P., & Merz, K. M. Jr, (2021). Parameterization of monovalent ions for the Opc3, Opc, Tip3p-Fb, and Tip4p-Fb water models. Journal of Chemical Information and Modeling, 61(2), 869–880. https://doi.org/10.1021/acs.jcim.0c01390
   PubMed Web of Science ®Google Scholar
• Tang, S., & Kim, P. S. (2019). A high-affinity human PD-1/PD-L2 complex informs avenues for small-molecule immune checkpoint drug discovery. Proceedings of the National Academy of Sciences of the United States of America, 116(49), 24500–24506. https://doi.org/10.1073/pnas.1916916116
   PubMed Web of Science ®Google Scholar
• Tian, C., Kasavajhala, K., Belfon, K. A. A., Raguette, L., Huang, H., Migues, A. N., Bickel, J., Wang, Y., Pincay, J., Wu, Q., & Simmerling, C. (2020). ff19SB: Amino-acid-specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. Journal of Chemical Theory and Computation, 16(1), 528–552. https://doi.org/10.1021/acs.jctc.9b00591
   PubMed Web of Science ®Google Scholar
• ULC. (2020a) Molecular Operating Environment (MOE), 2019.01: Chemical Computing Group ULC 1010 Sherbooke St. West, Suite# 910, Montreal.
   Google Scholar
• ULC. (2020b). Molecular Operating Environment (MOE), 2020.09.
   Google Scholar
• Veber, D. F., Johnson, S. R., Cheng, H.-Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
   PubMed Web of Science ®Google Scholar
• Wang, B., & Merz, K. M. (2006). A fast QM/MM (quantum mechanical/molecular mechanical) approach to calculate nuclear magnetic resonance chemical shifts for macromolecules. Journal of Chemical Theory and Computation, 2(1), 209–215. https://doi.org/10.1021/ct050212s
   PubMed Web of Science ®Google Scholar
• Wang, M., Wang, J., Wang, R., Jiao, S., Wang, S., Zhang, J., & Zhang, M. (2019). Identification of a monoclonal antibody that targets PD-1 in a manner requiring PD-1 Asn58 glycosylation. Communications Biology, 2(1), 1–10. https://doi.org/10.1038/s42003-019-0642-9
   PubMedGoogle Scholar
• Wang, Y., Zhou, S., Yang, F., Qi, X., Wang, X., Guan, X., Shen, C., Duma, N., Vera Aguilera, J., Chintakuntlawar, A., Price, K. A., Molina, J. R., Pagliaro, L. C., Halfdanarson, T. R., Grothey, A., Markovic, S. N., Nowakowski, G. S., Ansell, S. M., & Wang, M. L. (2019). Treatment-related adverse events of PD-1 and PD-L1 inhibitors in clinical trials: A systematic review and meta-analysis. JAMA Oncology, 5(7), 1008–1019. https://doi.org/10.1001/jamaoncol.2019.0393
   PubMed Web of Science ®Google Scholar
• Yang, T., Wu, J. C., Yan, C., Wang, Y., Luo, R., Gonzales, M. B., Dalby, K. N., & Ren, P. (2011). Virtual screening using molecular simulations. Proteins, 79(6), 1940–1951. https://doi.org/10.1002/prot.23018
   PubMed Web of Science ®Google Scholar
• Zhang, N., Tu, J., Wang, X., & Chu, Q. (2019). Programmed cell death-1/programmed cell death ligand-1 checkpoint inhibitors: Differences in mechanism of action. Immunotherapy, 11(5), 429–441. https://doi.org/10.2217/imt-2018-0110
   PubMed Web of Science ®Google Scholar
• Zhang, R., Zhu, Z., Lv, H., Li, F., Sun, S., Li, J., & Lee, C. S. (2019). Immune checkpoint blockade mediated by a small‐molecule nanoinhibitor targeting the PD‐1/PD‐L1 pathway synergizes with photodynamic therapy to elicit antitumor immunity and antimetastatic effects on breast cancer. Small, 15(49), 1903881. https://doi.org/10.1002/smll.201903881
   PubMed Web of Science ®Google Scholar