Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, Harvey JD, et al. Cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life years for 29 cancer groups from 2010 to 2019: a systematic analysis for the global burden of disease study 2019. JAMA Oncol. 2022;8:420–44.

Article  PubMed  Google Scholar 

Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7–34.

Article  PubMed  Google Scholar 

United Nations Development Programme. The SDGs in action. 2030 Sustainable Development Goals. 2023.

Google Scholar 

De B, Bhandari K, Mendonça FJB, Scotti MT, Scotti L. Computational studies in drug design against cancer. Anticancer Agents Med Chem. 2019;19:587–91.

Article  CAS  PubMed  Google Scholar 

Geromichalos GD, Alifieris CE, Geromichalou EG, Trafalis DT. Overview on the current status on virtual high-throughput screening and combinatorial chemistry approaches in multi-target anticancer drug discovery. Part II J BUON. 2016;21:1337–58.

PubMed  Google Scholar 

Geromichalos GD. Importance of molecular computer modeling in anticancer drug development. J BUON. 2007;12(Suppl 1):S101–18.

PubMed  Google Scholar 

Hameed R, Khan A, Khan S, Perveen S. Computational Approaches Towards Kinases as Attractive Targets for Anticancer Drug Discovery and Development. Anticancer Agents Med Chem. 2019;19:592–8.

Article  CAS  PubMed  Google Scholar 

Qiao Y, Dsouza C, Matthews AA, Jin Y, He W, Bao J, et al. Discovery of small molecules targeting GRP78 for antiangiogenic and anticancer therapy. Eur J Med Chem. 2020;193: 112228.

Article  CAS  PubMed  Google Scholar 

Abu-Mahfouz A, Ali M, Elfiky A. Anti-breast cancer drugs targeting cell-surface glucose-regulated protein 78: a drug repositioning in silico study. J Biomol Struct Dyn. 2022:1-15. https://doi.org/10.1080/07391102.2022.2125076.

Madhavan S, Nagarajan S. GRP78 and next generation cancer hallmarks: an underexplored molecular target in cancer chemoprevention research. Biochimie. 2020;175:69–76.

Article  CAS  PubMed  Google Scholar 

Yoneda Y, Steiniger SCJ, Capková K, Mee JM, Liu Y, Kaufmann GF, et al. A cell-penetrating peptidic GRP78 ligand for tumor cell-specific prodrug therapy. Bioorg Med Chem Lett. 2008;18:1632–6.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cicalese S, Okuno K, Elliott KJ, Kawai T, Scalia R, Rizzo V, Eguchi S. 78 kDa Glucose-Regulated Protein Attenuates Protein Aggregation and Monocyte Adhesion Induced by Angiotensin II in Vascular Cells. Int J Mol Sci. 2020;21(14):4980. https://doi.org/10.3390/ijms21144980.

Xia S, Duan W, Liu W, Zhang X, Wang Q. GRP78 in lung cancer. J Transl Med. 2021;19:118.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Araujo N, Hebbar N, Rangnekar VM. GRP78 is a targetable receptor on cancer and stromal cells. EBioMedicine. 2018;33:2–3.

Article  PubMed  PubMed Central  Google Scholar 

Santamaría PG, Mazón MJ, Eraso P, Portillo F. UPR: an upstream signal to EMT induction in cancer. J Clin Med. 2019;8:624.

Article  PubMed  PubMed Central  Google Scholar 

Elfiky AA, Ibrahim IM, Ibrahim MN, Elshemey WM. Host-cell recognition of SARS-CoV-2 spike receptor binding domain from different variants. J Infect. 2022;85:702–69.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang J, Lee J, Liem D, Ping P. HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum. Gene. 2017;618:14–23.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ni M, Zhang Y, Lee AS. Beyond the endoplasmic reticulum: atypical GRP78 in cell viability, signalling and therapeutic targeting. Biochem J. 2011;434:181–8.

Article  CAS  PubMed  Google Scholar 

Arap MA, Lahdenranta J, Mintz PJ, Hajitou A, Sarkis AS, Arap W, et al. Cell surface expression of the stress response chaperone GRP78 enables tumor targeting by circulating ligands. Cancer Cell. 2004;6:275–84.

Article  CAS  PubMed  Google Scholar 

Burikhanov R, Zhao Y, Goswami A, Qiu S, Schwarze SR, Rangnekar VM. The tumor suppressor par-4 activates an extrinsic pathway for apoptosis. Cell. 2009;138:377–88.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kao C, Chandna R, Ghode A, Dsouza C, Chen M, Larsson A, et al. Proapoptotic Cyclic Peptide BC71 Targets Cell-Surface GRP78 and Functions as an Anticancer Therapeutic in Mice. EBioMedicine. 2018;33:22–32.

Article  PubMed  PubMed Central  Google Scholar 

Vajda S, Yueh C, Beglov D, Bohnuud T, Mottarella SE, Xia B, et al. New additions to the ClusPro server motivated by CAPRI. Proteins Struct Functi Bioinform. 2017;85:435–44.

Article  CAS  Google Scholar 

Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The ClusPro web server for protein–protein docking. Nat Protoc. 2017;12:255–78.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kozakov D, Beglov D, Bohnuud T, Mottarella SE, Xia B, Hall DR, et al. How good is automated protein docking? Proteins. 2013;81:2159–66.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Weng G, Wang E, Wang Z, Liu H, Zhu F, Li D, et al. HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA. Nucleic Acids Res. 2019;47:W322–30.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Robert X, Gouet P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 2014;42 Web Server issue:W320-4.

Article  Google Scholar 

Wilkins MR, Gasteiger E, Bairoch A, Sanchez JC, Williams KL, Appel RD, et al. Protein identification and analysis tools in the ExPASy server. Methods Mol Biol. 1999;112:531–52.

CAS  PubMed  Google Scholar 

Lear S, Cobb SL. Pep-Calc.com: a set of web utilities for the calculation of peptide and peptoid properties and automatic mass spectral peak assignment. J Comput Aided Mol Des. 2016;30:271–7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000;16:404–5.

Article  CAS  PubMed  Google Scholar 

Lamiable A, Thévenet P, Rey J, Vavrusa M, Derreumaux P, Tufféry P. PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex. Nucleic Acids Res. 2016;44:W449–54.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Thévenet P, Shen Y, Maupetit J, Guyon F, Derreumaux P, Tufféry P. PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides. Nucleic Acids Res. 2012;40 Web Server issue:W288-93.

Article  Google Scholar 

Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr. 1993;26:283–91.

Article  CAS  Google Scholar 

Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35 Web Server issue:W407-10.

Article  Google Scholar 

Jo S, Kim T, Iyer VG, Im W. CHARMM-GUI: a web-based graphical user interface for CHARMM. J Comput Chem. 2008;29:1859–65.

Article  CAS  PubMed  Google Scholar 

Kim S, Lee J, Jo S, Brooks CL 3rd, Lee HS, Im W. CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules. J Comput Chem. 2017;38:1879–86.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jo S, Cheng X, Islam SM, Huang L, Rui H, Zhu A, et al. CHARMM-GUI PDB manipulator for advanced modeling and simulations of proteins containing nonstandard residues. Adv Protein Chem Struct Biol. 2014;96:235–65.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pronk S, Páll S, Schulz R, Larsson P, Bjelkmar P, Apostolov R, et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics. 2013;29:845–54.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Huang J, MacKerell AD Jr. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. J Comput Chem. 2013;34:2135–45.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mark P, Nilsson L. Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. J Phys Chem A. 2001;105:9954–60.

Article  CAS