{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T22:35:41Z","timestamp":1782513341701,"version":"3.54.5"},"reference-count":33,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T00:00:00Z","timestamp":1663286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001411","name":"Indian Council of Medical Research","doi-asserted-by":"publisher","award":["3\/1\/3PDF(19)\/2019-HRD"],"award-info":[{"award-number":["3\/1\/3PDF(19)\/2019-HRD"]}],"id":[{"id":"10.13039\/501100001411","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>Punicalagin is the most bioactive pomegranate polyphenol with high antioxidant and free-radical scavenging activity and can potentially cure different ailments related to the cardiovascular system. The current research work was envisioned to predict the targeting efficiency of punicalagin (PG) nanoparticles to the macrophages, more specifically to bone marrow macrophages. For this, we selected mannose-decorated PLGA-punicalagin nanoparticles (Mn-PLGA-PG), and before formulating this nanocarrier in laboratory settings, we predicted the targeting efficiency of this nanocarrier by in silico analysis. The analysis proceeded with macrophage mannose receptors to be acquainted with the binding affinity and punicalagin-based nanocarrier interactions with this receptor. In silico docking studies of macrophage mannose receptors and punicalagin showed binding interactions on its surface. PG interacted with hydrogen bonds to the charged residue ASP668 and GLY666 and polar residue GLN760 of the Mn receptor. Mannose with a docking score of \u22125.811 Kcal\/mol interacted with four hydrogen bonds and the mannose receptor of macrophage, and in PLGA, it showed a \u22124.334 Kcal\/mol docking score. Further, the analysis proceeded with density functional theory analysis (DFT) and HOMO\u2013LUMO analysis, followed by an extensive 100 ns molecular dynamics simulation to analyse the trajectories showing the slightest deviation and fluctuation. While analysing the ligand and protein interaction, a wonderful interaction was found among the atoms of the ligand and protein residues. This computational study confirms that this nanocarrier could be a promising lead molecule to regulate the incidence of drug-induced neutropenia. Furthermore, experimental validation is required before this can be stated with complete confidence or before human use.<\/jats:p>","DOI":"10.3390\/molecules27186034","type":"journal-article","created":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T02:06:50Z","timestamp":1663553210000},"page":"6034","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Macrophage-Targeted Punicalagin Nanoengineering to Alleviate Methotrexate-Induced Neutropenia: A Molecular Docking, DFT, and MD Simulation Analysis"],"prefix":"10.3390","volume":"27","author":[{"given":"Ritu","family":"Karwasra","sequence":"first","affiliation":[{"name":"ICMR-National Institute of Pathology, Safdarjung Hospital Campus, New Delhi 110029, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9832-2830","authenticated-orcid":false,"given":"Shaban","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nagmi","family":"Bano","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sahar","family":"Qazi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3646-6828","authenticated-orcid":false,"given":"Khalid","family":"Raza","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Surender","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, All India Institute of Medical Science (AIIMS), New Delhi 110029, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saurabh","family":"Varma","sequence":"additional","affiliation":[{"name":"ICMR-National Institute of Pathology, Safdarjung Hospital Campus, New Delhi 110029, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40169-017-0175-0","article-title":"Cancer nanomedicine: A review of recent success in drug delivery","volume":"6","author":"Tran","year":"2017","journal-title":"Clin. Transl. Med."},{"key":"ref_2","first-page":"769","article-title":"Cancer active targeting by nanoparticles: A comprehensive review of literature","volume":"141","author":"Remon","year":"2016","journal-title":"J. Cancer Res. Clin. Oncol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41524-019-0153-8","article-title":"Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design","volume":"5","author":"Lookman","year":"2019","journal-title":"NPJ Comput. Mater."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"20180063","DOI":"10.1098\/rsfs.2018.0063","article-title":"A quantitative in silico platform for simulating cytotoxic and nanoparticle drug delivery to solid tumours","volume":"9","author":"Wijeratne","year":"2019","journal-title":"Interface Focus"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ramlal, A., Ahmad, S., Kumar, L., Khan, F.N., and Chongtham, R. (2021). From molecules to patients: The clinical applications of biological databases and electronic health record. Translational Bioinformatics in Healthcare and Medicine, Elsevier.","DOI":"10.1016\/B978-0-323-89824-9.00009-4"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1093\/rheumatology\/keh685","article-title":"Methotrexate-induced pancytopenia: Serious and under-reported? Our experience of 25 cases in 5 years","volume":"44","author":"Lim","year":"2005","journal-title":"Rheumatology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.rbr.2014.03.011","article-title":"Severe leukopenia in a rheumatoid arthritis patient treated with a methotrexate\/leflunomide combination","volume":"54","author":"Toth","year":"2014","journal-title":"Rev. Bras. Reumatol. Engl. Ed."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"79","DOI":"10.4103\/0971-5851.73590","article-title":"Granulocyte colony-stimulating factor (filgrastim) in chemotherapy-induced febrile neutropenia","volume":"31","author":"Advani","year":"2010","journal-title":"Indian J. Med Paediatr. Oncol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7124251","DOI":"10.1155\/2016\/7124251","article-title":"Punicalagin induces serum low-density lipoprotein influx to macrophages","volume":"2016","author":"Atrahimovich","year":"2016","journal-title":"Oxidative Med. Cell. Longev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2943","DOI":"10.1039\/C6FO00485G","article-title":"An update on dietary phenolic compounds in the prevention and management of rheumatoid arthritis","volume":"7","author":"Rosillo","year":"2016","journal-title":"Food Funct."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e12959","DOI":"10.1111\/jfbc.12959","article-title":"Pomegranate supplementation attenuates inflammation, joint dysfunction via inhibition of NF-\u03baB signaling pathway in experimental models of rheumatoid arthritis","volume":"43","author":"Karwasra","year":"2019","journal-title":"J. Food Biochem."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3091","DOI":"10.1039\/C6FO00188B","article-title":"Antioxidant and anti-inflammatory potential of pomegranate rind extract to ameliorate cisplatin-induced acute kidney injury","volume":"7","author":"Karwasra","year":"2016","journal-title":"Food Funct."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Quir\u00f3s-Fern\u00e1ndez, R., L\u00f3pez-Plaza, B., Bermejo, L.M., Palma-Milla, S., and G\u00f3mez-Candela, C. (2019). Supplementation with hydroxytyrosol and punicalagin improves early atherosclerosis markers involved in the asymptomatic phase of atherosclerosis in the adult population: A randomised, placebo-controlled, crossover trial. Nutrients, 11.","DOI":"10.3390\/nu11030640"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21539","DOI":"10.1074\/jbc.M002366200","article-title":"structure of a C-type carbohydrate recognition domain from the macrophage mannose receptor","volume":"275","author":"Feinberg","year":"2000","journal-title":"J. Biol. Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2785","DOI":"10.1002\/jcc.21256","article-title":"AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility","volume":"30","author":"Morris","year":"2009","journal-title":"J. Comput. Chem."},{"key":"ref_16","unstructured":"Release, S. (2020). 1: Maestro Desmond Interoperability Tools, Schr\u00f6dinger."},{"key":"ref_17","unstructured":"Schrodinger, L. (The PyMOL Molecular Graphics System, 2010). The PyMOL Molecular Graphics System, Version 1.3r1."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2110","DOI":"10.1002\/qua.24481","article-title":"Jaguar: A high-performance quantum chemistry software program with strengths in life and materials sciences","volume":"113","author":"Bochevarov","year":"2013","journal-title":"Int. J. Quantum Chem."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2504","DOI":"10.1039\/C4CP04399E","article-title":"Theoretical insight into hydrogen adsorption onto graphene: A first-principles B3LYP-D3 study","volume":"17","author":"Ganji","year":"2015","journal-title":"Phys. Chem. Chem. Phys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1021\/ja00214a001","article-title":"The OPLS [optimised potentials for liquid simulations] potential functions for proteins, energy minimisations for crystals of cyclic peptides and crambin","volume":"110","author":"Jorgensen","year":"1988","journal-title":"J. Am. Chem. Soc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4291","DOI":"10.1021\/acs.jctc.1c00302","article-title":"OPLS4: Improving force field accuracy on challenging regimes of chemical space","volume":"17","author":"Lu","year":"2021","journal-title":"J. Chem. Theory Comput."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"9954","DOI":"10.1021\/jp003020w","article-title":"Structure and dynamics of the TIP3P, SPC, and SPC\/E water models at 298 K","volume":"105","author":"Mark","year":"2001","journal-title":"J. Phys. Chem. A"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1080\/00268977200100031","article-title":"NpT-ensemble Monte Carlo calculations for binary liquid mixtures","volume":"23","author":"McDonald","year":"1972","journal-title":"Mol. Phys."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Bowers, K.J., Chow, D.E., Xu, H., Dror, R.O., Eastwood, M.P., Gregersen, B.A., Klepeis, J.L., Kolossvary, I., Moraes, M.A., and Sacerdoti, F.D. (2006, January 11\u201317). Scalable algorithms for molecular dynamics simulations on commodity clusters. Proceedings of the 2006 ACM\/IEEE Conference on Supercomputing, Tampa, FL, USA.","DOI":"10.1145\/1188455.1188544"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3633","DOI":"10.1080\/07391102.2019.1680435","article-title":"Probing the effect of a plus 1bp frameshift mutation in protein-DNA interface of domestication gene, NAMB1, in wheat","volume":"38","author":"Kaul","year":"2020","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1038\/ncponc1237","article-title":"In silico cancer modeling: Is it ready for prime time?","volume":"6","author":"Deisboeck","year":"2009","journal-title":"Nat. Clin. Pract. Oncol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"8352","DOI":"10.1039\/C9NR00844F","article-title":"In silico profiling nanoparticles: Predictive nanomodeling using universal nanodescriptors and various machine learning approaches","volume":"11","author":"Yan","year":"2019","journal-title":"Nanoscale"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.1021\/acs.jpcc.8b07616","article-title":"In silico study of gold nanoparticle uptake into a mammalian cell: Interplay of size, shape, surface charge, and aggregation","volume":"123","author":"Lunnoo","year":"2019","journal-title":"J. Phys. Chem. C"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6383","DOI":"10.1021\/acsnano.0c03697","article-title":"Toward nanotechnology-enabled approaches against the COVID-19 pandemic","volume":"14","author":"Weiss","year":"2020","journal-title":"ACS Nano"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ahmad, S., Chitkara, P., Khan, F.N., Kishan, A., Alok, V., Ramlal, A., and Mehta, S. (2021). Mobile technology solution for COVID-19: Surveillance and prevention. Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis, Springer.","DOI":"10.1007\/978-981-15-8534-0_5"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Khan, F.N., Khanam, A.A., Ramlal, A., and Ahmad, S. (2021). A Review on Predictive Systems and Data Models for COVID-19. Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis, Springer.","DOI":"10.1007\/978-981-15-8534-0_7"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4466","DOI":"10.1021\/acs.jpcb.9b11989","article-title":"Atomistic simulations on interactions between amphiphilic Janus nanoparticles and lipid bilayers: Effects of lipid ordering and leaflet asymmetry","volume":"124","author":"Ou","year":"2020","journal-title":"J. Phys. Chem. B"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"268","DOI":"10.3389\/fbioe.2019.00268","article-title":"Molecular modeling for nanomaterial\u2013biology interactions: Opportunities, challenges, and perspectives","volume":"7","author":"Casalini","year":"2019","journal-title":"Front. Bioeng. Biotechnol."}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/27\/18\/6034\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:32:39Z","timestamp":1760142759000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/27\/18\/6034"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,16]]},"references-count":33,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["molecules27186034"],"URL":"https:\/\/doi.org\/10.3390\/molecules27186034","relation":{},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,16]]}}}