{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:34:31Z","timestamp":1774542871471,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,22]],"date-time":"2023-07-22T00:00:00Z","timestamp":1689984000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NSF","award":["1850319"],"award-info":[{"award-number":["1850319"]}]},{"name":"NSF","award":["2231498"],"award-info":[{"award-number":["2231498"]}]},{"name":"NSF","award":["2023"],"award-info":[{"award-number":["2023"]}]},{"name":"UAlbany SAGES","award":["1850319"],"award-info":[{"award-number":["1850319"]}]},{"name":"UAlbany SAGES","award":["2231498"],"award-info":[{"award-number":["2231498"]}]},{"name":"UAlbany SAGES","award":["2023"],"award-info":[{"award-number":["2023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Understanding the binding behavior and conformational dynamics of intrinsically disordered proteins (IDPs) is crucial for unraveling their regulatory roles in biological processes. However, their lack of stable 3D structures poses challenges for analysis. To address this, we propose an algorithm that explores IDP binding behavior with protein complexes by extracting topological and geometric features from the protein surface model. Our algorithm identifies a geometrically favorable binding pose for the IDP and plans a feasible trajectory to evaluate its transition to the docking position. We focus on IDPs from Homo sapiens and Mus-musculus, investigating their interaction with the Plasmodium falciparum (PF) pathogen associated with malaria-related deaths. We compare our algorithm with HawkDock and HDOCK docking tools for quantitative (computation time) and qualitative (binding affinity) measures. Our results indicated that our method outperformed the compared methods in computation performance and binding affinity in experimental conformations.<\/jats:p>","DOI":"10.3390\/ijms241411785","type":"journal-article","created":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T00:47:03Z","timestamp":1690159623000},"page":"11785","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A New Tool to Study the Binding Behavior of Intrinsically Disordered Proteins"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6490-1532","authenticated-orcid":false,"given":"Aakriti","family":"Upadhyay","sequence":"first","affiliation":[{"name":"Department of Computer Science, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chinwe","family":"Ekenna","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6424","DOI":"10.1021\/acs.chemrev.5b00548","article-title":"Dynamic protein interaction networks and new structural paradigms in signaling","volume":"116","author":"Csizmok","year":"2016","journal-title":"Chem. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.sbi.2011.03.011","article-title":"Intrinsically disordered proteins: Regulation and disease","volume":"21","author":"Babu","year":"2011","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1146\/annurev.biophys.37.032807.125924","article-title":"Intrinsically disordered proteins in human diseases: Introducing the D2 concept","volume":"37","author":"Uversky","year":"2008","journal-title":"Annu. Rev. Biophys."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.sbi.2015.08.009","article-title":"Intrinsically disordered proteins: Emerging interaction specialists","volume":"35","author":"Tompa","year":"2015","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/nrm3920","article-title":"Intrinsically disordered proteins in cellular signalling and regulation","volume":"16","author":"Wright","year":"2015","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kulkarni, P., and Uversky, V.N. (2019). Intrinsically disordered proteins in chronic diseases. Biomolecules, 9.","DOI":"10.3390\/biom9040147"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6511","DOI":"10.1128\/IAI.68.12.6511-6518.2000","article-title":"Host-pathogen interactions: Basic concepts of microbial commensalism, colonization, infection, and disease","volume":"68","author":"Casadevall","year":"2000","journal-title":"Infect. Immun."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e4507","DOI":"10.1002\/pro.4507","article-title":"Inhibition of a malaria host\u2013pathogen interaction by a computationally designed inhibitor","volume":"32","author":"Tobin","year":"2023","journal-title":"Protein Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"68","DOI":"10.4269\/ajtmh.2001.64.68","article-title":"Impact of Plasmodium falciparum malaria on performance and learning: Review of the evidence","volume":"64","author":"Holding","year":"2001","journal-title":"Am. J. Trop. Med. Hyg."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2183","DOI":"10.3389\/fmicb.2017.02183","article-title":"The promise of systems biology approaches for revealing host pathogen interactions in malaria","volume":"8","author":"Zuck","year":"2017","journal-title":"Front. Microbiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10930-021-10031-8","article-title":"Protein\u2013protein docking: Past, present, and future","volume":"41","author":"Sunny","year":"2022","journal-title":"Protein J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1771","DOI":"10.1093\/bioinformatics\/btu097","article-title":"ZDOCK server: Interactive docking prediction of protein\u2013protein complexes and symmetric multimers","volume":"30","author":"Pierce","year":"2014","journal-title":"Bioinformatics"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1002\/prot.10460","article-title":"RDOCK: Refinement of rigid-body protein docking predictions","volume":"53","author":"Li","year":"2003","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1698","DOI":"10.1093\/bioinformatics\/btt262","article-title":"pyDockWEB: A web server for rigid-body protein\u2013protein docking using electrostatics and desolvation scoring","volume":"29","author":"Pons","year":"2013","journal-title":"Bioinformatics"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chaudhury, S., Berrondo, M., Weitzner, B.D., Muthu, P., Bergman, H., and Gray, J.J. (2011). Benchmarking and analysis of protein docking performance in Rosetta v3.2. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0022477"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2386","DOI":"10.1093\/bioinformatics\/btw141","article-title":"FRODOCK 2.0: Fast protein\u2013protein docking server","volume":"32","year":"2016","journal-title":"Bioinformatics"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1829","DOI":"10.1038\/s41596-020-0312-x","article-title":"The HDOCK server for integrated protein\u2013protein docking","volume":"15","author":"Yan","year":"2020","journal-title":"Nat. Protoc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"W322","DOI":"10.1093\/nar\/gkz397","article-title":"HawkDock: A web server to predict and analyze the protein\u2013protein complex based on computational docking and MM\/GBSA","volume":"47","author":"Weng","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/j.bpj.2014.12.015","article-title":"A web interface for easy flexible protein-protein docking with ATTRACT","volume":"108","author":"Schindler","year":"2015","journal-title":"Biophys. J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1093\/nar\/28.1.235","article-title":"The protein data bank","volume":"28","author":"Berman","year":"2000","journal-title":"Nucleic Acids Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/S0022-2836(77)80200-3","article-title":"The Protein Data Bank: A computer-based archival file for macromolecular structures","volume":"112","author":"Bernstein","year":"1977","journal-title":"J. Mol. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1002\/jcc.20084","article-title":"UCSF Chimera\u2014A visualization system for exploratory research and analysis","volume":"25","author":"Pettersen","year":"2004","journal-title":"J. Comput. Chem."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"D439","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database: Massively expanding the structural coverage of protein-sequence space with high-accuracy models","volume":"50","author":"Varadi","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_24","unstructured":"Lab, P. (2023, April 12). Parasol Planning Library. Available online: https:\/\/github.com\/parasol-ppl\/ppl."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1146\/annurev.biophys.36.040306.132550","article-title":"Calculation of protein-ligand binding affinities","volume":"36","author":"Gilson","year":"2007","journal-title":"Annu. Rev. Biophys. Biomol. Struct."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.sbi.2018.09.007","article-title":"Elucidating binding mechanisms and dynamics of intrinsically disordered protein complexes using NMR spectroscopy","volume":"54","author":"Schneider","year":"2019","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"9614","DOI":"10.1073\/pnas.1512799112","article-title":"Conformational propensities of intrinsically disordered proteins influence the mechanism of binding and folding","volume":"112","author":"Arai","year":"2015","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"12219","DOI":"10.1021\/jacs.7b05823","article-title":"Structure and dynamics of an intrinsically disordered protein region that partially folds upon binding by chemical-exchange NMR","volume":"139","author":"Charlier","year":"2017","journal-title":"J. Am. Chem. Soc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1021\/jacs.7b12407","article-title":"Deciphering the dynamic interaction profile of an intrinsically disordered protein by NMR exchange spectroscopy","volume":"140","author":"Delaforge","year":"2018","journal-title":"J. Am. Chem. Soc."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.2174\/1568026619666181224101744","article-title":"Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes","volume":"18","author":"Antunes","year":"2018","journal-title":"Curr. Top. Med. Chem."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/S0959-440X(02)00285-3","article-title":"Prediction of protein-protein interactions by docking methods","volume":"12","author":"Smith","year":"2002","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1016\/j.bpj.2014.08.033","article-title":"Protein-protein docking: From interaction to interactome","volume":"107","author":"Vakser","year":"2014","journal-title":"Biophys. J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"11569","DOI":"10.3390\/molecules200611569","article-title":"Surfing the protein-protein interaction surface using docking methods: Application to the design of PPI inhibitors","volume":"20","author":"Sable","year":"2015","journal-title":"Molecules"},{"key":"ref_34","first-page":"1","article-title":"Recent advances in the development of protein\u2013protein interactions modulators: Mechanisms and clinical trials","volume":"5","author":"Lu","year":"2020","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.cbpa.2019.07.003","article-title":"Bifunctional chemical probes inducing protein\u2013protein interactions","volume":"52","author":"Maniaci","year":"2019","journal-title":"Curr. Opin. Chem. Biol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1038\/s41467-022-28865-w","article-title":"Improved prediction of protein-protein interactions using AlphaFold2","volume":"13","author":"Bryant","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1592","DOI":"10.1109\/TCBB.2021.3050102","article-title":"DPCMNE: Detecting protein complexes from protein-protein interaction networks via multi-level network embedding","volume":"19","author":"Meng","year":"2021","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Devaurs, D., Antunes, D.A., Hall-Swan, S., Mitchell, N., Moll, M., Liz\u00e9e, G., and Kavraki, L.E. (2019). Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins. BMC Mol. Cell Biol., 20.","DOI":"10.1186\/s12860-019-0218-z"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.sbi.2008.01.004","article-title":"Flexible ligand docking to multiple receptor conformations: A practical alternative","volume":"18","author":"Totrov","year":"2008","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1016\/j.str.2020.06.006","article-title":"Performance and its limits in rigid body protein-protein docking","volume":"28","author":"Desta","year":"2020","journal-title":"Structure"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1042\/ETLS20210225","article-title":"Graph representation learning for structural proteomics","volume":"5","author":"Fasoulis","year":"2021","journal-title":"Emerg. Top. Life Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3968","DOI":"10.1093\/bioinformatics\/btac440","article-title":"Topological analysis as a tool for detection of abnormalities in protein-protein interaction data","volume":"38","author":"Nowakowska","year":"2022","journal-title":"Bioinformatics"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1038\/s42256-020-0149-6","article-title":"A topology-based network tree for the prediction of protein\u2013protein binding affinity changes following mutation","volume":"2","author":"Wang","year":"2020","journal-title":"Nat. Mach. Intell."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Chen, K.H., Wang, T.F., and Hu, Y.J. (2019). Protein-protein interaction prediction using a hybrid feature representation and a stacked generalization scheme. BMC Bioinform., 20.","DOI":"10.1186\/s12859-019-2907-1"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3185","DOI":"10.1007\/s00018-017-2561-6","article-title":"To be disordered or not to be disordered: Is that still a question for proteins in the cell?","volume":"74","author":"Pauwels","year":"2017","journal-title":"Cell. Mol. Life Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1016\/j.sbi.2013.02.007","article-title":"Describing intrinsically disordered proteins at atomic resolution by NMR","volume":"23","author":"Jensen","year":"2013","journal-title":"Curr. Opin. Struct. Biol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"18314","DOI":"10.1021\/ja904716h","article-title":"Determination of the free energy landscape of \u03b1-synuclein using spin label nuclear magnetic resonance measurements","volume":"131","author":"Allison","year":"2009","journal-title":"J. Am. Chem. Soc."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.pnmrs.2018.07.001","article-title":"Characterization of intrinsically disordered proteins and their dynamic complexes: From in vitro to cell-like environments","volume":"109","author":"Milles","year":"2018","journal-title":"Prog. Nucl. Magn. Reson. Spectrosc."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.drudis.2018.09.017","article-title":"Targeting intrinsically disordered proteins at the edge of chaos","volume":"24","author":"Ruan","year":"2019","journal-title":"Drug Discov. Today"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"e4334","DOI":"10.1002\/pro.4334","article-title":"Topological dynamics of an intrinsically disordered N-terminal domain of the human androgen receptor","volume":"31","author":"Sheikhhassani","year":"2022","journal-title":"Protein Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.cosrev.2012.07.002","article-title":"Motion planning algorithms for molecular simulations: A survey","volume":"6","year":"2012","journal-title":"Comput. Sci. Rev."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Ekenna, C., Thomas, S., and Amato, N.M. (2016). Adaptive local learning in sampling based motion planning for protein folding. BMC Syst. Biol., 10.","DOI":"10.1186\/s12918-016-0297-9"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Adamson, T., Camarena, J.A., Tapia, L., and Jacobson, B. (2019, January 18\u201321). Optimizing low energy pathways in receptor-ligand binding with motion planning. Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, CA, USA.","DOI":"10.1109\/BIBM47256.2019.8983169"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Upadhyay, A., Tran, T., and Ekenna, C. (2021, January 9\u201312). A topology approach towards modeling activities and properties on a biomolecular surface. Proceedings of the BIBM: IEEE International Conference on Bioinformatics and Biomedicine, Houston, TX, USA.","DOI":"10.1109\/BIBM52615.2021.9669313"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1007\/s10846-018-0877-6","article-title":"Sampling-based motion planning for tracking evolution of dynamic tunnels in molecular dynamics simulations","volume":"93","year":"2019","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_56","unstructured":"LaValle, S.M. (1998). Rapidly-Exploring Random Trees: A New Tool for Path Planning, Department of Computer Science, Iowa State University. Research Report 9811."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Afrasiabi, F., and Haspel, N. (2020, January 21\u201324). Efficient exploration of protein conformational pathways using rrt* and mc. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Virtual.","DOI":"10.1145\/3388440.3414705"},{"key":"ref_58","unstructured":"Estana, A. (2020). Algorithms and Computational Tools for the Study of Intrinsically Disordered Proteins. [Ph.D. Thesis, Institut National des Sciences Appliqu\u00e9es de Toulouse]."},{"key":"ref_59","unstructured":"Upadhyay, A., Goldfarb, B., Wang, W., and Ekenna, C. (2023). International Workshop on the Algorithmic Foundations of Robotics, Springer."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Upadhyay, A., Wang, W., and Ekenna, C. (2019, January 3\u20138). Approximating C free Space Topology by Constructing Vietoris-Rips Complex. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China.","DOI":"10.1109\/IROS40897.2019.8968148"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Upadhyay, A., Goldfarb, B., and Ekenna, C. (2022, January 23\u201327). Incremental Path Planning Algorithm via Topological Mapping with Metric Gluing. Proceedings of the 2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan.","DOI":"10.1109\/IROS47612.2022.9981379"}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/24\/14\/11785\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:17:02Z","timestamp":1760127422000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/24\/14\/11785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,22]]},"references-count":61,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["ijms241411785"],"URL":"https:\/\/doi.org\/10.3390\/ijms241411785","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,22]]}}}