{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T19:36:19Z","timestamp":1784576179007,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T00:00:00Z","timestamp":1650931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["20K19917"],"award-info":[{"award-number":["20K19917"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009619","name":"Japan Agency for Medical Research and Development","doi-asserted-by":"publisher","award":["JP20am0101112"],"award-info":[{"award-number":["JP20am0101112"]}],"id":[{"id":"10.13039\/100009619","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001700","name":"Ministry of Education, Culture, Sports, Science and Technology","doi-asserted-by":"publisher","award":["Program for Building Regional Innovation Ecosystems \u2018Program to Industrialize an Innovative Middle Molecule Drug Discovery Flow through Fusion of Computational Drug Design and Chemical Synthesis Technology\u2019"],"award-info":[{"award-number":["Program for Building Regional Innovation Ecosystems \u2018Program to Industrialize an Innovative Middle Molecule Drug Discovery Flow through Fusion of Computational Drug Design and Chemical Synthesis Technology\u2019"]}],"id":[{"id":"10.13039\/501100001700","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>To ensure efficiency in discovery and development, the application of computational technology is essential. Although virtual screening techniques are widely applied in the early stages of drug discovery research, the computational methods used in lead optimization to improve activity and reduce the toxicity of compounds are still evolving. In this study, we propose a method to construct the residue interaction profile of the chemical structure used in the lead optimization by performing \u201cinverse\u201d mixed-solvent molecular dynamics (MSMD) simulation. Contrary to constructing a protein-based, atom interaction profile, we constructed a probe-based, protein residue interaction profile using MSMD trajectories. It provides us the profile of the preferred protein environments of probes without co-crystallized structures. We assessed the method using three probes: benzamidine, catechol, and benzene. As a result, the residue interaction profile of each probe obtained by MSMD was a reasonable physicochemical description of the general non-covalent interaction. Moreover, comparison with the X-ray structure containing each probe as a ligand shows that the map of the interaction profile matches the arrangement of amino acid residues in the X-ray structure.<\/jats:p>","DOI":"10.3390\/ijms23094749","type":"journal-article","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T11:45:55Z","timestamp":1650973555000},"page":"4749","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Inverse Mixed-Solvent Molecular Dynamics for Visualization of the Residue Interaction Profile of Molecular Probes"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0224-0035","authenticated-orcid":false,"given":"Keisuke","family":"Yanagisawa","sequence":"first","affiliation":[{"name":"Department of Computer Science, School of Computing, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku 152-8550, Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryunosuke","family":"Yoshino","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"},{"name":"Transborder Medical Research Center, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Ibaraki, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4727-7002","authenticated-orcid":false,"given":"Genki","family":"Kudo","sequence":"additional","affiliation":[{"name":"Physics Department, Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8571, Ibaraki, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takatsugu","family":"Hirokawa","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"},{"name":"Transborder Medical Research Center, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Ibaraki, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,26]]},"reference":[{"key":"ref_1","first-page":"939","article-title":"An overview of drug discovery and development","volume":"12","author":"Berdigaliyev","year":"2020","journal-title":"Future Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yoshino, R., Yasuo, N., Inaoka, D.K., Hagiwara, Y., Ohno, K., Orita, M., Inoue, M., Shiba, T., Harada, S., and Honma, T. (2015). Pharmacophore Modeling for Anti-Chagas Drug Design Using the Fragment Molecular Orbital Method. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0125829"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6666","DOI":"10.1038\/s41598-017-06411-9","article-title":"In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease","volume":"7","author":"Yoshino","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"17209","DOI":"10.1038\/srep17209","article-title":"Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target","volume":"5","author":"Chiba","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"12038","DOI":"10.1038\/s41598-017-10275-4","article-title":"An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes","volume":"7","author":"Chiba","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"108730","DOI":"10.1016\/j.abb.2020.108730","article-title":"Artificial intelligence in the early stages of drug discovery","volume":"698","author":"Cavasotto","year":"2021","journal-title":"Arch. Biochem. Biophys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/978-1-0716-0826-5_6","article-title":"Computational Approaches for De Novo Drug Design: Past, Present, and Future","volume":"Volume 2190","author":"Cartwright","year":"2021","journal-title":"Methods in Molecular Biology"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lin, X., Li, X., and Lin, X. (2020). A Review on Applications of Computational Methods in Drug Screening and Design. Molecules, 25.","DOI":"10.3390\/molecules25061375"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kimber, T.B., Chen, Y., and Volkamer, A. (2021). Deep Learning in Virtual Screening: Recent Applications and Developments. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22094435"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"343","DOI":"10.3389\/fchem.2020.00343","article-title":"Structure-Based Virtual Screening: From Classical to Artificial Intelligence","volume":"8","author":"Maia","year":"2020","journal-title":"Front. Chem."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1528","DOI":"10.1021\/cb5001636","article-title":"Increasing Chemical Space Coverage by Combining Empirical and Computational Fragment Screens","volume":"9","author":"Barelier","year":"2014","journal-title":"ACS Chem. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tidten-Luksch, N., Grimaldi, R., Torrie, L.S., Frearson, J.A., Hunter, W.N., and Brenk, R. (2012). IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0035792"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2701","DOI":"10.1021\/ci4003156","article-title":"Complementarity between in Silico and Biophysical Screening Approaches in Fragment-Based Lead Discovery against the A2A Adenosine Receptor","volume":"53","author":"Chen","year":"2013","journal-title":"J. Chem. Inf. Model."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4302","DOI":"10.1021\/acs.jmedchem.5b01974","article-title":"A Prospective Virtual Screening Study: Enriching Hit Rates and Designing Focus Libraries to Find Inhibitors of PI3K\u03b4 and PI3K\u03b3","volume":"59","author":"Bembenek","year":"2016","journal-title":"J. Med. Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"021914","DOI":"10.1103\/PhysRevE.79.021914","article-title":"Massively parallel computation of absolute binding free energy with well-equilibrated states","volume":"79","author":"Fujitani","year":"2009","journal-title":"Phys. Rev. E"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1021\/acs.accounts.7b00083","article-title":"Advancing Drug Discovery through Enhanced Free Energy Calculations","volume":"50","author":"Abel","year":"2017","journal-title":"Acc. Chem. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3120","DOI":"10.1021\/acs.jcim.0c00165","article-title":"Assessment of Binding Affinity via Alchemical Free-Energy Calculations","volume":"60","author":"Kuhn","year":"2020","journal-title":"J. Chem. Inf. Model."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5520","DOI":"10.1021\/acs.chemrev.5b00630","article-title":"Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods","volume":"116","author":"Ryde","year":"2016","journal-title":"Chem. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"D301","DOI":"10.1093\/nar\/gkl971","article-title":"The worldwide Protein Data Bank (wwPDB): Ensuring a single, uniform archive of PDB data","volume":"35","author":"Berman","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1021\/jm061038a","article-title":"Propensities of Polar and Aromatic Amino Acids in Noncanonical Interactions:\u2009 Nonbonded Contacts Analysis of Protein\u2212Ligand Complexes in Crystal Structures","volume":"50","author":"Imai","year":"2007","journal-title":"J. Med. Chem."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1021\/ci100386y","article-title":"Residue Preference Mapping of Ligand Fragments in the Protein Data Bank","volume":"51","author":"Wang","year":"2011","journal-title":"J. Chem. Inf. Model."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1021\/ci300377f","article-title":"Comprehensive Classification and Diversity Assessment of Atomic Contacts in Protein\u2013Small Ligand Interactions","volume":"53","author":"Kasahara","year":"2013","journal-title":"J. Chem. Inf. Model."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"19118","DOI":"10.1038\/s41598-019-55394-2","article-title":"Cosolvent Analysis Toolkit (CAT): A robust hotspot identification platform for cosolvent simulations of proteins to expand the druggable proteome","volume":"9","author":"Zariquiey","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1021\/acs.jcim.7b00487","article-title":"Large-Scale Validation of Mixed-Solvent Simulations to Assess Hotspots at Protein\u2212Protein Interaction Interfaces","volume":"58","author":"Ghanakota","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3331","DOI":"10.1021\/acs.jctc.8b01295","article-title":"Cosolvent-Enhanced Sampling and Unbiased Identification of Cryptic Pockets Suitable for Structure-Based Drug Design","volume":"15","author":"Schmidt","year":"2019","journal-title":"J. Chem. Theory Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1021\/acs.jcim.6b00623","article-title":"Deciphering Cryptic Binding Sites on Proteins by Mixed-Solvent Molecular Dynamics","volume":"57","author":"Kimura","year":"2017","journal-title":"J. Chem. Inf. Model."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1021\/ci7002363","article-title":"Identification of the Druggable Concavity in Homology Models Using the PLB Index","volume":"47","author":"Soga","year":"2007","journal-title":"J. Chem. Inf. Model."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1002\/prot.10613","article-title":"A Hierarchical Approach to All-Atom Protein Loop Prediction","volume":"55","author":"Jacobson","year":"2004","journal-title":"Proteins Struct. Funct. Genet."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1021\/ct100578z","article-title":"PROPKA3: Consistent treatment of internal and surface residues in empirical pKa predictions","volume":"7","author":"Olsson","year":"2011","journal-title":"J. Chem. Theory Comput."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1002\/wcms.1121","article-title":"An overview of the Amber biomolecular simulation package","volume":"3","author":"Case","year":"2013","journal-title":"Wiley Interdiscip. Rev. Comput. Mol. Sci."},{"key":"ref_31","unstructured":"Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A., Cheeseman, J.R., Scalmani, G., Barone, V., Petersson, G.A., and Nakatsuji, H. (2016). Gaussian 16, Gaussian Inc.. Revision B.01."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2744","DOI":"10.1021\/acs.jcim.1c00134","article-title":"EXPRORER: Rational Cosolvent Set Construction Method for Cosolvent Molecular Dynamics Using Large-Scale Computation","volume":"61","author":"Yanagisawa","year":"2021","journal-title":"J. Chem. Inf. Model."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2157","DOI":"10.1002\/jcc.21224","article-title":"PACKMOL: A package for building initial configurations for molecular dynamics simulations","volume":"30","author":"Andrade","year":"2009","journal-title":"J. Comput. Chem."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1063\/1.445869","article-title":"Comparison of simple potential functions for simulating liquid water","volume":"79","author":"Jorgensen","year":"1983","journal-title":"J. Chem. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1021\/ct700200b","article-title":"P-LINCS: A parallel linear constraint solver for molecular simulation","volume":"4","author":"Hess","year":"2008","journal-title":"J. Chem. Theory Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"014101","DOI":"10.1063\/1.2408420","article-title":"Canonical sampling through velocity rescaling","volume":"126","author":"Bussi","year":"2007","journal-title":"J. Chem. Phys."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.cpc.2008.01.006","article-title":"Stochastic thermostats: Comparison of local and global schemes","volume":"179","author":"Bussi","year":"2008","journal-title":"Comput. Phys. Commun."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"074101","DOI":"10.1063\/1.3073889","article-title":"Isothermal-isobaric molecular dynamics using stochastic velocity rescaling","volume":"130","author":"Bussi","year":"2009","journal-title":"J. Chem. Phys."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3684","DOI":"10.1063\/1.448118","article-title":"Molecular dynamics with coupling to an external bath","volume":"81","author":"Berendsen","year":"1984","journal-title":"J. Chem. Phys."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.softx.2015.06.001","article-title":"Gromacs: High performance molecular simulations through multi-level parallelism from laptops to super-computers","volume":"1\u20132","author":"Abraham","year":"2015","journal-title":"SoftwareX"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s10822-016-9977-1","article-title":"Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset","volume":"31","author":"Shirts","year":"2017","journal-title":"J. Comput. Aided Mol. Des."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"7182","DOI":"10.1063\/1.328693","article-title":"Polymorphic transitions in single crystals: A new molecular dynamics method","volume":"52","author":"Parrinello","year":"1981","journal-title":"J. Appl. Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"129519","DOI":"10.1016\/j.bbagen.2020.129519","article-title":"Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots)","volume":"1864","author":"MacKerell","year":"2020","journal-title":"Biochim. Biophys. Acta Gen. Subj."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1093\/bioinformatics\/btp163","article-title":"Biopython: Freely available Python tools for computational molecular biology and bioinformatics","volume":"25","author":"Cock","year":"2009","journal-title":"Bioinformatics"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5845","DOI":"10.1021\/jm4017625","article-title":"Rings in drugs","volume":"57","author":"Richard","year":"2014","journal-title":"J. Med. Chem."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1002\/cmdc.201200512","article-title":"Efficient Stacking on Protein Amide Fragments","volume":"8","author":"Harder","year":"2013","journal-title":"ChemMedChem"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2035","DOI":"10.1021\/acs.jcim.8b00925","article-title":"Free Energies and Entropies of Binding Sites Identified by MixMD Cosolvent Simulations","volume":"59","author":"Ghanakota","year":"2019","journal-title":"J. Chem. Inf. Model."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/23\/9\/4749\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:01:06Z","timestamp":1760137266000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/23\/9\/4749"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,26]]},"references-count":47,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["ijms23094749"],"URL":"https:\/\/doi.org\/10.3390\/ijms23094749","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,26]]}}}