{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:06:34Z","timestamp":1760144794599,"version":"build-2065373602"},"reference-count":83,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T00:00:00Z","timestamp":1715212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CONAHCyT","award":["251726"],"award-info":[{"award-number":["251726"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies of natural and synthetic auxins have been made in an effort to understand their role in plant growth. However, molecular details of the binding and recognition process are still an open question. Herein, we present a comprehensive in silico pipeline for the assessment of TIR1 ligands using several structure-based methods. Our results suggest that subtle dynamics within the binding pocket arise from water\u2013ligand interactions. We also show that this trait distinguishes effective binders. Finally, we construct a database of putative ligands and decoy compounds, which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1.<\/jats:p>","DOI":"10.3390\/computation12050094","type":"journal-article","created":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T05:25:47Z","timestamp":1715318747000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus In Silico Approaches"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0054-0862","authenticated-orcid":false,"given":"Fernando D.","family":"Prieto-Mart\u00ednez","sequence":"first","affiliation":[{"name":"Instituto de Qu\u00edmica Unidad M\u00e9rida, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Carretera M\u00e9rida-Tetiz, Km. 4.5, Uc\u00fa 97357, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0041-891X","authenticated-orcid":false,"given":"Jennifer","family":"Mendoza-Ca\u00f1as","sequence":"additional","affiliation":[{"name":"Facultad de Qu\u00edmica, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Avenida Universidad 3000, Mexico City 04510, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karina","family":"Mart\u00ednez-Mayorga","sequence":"additional","affiliation":[{"name":"Instituto de Qu\u00edmica Unidad M\u00e9rida, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Carretera M\u00e9rida-Tetiz, Km. 4.5, Uc\u00fa 97357, Mexico"},{"name":"Instituto de Investigaciones en Matem\u00e1ticas Aplicadas y en Sistemas, Unidad M\u00e9rida, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Sierra Papacal, M\u00e9rida 97302, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"key":"ref_1","unstructured":"Ritchie, H., Rosado, P., and Roser, M. (2024, March 17). Agricultural Production. Our World in Data, January 2023. Available online: https:\/\/ourworldindata.org\/agricultural-production."},{"key":"ref_2","unstructured":"(2024, March 17). 2.1 Food Security Indicators\u2014Latest Updates and Progress towards Ending Hunger and Ensuring Food Security. Available online: https:\/\/www.fao.org\/3\/cc0639en\/online\/sofi-2022\/food-security-nutrition-indicators.html."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Carvalho-Moore, P., Rangani, G., Heiser, J., Findley, D., Bowe, S.J., and Roma-Burgos, N. (2021). PPO2 Mutations in Amaranthus palmeri: Implications on Cross-Resistance. Agriculture, 11.","DOI":"10.3390\/agriculture11080760"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1614\/WS-D-13-00109.1","article-title":"Lessons Learned From the History of Herbicide Resistance","volume":"62","author":"Shaner","year":"2014","journal-title":"Weed Sci."},{"key":"ref_5","unstructured":"Heap, I. (2024, February 01). The International Survey of Herbicide Resistant Weeds. Available online: http:\/\/www.weedscience.com\/Home.aspx."},{"key":"ref_6","unstructured":"Gupta, R.C. (2017). Reproductive and Developmental Toxicology, Academic Press. [2nd ed.]."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Amaresan, N., Patel, P., and Amin, D. (2022). Practical Handbook on Agricultural Microbiology, Springer.","DOI":"10.1007\/978-1-0716-1724-3"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1038\/nrm2020","article-title":"Auxin in action: Signalling, transport and the control of plant growth and development","volume":"7","author":"Teale","year":"2006","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1021\/cb200404c","article-title":"Rational Design of an Auxin Antagonist of the SCFTIR1 Auxin Receptor Complex","volume":"7","author":"Hayashi","year":"2012","journal-title":"ACS Chem. Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1007\/s00344-003-0020-0","article-title":"Mediation of Herbicide Effects by Hormone Interactions","volume":"22","author":"Grossmann","year":"2003","journal-title":"J. Plant Growth Regul."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1104\/pp.113.215582","article-title":"Mutations in the TIR1 Auxin Receptor That Increase Affinity for Auxin\/Indole-3-Acetic Acid Proteins Result in Auxin Hypersensitivity","volume":"162","author":"Yu","year":"2013","journal-title":"Plant Physiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.tplants.2004.04.003","article-title":"Auxin signaling and regulated protein degradation","volume":"9","author":"Dharmasiri","year":"2004","journal-title":"Trends Plant Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.pbi.2014.06.006","article-title":"Diversity and specificity: Auxin perception and signaling through the TIR1\/AFB pathway","volume":"21","author":"Wang","year":"2014","journal-title":"Curr. Opin. Plant Biol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"110631","DOI":"10.1016\/j.plantsci.2020.110631","article-title":"Synthetic auxin herbicides: Finding the lock and key to weed resistance","volume":"300","author":"Todd","year":"2020","journal-title":"Plant Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1093\/jxb\/erx375","article-title":"Auxin signaling: A big question to be addressed by small molecules","volume":"69","author":"Ma","year":"2018","journal-title":"J. Exp. Bot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4171","DOI":"10.1021\/acs.jmedchem.5b00886","article-title":"OpenGrowth: An Automated and Rational Algorithm for Finding New Protein Ligands","volume":"59","author":"Jasty","year":"2016","journal-title":"J. Med. Chem."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2134","DOI":"10.1093\/bioinformatics\/btab080","article-title":"Generating property-matched decoy molecules using deep learning","volume":"37","author":"Imrie","year":"2021","journal-title":"Bioinformatics"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s13321-018-0258-y","article-title":"Mordred: A molecular descriptor calculator","volume":"10","author":"Moriwaki","year":"2018","journal-title":"J. Cheminform."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i11","article-title":"Feature selection with the Boruta package","volume":"36","author":"Kursa","year":"2010","journal-title":"J. Stat. Softw."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1021\/ci500588j","article-title":"DataWarrior: An Open-Source Program For Chemistry Aware Data Visualization And Analysis","volume":"55","author":"Sander","year":"2015","journal-title":"J. Chem. Inf. Model."},{"key":"ref_21","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_23","first-page":"100008","article-title":"An in silico pipeline for the discovery of multitarget ligands: A case study for epi-polypharmacology based on DNMT1\/HDAC2 inhibition","volume":"1","year":"2021","journal-title":"Artif. Intell. Life Sci."},{"key":"ref_24","unstructured":"Landrum, G., Tosco, P., Kelley, B., Cosgrove, D., Vianello, R., and Jones, G. (2024). rdkit\/rdkit: 2024_03_1 (Q1 2024) Release Beta, Zenodo."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2542","DOI":"10.1021\/acs.biochem.8b01300","article-title":"K-RasG12D Has a Potential Allosteric Small Molecule Binding Site","volume":"58","author":"Feng","year":"2019","journal-title":"Biochemistry"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10383","DOI":"10.1021\/acs.jmedchem.6b00399","article-title":"Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics: Miniperspective","volume":"59","author":"Ghanakota","year":"2016","journal-title":"J. Med. Chem."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Barrera-T\u00e9llez, F.J., Prieto-Mart\u00ednez, F.D., Hern\u00e1ndez-Campos, A., Mart\u00ednez-Mayorga, K., and Castillo-Bocanegra, R. (2023). In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms242216046"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1016\/S1074-5521(96)90164-7","article-title":"Just add water! The effect of water on the specificity of protein-ligand binding sites and its potential application to drug design","volume":"3","author":"Ladbury","year":"1996","journal-title":"Chem. Biol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.bmc.2017.10.042","article-title":"Exploiting a water network to achieve enthalpy-driven, bromodomain-selective BET inhibitors","volume":"26","author":"Shadrick","year":"2018","journal-title":"Bioorganic Med. Chem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1021\/acs.jctc.1c00590","article-title":"Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques","volume":"18","author":"Ge","year":"2022","journal-title":"J. Chem. Theory Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6209","DOI":"10.1021\/acs.jcim.2c01142","article-title":"Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein\u2013Ligand Binding Poses","volume":"62","author":"Lukauskis","year":"2022","journal-title":"J. Chem. Inf. Model."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bowers, K., Chow, E., Xu, H., Dror, R., Eastwood, M., Gregersen, B., Klepeis, J., Kolossvary, I., Moraes, M., and Sacerdoti, F. (2006, January 11\u201317). Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters. Proceedings of the ACM\/IEEE SC 2006 Conference (SC\u201906), Tampa, FL, USA.","DOI":"10.1109\/SC.2006.54"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"224117","DOI":"10.1063\/5.0021496","article-title":"Midtown splines: An optimal charge assignment for electrostatics calculations","volume":"153","author":"Predescu","year":"2020","journal-title":"J. Chem. Phys."},{"key":"ref_34","unstructured":"McGibbon, R.T., Harrigan, M., Beauchamp, K., Klein, C., Swails, J., Hern\u00e1ndez, C., Scherer, M.K., Schwantes, C. (2019). Mdtraj\/mdtraj: MDTraj 1.9 2017, Zenodo."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/s42004-018-0019-x","article-title":"Large-scale analysis of water stability in bromodomain binding pockets with grand canonical Monte Carlo","volume":"1","author":"Aldeghi","year":"2018","journal-title":"Commun. Chem."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.cbpa.2011.05.021","article-title":"Free energy calculations of protein-ligand interactions","volume":"15","author":"Oostenbrink","year":"2011","journal-title":"Curr. Opin. Chem. Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4436","DOI":"10.1021\/acs.jcim.0c00648","article-title":"grand: A Python Module for Grand Canonical Water Sampling in OpenMM","volume":"60","author":"Samways","year":"2020","journal-title":"J. Chem. Inf. Model."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1021\/acs.jcim.8b00271","article-title":"Placement of Water Molecules in Protein Structures: From Large-Scale Evaluations to Single-Case Examples","volume":"58","author":"Nittinger","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1007\/s10822-019-00240-w","article-title":"Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4","volume":"33","author":"Sasmal","year":"2019","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1021\/cb400618m","article-title":"Defining Binding Efficiency and Specificity of Auxins for SCFTIR1\/AFB-Aux\/IAA Co-receptor Complex Formation","volume":"9","author":"Lee","year":"2014","journal-title":"ACS Chem. Biol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"125402","DOI":"10.1016\/j.jhazmat.2021.125402","article-title":"Diclofenac modified the root system architecture of Arabidopsis via interfering with the hormonal activities of auxin","volume":"413","author":"Cho","year":"2021","journal-title":"J. Hazard. Mater."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"P25","DOI":"10.1186\/1758-2946-2-S1-P25","article-title":"Ensemble docking revisited","volume":"2","author":"Korb","year":"2010","journal-title":"J. Cheminform."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1021\/ci800298z","article-title":"Empirical scoring functions for advanced Protein-Ligand docking with PLANTS","volume":"49","author":"Korb","year":"2009","journal-title":"J. Chem. Inf. Model."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.1021\/acs.jcim.8b00329","article-title":"Novel Consensus Docking Strategy to Improve Ligand Pose Prediction","volume":"58","author":"Ren","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3584","DOI":"10.1021\/acs.jcim.9b00383","article-title":"Getting Docking into Shape Using Negative Image-Based Rescoring","volume":"59","author":"Kurkinen","year":"2019","journal-title":"J. Chem. Inf. Model."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1021\/ci800420z","article-title":"Influence of Protonation, Tautomeric, and Stereoisomeric States on Protein\u2212Ligand Docking Results","volume":"49","author":"Exner","year":"2009","journal-title":"J. Chem. Inf. Model."},{"key":"ref_47","unstructured":"Swenson, D.W.H., Roet, S., and Faruk, N. (2020). Dwhswenson\/contact_map: Contact_map 0.7.0, Zenodo."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1038\/s42254-020-0153-0","article-title":"Using metadynamics to explore complex free-energy landscapes","volume":"2","author":"Bussi","year":"2020","journal-title":"Nat. Rev. Phys."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4807","DOI":"10.1021\/jp803936q","article-title":"Exploring Complex Protein\u2212Ligand Recognition Mechanisms with Coarse Metadynamics","volume":"113","author":"Masetti","year":"2009","journal-title":"J. Phys. Chem. B"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bonomi, M., and Camilloni, C. (2019). Biomolecular Simulations: Methods and Protocols, Springer.","DOI":"10.1007\/978-1-4939-9608-7"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1038\/s41596-020-0342-4","article-title":"Ligand binding free-energy calculations with funnel metadynamics","volume":"15","author":"Raniolo","year":"2020","journal-title":"Nat. Protoc."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2024","DOI":"10.1038\/s41598-022-05875-8","article-title":"A highly accurate metadynamics-based Dissociation Free Energy method to calculate protein\u2013protein and protein\u2013ligand binding potencies","volume":"12","author":"Wang","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Uzunova, V.V., Quareshy, M., del Genio, C.I., and Napier, R.M. (2016). Tomographic docking suggests the mechanism of auxin receptor TIR1 selectivity. Open Biol., 6.","DOI":"10.1101\/081794"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.addr.2016.01.018","article-title":"Molecular inflation, attrition and the rule of five","volume":"101","author":"Leeson","year":"2015","journal-title":"Adv. Drug Deliv. Rev."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1038\/nrd4163","article-title":"The role of ligand efficiency metrics in drug discovery","volume":"13","author":"Hopkins","year":"2014","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1021\/ci060117s","article-title":"On Outliers and Activity CliffsWhy QSAR Often Disappoints","volume":"46","author":"Maggiora","year":"2006","journal-title":"J. Chem. Inf. Model."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"14360","DOI":"10.1021\/acsomega.9b02221","article-title":"Evolving Concept of Activity Cliffs","volume":"4","author":"Stumpfe","year":"2019","journal-title":"ACS Omega"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1007\/s10822-020-00315-z","article-title":"Advances in exploring activity cliffs","volume":"34","author":"Stumpfe","year":"2020","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0169-409X(00)00129-0","article-title":"Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1","volume":"46","author":"Lipinski","year":"2001","journal-title":"Adv. Drug Deliv. Rev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1701","DOI":"10.1021\/acs.jmedchem.8b00686","article-title":"Two Decades under the Influence of the Rule of Five and the Changing Properties of Approved Oral Drugs","volume":"62","author":"Shultz","year":"2019","journal-title":"J. Med. Chem."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1870","DOI":"10.1021\/acs.jcim.8b00400","article-title":"Prospectively Validated Proteochemometric Models for the Prediction of Small-Molecule Binding to Bromodomain Proteins","volume":"58","author":"Giblin","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"6174","DOI":"10.1039\/C5CP00288E","article-title":"A review of methods for the calculation of solution free energies and the modelling of systems in solution","volume":"17","author":"Skyner","year":"2015","journal-title":"Phys. Chem. Chem. Phys."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Pardalos, P.M., Boginski, V.L., and Vazacopoulos, A. (2007). Data Mining in Biomedicine, Springer.","DOI":"10.1007\/978-0-387-69319-4"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1517\/17460441.2016.1146250","article-title":"Use of machine learning approaches for novel drug discovery","volume":"11","author":"Lima","year":"2016","journal-title":"Expert Opin. Drug Discov."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.comtox.2018.07.002","article-title":"Utilizing Threshold of Toxicological Concern (TTC) with high throughput exposure predictions (HTE) as a risk-based prioritization approach for thousands of chemicals","volume":"7","author":"Patlewicz","year":"2018","journal-title":"Comput. Toxicol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"2650","DOI":"10.1021\/ci2001549","article-title":"DEKOIS: Demanding Evaluation Kits for Objective in Silico Screening\u2014A Versatile Tool for Benchmarking Docking Programs and Scoring Functions","volume":"51","author":"Vogel","year":"2011","journal-title":"J. Chem. Inf. Model."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1021\/acs.jcim.0c00598","article-title":"Property-Unmatched Decoys in Docking Benchmarks","volume":"61","author":"Stein","year":"2021","journal-title":"J. Chem. Inf. Model."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1021\/ci300493w","article-title":"ID-Score: A New Empirical Scoring Function Based on a Comprehensive Set of Descriptors Related to Protein\u2013Ligand Interactions","volume":"53","author":"Li","year":"2013","journal-title":"J. Chem. Inf. Model."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"4540","DOI":"10.1021\/acs.jcim.9b00645","article-title":"Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions","volume":"59","author":"Lu","year":"2019","journal-title":"J. Chem. Inf. Model."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.str.2009.02.010","article-title":"Binding of Small-Molecule Ligands to Proteins: \u201cWhat You See\u201d Is Not Always \u201cWhat You Get\u201d","volume":"17","author":"Mobley","year":"2009","journal-title":"Structure"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2514","DOI":"10.1021\/acs.jcim.7b00412","article-title":"Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study","volume":"57","author":"Liu","year":"2017","journal-title":"J. Chem. Inf. Model."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1093\/bioinformatics\/btp036","article-title":"Fragment-based identification of druggable \u2018hot spots\u2019 of proteins using Fourier domain correlation techniques","volume":"25","author":"Brenke","year":"2009","journal-title":"Bioinformatics"},{"key":"ref_73","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\u2013Protein Interaction Interfaces","volume":"58","author":"Ghanakota","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Hao, G.-F., and Yang, G.-F. (2010). The Role of Phe82 and Phe351 in Auxin-Induced Substrate Perception by TIR1 Ubiquitin Ligase: A Novel Insight from Molecular Dynamics Simulations. PLoS ONE, 5.","DOI":"10.1371\/journal.pone.0010742"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1038\/nature05731","article-title":"Mechanism of auxin perception by the TIR1 ubiquitin ligase","volume":"446","author":"Tan","year":"2007","journal-title":"Nature"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1146\/annurev.cellbio.23.090506.123214","article-title":"Auxin receptors and plant development: A new signaling paradigm","volume":"24","author":"Mockaitis","year":"2008","journal-title":"Annu. Rev. Cell Dev. Biol."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Ju\u00e1rez-Mercado, K.E., Prieto-Mart\u00ednez, F.D., S\u00e1nchez-Cruz, N., Pe\u00f1a-Castillo, A., Prada-Gracia, D., and Medina-Franco, J.L. (2021). Expanding the Structural Diversity of DNA Methyltransferase Inhibitors. Pharmaceuticals, 14.","DOI":"10.3390\/ph14010017"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.1021\/acs.jctc.9b01211","article-title":"Defining, Calculating, and Converging Observables of a Kinetic Transition Network","volume":"16","author":"Swinburne","year":"2020","journal-title":"J. Chem. Theory Comput."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"4266","DOI":"10.1021\/ct4004228","article-title":"One Size Does Not Fit All: The Limits of Structure-Based Models in Drug Discovery","volume":"9","author":"Ross","year":"2013","journal-title":"J. Chem. Theory Comput."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1021\/acs.jcim.5b00745","article-title":"Three-Dimensional Similarity in Molecular Docking: Prioritizing Ligand Poses on the Basis of Experimental Binding Modes","volume":"56","author":"Anighoro","year":"2016","journal-title":"J. Chem. Inf. Model."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1093\/jxb\/erx258","article-title":"A cheminformatics review of auxins as herbicides","volume":"69","author":"Quareshy","year":"2018","journal-title":"J. Exp. Bot."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.bmc.2015.08.011","article-title":"The discovery of ArylexTM active and RinskorTM active: Two novel auxin herbicides","volume":"24","author":"Epp","year":"2016","journal-title":"Bioorganic Med. Chem."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1305","DOI":"10.1002\/ps.7294","article-title":"The differential binding and biological efficacy of auxin herbicides","volume":"79","author":"Prusinska","year":"2023","journal-title":"Pest Manag. 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