{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T06:58:06Z","timestamp":1774076286109,"version":"3.50.1"},"reference-count":85,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T00:00:00Z","timestamp":1730851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon (Rede Bionorte)"},{"name":"PROPESP\/UFPA"},{"name":"Laboratory of Modeling and Computational Chemistry (LMQC)"},{"name":"Health Science Institute at Federal University of Par\u00e1"},{"name":"University of the State of Amap\u00e1 (UEAP)"},{"name":"Institute of Biosanitary Research ibs.GRANADA\u2014University of Granada"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceuticals"],"abstract":"<jats:p>Background: This study began with a search in three databases, totaling six libraries (ChemBridge-DIVERSet, ChemBridge-DIVERSet-EXP, Zinc_Drug Database, Zinc_Natural_Stock, Zinc_FDA_BindingDB, Maybridge) with approximately 2.5 million compounds with the aim of selecting potential inhibitors with antiproliferative activity on the chimeric tyrosine kinase encoded by the BCR-ABL gene. Methods: Through hierarchical biochemoinformatics, ADME\/Tox analyses, biological activity prediction, molecular docking simulations, synthetic accessibility and theoretical synthetic routes of promising compounds and their lipophilicity and water solubility were realized. Results: Predictions of toxicological and pharmacokinetic properties (ADME\/Tox) using the top100\/base (600 structures), in comparison with the commercial drug imatinib, showed that only nine exhibited the desired properties. In the prediction of biological activity, the results of the nine selected structures ranged from 13.7% &lt; Pa &lt; 65.8%, showing them to be potential protein kinase inhibitors. In the molecular docking simulations, the promising molecules LMQC01 and LMQC04 showed significant values in molecular targeting (PDB 1IEP\u2014resolution 2.10 \u00c5). LMQC04 presented better binding affinity (\u2206G = \u221212.2 kcal mol\u22121 with a variation of \u00b13.6 kcal mol\u22121) in relation to LMQC01. The LMQC01 and LMQC04 molecules were advanced for molecular dynamics (MD) simulation followed by Molecular Mechanics with generalized Born and Surface Area solvation (MM-GBSA); the comparable, low and stable RMSD and \u0394E values for the protein and ligand in each complex suggest that the selected compounds form a stable complex with the Abl kinase domain. This stability is a positive indicator that LMQC01 and LMQC04 can potentially inhibit enzyme function. Synthetic accessibility (SA) analysis performed on the AMBIT and SwissADME webservers showed that LMQC01 and LMQC04 can be considered easy to synthesize. Our in silico results show that these molecules could be potent protein kinase inhibitors with potential antiproliferative activity on tyrosine kinase encoded by the BCR-ABL gene. Conclusions: In conclusion, the results suggest that these ligands, particularly LMQC04, may bind strongly to the studied target and may have appropriate ADME\/Tox properties in experimental studies. Considering future in vitro or in vivo assays, we elaborated the theoretical synthetic routes of the promising compounds identified in the present study. Based on our in silico findings, the selected ligands show promise for future studies in developing chronic myeloid leukemia treatments.<\/jats:p>","DOI":"10.3390\/ph17111491","type":"journal-article","created":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T04:22:56Z","timestamp":1730953376000},"page":"1491","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rational Approach to New Chemical Entities with Antiproliferative Activity on Ab1 Tyrosine Kinase Encoded by the BCR-ABL Gene: An Hierarchical Biochemoinformatics Analysis"],"prefix":"10.3390","volume":"17","author":[{"given":"Vitor H. da S.","family":"Sanches","sequence":"first","affiliation":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon, Biotechnology Department, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program in Medicinal Chemistry and Molecular Modeling, Federal University of Par\u00e1, Bel\u00e9m 66075-110, PA, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cleison C.","family":"Lobato","sequence":"additional","affiliation":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon, Biotechnology Department, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program in Medicinal Chemistry and Molecular Modeling, Federal University of Par\u00e1, Bel\u00e9m 66075-110, PA, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luciane B.","family":"Silva","sequence":"additional","affiliation":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon, Biotechnology Department, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program in Medicinal Chemistry and Molecular Modeling, Federal University of Par\u00e1, Bel\u00e9m 66075-110, PA, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Igor V. F.","family":"dos Santos","sequence":"additional","affiliation":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon, Biotechnology Department, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elcimar de S.","family":"Barros","sequence":"additional","affiliation":[{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program of Pharmaceutical Innovation, Federal University of Amap\u00e1, Macap\u00e1 68902-280, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9707-1408","authenticated-orcid":false,"given":"Alexandre de A.","family":"Maciel","sequence":"additional","affiliation":[{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program of Pharmaceutical Innovation, Federal University of Amap\u00e1, Macap\u00e1 68902-280, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elenilze F. B.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program of Pharmaceutical Innovation, Federal University of Amap\u00e1, Macap\u00e1 68902-280, AP, Brazil"},{"name":"Laboratory of Organic Chemistry and Biochemistry, University of the State of Amap\u00e1, Macap\u00e1 68900-070, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2735-8016","authenticated-orcid":false,"given":"Kau\u00ea S.","family":"da Costa","sequence":"additional","affiliation":[{"name":"Computational Simulation Laboratory, Institute of Biodiversity, Federal University of Western Par\u00e1, Vera Paz Street, w\/n Sal\u00e9, Santar\u00e9m 68040-255, PA, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3231-1095","authenticated-orcid":false,"given":"Jos\u00e9 M.","family":"Espejo-Rom\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Campus of Cartuja, University of Granada, 18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9035-8123","authenticated-orcid":false,"given":"Joaqu\u00edn M. C.","family":"Rosa","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Campus of Cartuja, University of Granada, 18071 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5171-1940","authenticated-orcid":false,"given":"Njogu M.","family":"Kimani","sequence":"additional","affiliation":[{"name":"Natural Product Chemistry and Computational Drug Discovery Laboratory, Embu P.O. Box 6-60100, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0271-335X","authenticated-orcid":false,"given":"Cleydson B. R.","family":"Santos","sequence":"additional","affiliation":[{"name":"Biodiversity and Biotechnology Network of the Legal Amazon, Biotechnology Department, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program in Medicinal Chemistry and Molecular Modeling, Federal University of Par\u00e1, Bel\u00e9m 66075-110, PA, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macap\u00e1 68903-419, AP, Brazil"},{"name":"Graduate Program of Pharmaceutical Innovation, Federal University of Amap\u00e1, Macap\u00e1 68902-280, AP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s00277-015-2325-z","article-title":"Natural course and biology of CML","volume":"94","author":"Chereda","year":"2015","journal-title":"Ann. Hematol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Amarante-Mendes, G.P., Rana, A., Datoguia, T.S., Hamerschlak, N., and Brumatti, G. (2022). BCR-ABL1 Tyrosine Kinase Complex Signaling Transduction: Challenges to Overcome Resistance in Chronic Myeloid Leukemia. Pharmaceutics, 14.","DOI":"10.3390\/pharmaceutics14010215"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s11899-011-0093-y","article-title":"Role of Tyrosine Kinase Inhibitors in the Management of Philadelphia Chromosome\u2013Positive Acute Lymphoblastic Leukemia","volume":"6","author":"Mathisen","year":"2011","journal-title":"Curr. Hematol. Malig. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.clml.2013.03.018","article-title":"Resistance to Tyrosine Kinase Inhibition Therapy for Chronic Myelogenous Leukemia: A Clinical Perspective and Emerging Treatment Options","volume":"13","author":"Jabbour","year":"2013","journal-title":"Clin. Lymphoma Myeloma Leuk."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Raslan, M.A., Raslan, S.A., Shehata, E.M., Mahmoud, A.S., and Sabri, N.A. (2023). Advances in the Applications of Bioinformatics and Chemoinformatics. Pharmaceuticals, 16.","DOI":"10.3390\/ph16071050"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xing, W.-L., and Cheng, J. (2006). An Integrated Biochemoinformatics System for Drug Discovery. Frontiers in Biochip Technology, Springer.","DOI":"10.1007\/b135657"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Banavath, H.N., Sharma, O.P., Kumar, M.S., and Baskaran, R. (2014). Identification of novel tyrosine kinase inhibitors for drug resistant T315I mutant BCR-ABL: A virtual screening and molecular dynamics simulations study. Sci. Rep., 4.","DOI":"10.1038\/srep06948"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Carofiglio, F., Trisciuzzi, D., Gambacorta, N., Leonetti, F., Stefanachi, A., and Nicolotti, O. (2020). Bcr-Abl Allosteric Inhibitors: Where We Are and Where We Are Going to. Molecules, 25.","DOI":"10.3390\/molecules25184210"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Martorana, A., La Monica, G., Bono, A., Mannino, S., Buscemi, S., Palumbo Piccionello, A., Gentile, C., Lauria, A., and Peri, D. (2022). Antiproliferative Activity Predictor: A New Reliable In Silico Tool for Drug Response Prediction against NCI60 Panel. Int. J. Mol. Sci., 23.","DOI":"10.3390\/ijms232214374"},{"key":"ref_10","first-page":"177","article-title":"Machine learning model for antiproliferative virtual screening of herbal compounds against hepatocellular carcinoma","volume":"13","author":"Firdayani","year":"2023","journal-title":"J. Appl. Pharm. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/s13321-022-00647-y","article-title":"Development of machine learning classifiers to predict compound activity on prostate cancer cell lines","volume":"14","author":"Bonanni","year":"2022","journal-title":"J. Cheminform."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"K\u00f6hn, H.-F., and Hubert, L.J. (2015). Hierarchical Cluster Analysis. Wiley StatsRef: Statistics Reference Online, Wiley.","DOI":"10.1002\/9781118445112.stat02449.pub2"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1038\/s41588-023-01429-4","article-title":"Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia","volume":"55","author":"Kim","year":"2023","journal-title":"Nat. Genet."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Nishiwaki, S., Kim, J.H., Ito, M., Maeda, M., Okuno, Y., Koyama, D., Ozawa, Y., Gunji, M., Osaki, M., and Kitamura, K. (2020). Multi-Lineage BCR-ABL Expression in Philadelphia Chromosome-Positive Acute Lymphoblastic Leukemia Is Associated With Improved Prognosis but No Specific Molecular Features. Front. Oncol., 10.","DOI":"10.3389\/fonc.2020.586567"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s13065-015-0108-1","article-title":"Protease-inhibiting, molecular modeling and antimicrobial activities of extracts and constituents from Helichrysum foetidum and Helichrysum mechowianum (compositae)","volume":"9","author":"Malolo","year":"2015","journal-title":"Chem. Cent. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1007\/s10593-014-1496-1","article-title":"Prediction of the Biological Activity Spectra of Organic Compounds Using the Pass Online Web Resource","volume":"50","author":"Filimonov","year":"2014","journal-title":"Chem. Heterocycl. Compd."},{"key":"ref_17","unstructured":"(2024, April 12). PASS Online. Available online: http:\/\/www.pharmaexpert.ru\/passonline\/predict.php."},{"key":"ref_18","unstructured":"Klaassen, C.D. (2019). Toxic Responses of the Blood. Casarett & Doull\u2019s Toxicology: The Basic Science of Poisons, McGraw-Hill Education. [9th ed.]."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1124\/pr.55.3.4","article-title":"Specific Targeted Therapy of Chronic Myelogenous Leukemia with Imatinib","volume":"55","author":"Deininger","year":"2003","journal-title":"Pharmacol. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1080\/17425255.2017.1389897","article-title":"In silico ADME-Tox modeling: Progress and prospects","volume":"13","author":"Alqahtani","year":"2017","journal-title":"Expert Opin. Drug Metab. Toxicol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s40203-017-0034-0","article-title":"Molecular docking analysis of curcumin analogues against kinase domain of ALK5","volume":"5","author":"Kandagalla","year":"2017","journal-title":"In Silico Pharmacol."},{"key":"ref_22","first-page":"65","article-title":"Molecular Properties Prediction of Phenothiazine Derivatives by Using Swiss ADME, PkCSM, Lazar and Protox","volume":"7","author":"Mohammed","year":"2019","journal-title":"World J. Pharm. Sci."},{"key":"ref_23","unstructured":"(2024). Schr\u00f6dinger Release 2024-3: QikProp, Schr\u00f6dinger, LLC."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1590\/S0103-507X2011000200016","article-title":"Mecanismos de disfun\u00e7\u00e3o da barreira hematoencef\u00e1lica no paciente criticamente enfermo: \u00canfase no papel das metaloproteinases de matriz","volume":"23","author":"Rojas","year":"2011","journal-title":"Rev. Bras.Ter. Intensiv."},{"key":"ref_25","unstructured":"(2024, April 10). DRUGBANK Online. Available online: https:\/\/www.drugbank.ca."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1021\/ci020048r","article-title":"PASS Biological Activity Spectrum Predictions in the Enhanced Open NCI Database Browser","volume":"43","author":"Poroikov","year":"2003","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1590\/S0100-40422005000100021","article-title":"Cancer and cell cicle-specific and cell cicle nonspecific anticancer DNA-interactive agents: An introduction","volume":"28","author":"Almeida","year":"2005","journal-title":"Qu\u00edmica Nova"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1023\/B:JCAM.0000017496.76572.6f","article-title":"Comparative study of several algorithms for flexible ligand docking","volume":"17","author":"Bursulaya","year":"2003","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1002\/prot.20497","article-title":"Comparing protein\u2013ligand docking programs is difficult","volume":"60","author":"Cole","year":"2005","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1021\/ci800293n","article-title":"Validation of molecular docking programs for virtual screening against dihydropteroate synthase","volume":"49","author":"Hevener","year":"2009","journal-title":"J. Chem. Inf. Model."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1021\/jm0302997","article-title":"Evaluation of Docking Performance:\u2009 Comparative Data on Docking Algorithms","volume":"47","author":"Kontoyianni","year":"2004","journal-title":"J. Med. Chem."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1002\/prot.10232","article-title":"A new test set for validating predictions of protein\u2013ligand interaction","volume":"49","author":"Nissink","year":"2002","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1080\/07391102.2018.1444511","article-title":"Pharmacophore and structure-based drug design, molecular dynamics and admet\/tox studies to design novel potential pad4 inhibitors","volume":"37","author":"Barcellos","year":"2019","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Borges, R.S., Palheta, I.C., Ota, S.S.B., Morais, R.B., Barros, V.A., Ramos, R.S., Silva, R.C., Costa, J.d.S., Silva, C.H.T.P., and Campos, J.M. (2019). Toward of Safer Phenylbutazone Derivatives by Exploration of Toxicity Mechanism. Molecules, 24.","DOI":"10.3390\/molecules24010143"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Costa, J.d.S., Ramos, R.d.S., Costa, K.d.S.L., Brasil, D.d.S.B., Silva, C.H.T.d.P.d., Ferreira, E.F.B., Borges, R.d.S., Campos, J.M., Mac\u00eado, W.J.d.C., and Santos, C.B.R.d. (2018). An In Silico Study of the Antioxidant Ability for Two Caffeine Analogs Using Molecular Docking and Quantum Chemical Methods. Molecules, 23.","DOI":"10.3390\/molecules23112801"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Cruz, J.V., Neto, M.F.A., Silva, L.B., Ramos, R.D.S., Costa, J.D.S., Brasil, D.S.B., Lobato, C.C., Da Costa, G.V., Bittencourt, J.A.H.M., and Da Silva, C.H.T.P. (2018). Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening. Molecules, 23.","DOI":"10.3390\/molecules23020453"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Ramos, R.d.S., Costa, J.d.S., Silva, R.C., da Costa, G.V., Rodrigues, A.B.L., Rabelo, \u00c9.d.M., Souto, R.N.P., Taft, C.A., Silva, C.H.T.d.P.d., and Rosa, J.M.C. (2019). Identification of Potential Inhibitors from Pyriproxyfen with Insecticidal Activity by Virtual Screening. Pharmaceuticals, 12.","DOI":"10.3390\/ph12010020"},{"key":"ref_38","first-page":"4236","article-title":"Crystal Structures of the Kinase Domain of c-Abl in Complex with the Small Molecule Inhibitors PD173955 and Imatinib (STI-571)1","volume":"62","author":"Nagar","year":"2002","journal-title":"Cancer Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.1002\/1521-3773(20020802)41:15<2644::AID-ANIE2644>3.0.CO;2-O","article-title":"Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors","volume":"41","author":"Gohlke","year":"2002","journal-title":"Angew. Chem. (Int. Ed. Engl.)"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Cera, E.D. (1995). Thermodynamic Theory of Site-Specific Binding Processes in Biological Macromolecules, Cambridge University Press.","DOI":"10.1017\/CBO9780511524837"},{"key":"ref_41","unstructured":"(2024, June 21). PubChem, Available online: https:\/\/pubchem.ncbi.nlm.nih.gov\/."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1055\/s-2000-6357","article-title":"The Flourishing Syntheses of Non-Nucleoside Reverse Transcriptase Inhibitors","volume":"2000","author":"Pedersen","year":"2000","journal-title":"Synthesis"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"14472","DOI":"10.1021\/acs.joc.8b02180","article-title":"Carboxylic Acid-Promoted Single-Step Indole Construction from Simple Anilines and Ketones via Aerobic Cross-Dehydrogenative Coupling","volume":"83","author":"Ren","year":"2018","journal-title":"J. Org. Chem."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3851","DOI":"10.1016\/j.bmcl.2017.06.049","article-title":"Discovery of novel dengue virus entry inhibitors via a structure-based approach","volume":"27","author":"Leal","year":"2017","journal-title":"Bioorg. Med. Chem. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Daina, A., Michielin, O., and Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep., 7.","DOI":"10.1038\/srep42717"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1021\/ci500467k","article-title":"iLOGP: A Simple, Robust, and Efficient Description of n-Octanol\/Water Partition Coefficient for Drug Design Using the GB\/SA Approach","volume":"54","author":"Daina","year":"2014","journal-title":"J. Chem. Inf. Model."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Lima, L.R., Bastos, R.S., Ferreira, E.F.B., Le\u00e3o, R.P., Ara\u00fajo, P.H.F., Pita, S.S.d.R., De Freitas, H.F., Espejo-Rom\u00e1n, J.M., Dos Santos, E.L.V.S., and Ramos, R.d.S. (2022). Identification of Potential New Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl Piperidine Derivatives: A Bioinformatics Approach. Int. J. Mol. Sci., 23.","DOI":"10.3390\/ijms23179927"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Di, L., and Kerns, E.H. (2016). Chapter 5\u2014Lipophilicity. Drug-Like Properties, Academic Press. [2nd ed.].","DOI":"10.1016\/B978-0-12-801076-1.00002-2"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"6401","DOI":"10.1021\/acs.jmedchem.8b00077","article-title":"Lipophilic Efficiency as an Important Metric in Drug Design","volume":"61","author":"Johnson","year":"2018","journal-title":"J. Med. Chem."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1517\/17460441003605098","article-title":"Lipophilicity in drug discovery","volume":"5","author":"Waring","year":"2010","journal-title":"Expert Opin. Drug Discov."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1007\/s11224-020-01537-5","article-title":"In silico fight against novel coronavirus by finding chromone derivatives as inhibitor of coronavirus main proteases enzyme","volume":"31","author":"Sepay","year":"2020","journal-title":"Struct. Chem."},{"key":"ref_52","unstructured":"OpenEye (2024). ROCS, 3.6.2.0, Cadence Molecular Sciences."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1021\/jm0603365","article-title":"Comparison of Shape-Matching and Docking as Virtual Screening Tools","volume":"50","author":"Hawkins","year":"2007","journal-title":"J. Med. Chem."},{"key":"ref_54","unstructured":"Coumar, M.S. (2021). Chapter 4\u2014Best Practices for Docking-Based Virtual Screening. Molecular Docking for Computer-Aided Drug Design, Academic Press."},{"key":"ref_55","unstructured":"OpenEye (2024). EON, 3.0.0.0, Cadence Molecular Sciences."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1080\/15376510701857320","article-title":"In silico tools for sharing data and knowledge on toxicity and metabolism: Derek for windows, meteor, and vitic","volume":"18","author":"Marchant","year":"2008","journal-title":"Toxicol. Mech. Methods"},{"key":"ref_57","first-page":"845","article-title":"The performance of current methods in ligand\u2013protein docking","volume":"83","author":"McConkey","year":"2002","journal-title":"Curr. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"146","DOI":"10.2174\/157340911795677602","article-title":"Molecular docking: A powerful approach for structure-based drug discovery","volume":"7","author":"Meng","year":"2011","journal-title":"Curr. Comput.-Aided Drug Des."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1002\/jcc.21334","article-title":"AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading","volume":"31","author":"Trott","year":"2010","journal-title":"J. Comput. Chem."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/978-1-4939-2269-7_19","article-title":"Small-molecule library screening by docking with PyRx","volume":"1263","author":"Dallakyan","year":"2015","journal-title":"Methods Mol. Biol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/S0009-2614(00)00318-3","article-title":"Implementation of Lamarckian concepts in a Genetic Algorithm for structure solution from powder diffraction data","volume":"321","author":"Turner","year":"2000","journal-title":"Chem. Phys. Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1186\/s40064-016-1972-4","article-title":"CrossDocker: A tool for performing cross-docking using Autodock Vina","volume":"5","author":"Shamsara","year":"2016","journal-title":"SpringerPlus"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Sousa dos Santos, E.L.V., Cruz, J.N., da Costa, G.V., de S\u00e1, E.M.F., da Silva, A.K.P., Fernandes, C.P., de Faria Mota Oliveira, A.E.M., Duarte, J.L., Bezerra, R.M., and Tavares, J.F. (2024). Essential Oil of Ocimum basilicum against Aedes aegypti and Culex quinquefasciatus: Larvicidal Activity of a Nanoemulsion and In Silico Study. Separations, 11.","DOI":"10.3390\/separations11040097"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"de Almeida, R.B.M., Barbosa, D.B., do Bomfim, M.R., Amparo, J.A.O., Andrade, B.S., Costa, S.L., Campos, J.M., Cruz, J.N., Santos, C.B.R., and Leite, F.H.A. (2023). Identification of a Novel Dual Inhibitor of Acetylcholinesterase and Butyrylcholinesterase: In Vitro and In Silico Studies. Pharmaceuticals, 16.","DOI":"10.3390\/ph16010095"},{"key":"ref_65","unstructured":"(2024, April 02). Protein Data Bank. Available online: https:\/\/www.rcsb.org\/."},{"key":"ref_66","unstructured":"BIOVIA_Dassault_Syst\u00e8mes (2017). Discovery Studio Visualizer, 17.2, Dassault Syst\u00e8mes."},{"key":"ref_67","unstructured":"(2024). Schr\u00f6dinger Release 2024-3: Desmond Molecular Dynamics System, D.E. Shaw Research."},{"key":"ref_68","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 SC \u201806: Proceedings of the 2006 ACM\/IEEE Conference on Supercomputing, Tampa, FL, USA.","DOI":"10.1109\/SC.2006.54"},{"key":"ref_69","unstructured":"(2024). Schr\u00f6dinger Release 2024-3: Maestro, Schr\u00f6dinger, LLC."},{"key":"ref_70","unstructured":"(2024). Schr\u00f6dinger Release 2024-3: Prime, Schr\u00f6dinger, LLC."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"351","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. Bioinform."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/S0022-2836(02)00470-9","article-title":"On the Role of the Crystal Environment in Determining Protein Side-chain Conformations","volume":"320","author":"Jacobson","year":"2002","journal-title":"J. Mol. Biol."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Ferreira, E.F.B., Silva, L.B., Costa, G.V., Costa, J.S., Fujishima, M.A.T., Le\u00e3o, R.P., Ferreira, A.L.S., Federico, L.B., Silva, C.H.T.P., and Rosa, J.M.C. (2019). Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening. Molecules, 24.","DOI":"10.3390\/molecules24162943"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Silva, L.B., Ferreira, E.F.B., Espejo-Rom\u00e1n, J.M., Costa, G.V., Cruz, J.V., Kimani, N.M., Costa, J.S., Bittencourt, J.A.H.M., and Cruz, J.N. (2023). Galantamine Based Novel Acetylcholinesterase Enzyme Inhibitors: A Molecular Modeling Design Approach. Molecules, 28.","DOI":"10.3390\/molecules28031035"},{"key":"ref_75","first-page":"588","article-title":"SciFinder","volume":"106","author":"Gabrielson","year":"2018","journal-title":"J. Med. Libr. Assoc. JMLA"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"dos Santos, I.V.F., Borges, R.S., Silva, G.M., de Lima, L.R., Bastos, R.S., Ramos, R.S., Silva, L.B., da Silva, C.H.T.P., and dos Santos, C.B.R. (2022). Hierarchical Virtual Screening Based on Rocaglamide Derivatives to Discover New Potential Anti-Skin Cancer Agents. Front. Mol. Biosci., 9.","DOI":"10.3389\/fmolb.2022.836572"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"576","DOI":"10.2174\/1381612823666170711112510","article-title":"Virtual Screening and Statistical Analysis in the Design of New Caffeine Analogues Molecules with Potential Epithelial Anticancer Activity","volume":"24","year":"2018","journal-title":"Curr. Pharm. Des."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1002\/jps.21494","article-title":"Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compounds","volume":"98","author":"Mannhold","year":"2009","journal-title":"J. Pharm. Sci."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"2140","DOI":"10.1021\/ci700257y","article-title":"Computation of Octanol\u2212Water Partition Coefficients by Guiding an Additive Model with Knowledge","volume":"47","author":"Cheng","year":"2007","journal-title":"J. Chem. Inf. Model."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"868","DOI":"10.1021\/ci990307l","article-title":"Prediction of Physicochemical Parameters by Atomic Contributions","volume":"39","author":"Wildman","year":"1999","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1248\/cpb.42.976","article-title":"Comparison of Reliability of log P Values for Drugs Calculated by Several Methods","volume":"42","author":"Moriguchi","year":"1994","journal-title":"Chem. Pharm. Bull."},{"key":"ref_82","unstructured":"(2024, June 21). Silicos-It. Available online: http:\/\/www.silicos-it.be\/software.html."},{"key":"ref_83","first-page":"195727","article-title":"Drug solubility: Importance and enhancement techniques","volume":"2012","author":"Savjani","year":"2012","journal-title":"ISRN Pharm"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1021\/ci034243x","article-title":"ESOL:\u2009 Estimating Aqueous Solubility Directly from Molecular Structure","volume":"44","author":"Delaney","year":"2004","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1021\/ci200387c","article-title":"Revisiting the General Solubility Equation: In Silico Prediction of Aqueous Solubility Incorporating the Effect of Topographical Polar Surface Area","volume":"52","author":"Ali","year":"2012","journal-title":"J. Chem. Inf. Model."}],"container-title":["Pharmaceuticals"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8247\/17\/11\/1491\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:27:34Z","timestamp":1760113654000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8247\/17\/11\/1491"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,6]]},"references-count":85,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["ph17111491"],"URL":"https:\/\/doi.org\/10.3390\/ph17111491","relation":{},"ISSN":["1424-8247"],"issn-type":[{"value":"1424-8247","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,6]]}}}