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https://dspace.iiti.ac.in/handle/123456789/18779
| Title: | Conformational landscapes and binding free energies of multitarget phytochemicals reveal molecular recognition mechanisms in colorectal cancer-associated proteins |
| Authors: | Samanta, Sampak Kar, P. |
| Issue Date: | 2026 |
| Publisher: | Taylor and Francis Ltd. |
| Citation: | Deshmukh, Samanta, Kanwar, Verma, Chowdhary, & Kar. (2026). Conformational landscapes and binding free energies of multitarget phytochemicals reveal molecular recognition mechanisms in colorectal cancer-associated proteins. SAR and QSAR in Environmental Research, 37(6), 499–532. https://doi.org/10.1080/1062936X.2026.2685532 |
| Abstract: | Colorectal cancer (CRC) significantly contributes to global cancer-related morbidity and mortality. As systemic toxicity, poor selectivity, and drug resistance restrict the usefulness of available chemotherapy and radiotherapy, phytochemicals present a promising substitute strategy with their generally low toxicity and potential for multitarget action. In this study, key proteins involved in CRC signalling were selected as therapeutic targets, and baicalin, berberine, luteolin, quercetin, and licorice glycoside D1 (licorice) were evaluated as potential multitarget therapeutics. Molecular docking revealed key stabilizing interactions, such as hydrogen bonds, π–π stacking, and π-cation contacts. Additionally, eight complexes investigated via 200 ns all-atom molecular dynamics simulations consistently showed stability in the protein RMSD profiles. MM/PBSA binding free energy calculations identified the BCL-2-baicalin, IL-1β-baicalin, IL-1β-licorice, and TNF-α-licorice complexes (ΔGbind of −27.66, −26.47, −29.69, and −29.87 kcal/mol, respectively) as exhibiting the strongest protein-ligand affinities, where strong van der Waals interactions effectively offset opposing polar contributions. Free-energy surface analyses revealed prominent protein conformations as well as ligand conformations that varied depending on the bound protein. Overall, insights from our computational analyses identified baicalin and licorice as promising multitarget inhibitors while also providing energetic and mechanistic understanding that can be leveraged in future rational drug design. © 2026 Informa UK Limited, trading as Taylor & Francis Group. |
| URI: | https://dx.doi.org/10.1080/1062936X.2026.2685532 https://dspace.iiti.ac.in:8080/jspui/handle/123456789/18779 |
| ISSN: | 1062-936X |
| Type of Material: | Journal Article |
| Appears in Collections: | Mehta Family School of Biosciences and Biomedical Engineering |
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