Energy decomposition and waterswapping analysis to investigate the SNP associated DPD mediated 5-FU resistance

References

• H. Verma, M.B. Singh, S. Choudhary, P.K. Singh, and O. Silakari, Drug metabolizing enzymes-associated chemo resistance and strategies to overcome it, Drug Metab. Rev. 51 (2019), pp. 196–223. doi:10.1080/03602532.2019.1632886.
   PubMed Web of Science ®Google Scholar
• D. Salonga, K.D. Danenberg, M. Johnson, R. Metzger, S. Groshen, D.D. Tsao-Wei, H.J. Lenz, C.G. Leichman, L. Leichman, and R.B. Diasio, Colorectal tumors responding to 5-fluorouracil have low gene expression levels of dihydropyrimidine dehydrogenase, thymidylate synthase, and thymidine phosphorylase, Clin. Cancer Res. 6 (2000), pp. 1322–1327.
   PubMed Web of Science ®Google Scholar
• Y. Ishikawa, T. Kubota, Y. Otani, M. Watanabe, T. Teramoto, K. Kumai, T. Takechi, H. Okabe, M. Fukushima, and M. Kitajima, Thymidylate synthetase and dihydropyrimidine dehydrogenase levels in gastric cancer, Anticancer Res. 19 (1999), pp. 5635–5640.
   PubMed Web of Science ®Google Scholar
• Y. Ishikawa, T. Kubota, Y. Otani, M. Watanabe, T. Teramoto, K. Kumai, T. Takechi, H. Okabe, M. Fukushima, and M. Kitajima, Dihydropyrimidine dehydrogenase and messenger RNA levels in gastric cancer: Possible predictor for sensitivity to 5‐fluorouracil, Jpn. J. Cancer Res. 91 (2000), pp. 105–112.
   PubMedGoogle Scholar
• C.I. Huang, H. Yokomise, S. Kobayashi, M. Fukushima, S. Hitomi, and H. Wada, Intratumoral expression of thymidylate synthase and dihydropyrimidine dehydrogenase in non-small cell lung cancer patients treated with 5-FU-basedchemotherapy, Int. J. Oncol. 17 (2000), pp. 47–101.
   PubMed Web of Science ®Google Scholar
• H. Kobayashi, T. Koike, A. Nakatsuka, H. Kurita, J. Sagara, S. Taniguchi, and K. Kurashina, Dihydropyrimidine dehydrogenase expression predicts survival outcome and chemosensitivity to 5-fluorouracil in patients with oral squamous cell carcinoma, Oral Oncol. 41 (2005), pp. 38–47. doi:10.1016/j.oraloncology.2004.06.003.
   PubMed Web of Science ®Google Scholar
• M.E. Nita, O. Tominaga, H. Nagawa, T. Tsuruo, and T. Muto, Dihydropyrimidine dehydrogenase but not thymidylate synthase expression is associated with resistance to 5-fluorouracil in colorectal cancer, Hepato-gastroenterology 45 (1998), pp. 2117–2122.
   PubMedGoogle Scholar
• K. Yoshinare, T. Kubota, M. Watanabe, N. Wada, H. Nishibori, H. Hasegawa, M. Kitajima, T. Takechi, and M. Fukushima, Gene expression in colorectal cancer and in vitro chemosensitivity to 5‐fluorouracil: A study of 88 surgical specimens, Cancer Sci. 94 (2003), pp. 633–638. doi:10.1111/j.1349-7006.2003.tb01495.x.
   PubMed Web of Science ®Google Scholar
• O. Kikuchi, S. Ohashi, Y. Nakai, S. Nakagawa, K. Matsuoka, T. Kobunai, T. Takechi, Y. Amanuma, M. Yoshioka, and T. Ida, Novel 5-fluorouracil-resistant human esophageal squamous cell carcinoma cells with dihydropyrimidine dehydrogenase overexpression, Am. J. Cancer Res. 5 (2015), pp. 2431.
   PubMed Web of Science ®Google Scholar
• K. Omura, Clinical implications of dihydropyrimidine dehydrogenase (DPD) activity in 5-FU-based chemotherapy: Mutations in the DPD gene, and DPD inhibitory fluoropyrimidines, Int. J. Clin. Oncol. 8 (2003), pp. 132–138. doi:10.1007/s10147-003-0330-z.
   PubMedGoogle Scholar
• R.B. Diasio and M.R. Johnson, Dihydropyrimidine dehydrogenase: Its role in 5-fluorouracil clinical toxicity and tumor resistance, Clin. Cancer Res. 5 (1999), pp. 2672–2673.
   PubMed Web of Science ®Google Scholar
• H. Verma and O. Silakari, Investigating the role of missense SNPs on ALDH 1A1 mediated pharmacokinetic resistance to cyclophosphamide, Comput. Biol. Med. 125 (2020), pp. 103979. doi:10.1016/j.compbiomed.2020.103979.
   PubMed Web of Science ®Google Scholar
• D.T. Kumar, L.J. Emerald, C.G.P. Doss, P. Sneha, R. Siva, W.C.E. Jebaraj, and H. Zayed, Computational approach to unravel the impact of missense mutations of proteins (D2HGDH and IDH2) causing D-2-hydroxyglutaric aciduria 2, Metab. Brain Dis. 33 (2018), pp. 1699–1710. doi:10.1007/s11011-018-0278-3.
   PubMed Web of Science ®Google Scholar
• K. Maekawa, M. Saeki, Y. Saito, S. Ozawa, K. Kurose, N. Kaniwa, M. Kawamoto, N. Kamatani, K. Kato, T. Hamaguchi, Y. Yamada, K. Shirao, Y. Shimada, M. Muto, T. Doi, A. Ohtsu, T. Yoshida, Y. Matsumura, N. Saijo, and J.I. Sawada, Genetic variations and haplotype structures of the DPYD gene encoding dihydropyrimidine dehydrogenase in Japanese and their ethnic differences, J. Hum. Genet. 10 (2007), pp. 804–819. doi:10.1007/s10038-007-0186-6.
   Google Scholar
• A.B.V. Kuilenburg, J. Meijer, D. Maurer, D. Dobritzsch, R. Meinsma, M. Los, L.C. Knegt, L. Zoetekouw, R.L. Jansen, and V. Dezentjé, Severe fluoropyrimidine toxicity due to novel and rare DPYD missense mutations, deletion and genomic amplification affecting DPD activity and mRNA splicing, Biochim. Biophys. Acta - Mol. Basis Dis. 1863 (2017), pp. 721–730. doi:10.1016/j.bbadis.2016.12.010.
   PubMed Web of Science ®Google Scholar
• A.M. Elrashid, M.Y. Basher, A. Gharib, M.A. Alfaki, N.M. Mohammed, A.M. Elmoselhy, S.G. Elbager, and S.I. Khalil, In silico analysis for DPYD gene and the effect of the mutation on dihydropyrimidine dehydrogenase enzyme, J. Adv. Med. Pharm. Sci. 16 (2018), pp. 1–10. doi:10.9734/JAMPS/2018/40300.
   Google Scholar
• X. Garcia-Gonzalez, B. Kaczmarczyk, J. Abarca-Zabalia, F. Thomas, P. Garcia-Alfonso, L. Robles, V. Pachon, Á. Vaz, S. Salvador-Martin, and M. Sanjurjo-Saez, New DPYD variants causing DPD deficiency in patients treated with fluoropyrimidine, Cancer Chemother. Pharmacol. 86 (2020), pp. 45–54. doi:10.1007/s00280-020-04093-1.
   PubMed Web of Science ®Google Scholar
• D. Dobritzsch, G. Schneider, K.D. Schnackerz, and Y. Lindqvist, Crystal structure of dihydropyrimidine dehydrogenase, a major determinant of the pharmacokinetics of the anti-cancer drug 5-fluorouracil, EMBO J. 20 (2001), pp. 650–660. doi:10.1093/emboj/20.4.650.
   PubMed Web of Science ®Google Scholar
• G. Kiran, L. Karthik, M.S. Devi, P. Sathiyarajeswaran, K. Kanakavalli, K. Kumar, and D.R. Kumar, In silico computational screening of kabasura kudineer-official Siddha formulation and JACOM against SARS-CoV-2 spike protein, J. Ayurveda Integr. Med. 13 (2020), pp. 100324. doi:10.1016/j.jaim.2020.05.009.
   PubMed Web of Science ®Google Scholar
• J. Liu, H. Dai, B. Wang, H. Liu, Z. Tian, and Y. Zhang, Exploring disordered loops in DprE1 provides a functional site to combat drug-resistance in Mycobacterium strains, Eur. J. Med. Chem. 227 (2022), pp. 113932. doi:10.1016/j.ejmech.2021.113932.
   PubMed Web of Science ®Google Scholar
• E. Capriotti, P. Fariselli, and R. Casadio, I-Mutant2. 0: Predicting stability changes upon mutation from the protein sequence or structure, Nucleic Acids Res. 33 (2005), pp. W306–W10. doi:10.1093/nar/gki375.
   PubMed Web of Science ®Google Scholar
• V. Parthiban, M.M. Gromiha, and D. Schomburg, CUPSAT: Prediction of protein stability upon point mutations, Nucleic Acids Res. 34 (2006), pp. W239–W42. doi:10.1093/nar/gkl190.
   PubMed Web of Science ®Google Scholar
• J. Laimer, J. Hiebl-Flach, D. Lengauer, and P. Lackner, MAESTROweb: A web server for structure-based protein stability prediction, Bioinformatics 32 (2016), pp. 1414–1416. doi:10.1093/bioinformatics/btv769.
   PubMed Web of Science ®Google Scholar
• L. Quan, Q. Lv, and Y. Zhang, STRUM: Structure-based prediction of protein stability changes upon single-point mutation, Bioinformatics 32 (2016), pp. 2936–2946. doi:10.1093/bioinformatics/btw361.
   PubMed Web of Science ®Google Scholar
• B. Garn and D.E. Simos, Eris: A tool for combinatorial testing of the Linux system call interface, IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops, 2014, pp. 58–67.
   Google Scholar
• C.L. Worth, R. Preissner, and T.L. Blundell, SDM—A server for predicting effects of mutations on protein stability and malfunction, Nucleic Acids Res. 39 (2011), pp. W215–W22. doi:10.1093/nar/gkr363.
   PubMed Web of Science ®Google Scholar
• D.E. Pires, D.B. Ascher, and T.L. Blundell, DUET: A server for predicting effects of mutations on protein stability using an integrated computational approach, Nucleic Acids Res. 42 (2014), pp. W314–W9. doi:10.1093/nar/gku411.
   PubMed Web of Science ®Google Scholar
• M.A. Beg and L.S. Meena, Mutational effects on structural stability of SRP pathway dependent co-translational protein ftsY of Mycobacterium tuberculosis H37Rv, Gene Rep. 15 (2019), pp. 100395. doi:10.1016/j.genrep.2019.100395.
   Web of Science ®Google Scholar
• M.R. Bauer and M.D. Mackey, Electrostatic complementarity as a fast and effective tool to optimize binding and selectivity of protein–ligand complexes, J. Med. Chem. 62 (2019), pp. 3036–3050. doi:10.1021/acs.jmedchem.8b01925.
   PubMed Web of Science ®Google Scholar
• H. Verma, G. Narendra, B. Raju, M. Kumar, S.K. Jain, G.K. Tung, P.K. Singh, and O. Silakari, 3D-QSAR and scaffold hopping based designing of benzo[d]ox-azol-2(3H)-one and 2-oxazolo[4,5-b]pyridin-2(3H)-one derivatives as selective aldehyde dehydrogenase 1A1 inhibitors: Synthesis and biological evaluation, Arch. Pharm. 355 (2022), pp. e2200108. doi:10.1002/ardp.202200108.
   PubMed Web of Science ®Google Scholar
• J. Lemkul, From proteins to perturbed hamiltonians: A suite of tutorials for the GROMACS-2018 molecular simulation package, Living J. Comput. Mol. Sci. 1 (2018), pp. 5068. doi:10.33011/livecoms.1.1.5068.
   Google Scholar
• B.R. Brooks, C.L. Brooks III, A.D. Mackerell Jr, L. Nilsson, R.J. Petrella, B. Roux, Y. Won, G. Archontis, C. Bartels, and S. Boresch, CHARMM: The biomolecular simulation program, J. Comput. Chem. 30 (2009), pp. 1545–1614. doi:10.1002/jcc.21287.
   PubMed Web of Science ®Google Scholar
• U. Essmann, L. Perera, M.L. Berkowitz, T. Darden, H. Lee, and L.G. Pedersen, A smooth particle mesh Ewald method, J. Chem. Phys. 103 (1995), pp. 8577–8593. doi:10.1063/1.470117.
   Web of Science ®Google Scholar
• Y.X. Yuan, A new stepsize for the steepest descent method, J. Comput. Math. 24 (2006), pp. 149–156.
   Web of Science ®Google Scholar
• L.B.A. Oliveira and G. Colherinhas, Can CHARMM36 atomic charges described correctly the interaction between amino acid and water molecules by molecular dynamics simulations? J. Mol. Liq. 317 (2020), pp. 113919. doi:10.1016/j.molliq.2020.113919.
   Web of Science ®Google Scholar
• A. Khezri, A. Karimi, F. Yazdian, M. Jokar, S.R. Mofradnia, H. Rashedi, and Z. Tavakoli, Molecular dynamic of curcumin/chitosan interaction using a computational molecular approach: Emphasis on biofilm reduction, Int. J. Biol. Macromol. 114 (2018), pp. 972–978. doi:10.1016/j.ijbiomac.2018.03.100.
   PubMed Web of Science ®Google Scholar
• R. Kumari, R. Kumar, O.S.D.D. Consortium, and A. Lynn, g_mmpbsa: A GROMACS tool for high-throughput MM-PBSA calculations, J. Chem. Inf. Model. 54 (2014), pp. 1951–1962. doi:10.1021/ci500020m.
   PubMed Web of Science ®Google Scholar
• A. Gupta, N. Chaudhary, and P. Aparoy, MM-PBSA and per-residue decomposition energy studies on 7-phenyl-imidazoquinolin-4 (5H)-one derivatives: Identification of crucial site points at microsomal prostaglandin E synthase-1 (mPGES-1) active site, Int. J. Biol. Macromol. 119 (2018), pp. 352–359. doi:10.1016/j.ijbiomac.2018.07.050.
   PubMed Web of Science ®Google Scholar
• T. Tozer, K. Heale, C. Manto Chagas, A.L.B. de Barros, and L. Alisaraie, Interdomain twists of human thymidine phosphorylase and its active–inactive conformations: Binding of 5‐FU and its analogues to human thymidine phosphorylase versus dihydropyrimidine dehydrogenase, Chem. Biol. Drug Des. 94 (2019), pp. 1956–1972. doi:10.1111/cbdd.13596.
   PubMed Web of Science ®Google Scholar
• D.J. Belle and H. Singh, Genetic factors in drug metabolism, Am. Fam. Phys. 77 (2008), pp. 1553–1560.
   PubMed Web of Science ®Google Scholar
• C.W. Chen, M.H. Lin, C.C. Liao, H.P. Chang, and Y.W. Chu, iStable 2.0: Predicting protein thermal stability changes by integrating various characteristic modules, Comput. Struct. Biotechnol. J. 18 (2020), pp. 622–630. doi:10.1016/j.csbj.2020.02.021.
   PubMed Web of Science ®Google Scholar
• N.A. Baker, D. Sept, S. Joseph, M.J. Holst, and J.A. McCammon, Electrostatics of nanosystems: Application to microtubules and the ribosome, Proc. Natl. Acad. Sci. U.S.A. 98 (2001), pp. 10037–10041. doi:10.1073/pnas.181342398.
   PubMed Web of Science ®Google Scholar
• H. Verma, G. Narendra, B. Raju, P.K. Singh, and O. Silakari, Dihydropyrimidine dehydrogenase-mediated resistance to 5-fluorouracil: Mechanistic investigation and solution, ACS Pharmacol. Transl. Sci. 5 (2022), pp. 1017–1033. doi:10.1021/acsptsci.2c00117.
   Google Scholar