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Research Article

Enhancing bezlotoxumab binding to C. difficile toxin B2: insights from computational simulations and mutational analyses for antibody design

, , &
Received 09 Nov 2023, Accepted 06 Mar 2024, Published online: 21 Mar 2024

References

  • Adedeji, W. A. (2016). The treasure called antibiotics. Annals of Ibadan Postgraduate Medicine, 14, 56. https://doi.org/10.1016/j.mib.2019.10.008
  • Adolf-Bryfogle, J., Teets, F. D., & Bahl, C. D. (2021). Toward complete rational control over protein structure and function through computational design. Current Opinion in Structural Biology, 66, 170–177. https://doi.org/10.1016/j.sbi.2020.10.015
  • Baase, W. A., Liu, L., Tronrud, D. E., & Matthews, B. W. (2010). Lessons from the lysozyme of phage T4. Protein Science: A Publication of the Protein Society, 19(4), 631–641. https://doi.org/10.1002/pro.344
  • Babcock, G. J., Broering, T. J., Hernandez, H. J., Mandell, R. B., Donahue, K., Boatright, N., Stack, A. M., Lowy, I., Graziano, R., Molrine, D., Ambrosino, D. M., & Thomas, W. D. Jr. (2006). Human monoclonal antibodies directed against toxins A and B prevent Clostridium difficile-induced mortality in hamsters. Infection and Immunity, 74(11), 6339–6347. https://doi.org/10.1128/IAI.00982-06
  • Barlow, K. A., Ó Conchúir, S., Thompson, S., Suresh, P., Lucas, J. E., Heinonen, M., & Kortemme, T. (2018). Flex ddG: Rosetta ensemble-based estimation of changes in protein-protein binding affinity upon mutation. The Journal of Physical Chemistry B, 122(21), 5389–5399. https://doi.org/10.1021/acs.jpcb.7b11367
  • Bartlett, J. G., Moon, N., Chang, T. W., Taylor, N., & Onderdonk, A. B. (1978). Role of Clostridium difficile in antibiotic-associated pseudomembranous colitis. Gastroenterology, 75(5), 778–782. https://doi.org/10.1016/0016-5085(78)90457-2
  • Berendsen, H., Postma, J. P. M., van Gunsteren, W., DiNola, A. D., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8), 3684–3690. https://doi.org/10.1063/1.448118
  • Browne, A. J., Chipeta, M. G., Haines-Woodhouse, G., Kumaran, E. P. A., Hamadani, B. H. K., Zaraa, S., Henry, N. J., Deshpande, A., Reiner, R. C., Jr., Day, N. P. J., Lopez, A. D., Dunachie, S., Moore, C. E., Stergachis, A., Hay, S. I., & Dolecek, C. (2021). Global antibiotic consumption and usage in humans, 2000-18: A spatial modelling study. The Lancet Planetary Health, 5(12), e893–e904. https://doi.org/10.1016/S2542-5196(21)00280-1
  • Case, D. A., Aktulga, H. M., Belfon, K., Ben-Shalom, I. Y., Berryman, J. T., Brozell, S. R., Cerutti, D. S., Cheatham, T. E., III, Cisneros, G. A., Cruzeiro, V. W. D., Darden, T. A., Duke, R. E., Giambasu, G., Gilson, M. K., Gohlke, H., Goetz, A. W., Harris, R., Izadi, S.,… Kollman, P. A. (2022). AMBER. University of California.
  • Chapin, R. W., Lee, T., McCoy, C., Alonso, C. D., & Mahoney, M. V. (2017). Bezlotoxumab: Could this be the answer for clostridium difficile recurrence? The Annals of Pharmacotherapy, 51(9), 804–810. https://doi.org/10.1177/1060028017706374
  • Chen, F., Liu, H., Sun, H., Pan, P., Li, Y., Li, D., & Hou, T. (2016). Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein docking. Physical Chemistry Chemical Physics, 18(32), 22129–22139. https://doi.org/10.1039/c6cp03670h
  • Chen, P., Zeng, J., Liu, Z., Thaker, H., Wang, S., Tian, S., Zhang, J., Tao, L., Gutierrez, C. B., Xing, L., Gerhard, R., Huang, L., Dong, M., & Jin, R. (2021). Structural basis for CSPG4 as a receptor for TcdB and a therapeutic target in Clostridioides difficile infection. Nature Communications, 12(1), 3748. https://doi.org/10.1038/s41467-021-23878-3
  • Clementel, D., Del Conte, A., Monzon, A. M., Camagni, G. F., Minervini, G., Piovesan, D., & Tosatto, S. C. E. (2022). RING 3.0: Fast generation of probabilistic residue interaction networks from structural ensembles. Nucleic Acids Research, 50(W1), W651–W656. https://doi.org/10.1093/nar/gkac365
  • Conway, P., Tyka, M. D., DiMaio, F., Konerding, D. E., & Baker, D. (2014). Relaxation of backbone bond geometry improves protein energy landscape modeling. Protein Science: A Publication of the Protein Society, 23(1), 47–55. https://doi.org/10.1002/pro.2389
  • Cui, Q., Sulea, T., Schrag, J. D., Munger, C., Hung, M.-N., Naïm, M., Cygler, M., & Purisima, E. O. (2008). Molecular dynamics-solvated interaction energy studies of protein-protein interactions: The MP1-p14 scaffolding complex. Journal of Molecular Biology, 379(4), 787–802. https://doi.org/10.1016/j.jmb.2008.04.035
  • Czepiel, J., Dróżdż, M., Pituch, H., Kuijper, E. J., Perucki, W., Mielimonka, A., Goldman, S., Wultańska, D., Garlicki, A., & Biesiada, G. (2019). Clostridium difficile infection: Review. European Journal of Clinical Microbiology & Infectious Diseases, 38(7), 1211–1221. https://doi.org/10.1007/s10096-019-03539-6
  • Davey, J. A., & Chica, R. A. (2012). Multistate approaches in computational protein design. Protein Science: A Publication of the Protein Society, 21(9), 1241–1252. https://doi.org/10.1002/pro.2128
  • Dolgikh, B., & Woldring, D. (2022). Site-wise diversification of combinatorial libraries using insights from structure-guided stability calculations. Methods in Molecular Biology (Clifton, NJ), 2491, 63–73. https://doi.org/10.1007/978-1-0716-2285-8_3
  • Dubberke, E. R., Gerding, D. N., Kelly, C. P., Garey, K. W., Rahav, G., Mosley, A., Tipping, R., & Dorr, M. B. (2020). Efficacy of bezlotoxumab in participants receiving metronidazole, vancomycin, or fidaxomicin for treatment of clostridioides (Clostridium) difficile infection. Open Forum Infectious Diseases, 7, ofaa157.
  • Fekety, R., McFarland, L. V., Surawicz, C. M., Greenberg, R. N., Elmer, G. W., & Mulligan, M. E. (1997). Recurrent Clostridium difficile diarrhea: Characteristics of and risk factors for patients enrolled in a prospective, randomized, double-blinded trial. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, 24(3), 324–333. https://doi.org/10.1093/clinids/24.3.324
  • Francis, M. B., Allen, C. A., Shrestha, R., & Sorg, J. A. (2013). Bile acid recognition by the Clostridium difficile germinant receptor, CspC, is important for establishing infection. PLoS Pathogens, 9(5), e1003356. https://doi.org/10.1371/journal.ppat.1003356
  • Frenz, B., Lewis, S. M., King, I., DiMaio, F., Park, H., & Song, Y. (2020). Prediction of protein mutational free energy: Benchmark and sampling improvements increase classification accuracy. Frontiers in Bioengineering and Biotechnology, 8, 558247. https://doi.org/10.3389/fbioe.2020.558247
  • Hernandez, L. D., Racine, F., Xiao, L., DiNunzio, E., Hairston, N., Sheth, P. R., Murgolo, N. J., & Therien, A. G. (2015). Broad coverage of genetically diverse strains of Clostridium difficile by actoxumab and bezlotoxumab predicted by in vitro neutralization and epitope modeling. Antimicrobial Agents and Chemotherapy, 59(2), 1052–1060. https://doi.org/10.1128/AAC.04433-14
  • Hou, T., Wang, J., Li, Y., & Wang, W. (2011a). Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. Journal of Chemical Information and Modeling, 51(1), 69–82. https://doi.org/10.1021/ci100275a
  • Hou, T., Wang, J., Li, Y., & Wang, W. (2011b). Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. Journal of Computational Chemistry, 32(5), 866–877. https://doi.org/10.1002/jcc.21666
  • Hutchings, M. I., Truman, A. W., & Wilkinson, B. (2019). Antibiotics: Past, present and future. Current Opinion in Microbiology, 51, 72–80. https://doi.org/10.1016/j.mib.2019.10.008
  • Jin, K., Wang, S., Zhang, C., Xiao, Y., Lu, S., & Huang, Z. (2013). Protective antibody responses against Clostridium difficile elicited by a DNA vaccine expressing the enzymatic domain of toxin B. Human Vaccines & Immunotherapeutics, 9(1), 63–73. https://doi.org/10.4161/hv.22434
  • Joana, I., Aristides, L. M., Mónica, S., Adriano, O. H., & Mónica, O. (2017). In: E. Shymaa (Ed.), Clostridium difficile (p. 2.). IntechOpen.
  • Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols, 10(6), 845–858. https://doi.org/10.1038/nprot.2015.053
  • Khatib, F., Cooper, S., Tyka, M. D., Xu, K., Makedon, I., Popovic, Z., Baker, D., & Players, F. (2011). Algorithm discovery by protein folding game players. Proceedings of the National Academy of Sciences of the United States of America, 108(47), 18949–18953. https://doi.org/10.1073/pnas.1115898108
  • Knowles, R., Sharland, M., Hsia, Y., Magrini, N., Moja, L., Siyam, A., & Tayler, E. (2020). Measuring antibiotic availability and use in 20 low- and middle-income countries. Bulletin of the World Health Organization, 98(3), 177–187C. https://doi.org/10.2471/BLT.19.241349
  • Leaver-Fay, A., Tyka, M., Lewis, S. M., Lange, O. F., Thompson, J., Jacak, R., Kaufman, K., Renfrew, P. D., Smith, C. A., Sheffler, W., Davis, I. W., Cooper, S., Treuille, A., Mandell, D. J., Richter, F., Ban, Y. E., Fleishman, S. J., Corn, J. E., Kim, D. E., … Bradley, P. (2011). ROSETTA3: An object-oriented software suite for the simulation and design of macromolecules. Methods in Enzymology, 487, 545–574. https://doi.org/10.1016/B978-0-12-381270-4.00019-6
  • Li, G., Fang, X., Su, F., Chen, Y., Xu, L., & Yan, Y. (2018). Enhancing the thermostability of Rhizomucor miehei lipase with a limited screening library by rational-design point mutations and disulfide bonds. Applied and Environmental Microbiology, 84(2), e02129-17. https://doi.org/10.1128/AEM.02129-17
  • Lobionda, S., Sittipo, P., Kwon, H. Y., & Lee, Y. K. (2019). The role of gut microbiota in intestinal inflammation with respect to diet and extrinsic stressors. Microorganisms, 7(8), 271. https://doi.org/10.3390/microorganisms7080271
  • Madura, J. D., Davist, M. E., Gilson, M. K., Wades, R. C., Luty, B. A., & McCammon, J. A. (1994). Reviews in computational chemistry (pp. 229–267). Wiley.
  • Maier, J. A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K. E., & Simmerling, C. (2015). ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. Journal of Chemical Theory and Computation, 11(8), 3696–3713. https://doi.org/10.1021/acs.jctc.5b00255
  • Mansfield, M. J., Tremblay, B. J., Zeng, J., Wei, X., Hodgins, H., Worley, J., Bry, L., Dong, M., & Doxey, A. C. (2020). Phylogenomics of 8,839 Clostridioides difficile genomes reveals recombination-driven evolution and diversification of toxin A and B. PLoS Pathogens, 16(12), e1009181. https://doi.org/10.1371/journal.ppat.1009181
  • Mark, P., & Nilsson, L. (2001). Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. The Journal of Physical Chemistry A, 105(43), 9954–9960. https://doi.org/10.1021/jp003020w
  • Marozsan, A. J., Ma, D., Nagashima, K. A., Kennedy, B. J., Kang, Y. K., Arrigale, R. R., Donovan, G. P., Magargal, W. W., Maddon, P. J., & Olson, W. C. (2012). Protection against Clostridium difficile infection with broadly neutralizing antitoxin monoclonal antibodies. The Journal of Infectious Diseases, 206(5), 706–713. https://doi.org/10.1093/infdis/jis416
  • McFarland, L. V., Surawicz, C. M., Rubin, M., Fekety, R., Elmer, G. W., & Greenberg, R. N. (1999). Recurrent Clostridium difficile disease: Epidemiology and clinical characteristics. Infection Control and Hospital Epidemiology, 20(1), 43–50. https://doi.org/10.1086/501553
  • Naïm, M., Bhat, S., Rankin, K. N., Dennis, S., Chowdhury, S. F., Siddiqi, I., Drabik, P., Sulea, T., Bayly, C. I., Jakalian, A., & Purisima, E. O. (2007). Solvated interaction energy (SIE) for scoring protein-ligand binding affinities. 1. Exploring the parameter space. Journal of Chemical Information and Modeling, 47(1), 122–133. https://doi.org/10.1021/ci600406v
  • Nivón, L. G., Moretti, R., & Baker, D. (2013). A Pareto-optimal refinement method for protein design scaffolds. PLoS One, 8(4), e59004. https://doi.org/10.1371/journal.pone.0059004
  • Onufriev, A., Bashford, D., & Case, D. A. (2004). Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins: Structure, Function and Genetics, 55(2), 383–394. https://doi.org/10.1002/prot.20033
  • Orth, P., Xiao, L., Hernandez, L. D., Reichert, P., Sheth, P. R., Beaumont, M., Yang, X., Murgolo, N., Ermakov, G., DiNunzio, E., Racine, F., Karczewski, J., Secore, S., Ingram, R. N., Mayhood, T., Strickland, C., & Therien, A. G. (2014). Mechanism of action and epitopes of Clostridium difficile toxin B-neutralizing antibody bezlotoxumab revealed by X-ray crystallography. The Journal of Biological Chemistry, 289(26), 18008–18021. https://doi.org/10.1074/jbc.M114.560748
  • Park, H., Bradley, P., Greisen, P., Jr., Liu, Y., Mulligan, V. K., Kim, D. E., Baker, D., & DiMaio, F. (2016). Simultaneous optimization of biomolecular energy functions on features from small molecules and macromolecules. Journal of Chemical Theory and Computation, 12(12), 6201–6212. https://doi.org/10.1021/acs.jctc.6b00819
  • Peng, Z., Simeon, R., Mitchell, S. B., Zhang, J., Feng, H., & Chen, Z. (2019). Designed ankyrin repeat protein (DARPin) neutralizers of TcdB from clostridium difficile ribotype 027. mSphere, 4(5), e00596-19. https://doi.org/10.1128/mSphere.00596-19
  • Qing, R., Hao, S., Smorodina, E., Jin, D., Zalevsky, A., & Zhang, S. (2022). Protein design: From the aspect of water solubility and stability. Chemical Reviews, 122(18), 14085–14179. https://doi.org/10.1021/acs.chemrev.1c00757
  • Riahi, S., Lee, J. H., Wei, S., Cost, R., Masiero, A., Prades, C., Olfati-Saber, R., Wendt, M., Park, A., Qiu, Y., & Zhou, Y. (2021). Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers. Antibody Therapeutics, 4, 109–122.
  • Roe, D. R., & Cheatham, T. E. (2013). PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. Journal of Chemical Theory and Computation, 9(7), 3084–3095. https://doi.org/10.1021/ct400341p
  • Ryckaert, J. P., Ciccotti, G., & Berendsen, H. J. C. (1977). Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. Journal of Computational Physics, 23(3), 327–341. https://doi.org/10.1016/0021-9991(77)90098-5
  • Settle, C. D., & Wilcox, M. H. (1996). Review article: Antibiotic-induced clostridium difficile infection. Alimentary Pharmacology & Therapeutics, 10(6), 835–841. https://doi.org/10.1046/j.1365-2036.1996.79251000.x
  • Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498–2504. https://doi.org/10.1101/gr.1239303
  • Sindhikara, D. J., Yoshida, N., & Hirata, F. (2012). Placevent: An algorithm for prediction of explicit solvent atom distribution-application to HIV-1 protease and F-ATP synthase. Journal of Computational Chemistry, 33(18), 1536–1543. https://doi.org/10.1002/jcc.22984
  • Smith, C. A., & Kortemme, T. (2008). Backrub-like backbone simulation recapitulates natural protein conformational variability and improves mutant side-chain prediction. Journal of Molecular Biology, 380(4), 742–756. https://doi.org/10.1016/j.jmb.2008.05.023
  • Strokach, A., Corbi-Verge, C., & Kim, P. M. (2019). Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge. Human Mutation, 40(9), 1414–1423. https://doi.org/10.1002/humu.23852
  • Sulea, T., & Purisima, E. O. (2012). The solvated interaction energy method for scoring binding affinities. Methods in Molecular Biology (Clifton, NJ), 819, 295–303. https://doi.org/10.1007/978-1-61779-465-0_19
  • Sun, H., Li, Y., Shen, M., Tian, S., Xu, L., Pan, P., Guan, Y., & Hou, T. (2014). Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring. Physical Chemistry Chemical Physics, 16(40), 22035–22045. https://doi.org/10.1039/c4cp03179b
  • Sun, H., Li, Y., Tian, S., Xu, L., & Hou, T. (2014). Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set. Physical Chemistry Chemical Physics, 16(31), 16719–16729. https://doi.org/10.1039/c4cp01388c
  • Thanissery, R., Winston, J. A., & Theriot, C. M. (2017). Inhibition of spore germination, growth, and toxin activity of clinically relevant C. difficile strains by gut microbiota derived secondary bile acids. Anaerobe, 45, 86–100. https://doi.org/10.1016/j.anaerobe.2017.03.004
  • Tyka, M. D., Keedy, D. A., André, I., Dimaio, F., Song, Y., Richardson, D. C., Richardson, J. S., & Baker, D. (2011). Alternate states of proteins revealed by detailed energy landscape mapping. Journal of Molecular Biology, 405(2), 607–618. https://doi.org/10.1016/j.jmb.2010.11.008
  • Voth, D. E., & Ballard, J. D. (2005). Clostridium difficile toxins: Mechanism of action and role in disease. Clinical Microbiology Reviews, 18(2), 247–263. https://doi.org/10.1128/CMR.18.2.247-263.2005
  • Warn, P., Thommes, P., Sattar, A., Corbett, D., Flattery, A., Zhang, Z., Black, T., Hernandez, L. D., & Therien, A. G. (2016). Disease progression and resolution in rodent models of clostridium difficile infection and impact of antitoxin antibodies and vancomycin. Antimicrobial Agents and Chemotherapy, 60(11), 6471–6482. https://doi.org/10.1128/AAC.00974-16
  • Xu, L., Sun, H., Li, Y., Wang, J., & Hou, T. (2013). Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models. The Journal of Physical Chemistry B, 117(28), 8408–8421. https://doi.org/10.1021/jp404160y
  • York, D. M., Darden, T. A., & Pedersen, L. G. (1993). The effect of long-range electrostatic interactions in simulations of macromolecular crystals: A comparison of the Ewald and truncated list methods. The Journal of Chemical Physics, 99(10), 8345–8348. https://doi.org/10.1063/1.465608
  • Zayed, A. O. H., Altarabeen, M., AlShamaileh, E., & Zain, S. M. (2023). The potential of some functional group compounds substituted 8-Manzamine A as RSK1 inhibitors: Molecular docking and molecular dynamics simulations. Journal of Biomolecular Structure & Dynamics, 6, 1–10.

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