Skip to main content


Log in

Computational studies of polyurethanases from Pseudomonas

Journal of Molecular Modeling Aims and scope Submit manuscript


Polyurethanes (PU) are multifunctional polymers, used in automotive industry, in coatings, rigid and flexible foams, and also in biomimetic materials. In the same way as all plastic waste, the incorrect disposal of these materials leads to the accumulation of polyurethanes in the environment. To reduce the amount of waste as well as add value to degradation products, bioremediation methods have been studied for waste management of PU. Enzymes of the hydrolases class have been experimentally tested for enzymatic degradation of PU, with very promising results. In this work, two enzymes that can degrade polyurethanes were studied by molecular dynamics simulations: a protease and an esterase, both from Pseudomonas. From molecular dynamics simulations analysis, it was observed the stability of the structures, both in the simulations of the free enzymes and in the simulations of the complexes with a PU monomer. Hydrogen bonds were formed with the monomer and the enzymes throughout the simulation time, and the interaction free energy was found to be strongly negative, pointing to strong interactions in both cases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Data availability

Data can be made available upon request.


  1. Engels HW, Pirkl HG, Albers R, Albach RW, Krause J, Hoffmann A, Casselmann H, Dormish J (2013) Polyurethanes: versatile materials and sustainable problem solvers for today’s challenges. Angew. Chemie - Int. Ed. 52(36):9422–9441.

    Article  CAS  Google Scholar 

  2. Prisacariu C (2011) Polyurethane elastomers. Springer Vienna, Vienna.

    Book  Google Scholar 

  3. Sharmin E. Zafar, F, (2012) Polyurethane : An Introduction. Intech Open Books: Polyurethane 3–16.

  4. Hung KC, Tseng CS, Dai LG, Hsu SH (2016) Water-based polyurethane 3D printed scaffolds with controlled release function for customized cartilage tissue engineering. Biomaterials 83:156–168.

    Article  CAS  PubMed  Google Scholar 

  5. Zia F, Zia KM, Zuber M, Tabasum S, Rehman S (2016) Heparin based polyurethanes: a state-of-the-art review. Int J Biol Macromol 84:101–111.

    Article  CAS  PubMed  Google Scholar 

  6. Lucas N, Bienaime C, Belloy C, Queneudec M, Silvestre F, Nava-Saucedo JE (2008) Polymer biodegradation: mechanisms and estimation techniques - a review. Chemosphere 73(4):429–442.

    Article  CAS  PubMed  Google Scholar 

  7. Veronese VB, Menger RK, Forte MMC, Petzhold CL (2011) Rigid polyurethane foam based on modified vegetable oil. J Appl Polym Sci 120(1):530–537.

    Article  CAS  Google Scholar 

  8. Ragaert K, Delva L, Van Geem K (2017) Mechanical and chemical recycling of solid plastic waste. Waste Manag 69:24–58.

    Article  CAS  PubMed  Google Scholar 

  9. Moharir RV, Kumar S (2019) Challenges associated with plastic waste disposal and allied microbial routes for its effective degradation: a comprehensive review. J Clean Prod 208:65–76.

    Article  CAS  Google Scholar 

  10. Bhardwaj H, Gupta R, Tiwari A (2013) Communities of microbial enzymes associated with biodegradation of plastics. J Polym Environ 21(2):575–579.

    Article  CAS  Google Scholar 

  11. Singh R, Kumar M, Mittal A, Mehta PK (2016) Microbial enzymes: industrial progress in 21st century. 3 Biotech 6(2):1–15.

    Article  PubMed  Google Scholar 

  12. Rios NS, Pinheiro BB, Pinheiro MP, Bezerra RM, dos Santos JCS, Barros Gonçalves LR (2018) Biotechnological potential of lipases from Pseudomonas: sources properties and applications. Process Biochem 75(July):99–120.

    Article  CAS  Google Scholar 

  13. Loredo-Treviño A, Gutiérrez-Sánchez G, Rodríguez-Herrera R, Aguilar CN (2012) Microbial enzymes involved in polyurethane biodegradation: a review. J Polym Environ 20(1):258–265.

    Article  CAS  Google Scholar 

  14. Ozsagiroglu E, Iyisan B, Guvenilir YA (2012) Biodegradation and characterization studies of different kinds of polyurethanes with several enzyme solutions. Pol J Environ Stud 21(6):1777–1782

    CAS  Google Scholar 

  15. Cregut M, Bedas M, Durand MJ, Thouand G (2013) New insights into polyurethane biodegradation and realistic prospects for the development of a sustainable waste recycling process. Biotechnol Adv 31(8):1634–3647.

    Article  CAS  PubMed  Google Scholar 

  16. Howard GT (2002) Biodegradation of polyurethane: a review. Int Biodeterior Biodegrad 49(4):245–252.

    Article  CAS  Google Scholar 

  17. Howard GT, Ruiz C, Hilliard NP (1999) Growth of Pseudomonas chlororaphis on apolyester–polyurethane and the purification and characterization of a polyurethanase–esterase enzyme. Int Biodeterior Biodegradation 43(1):7–12.

    Article  CAS  Google Scholar 

  18. Akutsu Y, Nakajima-Kambe T, Nomura N, Nakahara T (1998) Purification and properties of a polyester polyurethane-degrading enzyme from Comamonas acidovorans TB-35. Appl Environ Microbiol 64(1):62–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Russell JR, Huang J, Anand P, Kucera K, Sandoval AG, Dantzler KW, Hickman D, Jee J, Kimovec FM, Koppstein D et al (2011) Biodegradation of polyester polyurethane by endophytic fungi. Appl Environ Microbiol 77(17):6076–6084.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Damborsky J, Brezovsky J (2014) Computational tools for designing and engineering enzymes. Curr Opin Chem Biol 19(1):8–16.

    Article  CAS  PubMed  Google Scholar 

  21. Kawabata T, Oda M, Kawai F (2017) Mutational analysis of cutinase-like enzyme, Cut190, based on the 3D docking structure with model compounds of polyethylene terephthalate. J Biosci Bioeng 124(1):28–35.

    Article  CAS  PubMed  Google Scholar 

  22. Groß C, Hamacher K, Schmitz K, Jager S (2017) Cleavage product accumulation decreases the activity of cutinase during PET hydrolysis. J Chem Inf Model 57(2):243–255.

    Article  CAS  PubMed  Google Scholar 

  23. Arora R, Issar U, Kakkar R (2018) In silico study of the active site of helicobacter pylori urease and its inhibition by hydroxamic acids. J Mol Graph Model 83:64–73.

    Article  CAS  PubMed  Google Scholar 

  24. van Gunsteren WF, Berendsen HJC (1990) Computer simulation of molecular dynamics: methodology, applications, and perspectives in chemistry. Angew Chem Int Ed Eng 29(9):992–1023.

    Article  Google Scholar 

  25. do Canto VP, Thompson CE, Netz PA (2019) Polyurethanases: three-dimensional structures and molecular dynamics simulations of enzymes that degrade polyurethane. J Mol Graph Model 89:82–95.

    Article  CAS  PubMed  Google Scholar 

  26. Wlodawer A, Li M, Dauter Z, Gustchina A, Uchida K, Oyama H, Dunn BM, Oda K (2001) Carboxyl proteinase from Pseudomonas defines a novel family of Subtilisin-like enzymes. Nat Struct Biol 8(5):442–446.

    Article  CAS  PubMed  Google Scholar 

  27. Howard GT, Crother B, Vicknair J (2001) Cloning, nucleotide sequencing and characterization of a polyurethanase gene (PueB) from Pseudomonas chlororaphis. Int Biodeterior Biodegrad 47(3):141–149.

    Article  CAS  Google Scholar 

  28. Dennington R, Keith TA, Millam JM (2016) GaussView {V}ersion {6}. Semichem Inc., Shawnee Mission, KS.

  29. Becke AD (1993) Density-functional Thermochemistry. III. The role of exact exchange. J Chem Phys 98(7):5648–5652.

    Article  CAS  Google Scholar 

  30. Rassolov VA, Ratner MA, Pople JA, Redfern PC, Curtiss LA (2001) 6-31G* basis set for third-row atoms. J Comput Chem 22(9):976–984.

    Article  CAS  Google Scholar 

  31. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA et al (2013) Gaussian 09, Rev. D. 01. Gaussian Inc., Wallingford

    Google Scholar 

  32. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31(2):455–461.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Sousa Da Silva AW, Vranken WF (2012) ACPYPE - AnteChamber PYthon Parser InterfacE. BMC Res Notes 5:367.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Berendsen HJC, van der Spoel D, van Drunen R (1995) GROMACS: a message-passing parallel molecular dynamics implementation. Comput Phys Commun 91(1–3):43–56.

    Article  CAS  Google Scholar 

  35. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, Lindah E (2015) Gromacs: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2:19–25.

    Article  Google Scholar 

  36. Duan Y, Wu C, Chowdhury S, Lee MC, Xiong G, Zhang W, Yang R, Cieplak P, Luo R, Lee T et al (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J Comput Chem 24(16):1999–2012.

    Article  CAS  PubMed  Google Scholar 

  37. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935.

    Article  CAS  Google Scholar 

  38. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126(1):014101.

    Article  CAS  PubMed  Google Scholar 

  39. Parrinello M, Rahman A (1981) Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys 52(12):7182–7190.

    Article  CAS  Google Scholar 

  40. Martínez L (2015) Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis. PLoS One 10(3):1–10.

    Article  CAS  Google Scholar 

  41. Kumari R, Kumar R, Lynn A (2014) G_mmpbsa —a GROMACS tool for high-throughput MM-PBSA calculations. J Chem Inf Model 54(7):1951–1962.

    Article  CAS  PubMed  Google Scholar 

  42. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A 98(18):10037–10041.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Code availability

Not applicable.


The authors acknowledge the Universidade Federal do Rio Grande do Sul (UFRGS) and Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA) and the National Center of Supercomputing (CESUP-UFRGS), CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) for the financial support.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Vanessa Petry do Canto.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper belongs to Topical Collection XX - Brazilian Symposium of Theoretical Chemistry (SBQT2019)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

do Canto, V.P., Thompson, C.E. & Netz, P.A. Computational studies of polyurethanases from Pseudomonas. J Mol Model 27, 46 (2021).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: