Degradation of PET Nanoplastic Oligomers at the Novel PHL7 Target:Insights from Molecular Docking and Machine Learning
Keywords:
Polyethylene terephthalate, Nanoplastic, Polyester Hydrolase Leipzig 7, binding affinity, Artificial Neutral NetworkAbstract
The versatility of Polyethylene terephthalate (PET) as a material with numerous applications in the food industry and its recalcitrance to chemical and microbial degradation has recently made it an environmental nuisance. In this study, we applied computational methods to ascertain the dependence of PET nanoplastic (NP) degradation on the chain length of the oligomer. The binding affinities of the NPs on the novel enzyme Polyester Hydrolase Leipzig 7 (PHL7) were used to relate their ease of degradation at the enzyme active site. The results revealed that the binding affinity of PET NPs at the enzyme target decreased from -5.2 kcal/mol to -0.8 kcal/mol, with an increase in PET chain length from 2.18 nm to 5.45 nm (2-5 PET chains). The binding affinities became positive at chain lengths 6.54 nm (6 PET chains) and above. These findings indicated that PET NP degradation at this enzyme’s active site is most efficient as chain length decreases from 5-2 units and is not likely to occur at longer PET chains. A feedforward Artificial Neutral Network (ANN) analysis predicted that the energy of the PET NPs is a very important factor in its degradation.
Published
How to Cite
Issue
Section
Copyright (c) 2023 C. E. Duru, C. E. Enyoh, I. A. Duru, M. C. Enedoh

This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Similar Articles
- Emma Panzi Mukhokosi, Stephen Tenywa, Nandipha L. Bothab, Shohreh Azizi, Mathapelo Pearl Seopela, Malik Maaza, Green synthesis of CuO nanoparticles from Cucurbita maxima leaf extract; a platinum free counter electrode for dye sensitized solar cells , Journal of the Nigerian Society of Physical Sciences: Volume 7, Issue 1, February 2025
- A. E. Ibor, E. B. Edim, A. A. Ojugo, Secure Health Information System with Blockchain Technology , Journal of the Nigerian Society of Physical Sciences: Volume 5, Issue 2, May 2023
- F. U. Salifu, O. A. Oladipo, E. O. Ebock, B. Nava, Deep neural network model for vertical total electron content prediction at a single low latitude station , Journal of the Nigerian Society of Physical Sciences: Volume 7, Issue 4, November 2025
- Benitho Ngwu, Godwin C. E. Mbah, Chika O. Mmaduakor, Sunday Isienyi, Oghenekevwe R. Ajewole, Felix D. Ajibade, Characterisation of Singular Domains in Threshold-Dependent Biological Networks , Journal of the Nigerian Society of Physical Sciences: Volume 4, Issue 3, August 2022
- Onyeke Idoko Charles, John Kolo Alhassan, Mohammed Danlami Abdulmalik, Kehinde Dele Tolorunse, A hybrid process-based and neural network post-processing model for cowpea yield prediction under climate variability in North Central Nigeria , Journal of the Nigerian Society of Physical Sciences: Volume 8, Issue 2, May 2026
- Misbaudeen Abdul-Hammed, Ibrahim Olaide Adedotun, Tolulope Irapada Afolabi Afolabi, Ubeydat Temitope Ismail, Praise Toluwalase Akande, Balqees Funmilayo Issa, Analysis of the Bioactive Compounds from Carica papaya in the Management of Psoriasis using Computational Techniques , Journal of the Nigerian Society of Physical Sciences: Volume 5, Issue 1, February 2023
- I. E. Otuokere, J. G. Ohwimu, K. C. Amadi, C. O. Alisa, F. C. Nwadire, O. U. Igwe, A. A. Okoyeagu, C. M. Ngwu, Synthesis, Characterization and Molecular Docking Studies of Mn (II) Complex of Sulfathiazole , Journal of the Nigerian Society of Physical Sciences: Volume 1, Issue 3, August 2019
- Chinedu L. Udeze, Idongesit E. Eteng, Ayei E. Ibor, Application of Machine Learning and Resampling Techniques to Credit Card Fraud Detection , Journal of the Nigerian Society of Physical Sciences: Volume 4, Issue 3, August 2022
- Kanak Saini, Monika Saini, Ashish Kumar, Dinesh Kumar Saini, Availability predictions of solar power plants using multiple regression and neural networks: an analytical study , Journal of the Nigerian Society of Physical Sciences: Volume 7, Issue 2, May 2025
- Majid Khan Bin Majahar Ali, Shahida Shahnawaz, An inverse physics-informed neural network (I-PINN) framework for parameter estimation in mixed convection and melting effects , Journal of the Nigerian Society of Physical Sciences: Volume 8, Issue 2, May 2026
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Chidi Duru, Ijeoma Duru, Chiagoziem Chidiebere, Virtual Screening of Selected Natural Products as Human Tyrosinase-Related Protein 1 Blockers , Journal of the Nigerian Society of Physical Sciences: Volume 3, Issue 3, August 2021

