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Jiayun Pang

Dr Jiayun Pang BSc, PGCert HE, MPhil, PhD

Associate Professor

Dr Pang received her BSc Medicinal Chemistry from Shenyang Pharmaceutical University, China, and her PhD in Computational Chemistry from the University of Birmingham in 2006. She then moved to the University of Manchester to work as a postdoctoral research associate, where her research focused on the study of quantum phenomenon in enzymes using a combined quantum mechanical and molecular mechanical (QM/MM) approach.

Dr Jiayun Pang joined the School of Science at the Çï¿ûÊÓƵ in October 2011 and was promoted to Associate Professor in September 2021. Dr Pang’s research expertise lies in the use of computational chemistry and machine learning methods to solve challenges within the field of biophysical, organic and pharmaceutical chemistry.

Chemistry Science

Responsibilities within the university

Module leader

  • Applied Physical Chemistry (Level 6)
  • Advanced Spectroscopy, Thermodynamics, and Quantum Mechanics (Level 6)

Course participation

  • Bioinformatics (Level 7)
  • Medicinal Chemistry (Level 7)
  • Physical Chemistry (Level 4)
  • Further Physical Chemistry (Level 5)
  • Computational Chemistry (Level 7)
  • BSc/MSc project

Awards
  • Royal Society of Chemistry Rita and John Cornforth Award (2009)

Recognition
  • Fellow of the Royal Society of Chemistry (FRSC)
  • Senior Fellow of the Higher Education Academy (SFHEA)
  • Elected Committee Member of the Molecular Graphics and Modelling Society (MGMS)

Research / Scholarly interests

Jiayun Pang’s research focus on the use of computational methods to understand molecular properties, chemical reactions, and biological macromolecules, such as enzymes. Her research areas include:

  • Incorporating machine learning algorithms to enhance the predictive power of computational chemistry, in particular using deep learning algorithms inspired by Natural Language Processing (NLP) to explore the vast chemical space to enable more accurate prediction of structure-property relationships.
  • Studying the mechanisms of organic reactions using DFT calculations and using feature-based machine learning models to predict reaction selectivity.
  • Enzyme catalysis using the combined QM/MM method, enhanced free-energy sampling and precise reaction rate calculations which take into account the hydrogen tunnelling effect.

Recent publications

Article

Pang, Jiayun and , Vulic, Ivan (2024), . Royal Society of Chemistry. In: , , , . Royal Society of Chemistry, Faraday Discussions ISSN: 1359-6640 (Print), 1364-5498 (Online) (doi: https://doi.org/10.1039/D4FD00104D).

Pang, Jiayun , Pine, Alexander, Sulemana, Abdulai (2023), . Royal Society of Chemistry. In: , , , . Royal Society of Chemistry, Digital Discovery 2635-098X (Online) (doi: https://doi.org/10.1039/d3dd00119a).

Yin, Lina , Guan, Ting, Cheng, Jie, Pan, Dongchao , Lu, Jinyang , Huang, Jiahui , Wu, Jiaqi , Chen, Xiaoli , You, Taiyun , Huo, Xuting (2022), . Nature Research. In: , , , . Nature Research, Communications Chemistry, 5: 140 (1) 2399-3669 (Online) (doi: https://doi.org/10.1038/s42004-022-00759-4).

Vivoli, Mirella , Pang, Jiayun, Harmer, Nicholas J. (2017), . Nature Publishing Group. In: , , , . Nature Publishing Group, Scientific Reports, 7: 16529 (1) ISSN: 2045-2322 (Print), 2045-2322 (Online) (doi: https://doi.org/10.1038/s41598-017-16421-2).

Tong, Xiaoxue , Busk, Peter Kamp, Lange, Lene, Pang, Jiayun (2016), . Taylor and Francis. In: , , , . Taylor and Francis, Molecular Simulation, 42 (5) . pp. 434-445 ISSN: 0892-7022 (Print), 1029-0435 (Online) (doi: http://dx.doi.org/10.1080/08927022.2015.1059938).