Dr John Mitchell: Research Group Home Page

   Welcome to the John Mitchell research group website

We are an Informatics and Computational Chemistry research group. Our group is based in the Purdie building on the North Haugh in St Andrews.

Research areas we are interested in are enzyme catalysis, protein-ligand interactions, modelling epidemics, molecular evolution and structural bioinformatics, computational toxicology, prediction of solubility and other molecular properties, and the classification of drugs used for doping in sport.


News


Recent publications

Computational Insights into the Catalytic Mechanism of Is-PETase: An Enzyme Capable of Degrading Poly(ethylene) Terephthalate,
E Shrimpton-Phoenix, JBO Mitchell, M Bühl
Physical Review E, 106, 014304 (2022)
doi: 10.1002/chem.202201728

Practical Application of a Bayesian Network Approach to Poultry Epigenetics and Stress,
EAV Rodriguez, F Pertille, C. Guerrero-Bosagna, JBO Mitchell, P Jensen, VA Smith
BMC Bioinformatics, 23, 261 (2022)
doi: 10.1186/s12859-022-04800-0

Degree correlations in graphs with clique clustering,
P Mann, VA Smith, JBO Mitchell, S Dobson
Physical Review E, 105, 044314 (2022)
doi: 10.1103/PhysRevE.105.044314

Allosteric inhibition of Acinetobacter baumannii ATP phosphoribosyltransferase by protein:dipeptide and protein:protein interactions,
BJ Read, G Fisher, OLR Wissett, TFG Machado, J Nicholson, JBO Mitchell, RG da Silva,
ACS Infectious Diseases. 8: 197-209 (2022)
doi: acsinfecdis.1c00539

EAV Rodriguez, JBO Mitchell, VA Smith,
A Bayesian Network Structure Learning Approach to Identify Genes Associated with Stress in Spleens of Chickens,
Scientific Reports 12, 7482 (2022)
doi: 10.1038/s41598-022-11633-7

Toward physics-based solubility computation for pharmaceuticals to rival informatics,
DJ Fowles, DS Palmer, R Guo, SL Price, JBO Mitchell,
J. Chem. Theor. Comput., 17, 3700-3709 (2021)
doi: 10.1021/acs.jctc.1c00130

Exact formula for bond percolation on cliques,
P Mann, VA Smith, JBO Mitchell, CA Jefferson, S Dobson
Physical Review E, 104, 024304 (2021)
doi: 10.1103/PhysRevE.104.024304

Symbiotic and antagonistic disease dynamics on clustered networks using bond percolation,
P Mann, VA Smith, JBO Mitchell, S Dobson
Physical Review E, 104, 024303 (2021)
doi: 10.1103/PhysRevE.104.024303

Two-pathogen model with competition on clustered networks,
P Mann, VA Smith, JBO Mitchell, S Dobson,
Physical Review E, 103, 062308 (2021)
doi: 10.1103/PhysRevE.103.062308

Cooperative coinfection dynamics on clustered networks,
P Mann, VA Smith, JBO Mitchell, S Dobson,
Physical Review E, 103, 042307 (2021)
doi: 10.1103/PhysRevE.103.042307

Percolation in random graphs with higher-order clustering,
P Mann, VA Smith, JBO Mitchell, S Dobson,
Physical Review E, 103, 012313 (2021)
doi: 10.1103/PhysRevE.103.012313

Random graphs with arbitrary clustering and their applications,
P Mann, VA Smith, JBO Mitchell, S Dobson,
Physical Review E, 103, 012309 (2021)
doi: 10.1103/PhysRevE.103.012309

In silico methods to predict solubility,
J. L. McDonagh, J. B. O. Mitchell, D. S. Palmer & R. E. Skyner,
in Solubility in Pharmaceutical Chemistry (Eds C Saal & A Nair), De Gruyter (2020)
ISBN 978-3-11-055983-5

Three machine learning models for the 2019 Solubility Challenge,
J. B. O. Mitchell,
ADMET & DMPK 8, 215-251 (2020)
doi: 10.5599/admet.835

In silico methods to predict solubility,
J. L. McDonagh, J. B. O. Mitchell, D. S. Palmer & R. E. Skyner,
in Solubility in Pharmaceutical Chemistry (Eds C Saal & A Nair), De Gruyter (2020)
ISBN 978-3-11-055983-5

We are probably not Sims
J. B. O. Mitchell
Science & Christian Belief, 32, 45-62 (2020)


Teaching material (sorry, St Andrews access only) for CH1202, CH3441, CH3717, CH4431, CH5714, ID1003, ID1004, ID2005, CRITICAT and SUPACCH.


Thanks to our Sponsors