Dr James Smith
- Position: Lecturer in Biochemistry (Metabolic & Biophysical Modelling)
- Areas of expertise: computational chemistry & biochemistry; drug target discovery; metabolic prediction; computational & mathematical systems biology; molecular epidemiology; biostatistics & machine learning
- Email: J.Smith252@leeds.ac.uk
- Phone: +44(0)113 343 1414
- Location: 7.65 EC Stoner
- Website: LinkedIn | Researchgate | ORCID
After graduating from the University of Leicester, I initially embarked on a DPhil in Biochemistry at the University of Oxford but was quickly lured over to the University of Cambridge with the offer of an industrially-funded PhD studentship in Drug Design at the Department of Pharmacology. This cutting-edge research into the selectivity of kinase drugs led to a postdoctoral career in drug target discovery with industry-related research positions in computational chemistry, ligand-protein interactions and xenobiotic metabolism funded by The Wellcome Trust (London) and industrially by AstraZeneca and Unilever. This research molecular recognition led to an invitation to join the MRC Centre for Protein Engineering with Sir Alan Ferscht to design a class of peptidomimetic drugs to inhibit critical tumourgenic protein-protein interactions. Drug target discovery and drug design for industry has remained a theme in my research career.
Research Career prior to joining The University of Leeds
2004 – 2007, worked at the University of Erlangen-Nuremburg, in Germany at the Computer Chemistry Center and the Biophysics Group, Centre for Medical Physics and Technology.
2007 – 2010, worked at Jacobs University Bremen as a Volkswagen Foundation-funded Research Fellow in Computational Systems Biology with Marc-Thorsten Hütt.
2010 – 2016, became an Affiliated Lecturer in Network Biology and Computational Structural Biology at the Cambridge Computational Biology Institute, Department of Applied Mathemtics and Theoreticsl Physics and joined Sir Tom Blundell in the Department of Biochemistry as part of the Genome3D collaborative project and Structure-based drug discovery groups.
2012 – 2013, fixed-term Lectureship for the BBSRC-funded SysMIC DTP consortium, based at Birkbeck and University College London,
2013 – 2016, MRC Senior Investigator Scientist in computational metabolomics & lipidomics at MRC Human Nutrition Research, Elsie Widdowson Laboratory, Cambridge.
- Natural Sciences MSci Link Tutor
- Undergraduate and Postgraduate Course Module Leader
James Smith is a University Lecturer in Biochemistry in Metabolic & Biophysical Modelling and joined the School in September 2016. Hiis research group focusses on aspects of machanistic nutritional biochemistry and systems chemistry using biocomputing. His nutrtitional interests lie in building statistical models useful for predicting emergent states in metabolism.
External and International Collaborators
- Garstka Malgorzata Anna, Xi'an Jiaotong University, Xi’an City, Shaanxi, China. Diagnostic biomarker discovery in early gestational diabetes mellitus.
- Ahmed M. Ibrahim, Mansoura, Dakahlia, Egypt. Adjusting gut microbe populations, potential pro-phylactic nutritional strategies for metabolic syndrome.
- Babiker Badri, Ahfad University for Women, Omdurman, Sudan. Natural product-derived re-design of leishmanicidal agents.
- Micheal J Wise, School of Physics, Mathematics & Computing, University of Western Australia, Australia.
- David Hauton, University of Oxford, UK.
- Albert Koulman, Metabolic Research Laboratories, University of Cambridge, UK.
- Valerie Speirs, The Institute of Medical Sciences, University of Aberdeen, UK.
- Shortlisted Nominee for the Inspirational Teaching Award from the Faculty of Mathematics and Physical Sciences, University of Leeds Partnership Awards 2018.
- NIHR Peer reviewer
- European Commission H2020 Registered Expert Evaluator
- Peer Reviewer for Computational & Mathematical Methods in Medicine, Journal of Theoretical Biology
- From the BBSRC Gateway to Research in collaboration with the Core Metabolomics and Lipidomics Laboratory, University of Cambridge Metabolic Research Laboratories, UK.
- British Council, Newton Funds, FAPESP (Brazilian Research agency) and ANII (Uruguayan Research Agency), UK, Brazil & Uruguay Exploring the potential of biological soft matter in AgriFood challenges 2018
- Ms Nienyun Sharon Hsu, co-supervised by Richard Bayliss, School of Biological Sciences. Drug target discovery and peptide-based drug design for novel Basal-subtype breast cancer chemotherapy targetting intrinsically disordered regions in memrane-associated signalling domains.
- Mr John Holden, jointly funded by DEFRA (HMGov UK) and the University of Newcastle, co-supervised by Melvin Holmes & Rammile Ettelaie, School of Food Science & Nutrition, and Nick Parker & Andrew Baggaley, School of Mathematics, Statstics and Physics, University of Newcastle - Lattice-based percolation and criticality of communicable diseases - Development of early warning detection of epidemic spread.
- Ms Yuwei Li (starting in 2019), co-supervised by Francisco M. Goycoolea, School of Food Science & Nutrition - Modelling bacterial colony spatio-temporal patterns on microfluidic droplet surfaces - Rock-paper-scissor dynamics, reciprical altruism and dispersity of E.coli populations.
- Co-supervising Ms Jaida Begum with Richard Foster, School of Chemistry - Manganese-metallo protease inhibitor drug design.
- PhD University of Cambridge
- BSc (Hons) University of Leicester
- Biochemistry Society
- British Biophysical Society
- Mathematical Biology Society
- Academic Personal Tutor
- Module Lead & Coordinator for both FOOD 2031 and FOOD M5241,
- Network and Systems Modelling for FOOD 3130 Food Research: Recent Revelations and Disputes,
I am always looking for motivated research project students interested in being trained in any of the following multi-disiplinary research areas: medicinal & biological chemistry, structural biochemistry & membrane pharmacology, metabolic & nutritional state prediction (eg in health and disease), cancer metabolic modelling, computational systems biology, mathematical biology, biomedical statistics and machine learning.
Every year, I also host Summer Vacation internships as additional project students. I also have collaborators interested in sharing students. Enquire by email early in the New Year, if you are interested in joining my research group for a scholarship-funded project during the Summer - A number of organisations and societies, listed here and here offer funding and scholarships.
Former and Current Research Students
- M Harland (2016-7) with David Hauton - Regressing QT and RR interval signals to both logarithmic and parabolic to determine the accuracy of QTc interval changes during cardiovascular exercise under nitrate supplementation.
- A Bawden (2016-7) 2D machine learning stratification of both fat lipid biomarkers and participants useful for molecular epidemiology and fish-oil intervention studies.
- A Ackroyd (2016-7) with Alan Mackie - Time-dependent correlation clustering analysis to reveal coherence between subjective self-reported satiety, with objective data collected from lateral MRI imaging and circulating blood biomarkers both linked to gastric emptying.
- W Pan (2017) Explicit solvation - Hydrogen-bonding networks determined from conformational sampling of MD-generated conformation ensembles (under AMBER) followed by geometry optimisation with DFT (under CASTEP).
- M Liu (2017) Discrimination of Her2 and Luminal A breast cancer patients revealed by hierarchical clustering of nuclear receptor expression patterns.
- H Tong (2017) University of Leeds and EPRSC-funded Summer Studentship: Canonical correlation analysis and combinatoric composition analysis of acyl abundance in phospholipids and neutral acylglycerol, derived from large scale lipidomics.
- D Wu (2017) Identification of potential drug targets from hub-associated motifs from nuclear receptor-based expression correlation networks, found in distinct subgroups of basal (triple-negative) breast cancer patients.
- Z Ma (2017) Molecular recognition of isosterol and triterpenoid-based ligand-binding constraints to inform structure-based drug design.
- W Zhou (2018) Characterising PPI binding motifs in intrinsically disordered regions used by KIT protein signalling, for peptidomimetic drug target discovery in signalling protein aggregates in breast cancer.
- Y Li (2018) Identification of functional motifs from GAB1 intrinsically disordered regions and an assessment of their stabilising interactions with SHC binding domains.
- L Yeo (2018) Phase I hydroxylation metabolic prediction of xenobiotics - A comparison of mechanistic biotransformations by CYP2D6 and CYP2C9 predicted using SPORCalc.
- K Daly (2018) Erasmus+ Project Student from DIT Dublin, Ireland: Quantitative methods for exploring metabolomics:
i) Biostatistical methods for anthropometry landscape modelling according to dominant phospholipids in circulating lymphocytes.
ii) Unsupervised machine learning pattern recognition to characterise physiological biomarkers indicative of gestational diabetes in the first trimester.
- L Potts (2018-9) Identifying unusual metabolic biomarker correlations in clinical data from early gestational diabetes.
- S Holmes (2018-9) Rock-paper-scissor dynamics in bacteria - Development of a cellular automaton model for interacting gut bacterial colonies.
- G Gornall (2018-9) Water activity and hydration shells of polyphenols.
- H Tong (2018-9) Modelling the interactions of aflatoxins and their metabolites with calcium phosphate, co-supervised with Helen Chappell.
Research groups and institutes
- Food Chemistry and Biochemistry
- Obesity, Cancer and Metabolic Disease
- Food Colloids and Soft Matter at Interfaces
- Novel Food Design and Processing
- Theoretical Modelling and Simulation
- Bayesian clustering, Dirichlet process mixture modelling and metabolic profile landscape analysis of fat and lipid biomarkers derived from large-scale lipidomics