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Professor JONATHAN HIRST


ML meets MLn: machine learning in ligand promoted homogeneous catalysis (2023)
Journal Article
Hirst, J. D., Boobier, S., Coughlan, J., Streets, J., Jacob, P. L., Pugh, O., …Woodward, S. (2023). ML meets MLn: machine learning in ligand promoted homogeneous catalysis. Artificial Intelligence Chemistry, 1(2), Article 100006. https://doi.org/10.1016/j.aichem.2023.100006

The benefits of using machine learning approaches in the design, optimisation and understanding of homogeneous catalytic processes are being increasingly realised. We focus on the understanding and implementation of key concepts, which serve as condu... Read More about ML meets MLn: machine learning in ligand promoted homogeneous catalysis.

Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics (2023)
Journal Article
Chio, H., Guest, E. E., Hobman, J. L., Dottorini, T., Hirst, J. D., & Stekel, D. J. (2023). Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics. Journal of Molecular Graphics and Modelling, 123, Article 108508. https://doi.org/10.1016/j.jmgm.2023.108508

Antibiotics enter the environment through waste streams, where they can exert selective pressure for antimicrobial resistance in bacteria. However, many antibiotics are excreted as partly metabolized forms, or can be subject to partial breakdown in w... Read More about Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics.

AI4Green: An Open-Source ELN for Green and Sustainable Chemistry (2023)
Journal Article
Boobier, S., Davies, J. C., Derbenev, I. N., Handley, C. M., & Hirst, J. D. (2023). AI4Green: An Open-Source ELN for Green and Sustainable Chemistry. Journal of Chemical Information and Modeling, 63(10), 2895–2901. https://doi.org/10.1021/acs.jcim.3c00306

An Electronic Laboratory Notebook (ELN) combining features, including data archival, collaboration tools, and green and sustainability metrics for organic chemistry, is presented. AI4Green is a web-based application, available as open-source code and... Read More about AI4Green: An Open-Source ELN for Green and Sustainable Chemistry.

Dynamic Disorder Drives Exciton Dynamics in Diketopyrrolopyrrole-Thiophene-Containing Molecular Crystals (2023)
Journal Article
Jiang, L., Hirst, J. D., & Do, H. (2023). Dynamic Disorder Drives Exciton Dynamics in Diketopyrrolopyrrole-Thiophene-Containing Molecular Crystals. Journal of Physical Chemistry C, 127(11), 5519-5532. https://doi.org/10.1021/acs.jpcc.2c07984

There is a growing interest in controllable molecular materials for potential nanophotonic and quantum information applications where excitons move beyond the incoherent transport regime. Thus, the ability to identify the key parameters that correlat... Read More about Dynamic Disorder Drives Exciton Dynamics in Diketopyrrolopyrrole-Thiophene-Containing Molecular Crystals.

Krein support vector machine classification of antimicrobial peptides (2023)
Journal Article
Redshaw, J., Ting, D. S., Brown, A., Hirst, J. D., & Gärtner, T. (2023). Krein support vector machine classification of antimicrobial peptides. Digital Discovery, 2(2), 502-511. https://doi.org/10.1039/d3dd00004d

Antimicrobial peptides (AMPs) represent a potential solution to the growing problem of antimicrobial resistance, yet their identification through wet-lab experiments is a costly and time-consuming process. Accurate computational predictions would all... Read More about Krein support vector machine classification of antimicrobial peptides.

Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C−C Bond Formation (2023)
Journal Article
Griffiths, R. C., Smith, F. R., Li, D., Wyatt, J., Rogers, D. M., Long, J. E., …Mitchell, N. (2023). Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C−C Bond Formation. Chemistry - A European Journal, 29(16), Article e202202503. https://doi.org/10.1002/chem.202202503

The site-selective modification of peptides and proteins facilitates the preparation of targeted therapeutic agents and tools to interrogate biochemical pathways. Among the numerous bioconjugation techniques developed to install groups of interest, t... Read More about Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C−C Bond Formation.

AI4Green: An Open-Source ELN for Green and Sustainable Chemistry (2023)
Working Paper
Boobier, S., Davies, J., Derbenev, I., Handley, C., & Hirst, J. AI4Green: An Open-Source ELN for Green and Sustainable Chemistry

An Electronic Laboratory Notebook (ELN) combining features, including data archival, collaboration tools, and green and sustainability metrics for organic chemistry, is presented. AI4Green is a web-based application, available as open-source code and... Read More about AI4Green: An Open-Source ELN for Green and Sustainable Chemistry.

Electronic circular dichroism of proteins computed using a diabatisation scheme (2022)
Journal Article
Rogers, D. M., Do, H., & Hirst, J. D. (2023). Electronic circular dichroism of proteins computed using a diabatisation scheme. Molecular Physics, 121(7-8), Article e2133748. https://doi.org/10.1080/00268976.2022.2133748

Circular dichroism (CD) spectroscopy is a powerful technique employed to study the structure of biomolecules. More accurate calculation of CD from first principles will aid both computational and experimental studies of protein structure and dynamics... Read More about Electronic circular dichroism of proteins computed using a diabatisation scheme.

Machine learning for yield prediction for chemical reactions using in situ sensors (2022)
Journal Article
Davies, J. C., Pattison, D., & Hirst, J. D. (2023). Machine learning for yield prediction for chemical reactions using in situ sensors. Journal of Molecular Graphics and Modelling, 118, Article 108356. https://doi.org/10.1016/j.jmgm.2022.108356

Machine learning models were developed to predict product formation from time-series reaction data for ten Buchwald-Hartwig coupling reactions. The data was provided by DeepMatter and was collected in their DigitalGlassware cloud platform. The reacti... Read More about Machine learning for yield prediction for chemical reactions using in situ sensors.

Free energy perturbation calculations of tetrahydroquinolines complexed to the first bromodomain of BRD4 (2022)
Journal Article
Silva, A. F., Guest, E. E., Falcone, B. N., Pickett, S. D., Rogers, D. M., & Hirst, J. D. (2023). Free energy perturbation calculations of tetrahydroquinolines complexed to the first bromodomain of BRD4. Molecular Physics, 121(9-10), Article e2124201. https://doi.org/10.1080/00268976.2022.2124201

Alchemical free energy perturbation (FEP) theory is widely used nowadays to calculate protein–ligand binding energies, often in support of drug discovery endeavours. We assess the accuracy and sensitivity of absolute FEP binding energies with respect... Read More about Free energy perturbation calculations of tetrahydroquinolines complexed to the first bromodomain of BRD4.