Handbook
Research
Principal investigators
University of Pittsburgh
Jacob Durrant

Jacob Durrant

Research focus

Durrant’s research is primarily concentrated in two key areas: computer-aided drug design (CADD) and computational structural biology. Overall, Durrant’s research aims to advance the field of computational biology and accelerate the drug discovery process by developing and applying novel computational methods and tools. Specifically:

  1. Small-molecule ligand identification: Durrant’s lab is at the forefront of developing and applying advanced computational techniques. These techniques are used to design small-molecule ligands that can bind to protein targets and potentially disrupt their functions. This work is particularly focused on accelerating drug discovery for infectious diseases, neurological conditions, and cancer.
  2. Improving CADD methods: The lab works on enhancing existing CADD techniques, particularly in molecular docking, scoring functions, and the use of machine learning and big data approaches to improve the accuracy of binding predictions.
  3. Molecular dynamics simulations: Durrant’s team uses molecular dynamics to study protein motions and how they affect ligand binding, including large-scale simulations of subcellular environments.
  4. Development of computational tools: Durrant has created several open-source software tools, such as AutoGrow, POVME, and LigMerge, to assist in drug discovery and molecular analysis.

Key publications

These publications give you a sample of current projects being undertaken in the lab. Obviously, these are not the only projects being worked on and you should contact the PI for more information.

  • Bhatt, R., Koes, D. R., & Durrant, J. D. (2024). CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks. Journal of Chemical Information and Modeling. DOI: 10.1021/acs.jcim.4c00825
  • Kochnev, Y., Ahmed, M., Maldonado, A. M., & Durrant, J. D. (2024). MolModa: accessible and secure molecular docking in a web browser. Nucleic Acids Research, gkae406. DOI: 10.1093/nar/gkae406
  • Hellemann, E., & Durrant, J. D. (2023). Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling. Journal of Chemical Theory and Computation, 19(17), 5677-5689. DOI: 10.1021/acs.jctc.3c00478
  • Van Wieren, A., Durrant, J. D., & Majumdar, S. (2023). Computational and experimental analyses of alanine racemase suggest new avenues for developing allosteric small‐molecule antibiotics. Drug Development Research, 84(5), 999-1007. DOI: 10.1002/ddr.22068
  • Hellemann, E., Walker, J. L., Lesko, M. A., Chandrashekarappa, D. G., Schmidt, M. C., O’Donnell, A. F., & Durrant, J. D. (2022). Novel mutation in hexokinase 2 confers resistance to 2-deoxyglucose by altering protein dynamics. PLoS Computational Biology, 18(3), e1009929. DOI: 10.1371/journal.pcbi.1009929

Funding

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Student opportunities

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Dr. Alex Maldonado works closely with Dr. Durrant and mentors undergraduate and graduate students. You could also consider reaching out to Dr. Maldonado to talk more about opportunities.

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