Adrian H. Elcock, DPhil
Introduction
Work in my laboratory focuses on using molecular simulation techniques to address a variety of fundamental biophysical questions. Research areas in which we have recently published work include: (1) simulation of diffusion and association of proteins in highly concentrated solutions (such as those that are found inside living cells), (2) simulation of amino acid associations at the very high temperatures encountered by hyperthermophilic organisms, (3) computational prediction of drug-receptor interactions, with a view to identifying all cellular targets of current anti-cancer drugs, and (4) computational prediction of functionally important residues in proteins given only the protein's structure. Other research areas that we have recently developed interests in include: (1) computational identification of cryptic binding sites in proteins that might be used to develop novel inhibitors, (2) molecular simulations of protein folding in physiological conditions (including the effects of chaperonins), (3) modeling the role of conformational flexibility in protein-protein association events, and (4) experimentally measuring the affinities of drug-receptor interactions to provide reliable data for testing our computational methods. Students in my laboratory come from a wide range of backgrounds, and do not have to be experts in the use of computers: most of our work involves developing ideas in our heads, and computer simulations are typically only used to test these ideas. To complement our simulation work, we will in the near future also be increasingly conducting our own experiments: students joining my laboratory will therefore have the opportunity to undertake combined theoretical and experimental research projects.
Current Positions
- Professor of Biochemistry and Molecular Biology
Education
- BSc in Department of Chemistry, University of East Anglia, Norwich, United Kingdom
- D.Phil. in Department of Chemistry, Oxford University, Oxford, England
- Postdoctoral Fellow in Department of Chemistry and Biochemistry, University of California, San Diego, San Diego, California, United States
Graduate Program Affiliations
Center, Program and Institute Affiliations
Research Interests
- Computer simulation of macromolecular interactions and behavior in physiological conditions
Selected Publications
- McDonnell RT, Henderson AN, Elcock AH (2024). Structure Prediction of Large RNAs with AlphaFold3 Highlights its Capabilities and Limitations. J. Mol. Biol. 436, 168816.
- McDonnell RT, Elcock AH (2024) AutoRNC: an automated modeling program for building atomic models of ribosome-nascent chain complexes. Structure 32, 621-629.
- McDonnell RT, Henderson AN, Elcock AH (2024) Structure Prediction of Large RNAs with AlphaFold3 Highlights its Capabilities and Limitations. J. Mol. Biol. 436, 168816.
- McDonnell RT, Elcock AH (2024) AutoRNC: an automated modeling program for building atomic models of ribosome-nascent chain complexes. Structure 32, 621-629.
- Sanaboyana VR, Elcock AH (2023). Improving Signal and Transit Peptide Predictions Using AlphaFold2-predicted Protein Structures. J Mol Biol. 2024 Jan 15;436(2):168393. doi: 10.1016/j.jmb.2023.168393. Epub 2023 Dec 6. PMID: 38065275; PMCID: PMC10843742.
- Tworek JW, Elcock AH (2023). Orientationally Averaged Version of the Rotne–Prager–Yamakawa Tensor Provides a Fast but Still Accurate Treatment of Hydrodynamic Interactions in Brownian Dynamics Simulations of Biological Macromolecules. J. Chem. Theory Comput. 19, 5099-5111.
- Hacker WC, Elcock AH (2023). spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes. Nucleic Acids Res. 51, e92.
- Powers KT, Elcock AH, Washington MT (2017). The C-terminal region of translesion synthesis DNA polymerase n is partially unstructured and has high conformational flexibility. Nucleic Acids Res. 46, 2107-2020.
- Singh Gautam AK, Yu H, Yellman C, Elcock AH, Matouschek A (2022). Design principles that protect the proteasome from self-destruction. Protein Sci. 2022 Mar;31(3):556-567. doi: 10.1002/pro.4251. Epub 2021 Dec 16. PubMed PMID: 34878680; PubMed Central PMCID: PMC8862440.
- Wehrspan ZJ, McDonnell RT, Elcock AH (2022). Identification of Iron-Sulfur (Fe-S) Cluster and Zinc (Zn) Binding Sites Within Proteomes Predicted by DeepMind's AlphaFold2 Program Dramatically Expands the Metalloproteome. J Mol Biol. 2022 Jan 30;434(2):167377. doi: 10.1016/j.jmb.2021.167377. Epub 2021 Nov 24. PubMed PMID: 34838520; PubMed Central PMCID: PMC8785651.