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Sisk TR, Robustelli P. Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model. Proc Natl Acad Sci U S A 2024; 121:e2313360121. [PMID: 38294935 PMCID: PMC10861926 DOI: 10.1073/pnas.2313360121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/22/2023] [Indexed: 02/02/2024] Open
Abstract
A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.
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Affiliation(s)
- Thomas R. Sisk
- Department of Chemistry, Dartmouth College, Hanover, NH03755
| | - Paul Robustelli
- Department of Chemistry, Dartmouth College, Hanover, NH03755
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Breen ME, Joy ST, Baruti OJ, Beyersdorf MS, Henley MJ, De Salle SN, Ycas PD, Croskey A, Cierpicki T, Pomerantz WCK, Mapp AK. Garcinolic Acid Distinguishes Between GACKIX Domains and Modulates Interaction Networks. Chembiochem 2023; 24:e202300439. [PMID: 37525583 PMCID: PMC10870240 DOI: 10.1002/cbic.202300439] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/26/2023] [Accepted: 07/27/2023] [Indexed: 08/02/2023]
Abstract
Natural products are often uniquely suited to modulate protein-protein interactions (PPIs) due to their architectural and functional group complexity relative to synthetic molecules. Here we demonstrate that the natural product garcinolic acid allosterically blocks the CBP/p300 KIX PPI network and displays excellent selectivity over related GACKIX motifs. It does so via a strong interaction (KD 1 μM) with a non-canonical binding site containing a structurally dynamic loop in CBP/p300 KIX. Garcinolic acid engages full-length CBP in the context of the proteome and in doing so effectively inhibits KIX-dependent transcription in a leukemia model. As the most potent small-molecule KIX inhibitor yet reported, garcinolic acid represents an important step forward in the therapeutic targeting of CBP/p300.
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Affiliation(s)
- Meghan E Breen
- Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Stephen T Joy
- Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Omari J Baruti
- Program in Chemical Biology, Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Matthew S Beyersdorf
- Program in Chemical Biology, Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Madeleine J Henley
- Program in Chemical Biology, Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Samantha N De Salle
- Program in Chemical Biology, Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Peter D Ycas
- Department of Chemistry, University of Minnesota, 207 Pleasant St SE, Minneapolis, MN-55455, USA
| | - Ayza Croskey
- Program in Chemical Biology, Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - Tomasz Cierpicki
- Department of Pathology, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
| | - William C K Pomerantz
- Department of Chemistry, University of Minnesota, 207 Pleasant St SE, Minneapolis, MN-55455, USA
| | - Anna K Mapp
- Department of Chemistry and Life Sciences Institute, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI-48109, USA
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Sisk T, Robustelli P. Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.550103. [PMID: 37546728 PMCID: PMC10401938 DOI: 10.1101/2023.07.21.550103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long-time scale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We do not, however, find evidence for the existence of canonical conformational selection or induced fit binding pathways. We observe four kinetically separated native-like bound states that interconvert on time scales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.
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Affiliation(s)
- Thomas Sisk
- Dartmouth College, Department of Chemistry, Hanover, NH, 03755
| | - Paul Robustelli
- Dartmouth College, Department of Chemistry, Hanover, NH, 03755
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