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Wang J, Miao Y. Protein-Protein Interaction-Gaussian Accelerated Molecular Dynamics (PPI-GaMD): Characterization of Protein Binding Thermodynamics and Kinetics. J Chem Theory Comput 2022; 18:1275-1285. [PMID: 35099970 DOI: 10.1021/acs.jctc.1c00974] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Protein-protein interactions (PPIs) play key roles in many fundamental biological processes such as cellular signaling and immune responses. However, it has proven challenging to simulate repetitive protein association and dissociation in order to calculate binding free energies and kinetics of PPIs due to long biological timescales and complex protein dynamics. To address this challenge, we have developed a new computational approach to all-atom simulations of PPIs based on a robust Gaussian accelerated molecular dynamics (GaMD) technique. The method, termed "PPI-GaMD", selectively boosts interaction potential energy between protein partners to facilitate their slow dissociation. Meanwhile, another boost potential is applied to the remaining potential energy of the entire system to effectively model the protein's flexibility and rebinding. PPI-GaMD has been demonstrated on a model system of the ribonuclease barnase interactions with its inhibitor barstar. Six independent 2 μs PPI-GaMD simulations have captured repetitive barstar dissociation and rebinding events, which enable calculations of the protein binding thermodynamics and kinetics simultaneously. The calculated binding free energies and kinetic rate constants agree well with the experimental data. Furthermore, PPI-GaMD simulations have provided mechanistic insights into barstar binding to barnase, which involves long-range electrostatic interactions and multiple binding pathways, being consistent with previous experimental and computational findings of this model system. In summary, PPI-GaMD provides a highly efficient and easy-to-use approach for binding free energy and kinetics calculations of PPIs.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
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Kurcinski M, Kmiecik S, Zalewski M, Kolinski A. Protein-Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations. Int J Mol Sci 2021; 22:ijms22147341. [PMID: 34298961 PMCID: PMC8306105 DOI: 10.3390/ijms22147341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 07/03/2021] [Accepted: 07/04/2021] [Indexed: 12/21/2022] Open
Abstract
Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.
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Kim J, Han W, Park T, Kim EJ, Bang I, Lee HS, Jeong Y, Roh K, Kim J, Kim JS, Kang C, Seok C, Han JK, Choi HJ. Sclerostin inhibits Wnt signaling through tandem interaction with two LRP6 ectodomains. Nat Commun 2020; 11:5357. [PMID: 33097721 PMCID: PMC7585440 DOI: 10.1038/s41467-020-19155-4] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 09/30/2020] [Indexed: 12/21/2022] Open
Abstract
Low-density lipoprotein receptor-related protein 6 (LRP6) is a coreceptor of the β-catenin-dependent Wnt signaling pathway. The LRP6 ectodomain binds Wnt proteins, as well as Wnt inhibitors such as sclerostin (SOST), which negatively regulates Wnt signaling in osteocytes. Although LRP6 ectodomain 1 (E1) is known to interact with SOST, several unresolved questions remain, such as the reason why SOST binds to LRP6 E1E2 with higher affinity than to the E1 domain alone. Here, we present the crystal structure of the LRP6 E1E2–SOST complex with two interaction sites in tandem. The unexpected additional binding site was identified between the C-terminus of SOST and the LRP6 E2 domain. This interaction was confirmed by in vitro binding and cell-based signaling assays. Its functional significance was further demonstrated in vivo using Xenopus laevis embryos. Our results provide insights into the inhibitory mechanism of SOST on Wnt signaling. The low-density lipoprotein receptor-related protein 6 (LRP6) is a co-receptor of the β-catenin-dependent Wnt signaling pathway and interacts with the Wnt inhibitor sclerostin (SOST). Here the authors present the crystal structure of SOST in complex with the LRP6 E1E2 ectodomain construct, which reveals that the SOST C-terminus binds to the LRP6 E2 domain, and further validate this binding site with in vitro and in vivo experiments.
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Affiliation(s)
- Jinuk Kim
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Wonhee Han
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Taeyong Park
- Department of Chemistry, Seoul National University, Seoul, 08826, Republic of Korea
| | - Eun Jin Kim
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.,Plumbline Life Sciences, Inc., Seoul, 06552, Republic of Korea
| | - Injin Bang
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.,Department of Physiology and Cellular Biophysics, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Hyun Sik Lee
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Yejing Jeong
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Kyeonghwan Roh
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jeesoo Kim
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.,Center for RNA Research, Institute for Basic Science, Seoul, 08826, Republic of Korea
| | - Jong-Seo Kim
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.,Center for RNA Research, Institute for Basic Science, Seoul, 08826, Republic of Korea
| | - Chanhee Kang
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jin-Kwan Han
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Hee-Jung Choi
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
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