<i>Switching Go</i>̅<i>-Martini</i> for Investigating Protein Conformational Transitions and Associated Protein–Lipid Interactions

Yang, Song; Song, Chen

doi:10.1021/acs.jctc.3c01222

Cited by 7 publications

(2 citation statements)

References 82 publications

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“…It is promising to further expand this kind of approach in the future, because it may be the key for the simultaneous representation of multiple conformational states. One recent implementation in this direction involves replacing the single-basin Gō model with a multiple-basin Gō model 120 or at least a double-well potential. This modification may allow large conformational changes, enabling a more accurate representation of the transitions between stable folded states of proteins.…”

Section: Discussionmentioning

confidence: 99%

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Souza,

Borges-Araújo,

Brasnett

et al. 2024

Preprint

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Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.

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Section: Discussionmentioning

confidence: 99%

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Souza,

Borges-Araújo,

Brasnett

et al. 2024

Preprint

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“…62,64 Due to its peculiarities, ADK has been the subject of several experimental [64][65][66][67][68] and computational 59,[69][70][71][72][73][74][75][76][77][78][79][80][81][82][83][84] studies shedding light on the details of the structural rearrangements and the energetics governing its biological activity. Moreover, ADK has been extensively employed as paradigm system to benchmark various computational strategies aiming to reproduce large/allosteric apo(open)/holo(closed) conformational transitions, 71,72,[76][77][78][79][85][86][87][88][89][90] as well as the ability of the predicted structures to correctly reproduce the binding of substrates and inhibitors in molecular docking calculations. 81,91 Here, we demonstrate that our new protocol can generate a significant fraction of structures of ADK that are very similar to those bound to a set of different ligands, without exploiting any information about these compounds.…”

Section: Introductionmentioning

confidence: 99%

Predicting binding events in very flexible, allosteric, multi-domain proteins

Basciu,

Athar,

Kurt

et al. 2024

Preprint

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Knowledge of the structures formed by proteins and small ligands is of fundamental importance for understanding molecular principles of chemotherapy and for designing new and more effective drugs. Due to the still high costs and to the several limitations of experimental techniques, it is most often desirable to predict these ligand-protein complexesin silico, particularly when screening for new putative drugs from databases of millions of compounds. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology aimed at generating bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites. Validation was performed on the enzyme adenylate kinase (ADK), a paradigmatic example of proteins that undergo very large conformational changes upon ligand binding. By only exploiting the unbound structure and the putative binding sites of the protein, we generated a significant fraction of bound-like structures, which employed in ensemble-docking calculations allowed to find native-like poses of substrates, inhibitors, and catalytically incompetent binders. Our protocol provides a general framework for the generation of bound-like conformations of flexible proteins that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein’s activity. We foresee applications in virtual screening for difficult targets, prediction of the impact of amino acid mutations on structure and dynamics, and protein engineering.

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A contact‐based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold‐switch

González‐Higueras,

Freiberger,

Galaz‐Davison

et al. 2024

Protein Science

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Fold‐switching enables metamorphic proteins to reversibly interconvert between two highly dissimilar native states to regulate their protein functions. While about 100 proteins have been identified to undergo fold‐switching, unveiling the key residues behind this mechanism for each protein remains challenging. Reasoning that fold‐switching in proteins is driven by dynamic changes in local energetic frustration, we combined fold‐switching simulations generated using simplified structure‐based models with frustration analysis to identify key residues involved in this process based on the change in the density of minimally frustrated contacts during refolding. Using this approach to analyze the fold‐switch of the bacterial transcription factor RfaH, we identified 20 residues that significantly change their frustration during its fold‐switch, some of which have been experimentally and computationally reported in previous works. Our approach, which we developed as an additional module for the FrustratometeR package, highlights the role of local frustration dynamics in protein fold‐switching and offers a robust tool to enhance our understanding of other proteins with significant conformational shifts.

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Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein–Lipid Interactions

Cited by 7 publications

References 82 publications

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Predicting binding events in very flexible, allosteric, multi-domain proteins

A contact‐based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold‐switch

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