Refinement of protein‐protein complexes in contact map space with metadynamics simulations

Pfeiffenberger, Erik; Bates, Paul A.

doi:10.1002/prot.25612

Cited by 13 publications

(10 citation statements)

References 53 publications

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“…Indeed, MD simulations are a common tool to improve the quality of docking complexes by refining them [ 30 , 31 , 32 ], since they can account for conformational changes needed for binding at different levels, particularly on the scale of atoms, sidechains, loops, small molecules, or interfaces [ 27 ]. Thus, even complexes that lose part of initial (docking pose) contacts may assume a stable conformation during the dynamics refinement.…”

Section: Results and Discussionmentioning

confidence: 99%

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

et al. 2021

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Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the aggregate-associated diseases, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. In fact, although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of the pathological cytoplasmic inclusions observed in ALS patients. Indeed, the deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied. Moreover, it has also been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether the aggregation of CTFs represents a primary cause of ALS, it is a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a computational model of interaction based on the evaluation of shape complementarity at the molecular interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of protein fragments, with the aim of exploring the equilibrium conformations. Adopting a newly developed approach based on Zernike polynomials, able to find complementary regions in the molecular surface, we sampled a large set of solvent-exposed portions of CTFs structures as obtained from MD simulations. Our analysis proposes and assesses a set of possible association mechanisms between the CTFs, which could drive the aggregation process of the CTFs. To further evaluate the structural details of such associations, we perform molecular docking and additional MD simulations to propose possible complexes and assess their stability, focusing on complexes whose interacting regions are both characterized by a high shape complementarity and involve β3 and β5 strands at their interfaces.

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Section: Results and Discussionmentioning

confidence: 99%

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

et al. 2021

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“…MetaD is one of the most attractive enhanced sampling methods whose popularity continues to grow, and it has been successfully adopted in a wide range of biomolecule systems, including evaluations of drug molecules unbinding kinetics [45−47], predictions of protein-ligand binding pose [48], refinements of proteinprotein complex [49], transfers of proton-coupled electron [50], and designs of selective cyclic pentapeptide [51].…”

Section: B Metadynamicsmentioning

confidence: 99%

Advances in enhanced sampling molecular dynamics simulations for biomolecules

Wang

Zhang

2019

Chinese Journal of Chemical Physics

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Molecular dynamics simulation has emerged as a powerful computational tool for studying biomolecules as it can provide atomic insights into the conformational transitions involved in biological functions. However, when applied to complex biological macromolecules, the conformational sampling ability of conventional molecular dynamics is limited by the rugged free energy landscapes, leading to inherent timescale gaps between molecular dynamics simulations and real biological processes. To address this issue, several advanced enhanced sampling methods have been proposed to improve the sampling efficiency in molecular dynamics. In this review, the theoretical basis, practical applications, and recent improvements of both constraint and unconstrained enhanced sampling methods are summarized. Furthermore, the combined utilizations of different enhanced sampling methods that take advantage of both approaches are also briefly discussed.

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“…at the level of atoms, sidechains, loops, small molecules or interfaces, MD is commonly applied to refine docked complexes with the aim of improving their quality. (15)(16)(17)(18)(19)(20)(21) MD can be used at a more extensive level, where the docking process is simulated, however modelling spontaneous association and dissociation of proteins is very rare unless coarse-grained models or enhanced sampling methods are used. (22)(23)(24)(25) With regard to all-atom MD simulations, enhanced sampling techniques like Markov states models, (26)(27)(28)(29) umbrella sampling combined with replica exchange MD, (30)(31)(32)(33)(34)(35) elastic-network approaches (35), string method (36), metadynamics (37,38) and other methods have been used to sample conformational change prior to or during binding and to facilitate such binding events under the condition that the binding interface is known (39).…”

Section: Introductionmentioning

confidence: 99%

Native or non-native protein-protein docking models? Molecular dynamics to the rescue

Jandová

Vargiu

Bonvin

2021

Preprint

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Molecular docking excels at creating a plethora of potential models of protein-protein complexes. To correctly distinguish the favourable, native-like models from the remaining ones remains, however, a challenge. We assessed here if a protocol based on molecular dynamics (MD) simulations would allow to distinguish native from non-native models to complement scoring functions used in docking. To this end, first models for 25 protein-protein complexes were generated using HADDOCK. Next, MD simulations complemented with machine learning were used to discriminate between native and non-native complexes based on a combination of metrics reporting on the stability of the initial models. Native models showed higher stability in almost all measured properties, including the key ones used for scoring in the CAPRI competition, namely the positional root mean square deviations and fraction of native contacts from the initial docked model. A Random Forest classifier was trained, reaching 0.85 accuracy in correctly distinguishing native from non-native complexes. Reasonably modest simulation lengths in the order of 50 to 100 ns are already sufficient to reach this accuracy, which makes this approach applicable in practice.

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Refinement of protein‐protein complexes in contact map space with metadynamics simulations

Cited by 13 publications

References 53 publications

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

Advances in enhanced sampling molecular dynamics simulations for biomolecules

Native or non-native protein-protein docking models? Molecular dynamics to the rescue

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