The importance of dynamics in integrative modeling of supramolecular assemblies

CLoNe: automated clustering based on local density neighborhoods for application to biomolecular structural ensembles

Motivation

Proteins are intrinsically dynamic entities. Flexibility sampling methods, such as molecular dynamics or those arising from integrative modeling strategies, are now commonplace and enable the study of molecular conformational landscapes in many contexts. Resulting structural ensembles increase in size as technological and algorithmic advancements take place, making their analysis increasingly demanding. In this regard, cluster analysis remains a go-to approach for their classification. However, many state-of-the-art algorithms are restricted to specific cluster properties. Combined with tedious parameter fine-tuning, cluster analysis of protein structural ensembles suffers from the lack of a generally applicable and easy to use clustering scheme.

Results

We present CLoNe, an original Python-based clustering scheme that builds on the Density Peaks algorithm of Rodriguez and Laio. CLoNe relies on a probabilistic analysis of local density distributions derived from nearest neighbors to find relevant clusters regardless of cluster shape, size, distribution and amount. We show its capabilities on many toy datasets with properties otherwise dividing state-of-the-art approaches and improves on the original algorithm in key aspects. Applied to structural ensembles, CLoNe was able to extract meaningful conformations from membrane binding events and ligand-binding pocket opening as well as identify dominant dimerization motifs or inter-domain organization. CLoNe additionally saves clusters as individual trajectories for further analysis and provides scripts for automated use with molecular visualization software.

Availability and implementation

www.epfl.ch/labs/lbm/resources, github.com/LBM-EPFL/CLoNe.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Human RNA Helicase DDX21 Presents a Dimerization Interface Necessary for Helicase Activity

Members of the DEAD-box helicase family are involved in all fundamental processes of RNA metabolism, and as such, their malfunction is associated with various diseases. Currently, whether and how oligomerization impacts their biochemical and biological functions is not well understood. In this work, we show that DDX21, a human DEAD-box helicase with RNA G-quadruplex resolving activity, is dimeric and that its oligomerization state influences its helicase activity. Solution small-angle X-ray scattering (SAXS) analysis uncovers a flexible multi-domain protein with a central dimerization domain. While the Arg/Gly rich C termini, rather than dimerization, are key to maintaining high affinity for RNA substrates, in vitro helicase assays indicate that an intact dimer is essential for both DDX21 ATP-dependent double-stranded RNA unwinding and ATP-independent G-quadruplex remodeling activities. Our results suggest that oligomerization plays a key role in regulating RNA DEAD-box helicase activity.

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The human RNA DEAD-box helicase DDX21 is dimeric

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DDX21 dimerization is mediated by a hydrophobic central core domain

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SAXS-based modeling reveals that DDX21 is intrinsically flexible

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Dimerization and C-terminal domains mediate G-quadruplex and dsRNA unwinding

The Polyglutamine Expansion at the N-Terminal of Huntingtin Protein Modulates the Dynamic Configuration and Phosphorylation of the C-Terminal HEAT Domain

The polyQ expansion in huntingtin protein (HTT) is the prime cause of Huntington's disease (HD). The recent cryoelectron microscopy (cryo-EM) structure of HTT-HAP40 complex provided the structural information on its HEAT-repeat domains. Here, we present analyses of the impact of polyQ length on the structure and function of HTT via an integrative structural and biochemical approach. The cryo-EM analysis of normal (Q23) and disease (Q78) type HTTs shows that the structures of apo HTTs significantly differ from the structure of HTT in a HAP40 complex and that the polyQ expansion induces global structural changes in the relative movements among the HTT domains. In addition, we show that the polyQ expansion alters the phosphorylation pattern across HTT and that Ser2116 phosphorylation in turn affects the global structure and function of HTT. These results provide a molecular basis for the effect of the polyQ segment on HTT structure and activity, which may be important for HTT pathology.

Will Cryo-Electron Microscopy Shift the Current Paradigm in Protein Structure Prediction?

Protein dynamics is undoubtedly a pervasive ingredient in all biological functions. However, structural biology has been strongly driven by a static-centered view of protein architecture. We argue that the recent advances of cryo-electron microscopy (EM) have the potential to more broadly explore the conformational landscapes of protein complexes and therefore will enhance our ability to predict the diverse conformations of tertiary and quaternary protein structures that are functionally relevant in physiological conditions.

Modelling structures in cryo-EM maps

Recent advances in structure determination of sub-cellular structures using cryo-electron microscopy and tomography have enabled us to understand their architecture in a more detailed manner and gain insight into their function. The choice of approach to use for atomic model building, fitting, refinement and validation in the 3D map resulting from these experiments depends primarily on the resolution of the map and the prior information on the corresponding model. Here, we survey some of such methods and approaches and highlight their uses in specific recent examples.

KAP1 is an antiparallel dimer with a functional asymmetry

This study reveals the architecture of human KAP1 by integrating molecular modeling with small-angle X-ray scattering and single-molecule experiments. KAP1 dimers feature a structural asymmetry at the C-terminal domains that has functional implications for recruitment of HP1.

KAP1 (KRAB domain–associated protein 1) plays a fundamental role in regulating gene expression in mammalian cells by recruiting different transcription factors and altering the chromatin state. In doing so, KAP1 acts both as a platform for macromolecular interactions and as an E3 small ubiquitin modifier ligase. This work sheds light on the overall organization of the full-length protein combining solution scattering data, integrative modeling, and single-molecule experiments. We show that KAP1 is an elongated antiparallel dimer with an asymmetry at the C-terminal domains. This conformation is consistent with the finding that the Really Interesting New Gene (RING) domain contributes to KAP1 auto-SUMOylation. Importantly, this intrinsic asymmetry has key functional implications for the KAP1 network of interactions, as the heterochromatin protein 1 (HP1) occupies only one of the two putative HP1 binding sites on the KAP1 dimer, resulting in an unexpected stoichiometry, even in the context of chromatin fibers.

Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.

Unspinning chromatin: Revealing the dynamic nucleosome landscape by NMR

NMR is an essential technique for obtaining information at atomic resolution on the structure, motions and interactions of biomolecules. Here, we review the contribution of NMR to our understanding of the fundamental unit of chromatin: the nucleosome. Nucleosomes compact the genome by wrapping the DNA around a protein core, the histone octamer, thereby protecting genomic integrity. Crucially, the imposed barrier also allows strict regulation of gene expression, DNA replication and DNA repair processes through an intricate system of histone and DNA modifications and a wide range of interactions between nucleosomes and chromatin factors. In this review, we describe how NMR has contributed to deciphering the molecular basis of nucleosome function. Starting from pioneering studies in the 1960s using natural abundance NMR studies, we focus on the progress in sample preparation and NMR methodology that has allowed high-resolution studies on the nucleosome and its subunits. We summarize the results and approaches of state-of-the-art NMR studies on nucleosomal DNA, histone complexes, nucleosomes and nucleosomal arrays. These studies highlight the particular strength of NMR in studying nucleosome dynamics and nucleosome-protein interactions. Finally, we look ahead to exciting new possibilities that will be afforded by on-going developments in solution and solid-state NMR. By increasing both the depth and breadth of nucleosome NMR studies, it will be possible to offer a unique perspective on the dynamic landscape of nucleosomes and its interacting proteins.

Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules

Fluctuating Finite Element Analysis (FFEA) is a software package designed to perform continuum mechanics simulations of proteins and other globular macromolecules. It combines conventional finite element methods with stochastic thermal noise, and is appropriate for simulations of large proteins and protein complexes at the mesoscale (length-scales in the range of 5 nm to 1 μm), where there is currently a paucity of modelling tools. It requires 3D volumetric information as input, which can be low resolution structural information such as cryo-electron tomography (cryo-ET) maps or much higher resolution atomistic co-ordinates from which volumetric information can be extracted. In this article we introduce our open source software package for performing FFEA simulations which we have released under a GPLv3 license. The software package includes a C ++ implementation of FFEA, together with tools to assist the user to set up the system from Electron Microscopy Data Bank (EMDB) or Protein Data Bank (PDB) data files. We also provide a PyMOL plugin to perform basic visualisation and additional Python tools for the analysis of FFEA simulation trajectories. This manuscript provides a basic background to the FFEA method, describing the implementation of the core mechanical model and how intermolecular interactions and the solvent environment are included within this framework. We provide prospective FFEA users with a practical overview of how to set up an FFEA simulation with reference to our publicly available online tutorials and manuals that accompany this first release of the package.

Structural database resources for biological macromolecules

This Briefing reviews the widely used, currently active, up-to-date databases derived from the worldwide Protein Data Bank (PDB) to facilitate browsing, finding and exploring its entries. These databases contain visualization and analysis tools tailored to specific kinds of molecules and interactions, often including also complex metrics precomputed by experts or external programs, and connections to sequence and functional annotation databases. Importantly, updates of most of these databases involves steps of curation and error checks based on specific expertise about the subject molecules or interactions, and removal of sequence redundancy, both leading to better data sets for mining studies compared with the full list of raw PDB entries. The article presents the databases in groups such as those aimed to facilitate browsing through PDB entries, their molecules and their general information, those built to link protein structure with sequence and dynamics, those specific for transmembrane proteins, nucleic acids, interactions of biomacromolecules with each other and with small molecules or metal ions, and those concerning specific structural features or specific protein families. A few webservers directly connected to active databases, and a few databases that have been discontinued but would be important to have back, are also briefly commented on. Along the Briefing, sample cases where these databases have been used to aid structural studies or advance our knowledge about biological macromolecules are referenced. A few specific examples are also given where using these databases is easier and more informative than using raw PDB data.

Disentangling constraints using viability evolution principles in integrative modeling of macromolecular assemblies

Predicting the structure of large molecular assemblies remains a challenging task in structural biology when using integrative modeling approaches. One of the main issues stems from the treatment of heterogeneous experimental data used to predict the architecture of native complexes. We propose a new method, applied here for the first time to a set of symmetrical complexes, based on evolutionary computation that treats every available experimental input independently, bypassing the need to balance weight components assigned to aggregated fitness functions during optimization.

Assessing the potential of atomistic molecular dynamics simulations to probe reversible protein-protein recognition and binding

Protein-protein recognition and binding are governed by diffusion, noncovalent forces and conformational flexibility, entangled in a way that only molecular dynamics simulations can dissect at high resolution. Here we exploited ubiquitin's noncovalent dimerization equilibrium to assess the potential of atomistic simulations to reproduce reversible protein-protein binding, by running submicrosecond simulations of systems with multiple copies of the protein at millimolar concentrations. The simulations essentially fail because they lead to aggregates, yet they reproduce some specificity in the binding interfaces as observed in known covalent and noncovalent ubiquitin dimers. Following similar observations in literature we hint at electrostatics and water descriptions as the main liable force field elements, and propose that their optimization should consider observables relevant to multi-protein systems and unfolded proteins. Within limitations, analysis of binding events suggests salient features of protein-protein recognition and binding, to be retested with improved force fields. Among them, that specific configurations of relative direction and orientation seem to trigger fast binding of two molecules, even over 50 Å distances; that conformational selection can take place within surface-to-surface distances of 10 to 40 Å i.e. well before actual intermolecular contact; and that establishment of contacts between molecules further locks their conformations and relative orientations.