Biology subjects

Lindorff-Larsen, K.

Publications and source records attributed to Lindorff-Larsen, K..

At least 91 records · Page 5Linked to original sources

bioRxiv2021

Double mutant of chymotrypsin inhibitor 2 stabilized through increased conformational entropy

The conformational heterogeneity of a folded protein can affect both its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here we have examined whether changed native state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side-chains with molecular dynamics simulations to quantify the native state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: A reduction in conformational dynamics (and entropy) of the native state of L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native state entropy might be needed to improve the predictions of the effect of mutations on protein stability.

biophysics↗

bioRxiv2021

Cryo-EM structure of the human NKCC1 transporter reveals mechanisms of ion coupling and specificity

The sodium-potassium-chloride transporter NKCC1 (SLC12A2) performs Na+-dependent Cl- and K+ ion uptake across plasma membranes. NKCC1 is important for regulating e.g. cell volume, hearing, blood pressure, and chloride gradients defining GABAergic and glycinergic signaling in brain. Here, we present a 2.6 [A] resolution cryo-electron microscopy (cryo-EM) structure of human NKCC1 in the substrate-loaded (Na+, K+, 2 Cl-) and inward-facing conformation adopting an occluded state that has also been observed for the SLC6 type transporters MhsT and LeuT. Cl- binding at the Cl1 site together with the nearby K+ ion provide a crucial bridge between the LeuT-fold scaffold and bundle domains. Cl- ion binding at the Cl2 site seems to undertake a structural role similar to a conserved glutamate of SLC6 transporters and may allow for chloride-sensitive regulation of transport. Supported by functional studies in mammalian cells and computational simulations we describe the Na+ binding site and a putative Na+ release pathway along transmembrane helix 5. The results provide insight into the structure-function relationship of NKCC1 with broader implications for other SLC12 family members.

biochemistry↗

bioRxiv2021

Disease-linked mutations trigger exposure of a protein quality control degron in the DHFR protein

Degrons are short stretches of amino acids or structural motifs that are embedded in proteins. They mediate recognition by E3 ubiquitin-protein ligases and thus confer protein degradation via the ubiquitin-proteasome system. Well-described degrons include the N-degrons, destruction boxes, and the PIP degrons, which mediate the controlled degradation of various proteins including signaling components and cell cycle regulators. In comparison, the so-called protein quality control (PQC) degrons that mediate the degradation of structurally destabilized or misfolded proteins are not well described. Here, we show that disease-linked DHFR missense variants are structurally destabilized and chaperone-dependent proteasome targets. We systematically mapped regions within DHFR to assess those that act as cytosolic PQC degrons in yeast cells. Two regions, DHFR-Deg13-36 (here Deg1) and DHFR-Deg61-84 (here Deg2), act as degrons and conferred degradation to unrelated fusion partners. The proteasomal turnover of Deg2 was dependent on the molecular chaperone Hsp70. Structural analyses by NMR and hydrogen/deuterium exchange revealed that Deg2 is buried in wild-type DHFR, but becomes transiently exposed in the disease-linked missense variants.

biochemistry↗

bioRxiv2021

Improving the global dimensions of intrinsically disordered proteins in Martini 3

Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small angle X-ray scattering (SAXS) data, and that increasing the strength of protein-water interactions favours more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multi-domain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.

biophysics↗

bioRxiv2021

A structural biology community assessment of AlphaFold 2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods have led to protein structure predictions that have reached the accuracy of experimentally determined models. While this has been independently verified, the implementation of these methods across structural biology applications remains to be tested. Here, we evaluate the use of AlphaFold 2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modelling of interactions; and modelling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modelled when compared to homology modelling, identifying structural features rarely seen in the PDB. AF2-based predictions of protein disorder and protein complexes surpass state-of-the-art tools and AF2 models can be used across diverse applications equally well compared to experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life science research.

biophysics↗

bioRxiv2021

Mg2+-dependent conformational equilibria in CorA: an integrated view on transport regulation

The CorA family of proteins regulates the homeostasis of divalent metal ions in many bacteria, archaea, and eukaryotic mitochondria, making it an important target in the investigation of the mechanisms of transport and its functional regulation. Although numerous structures of open and closed channels are now available for the CorA family, the mechanism of the transport regulation remains elusive. Here, we investigated the conformational distribution and associated dynamic behaviour of the pentameric Mg2+ channel CorA at room temperature using small-angle neutron scattering (SANS) in combination with molecular dynamics (MD) simulations and solid-state nuclear magnetic resonance spectroscopy (NMR). We find that neither the Mg2+-bound closed structure nor the Mg2+-free open forms are sufficient to explain the average conformation of CorA. Our data support the presence of conformational equilibria between multiple states, and we further find a variation in the behaviour of the backbone dynamics with and without Mg2+. We propose that CorA must be in a dynamic equilibrium between different non-conducting states, both symmetric and asymmetric, regardless of bound Mg2+ but that conducting states become more populated in Mg2+-free conditions. These properties are regulated by backbone dynamics and are key to understanding the functional regulation of CorA.

biophysics↗

bioRxiv2021

Predicting and interpreting large scale mutagenesis data using analyses of protein stability and conservation

Understanding and predicting the functional consequences of single amino acid is central in many areas of protein science. Here we collected and analysed experimental measurements of effects of >150,000 variants in 29 proteins. We used biophysical calculations to predict changes in stability for each variant, and assessed them in light of sequence conservation. We find that the sequence analyses give more accurate prediction of variant effects than predictions of stability, and that about half of the variants that show loss of function do so due to stability effects. We construct a machine learning model to predict variant effects from protein structure and sequence alignments, and show how the two sources of information are able to support one another. Together our results show how one can leverage large-scale experimental assessments of variant effects to gain deeper and general insights into the mechanisms that cause loss of function.

biophysics↗

bioRxiv2021

Accurate model of liquid-liquid phase behaviour of intrinsically-disordered proteins from data-driven optimization of single-chain properties

Many intrinsically disordered proteins (IDPs) may undergo liquidliquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalisation of intracellular biochemical reactions. The phase behaviour of IDPs is sequence-dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intra- and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

biophysics↗

bioRxiv2021

Computational and experimental assessment of backbone templates for computational protein design

Computational protein design has taken big strides over the recent years, however, the tools available are still not at a state where a sequence can be designed to fold into a given protein structure at will and with high probability. We have here applied a recent release of Rosetta Design to redesign a set of structurally very similar proteins belonging to the Thioredoxin fold. We determined design success using a combination of a genetic screening tool to assay folding/stability in E. coli and selecting the best hits from this for further biochemical characterization. We have previously used this set of template proteins for redesign and found that success was highly dependent on template structure, a trait which was also found in this study. Nevertheless, state of the art design software is now able to predict the best template, most likely due to the introduction of the cart_bonded energy term. The template that led to the greatest fraction of successful designs was the same (a Thioredoxin from spinach) as that identified in our previous study. Our previously described redesign of Thioredoxin, which also used the spinach protein as template, however also performed well. In the present study, both these templates yielded proteins with compact folded structures, and enforces the conclusion that any design project must carefully consider different design templates. Fortunately, selecting designs using the cart_bonded energy term appears to correctly identify such templates.

biochemistry↗

bioRxiv2021

Refining conformational ensembles of flexible proteins against small-angle X-ray scattering data

Intrinsically disordered proteins and flexible regions in multi-domain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modelling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model, i.e. an algorithm to calculate experimental observables from individual conformations or ensembles. In many cases, this involve one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle X-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data, but across the entire ensemble. Here, we present a protocol to dissect the effect of free-parameters on the calculated SAXS intensities, and to identify a reliable set of values. We have implemented this procedure in our Bayesian/Maximum Entropy framework for ensemble refinement, and demonstrate the results on four intrinsically disordered proteins and a three-domain protein connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects, and suggests that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins. SIGNIFICANCEThe flexibility of a protein is often key to its biological function, yet understanding and characterizing its conformational heterogeneity is difficult. We here describe a robust protocol for combining small-angle X-ray scattering experiments with computational modelling to obtain a conformational ensemble. In particular, we focus on the contribution of protein hydration to the experiments and how this is included in modelling the data. Our resulting algorithm and software should make modelling intrinsically disordered proteins and multi-domain proteins more robust, thus aiding in understanding the relationship between protein dynamics and biological function.

biophysics↗

bioRxiv2021

Transient exposure of a buried phosphorylation site in an autoinhibited protein

Autoinhibition is a mechanism used to regulate protein function, often by making functional sites inaccessible through the interaction with a cis-acting inhibitory domain. Such autoinhibitory domains often display a substantial degree of structural disorder when unbound, and only become structured in the inhibited state. This conformational dynamics makes it difficult to study the structural origin of regulation, including effects of regulatory post-translational modifications. Here, we study the autoinhibition of the Dbl Homology domain in the protein Vav1 by the so-called acidic inhibitory domain. We use molecular simulations to study the process by which a mostly unstructured inhibitory domain folds upon binding and how transient exposure of a key buried tyrosine residue makes it accessible for phosphorylation. We show that the inhibitory domain, which forms a helix in the bound and inhibited stated, samples helical structures already before binding and that binding occurs via a molten-globule-like intermediate state. Together, our results shed light on key interactions that enable the inhibitory domain to sample a finely-tuned equilibrium between an inhibited and a kinase-accessible state.

biophysics↗

bioRxiv2021

NMR structures and functional roles of two related chitin-binding domains of a lytic polysaccharide monooxygenase from Cellvibrio japonicus

Among the extensive repertoire of carbohydrate-active enzymes, lytic polysaccharide monooxygenases (LPMOs) have a key role in recalcitrant biomass degradation. LPMOs are copper-dependent enzymes that catalyze oxidative cleavage of glycosidic bonds in polysaccharides such as cellulose and chitin. Several LPMOs contain carbohydrate-binding modules (CBMs) that are known to promote LPMO efficiency. Still, structural and functional properties of some of these CBMs remain unknown and it is not clear why some LPMOs, like CjLPMO10A from Cellvibrio japonicus, have two CBMs (CjCBM5 and CjCBM73). Here, we studied substrate binding by these two CBMs to shine light on the functional variation, and determined the solution structures of both by NMR, which includes the first structure of a member of the CBM73 family. Chitin-binding experiments and molecular dynamics simulations showed that, while both CBMs bind crystalline chitin with Kd values in the {micro}M range, CjCBM73 has higher affinity than CjCBM5. Furthermore, NMR titration experiments showed that CjCBM5 binds soluble chitohexaose, whereas no binding to soluble chitin was detected for CjCBM73. These functional differences correlated with distinctly different architectures of the substrate-binding surfaces of the two CBMs. Taken together, these results provide insight into natural variation among related chitin-binding CBMs and the possible functional implications of such variation.

biochemistry↗

bioRxiv2021

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

bioinformatics↗

bioRxiv2021

Refinement of α-synuclein ensembles against SAXS data: Comparison of force fields and methods

The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulations times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein -synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.

biophysics↗

bioRxiv2020

Conformational Ensembles of Non-Coding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations

The 5' untranslated region (UTR) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome is a conserved, functional and structured genomic region consisting of several RNA stem-loop elements. While the secondary structure of such elements has been determined experimentally, their three-dimensional structures are not known yet. Here, we predict structure and dynamics of five RNA stem loops in the 5'-UTR of SARS-CoV-2 by extensive atomistic molecular dynamics simulations, more than 0.5ms of aggregate simulation time, in combination with enhanced sampling techniques. We compare simulations with available experimental data, describe the resulting conformational ensembles, and identify the presence of specific structural rearrangements in apical and internal loops that may be functionally relevant. Our atomic-detailed structural predictions reveal a rich dynamics in these RNA molecules, could help the experimental characterisation of these systems, and provide putative three-dimensional models for structure-based drug design studies.

biophysics↗

bioRxiv2020

Global analysis of multi-mutants to discover stabilizing amino acid substitutions

The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions. The GMMA method achieves a good fit to the data while being analytically transparent. The six top-ranking substitutions are demonstrated to progressively enhance GFP and in general, our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function, only using a single experiment as input. Significance StatementProtein engineering is carried out to improve proteins for practical applications by changing one or more amino acid residues in a protein. We present a method termed global multi-mutant analysis (GMMA) that helps solve two problems in protein engineering. First, because many proteins are already highly optimized, it can be difficult to identify individual variants that further improve function. Second, while it is possible to combine variants with small individual effects, such approaches may be hampered by non-additivity. GMMA identifies combinable effects of single substitutions from a large set of variants each carrying multiple substitutions. We demonstrate the approach on a set of 54,000 variants of green fluorescent protein and identify many enhancing single-substitutions from a single experiment.

biophysics↗

bioRxiv2020

Synergistic stabilization of a double mutant in CI2 from an in-cell library screen

Most single point mutations destabilize folded proteins. Mutations that stabilize a protein typically only have a small effect and multiple mutations are often needed to substantially increase the stability. Multiple point mutations may act synergistically on the stability, and it is not straightforward to predict their combined effect from the individual contributions. Here, we have applied an efficient in-cell assay to select variants of the barley chymotrypsin inhibitor 2 with increased stability. We find two variants that are more than 3.8 kJ/mol more stable than the wild-type. In one case the increased stability is the effect of the single substitution D55G. The other case is a double mutant, L49I/I57V, which is 5.1 kJ/mol more stable than the sum of the effects of the individual mutations. In addition to demonstrating the strength of our selection system for finding stabilizing mutations, our work also demonstrate how subtle conformational effects may modulate stability.

biophysics↗

bioRxiv2020

Properdin oligomers adopt rigid extended conformations supporting function

Properdin stabilizes convertases formed upon activation of the complement cascade within the immune system. The biological activity of properdin depends on the oligomerization state, but whether properdin oligomers are rigid and how their structure links to function remains unknown. We show by combining electron microscopy and solution scattering, that properdin oligomers adopt extended rigid and well-defined conformations that are well approximated by single models of apparent n-fold rotational symmetry with dimensions of 23-36 nm. Properdin monomers are pretzel shaped molecules with limited flexibility. In solution, properdin dimers are curved molecules whereas trimers and tetramers are close to being planar molecules. Structural analysis indicates that simultaneous binding through all binding sites to surface linked convertases is unlikely for properdin trimer and tetramers. We show that multivalency alone is insufficient for full activity in a cell lysis assay. Hence, the observed rigid extended oligomer structure is an integral component of properdin function.

immunology↗