Protein-protein crystal-packing contacts

High-resolution double vision of the allosteric phosphatase PTP1B

Protein tyrosine phosphatase 1B (PTP1B) plays important roles in cellular homeostasis and is a highly validated therapeutic target for multiple human ailments, including diabetes, obesity and breast cancer. However, much remains to be learned about how conformational changes may convey information through the structure of PTP1B to enable allosteric regulation by ligands or functional responses to mutations. High-resolution X-ray crystallography can offer unique windows into protein conformational ensembles, but comparison of even high-resolution structures is often complicated by differences between data sets, including non-isomorphism. Here, the highest resolution crystal structure of apo wild-type (WT) PTP1B to date is presented out of a total of ∼350 PTP1B structures in the PDB. This structure is in a crystal form that is rare for PTP1B, with two unique copies of the protein that exhibit distinct patterns of conformational heterogeneity, allowing a controlled comparison of local disorder across the two chains within the same asymmetric unit. The conformational differences between these chains are interrogated in the apo structure and between several recently reported high-resolution ligand-bound structures. Electron-density maps in a high-resolution structure of a recently reported activating double mutant are also examined, and unmodeled alternate conformations in the mutant structure are discovered that coincide with regions of enhanced conformational heterogeneity in the new WT structure. These results validate the notion that these mutations operate by enhancing local dynamics, and suggest a latent susceptibility to such changes in the WT enzyme. Together, these new data and analysis provide a detailed view of the conformational ensemble of PTP1B and highlight the utility of high-resolution crystallography for elucidating conformational heterogeneity with potential relevance for function.

Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

Protein Function Analysis through Machine Learning

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein–ligand binding, including allosteric effects, protein–protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.

Bridging the N-terminal and middle domains in FliG of the flagellar rotor

Flagella are necessary for bacterial movement and contribute to various aspects of virulence. They are complex cylindrical structures built of multiple molecular rings with self-assembly properties. The flagellar rotor is composed of the MS-ring and the C-ring. The FliG protein of the C-ring is central to flagellar assembly and function due to its roles in linking the C-ring with the MS-ring and in torque transmission from stator to rotor. No high-resolution structure of an assembled C-ring has been resolved to date, and the conformation adopted by FliG within the ring is unclear due to variations in available crystallographic data. Here, we use molecular dynamics (MD) simulations to study the conformation and dynamics of FliG in different states of assembly, including both in physiologically relevant and crystallographic lattice environments. We conclude that the linker between the FliG N-terminal and middle domain likely adopts an extended helical conformation in vivo, in contrast with the contracted conformation observed in some previous X-ray studies. We further support our findings with integrative model building of full-length FliG and a FliG ring model that is compatible with cryo-electron tomography (cryo-ET) and electron microscopy (EM) densities of the C-ring. Collectively, our study contributes to a better mechanistic understanding of the flagellar rotor assembly and its function.

The properties of human disease mutations at protein interfaces

The assembly of proteins into complexes and their interactions with other biomolecules are often vital for their biological function. While it is known that mutations at protein interfaces have a high potential to be damaging and cause human genetic disease, there has been relatively little consideration for how this varies between different types of interfaces. Here we investigate the properties of human pathogenic and putatively benign missense variants at homomeric (isologous and heterologous), heteromeric, DNA, RNA and other ligand interfaces, and at different regions in proteins with respect to those interfaces. We find that different types of interfaces vary greatly in their propensity to be associated with pathogenic mutations, with homomeric heterologous and DNA interfaces being particularly enriched in disease. We also find that residues that do not directly participate in an interface, but are close in three-dimensional space, show a significant disease enrichment. Finally, we observe that mutations at different types of interfaces tend to have distinct property changes when undergoing amino acid substitutions associated with disease, and that this is linked to substantial variability in their identification by computational variant effect predictors.

Nearly all proteins interact with other molecules as part of their biological function. For example, proteins can interact with other copies of the same type of protein, with different proteins, with DNA, or with small ligand molecules. Many mutations at protein interfaces, the regions of proteins that interact with other molecules, are known to cause human genetic disease. In this study, we first investigate how different types of protein interfaces have different tendencies to be associated with disease. We also show that the closer a mutation is to an interface, the more likely it is to cause disease. Finally, we study how mutations at different types of interfaces tend to be associated with different changes in amino acid properties, which appears to influence our ability to computationally predict the effects of mutations. Ultimately, we hope that consideration of protein interface properties will eventually improve our ability to identify new disease-causing mutations.

Parameterizing elastic network models to capture the dynamics of proteins

Coarse-grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff-based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay-based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental B-factors. To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non-linear optimization problem whose parameters describe both rigid-body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes.

InterPep2: global peptide-protein docking using interaction surface templates

Motivation

Interactions between proteins and peptides or peptide-like intrinsically disordered regions are involved in many important biological processes, such as gene expression and cell life-cycle regulation. Experimentally determining the structure of such interactions is time-consuming and difficult because of the inherent flexibility of the peptide ligand. Although several prediction-methods exist, most are limited in performance or availability.

Results

InterPep2 is a freely available method for predicting the structure of peptide–protein interactions. Improved performance is obtained by using templates from both peptide–protein and regular protein–protein interactions, and by a random forest trained to predict the DockQ-score for a given template using sequence and structural features. When tested on 252 bound peptide–protein complexes from structures deposited after the complexes used in the construction of the training and templates sets of InterPep2, InterPep2-Refined correctly positioned 67 peptides within 4.0 Å LRMSD among top10, similar to another state-of-the-art template-based method which positioned 54 peptides correctly. However, InterPep2 displays a superior ability to evaluate the quality of its own predictions. On a previously established set of 27 non-redundant unbound-to-bound peptide–protein complexes, InterPep2 performs on-par with leading methods. The extended InterPep2-Refined protocol managed to correctly model 15 of these complexes within 4.0 Å LRMSD among top10, without using templates from homologs. In addition, combining the template-based predictions from InterPep2 with ab initio predictions from PIPER-FlexPepDock resulted in 22% more near-native predictions compared to the best single method (22 versus 18).

Availability and implementation

The program is available from: http://wallnerlab.org/InterPep2.

Supplementary information

Supplementary data are available at Bioinformatics online.

Impact of protein dynamics on secondary structure prediction

Protein 3D structures support their biological functions. As the number of protein structures is negligible in regards to the number of available protein sequences, prediction methodologies relying only on protein sequences are essential tools. In this field, protein secondary structure prediction (PSSPs) is a mature area, and is considered to have reached a plateau. Nonetheless, proteins are highly dynamical macromolecules, a property that could impact the PSSP methods. Indeed, in a previous study, the stability of local protein conformations was evaluated demonstrating that some regions easily changed to another type of secondary structure. The protein sequences of this dataset were used by PSSPs and their results compared to molecular dynamics to investigate their potential impact on the quality of the secondary structure prediction. Interestingly, a direct link is observed between the quality of the prediction and the stability of the assignment to the secondary structure state. The more stable a local protein conformation is, the better the prediction will be. The secondary structure assignment not taken from the crystallized structures but from the conformations observed during the dynamics slightly increase the quality of the secondary structure prediction. These results show that evaluation of PSSPs can be done differently, but also that the notion of dynamics can be included in development of PSSPs and other approaches such as de novo approaches.

The current understanding of KRAS protein structure and dynamics

One of the most common drivers in human cancer is the mutant KRAS protein. Not so long ago KRAS was considered as an undruggable oncoprotein. After a long struggle, however, we finally see some light at the end of the tunnel as promising KRAS targeted therapies are in or approaching clinical trials. In recent years, together with the promising progress in RAS drug discovery, our understanding of KRAS has increased tremendously. This progress has been accompanied with a resurgence of publicly available KRAS structures, which were limited to nine structures less than ten years ago. Furthermore, the ever-increasing computational capacity has made biologically relevant timescales accessible, enabling molecular dynamics (MD) simulations to study the dynamics of KRAS protein in more detail at the atomistic level. In this minireview, my aim is to provide the reader an overview of the publicly available KRAS structural data, insights to conformational dynamics revealed by experiments and what we have learned from MD simulations. Also, I will discuss limitations of the current data and provide suggestions for future research related to KRAS, which would fill out the existing gaps in our knowledge and provide guidance in deciphering this enigmatic oncoprotein.

Topology independent structural matching discovers novel templates for protein interfaces

Motivation

Protein-protein interactions (PPI) are essential for the function of the cellular machinery. The rapid growth of protein-protein complexes with known 3D structures offers a unique opportunity to study PPI to gain crucial insights into protein function and the causes of many diseases. In particular, it would be extremely useful to compare interaction surfaces of monomers, as this would enable the pinpointing of potential interaction surfaces based solely on the monomer structure, without the need to predict the complete complex structure. While there are many structural alignment algorithms for individual proteins, very few have been developed for protein interfaces, and none that can align only the interface residues to other interfaces or surfaces of interacting monomer subunits in a topology independent (non-sequential) manner.

Results

We present InterComp, a method for topology and sequence-order independent structural comparisons. The method is general and can be applied to various structural comparison applications. By representing residues as independent points in space rather than as a sequence of residues, InterComp can be applied to a wide range of problems including interface-surface comparisons and interface-interface comparisons. We demonstrate a use-case by applying InterComp to find similar protein interfaces on the surface of proteins. We show that InterComp pinpoints the correct interface for almost half of the targets (283 of 586) when considering the top 10 hits, and for 24% of the top 1, even when no templates can be found with regular sequence-order dependent structural alignment methods.

Availability and implementation

The source code and the datasets are available at: http://wallnerlab.org/InterComp.

Supplementary information

Supplementary data are available at Bioinformatics online.

Accurate Classification of Biological and non-Biological Interfaces in Protein Crystal Structures using Subtle Covariation Signals

Proteins often work as oligomers or multimers in vivo. Therefore, elucidating their oligomeric or multimeric form (quaternary structure) is crucially important to ascertain their function. X-ray crystal structures of numerous proteins have been accumulated, providing information related to their biological units. Extracting information of biological units from protein crystal structures represents a meaningful task for modern biology. Nevertheless, although many methods have been proposed for identifying biological units appearing in protein crystal structures, it is difficult to distinguish biological protein-protein interfaces from crystallographic ones. Therefore, our simple but highly accurate classifier was developed to infer biological units in protein crystal structures using large amounts of protein sequence information and a modern contact prediction method to exploit covariation signals (CSs) in proteins. We demonstrate that our proposed method is promising even for weak signals of biological interfaces. We also discuss the relation between classification accuracy and conservation of biological units, and illustrate how the selection of sequences included in multiple sequence alignments as sources for obtaining CSs affects the results. With increased amounts of sequence data, the proposed method is expected to become increasingly useful.

Unit-cell response of tetragonal hen egg white lysozyme upon controlled relative humidity variation

Variation of relative humidity (rH) greatly affects the internal order of solvent-based protein crystals, and the rearrangement of molecules can be efficiently recorded in distinct diffraction patterns. This study focuses on this topic, reporting the effect of rH variation experiments on hen egg white lysozyme (HEWL) polycrystalline precipitates of tetragonal symmetry using X-ray powder diffraction (XRPD). In situ XRPD data were collected on HEWL specimens during dehydration and rehydration processes using laboratory instrumentation. A known polymorph [space group P43212, a = 79.07181 (1), c = 38.0776 (1) Å] was identified during gradual dehydration from 95 to 63% rH and vice versa. Pawley analysis of collected data sets and accurate extraction of unit-cell parameters indicated a characteristic evolution of the tetragonal axes with rH. In addition, there is a low humidity level below which samples do not retain their crystallinity. This work illustrates the accuracy of laboratory XRPD as a probe for time-resolved studies of proteins and in situ investigations of gradual structural modifications upon rH variation. These experiments provide essential information for improving production and post-production practices of microcrystalline protein-based pharmaceuticals.

Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

Metal-Assisted Assembly of Protein Containers Loaded with Inorganic Nanoparticles

Protein containers are suitable building blocks for bioinorganic materials. Here, we show that high concentrations of magnesium ions induce the formation of a unitary protein scaffold, whereas low magnesium concentration leads to a binary protein scaffold. The molecular interactions in the protein scaffold were characterized with X-ray crystallography to high resolution. We show that the unitary framework can be applied for the assembly of inorganic nanoparticles such as metal oxides into highly ordered bioinorganic structures. Our work emphasizes the structural tunability of protein-container-based materials, important for adjusting emerging properties of such materials.

MBP-binding DARPins facilitate the crystallization of an MBP fusion protein

Designed ankyrin-repeat proteins (DARPins) that bind to maltose-binding protein (MBP) with high affinity can facilitate the crystallization of an MBP fusion protein. The use of MBP-specific DARPins increases the probability of obtaining crystals.

The production of high-quality crystals is the main bottleneck in determining the structures of proteins using X-ray crystallography. In addition to being recognized as a very effective solubility-enhancing fusion partner, Escherichia coli maltose-binding protein (MBP) has also been successfully employed as a ‘fixed-arm’ crystallization chaperone in more than 100 cases. Here, it is reported that designed ankyrin-repeat proteins (DARPins) that bind with high affinity to MBP can promote the crystallization of an MBP fusion protein when the fusion protein alone fails to produce diffraction-quality crystals. As a proof of principle, three different co-crystal structures of MBP fused to the catalytic domain of human dual-specificity phosphatase 1 in complex with DARPins are reported.

Integrating co-evolutionary signals and other properties of residue pairs to distinguish biological interfaces from crystal contacts

It remains challenging to accurately discriminate between biological and crystal interfaces. Most existing analyses and algorithms focused on the features derived from a single side of the interface. However, less attention has been paid to the properties of residue pairs across protein interfaces. To address this problem, we defined a novel co-evolutionary feature for homodimers through integrating direct coupling analysis and image processing techniques. The residue pairs across biological homodimeric interfaces were significantly enriched in co-evolving residues compared to those across crystal contacts, resulting in a promising classification accuracy with area under the curves (AUCs) of >0.85. Considering the availability of co-evolutionary feature, we also designed other residue pair based features that were useful for both homodimers and heterodimers. The most informative residue pairs were identified to reflect the interaction preferences across protein interfaces. Regarding the other extant properties, we designed the new descriptors at the interface residue level as well as at the pairwise contact level. Extensive validation showed that these single properties can be used to identify biological interfaces with AUCs ranging from 0.60 to 0.88. By integrating co-evolutionary feature with other residue pair based properties, our final prediction model output excellent performance with AUCs of >0.91 on different datasets. Compared to existing methods, our algorithm not only yielded better or comparable results but also provided complementary information. An easy-to-use web server is freely accessible at http://liulab.hzau.edu.cn/RPAIAnalyst.

Ca2+-Triggered Synaptic Vesicle Fusion Initiated by Release of Inhibition

Recent structural and functional studies of the synaptic vesicle fusion machinery suggest an inhibited tripartite complex consisting of neuronal soluble N-ethylmaleimide sensitive factor attachment protein receptors (SNAREs), synaptotagmin, and complexin prior to Ca2+-triggered synaptic vesicle fusion. We speculate that Ca2+-triggered fusion commences with the release of inhibition by Ca2+ binding to synaptotagmin C2 domains. Subsequently, fusion is assisted by SNARE complex zippering and by active membrane remodeling properties of synaptotagmin. This additional, inhibitory role of synaptotagmin may be a general principle since other recent studies suggest that Ca2+ binding to extended synaptotagmin C2 domains enables lipid transport by releasing an inhibited state of the system, and that Munc13 may nominally be in an inhibited state, which is released upon Ca2+ binding to one of its C2 domains.

Maximal B-factors in protein crystal structures

Since the contribution of proteins atoms with exceptionally large B-factors, much larger than those of other atoms, to the observed structure factors is negligible, it is therefore recommended to consider with a care the parts of the models where B-factors are inflated to extremely large values. Otherwise, molecular biologists risk to over-interpret structural data, since the positions of these atoms is highly uncertain. In the present communication, maximal B-factor values, over which the atoms can be considered ‘invisible’, are estimated based on the relationships between B-factors and solvent accessible surface areas.

Structural characterization of free-state and product-state Mycobacterium tuberculosis methionyl-tRNA synthetase reveals an induced-fit ligand-recognition mechanism

Mycobacterium tuberculosis (MTB) caused 10.4 million cases of tuberculosis and 1.7 million deaths in 2016. The incidence of multidrug-resistant and extensively drug-resistant MTB is becoming an increasing threat to public health and the development of novel anti-MTB drugs is urgently needed. Methionyl-tRNA synthetase (MetRS) is considered to be a valuable drug target. However, structural characterization of M. tuberculosis MetRS (MtMetRS) was lacking for decades, thus hampering drug design. Here, two high-resolution crystal structures of MtMetRS are reported: the free-state structure (apo form; 1.9 Å resolution) and a structure with the intermediate product methionyl-adenylate (Met-AMP) bound (2.4 Å resolution). It was found that free-state MtMetRS adopts a previously unseen conformation that has never been observed in other MetRS homologues. The pockets for methionine and AMP are not formed in free-state MtMetRS, suggesting that it is in a nonproductive conformation. Combining these findings suggests that MtMetRS employs an induced-fit mechanism in ligand binding. By comparison with the structure of human cytosolic MetRS, additional pockets specific to MtMetRS that could be used for anti-MTB drug design were located.

The maximum penalty criterion for ridge regression: application to the calibration of the force constant in elastic network models

Tikhonov regularization, or ridge regression, is a popular technique to deal with collinearity in multivariate regression. We unveil a formal analogy between ridge regression and statistical mechanics, where the objective function is comparable to a free energy, and the ridge parameter plays the role of temperature. This analogy suggests two novel criteria for selecting a suitable ridge parameter: specific-heat (C_v) and maximum penalty (MP). We apply these fits to evaluate the relative contributions of rigid-body and internal fluctuations, which are typically highly collinear, to crystallographic B-factors. This issue is particularly important for computational models of protein dynamics, such as the elastic network model (ENM), since the amplitude of the predicted internal motion is commonly calibrated using B-factor data. After validation on simulated datasets, our results indicate that rigid-body motions account on average for more than 80% of the amplitude of B-factors. Furthermore, we evaluate the ability of different fits to reproduce the amplitudes of internal fluctuations in X-ray ensembles from the B-factors in the corresponding single X-ray structures. The new ridge criteria are shown to be markedly superior to the commonly used two-parameter fit that neglects rigid-body rotations and to the full fits regularized under generalized cross-validation. In conclusion, the proposed fits ensure a more robust calibration of the ENM force constant and should prove valuable in other applications.

Effects of protein-crystal hydration and temperature on side-chain conformational heterogeneity in monoclinic lysozyme crystals

The modulation of main-chain and side-chain conformational heterogeneity and solvent structure in monoclinic lysozyme crystals by dehydration (related to water activity) and temperature is examined. Decreasing the relative humidity (from 99 to 11%) and decreasing the temperature both lead to contraction of the unit cell, to an increased area of crystal contacts and to remodeling of primarily contact and solvent-exposed residues. Both lead to the depopulation of some minor side-chain conformers and to the generation of new conformations. Side-chain modifications and main-chain r.m.s.d.s associated with cooling from 298 to 100 K depend on relative humidity and are minimized at 85% relative humidity (r.h.). Dehydration from 99 to 93% r.h. and cooling from 298 to 100 K result in a comparable number of remodeled residues, with dehydration-induced remodeling somewhat more likely to arise from contact interactions. When scaled to equivalent temperatures based on unit-cell contraction, the evolution of side-chain order parameters with dehydration shows generally similar features to those observed on cooling to T = 100 K. These results illuminate the qualitative and quantitative similarities between structural perturbations induced by modest dehydration, which routinely occurs in samples prepared for 298 and 100 K data collection, and cryocooling. Differences between these perturbations in terms of energy landscapes and occupancies, and implications for variable-temperature crystallography between 180 and 298 K, are discussed. It is also noted that remodeling of a key lysozyme active-site residue by dehydration, which is associated with a radical decrease in the enzymatic activity of lysozyme powder, arises due to a steric clash with the residue of a symmetry mate.

We FRET so You Don't Have To: New Models of the Lipoprotein Lipase Dimer

Lipoprotein lipase (LPL) is a dimeric enzyme that is responsible for clearing triglyceride-rich lipoproteins from the blood. Although LPL plays a key role in cardiovascular health, an experimentally derived three-dimensional structure has not been determined. Such a structure would aid in understanding mutations in LPL that cause familial LPL deficiency in patients and help in the development of therapeutic strategies to target LPL. A major obstacle to structural studies of LPL is that LPL is an unstable protein that is difficult to produce in the quantities needed for nuclear magnetic resonance or crystallography. We present updated LPL structural models generated by combining disulfide mapping, computational modeling, and data derived from single-molecule Förster resonance energy transfer (smFRET). We pioneer the technique of smFRET for use with LPL by developing conditions for imaging active LPL and identifying positions in LPL for the attachment of fluorophores. Using this approach, we measure LPL-LPL intermolecular interactions to generate experimental constraints that inform new computational models of the LPL dimer structure. These models suggest that LPL may dimerize using an interface that is different from the dimerization interface suggested by crystal packing contacts seen in structures of pancreatic lipase.

Packing topology in crystals of proteins and small molecules: a comparison

We compared the topologies of protein and small molecule crystals, which have many common features - both are molecular crystals with intermolecular interactions much weaker than intramolecular interactions. They also have different features - a considerably large fraction of the volume of protein crystals is occupied by liquid water while no room is available to other molecules in small molecule crystals. We analyzed the overall and local topology and performed multilevel topological analyses (with the software package ToposPro) of carefully selected high quality sets of protein and small molecule crystal structures. Given the suboptimal packing of protein crystals, which is due the special shape and size of proteins, it would be reasonable to expect that the topology of protein crystals is different from the topology of small molecule crystals. Surprisingly, we discovered that these two types of crystalline compounds have strikingly similar topologies. This might suggest that molecular crystal formations share symmetry rules independent of molecular dimension.

Structure and dimerization of the catalytic domain of the protein phosphatase Cdc14p, a key regulator of mitotic exit in Saccharomyces cerevisiae

In the budding yeast Saccharomyces cerevisiae, the protein phosphatase Cdc14p orchestrates various events essential for mitotic exit. We have determined the X-ray crystal structures at 1.85 Å resolution of the catalytic domain of Cdc14p in both the apo state, and as a complex with S160-phosphorylated Swi6p peptide. Each asymmetric unit contains two Cdc14p chains arranged in an intimately associated homodimer, consistent with its oligomeric state in solution. The dimerization interface is located on the backside of the substrate-binding cleft. Structure-based mutational analyses indicate that the dimerization of Cdc14p is required for normal growth of yeast cells.

In silico analysis of Glanzmann variants of Calf-1 domain of αIIbβ3 integrin revealed dynamic allosteric effect

Integrin α_IIbβ₃ mediates platelet aggregation and thrombus formation. In a rare hereditary bleeding disorder, Glanzmann thrombasthenia (GT), α_IIbβ₃ expression / function are impaired. The impact of deleterious missense mutations on the complex structure remains unclear. Long independent molecular dynamics (MD) simulations were performed for 7 GT variants and reference structure of the Calf-1 domain of α_IIb. Simulations were analysed using a structural alphabet to describe local protein conformations. Common and flexible regions as well as deformable zones were observed in all the structures. The most flexible region of Calf-1 (with highest B-factor) is rather a rigid region encompassed into two deformable zones. Each mutated structure barely showed any modifications at the mutation sites while distant conformational changes were observed. These unexpected results question the relationship between molecular dynamics and allostery; and the role of these long-range effects in the impaired α_IIbβ₃ expression. This method is aimed at studying all α_IIbβ₃ sub-domains and impact of missense mutations at local and global structural level.

Structure determination of a major facilitator peptide transporter: Inward facing PepTSt from Streptococcus thermophilus crystallized in space group P3121

Major facilitator superfamily (MFS) peptide transporters (typically referred to as PepT, POT or PTR transporters) mediate the uptake of di- and tripeptides, and so play an important dietary role in many organisms. In recent years, a better understanding of the molecular basis for this process has emerged, which is in large part due to a steep increase in structural information. Yet, the conformational transitions underlying the transport mechanism are still not fully understood, and additional data is therefore needed. Here we report in detail the detergent screening, crystallization, experimental MIRAS phasing, and refinement of the peptide transporter PepT_St from Streptococcus thermophilus. The space group is P3₁21, and the protein is crystallized in a monomeric inward facing form. The binding site is likely to be somewhat occluded, as the lobe encompassing transmembrane helices 10 and 11 is markedly bent towards the central pore of the protein, but the extent of this potential occlusion could not be determined due to disorder at the apex of the lobe. Based on structural comparisons with the seven previously determined P2₁2₁2₁ and C222₁ structures of inward facing PepT_St, the structural flexibility as well as the conformational changes mediating transition between the inward open and inward facing occluded states are discussed. In conclusion, this report improves our understanding of the structure and conformational cycle of PepT_St, and can furthermore serve as a case study, which may aid in supporting future structure determinations of additional MFS transporters or other integral membrane proteins.

The "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e., crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure, and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular "sticky patch" model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer "sticky patches" which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the "sticky patch" model. We discuss state-of-the-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis.

Circulatory zinc transport is controlled by distinct interdomain sites on mammalian albumins

Zinc is an essential nutrient in the body; it is required for the catalytic activity of many hundreds of human enzymes and virtually all biological processes, therefore its homeostasis and trafficking is of crucial interest. Serum albumin is the major carrier of Zn2+ in the blood and is required for its systemic distribution. Here we present the first crystal structures of human serum albumin (HSA) and equine serum albumin (ESA) in complex with Zn2+. The structures allow unambiguous identification of the major zinc binding site on these two albumins, as well as several further, weaker zinc binding sites. The major site in both HSA and ESA has tetrahedral geometry and comprises three protein ligands from the sidechains of His67, His247 and Asp249 and a water molecule. Isothermal titration calorimetric studies of a HSA H67A mutant confirm this to be the highest affinity Zn2+ site. Furthermore, analysis of Zn2+ binding to HSA and ESA proved the presence of secondary sites with 20-50-fold weaker affinities, which may become of importance under particular physiological conditions. Both calorimetry and crystallography suggest that ESA possesses an additional site compared to HSA, involving Glu153, His157 and His288. The His157 residue is replaced by Phe in HSA, incapable of metal coordination. Collectively, these findings are critical to our understanding of the role serum albumin plays in circulatory Zn2+ handling and cellular delivery.

Crystal structures of MBP fusion proteins

Although chaperone-assisted protein crystallization remains a comparatively rare undertaking, the number of crystal structures of polypeptides fused to maltose-binding protein (MBP) that have been deposited in the Protein Data Bank (PDB) has grown dramatically during the past decade. Altogether, 102 fusion protein structures were detected by Basic Local Alignment Search Tool (BLAST) analysis. Collectively, these structures comprise a range of sizes, space groups, and resolutions that are typical of the PDB as a whole. While most of these MBP fusion proteins were equipped with short inter-domain linkers to increase their rigidity, fusion proteins with long linkers have also been crystallized. In some cases, surface entropy reduction mutations in MBP appear to have facilitated the formation of crystals. A comparison of the structures of fused and unfused proteins, where both are available, reveals that MBP-mediated structural distortions are very rare.

Glycosyltransferase complexes in eukaryotes: long-known, prevalent but still unrecognized

Glycosylation is the most common and complex cellular modification of proteins and lipids. It is critical for multicellular life and its abrogation often leads to a devastating disease. Yet, the underlying mechanistic details of glycosylation in both health and disease remain unclear. Partly, this is due to the complexity and dynamicity of glycan modifications, and the fact that not all the players are taken into account. Since late 1960s, a vast number of studies have demonstrated that glycosyltransferases typically form homomeric and heteromeric complexes with each other in yeast, plant and animal cells. To propagate their acceptance, we will summarize here accumulated data for their prevalence and potential functional importance for glycosylation focusing mainly on their mutual interactions, the protein domains mediating these interactions, and enzymatic activity changes that occur upon complex formation. Finally, we will highlight the few existing 3D structures of these enzyme complexes to pinpoint their individual nature and to emphasize that their lack is the main obstacle for more detailed understanding of how these enzyme complexes interact and function in a eukaryotic cell.

Mapping of Fab-1:VEGF Interface Using Carboxyl Group Footprinting Mass Spectrometry

A proof-of-concept study was performed to demonstrate that carboxyl group footprinting, a relatively simple, bench-top method, has utility for first-pass analysis to determine epitope regions of therapeutic mAb:antigen complexes. The binding interface of vascular endothelial growth factor (VEGF) and the Fab portion of a neutralizing antibody (Fab-1) was analyzed using carboxyl group footprinting with glycine ethyl ester (GEE) labeling. Tryptic peptides involved in the binding interface between VEGF and Fab-1 were identified by determining the specific GEE-labeled residues that exhibited a reduction in the rate of labeling after complex formation. A significant reduction in the rate of GEE labeling was observed for E93 in the VEGF tryptic peptide V5, and D28 and E57 in the Fab-1 tryptic peptides HC2 and HC4, respectively. Results from the carboxyl group footprinting were compared with the binding interface identified from a previously characterized crystal structure (PDB: 1BJ1). All of these residues are located at the Fab-1:VEGF interface according to the crystal structure, demonstrating the potential utility of carboxyl group footprinting with GEE labeling for mapping epitopes. Graphical Abstract ᅟ.

Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein–protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein–protein docking.

Supplementary information: Supplementary data are available at Bioinformatics online.

Contact:guido.capitani@psi.ch

A structural dissection of large protein-protein crystal packing contacts

With the rapid increase in crystal structures of protein-protein complexes deposited in the Protein Data Bank (PDB), more and more crystal contacts have been shown to have similar or even larger interface areas than biological interfaces. However, little attention has been paid to these large crystal packing contacts and their structural principles remain unknown. To address this issue, we used a comparative feature analysis to analyze the geometric and physicochemical properties of large crystal packing contacts by comparing two types of specific protein-protein interactions (PPIs), weak transient complexes and permanent homodimers. Our results show that although large crystal packing contacts have a similar interface area and contact size as permanent homodimers, they tend to be more planar, loosely packed and less hydrophobic than permanent homodimers and cannot form a central core region that is fully buried during interaction. However, the properties of large crystal packing contacts, except for the interface area and contact size, more closely resemble those of weak transient complexes. The large overlap between biological and large crystal packing contacts indicates that interface properties are not efficient indicators for classification of biological interfaces from large crystal packing contacts and finding other specific features urgently needed.

The MORPHEUS II protein crystallization screen

High-quality macromolecular crystals are a prerequisite for the process of protein structure determination by X-ray diffraction. Unfortunately, the relative yield of diffraction-quality crystals from crystallization experiments is often very low. In this context, innovative crystallization screen formulations are continuously being developed. In the past, MORPHEUS, a screen in which each condition integrates a mix of additives selected from the Protein Data Bank, a cryoprotectant and a buffer system, was developed. Here, MORPHEUS II, a follow-up to the original 96-condition initial screen, is described. Reagents were selected to yield crystals when none might be observed in traditional initial screens. Besides, the screen includes heavy atoms for experimental phasing and small polyols to ensure the cryoprotection of crystals. The suitability of the resulting novel conditions is shown by the crystallization of a broad variety of protein samples and their efficiency is compared with commercially available conditions.

Multiple crystal forms of N,N'-diacetylchitobiose deacetylase from Pyrococcus furiosus

Native N,N'-diacetylchitobiose deacetylase from Pyrococcus furiosus (Pf-Dac) and its selenomethionine derivative (Se-Pf-Dac) were crystallized and analyzed in the presence and absence of cadmium ion. The four crystal structures fell into three different crystal-packing groups, with the cadmium-free Pf-Dac and Se-Pf-Dac belonging to the same space group, with homologous unit-cell parameters. The crystal structures in the presence of cadmium contained distorted octahedral cadmium complexes coordinated by three chlorides, two O atoms and an S or Se atom from the N-terminal methionine or selenomethionine, respectively. The N-terminal cadmium complex was involved in crystal contacts between symmetry-related molecules through hydrogen bonding to the N-termini. While all six N-termini of Se-Pf-Dac were involved in cadmium-complex formation, only two of the Pf-Dac N-termini participated in complex formation in the Cd-containing crystal, resulting in different crystal forms. These differences are discussed in light of the higher stability of the Cd-Se bond than the Cd-S bond. This work provides an example of the contribution of cadmium towards determining protein crystal quality and packing depending on the use of the native protein or the selenomethionine derivative.

Simulation of protein association: Kinetic pathways towards crystal contacts

We conducted molecular dynamics simulations combined with distance-based umbrella sampling and forward flux sampling to investigate the early stages of protein crystallization. Formation of contacts with long-range interactions and/or an exposed position on the protein surface was kinetically preferred over more stable hydrophobic contacts with a shorter attractive range, while the thermodynamic stability of the protein crystal was provided by hydrophobic interactions. Contacts with a large interaction area showed complex dissociation pathways that were not detected by distance-based umbrella sampling. Instead, forward flux sampling simulations of contact dissociation identified long-range attractive interactions.

Use B-factor related features for accurate classification between protein binding interfaces and crystal packing contacts

Background

Distinction between true protein interactions and crystal packing contacts is important for structural bioinformatics studies to respond to the need of accurate classification of the rapidly increasing protein structures. There are many unannotated crystal contacts and there also exist false annotations in this rapidly expanding volume of data. Previous tools have been proposed to address this problem. However, challenging issues still remain, such as low performance when the training and test data contain mixed interfaces having diverse sizes of contact areas.

Methods and results

B factor is a measure to quantify the vibrational motion of an atom, a more relevant feature than interface size to characterize protein binding. We propose to use three features related to B factor for the classification between biological interfaces and crystal packing contacts. The first feature is the sum of the normalized B factors of the interfacial atoms in the contact area, the second is the average of the interfacial B factor per residue in the chain, and the third is the average number of interfacial atoms with a negative normalized B factor per residue in the chain. We investigate the distribution properties of these basic features and a compound feature on four datasets of biological binding and crystal packing, and on a protein binding-only dataset with known binding affinity. We also compare the cross-dataset classification performance of these features with existing methods and with a widely-used and the most effective feature interface area. The results demonstrate that our features outperform the interface area approach and the existing prediction methods remarkably for many tests on all of these datasets.

Conclusions

The proposed B factor related features are more effective than interface area to distinguish crystal packing from biological binding interfaces. Our computational methods have a potential for large-scale and accurate identification of biological interactions from the experimentally determined structural data stored at PDB which may have diverse interface sizes.

Fast photochemical oxidation of proteins (FPOP) maps the epitope of EGFR binding to adnectin

Epitope mapping is an important tool for the development of monoclonal antibodies, mAbs, as therapeutic drugs. Recently, a class of therapeutic mAb alternatives, adnectins, has been developed as targeted biologics. They are derived from the 10th type III domain of human fibronectin ((10)Fn3). A common approach to map the epitope binding of these therapeutic proteins to their binding partners is X-ray crystallography. Although the crystal structure is known for Adnectin 1 binding to human epidermal growth factor receptor (EGFR), we seek to determine complementary binding in solution and to test the efficacy of footprinting for this purpose. As a relatively new tool in structural biology and complementary to X-ray crystallography, protein footprinting coupled with mass spectrometry is promising for protein-protein interaction studies. We report here the use of fast photochemical oxidation of proteins (FPOP) coupled with MS to map the epitope of EGFR-Adnectin 1 at both the peptide and amino-acid residue levels. The data correlate well with the previously determined epitopes from the crystal structure and are consistent with HDX MS data, which are presented in an accompanying paper. The FPOP-determined binding interface involves various amino-acid and peptide regions near the N terminus of EGFR. The outcome adds credibility to oxidative labeling by FPOP for epitope mapping and motivates more applications in the therapeutic protein area as a stand-alone method or in conjunction with X-ray crystallography, NMR, site-directed mutagenesis, and other orthogonal methods.

ATP-induced dimerization of the F0F1 ε subunit from Bacillus PS3: a hydrogen exchange-mass spectrometry study

F0F1 ATP synthase harnesses a transmembrane electrochemical gradient for the production of ATP. When operated in reverse, this multiprotein complex catalyzes ATP hydrolysis. In bacteria, the ε subunit is involved in regulating this ATPase activity. Also, ε is essential for coupling ATP hydrolysis (or synthesis) to proton translocation. The ε subunit consists of a β sandwich and two C-terminal helices, α1 and α2. The protein can switch from a compact fold to an alternate conformation where α1 and α2 are separated, resulting in an extended structure. ε from the thermophile Bacillus PS3 (Tε) binds ATP with high affinity such that this protein may function as an intracellular ATP level sensor. ATP binding to isolated Tε triggers a major conformational transition. Earlier data were interpreted in terms of an ATP + Tεextended → ATP·Tεcompact transition that may mimic aspects of the regulatory switching within F0F1 (Yagi et al. (2007) Proc. Natl. Acad. Sci. U.S.A., 104, 11233–11238). In this work, we employ complementary biophysical techniques for examining the ATP-induced conformational switching of isolated Tε. CD spectroscopy confirmed the occurrence of a large-scale conformational transition upon ATP binding, consistent with the formation of stable helical structure. Hydrogen/deuterium exchange (HDX) mass spectrometry revealed that this transition is accompanied by a pronounced stabilization in the vicinity of the ATP-binding pocket. Surprisingly, dramatic stabilization is also seen in the β8−β9 region, which is remote from the site of ATP interaction. Analytical ultracentrifugation uncovered a previously unrecognized feature of Tε: a high propensity to undergo dimerization in the presence of ATP. Comparison with existing crystallography data strongly suggests that the unexpected β8−β9 HDX protection is due to newly formed protein–protein contacts. Hence, ATP binding to isolated Tε proceeds according to 2ATP + 2Tεextended → (ATP·Tεcompact)2. Implications of this dimerization propensity for the possible role of Tε as an antibiotic target are discussed.

B-factor Analysis and Conformational Rearrangement of Aldose Reductase

The NADPH-dependent reduction of glucose reaction that is catalyzed by Aldose Reductase (AR) follows a sequential ordered kinetic mechanism in which the co-factor NADPH binds to the enzyme prior to the aldehyde substrate. The kinetic/structural experiments have found a conformational change involving a hinge-like movement of a surface loop (residues 213-224) which is anticipated to take place upon the binding of the diphosphate moiety of NADPH. The reorientation of this loop, expected to permit the release of NADP⁺, represents the rate-limiting step of the catalytic mechanism. This study reveals: 1) The Translation/Libration/Screw (TLS) analysis of absolute B-factors of apo AR crystal structures indicates that the 212-224 loop might move as a rigid group. 2) Residues that make the flexible loop slide in the AR binary and ternary complexes. 3) The normalized B-factors separate this segment into three different clusters with fewer residues.

Effects of protein engineering and rational mutagenesis on crystal lattice of single chain antibody fragments

Protein crystallization is dependent upon, and sensitive to, the intermolecular contacts that assist in ordering proteins into a three-dimensional lattice. Here we used protein engineering and mutagenesis to affect the crystallization of single chain antibody fragments (scFvs) that recognize the EE epitope (EYMPME) with high affinity. These hypercrystallizable scFvs are under development to assist difficult proteins, such as membrane proteins, in forming crystals, by acting as crystallization chaperones. Guided by analyses of intermolecular crystal lattice contacts, two second-generation anti-EE scFvs were produced, which bind to proteins with installed EE tags. Surprisingly, although noncomplementarity determining region (CDR) lattice residues from the parent scFv framework remained unchanged through the processes of protein engineering and rational design, crystal lattices of the derivative scFvs differ. Comparison of energy calculations and the experimentally-determined lattice interactions for this basis set provides insight into the complexity of the forces driving crystal lattice choice and demonstrates the availability of multiple well-ordered surface features in our scFvs capable of forming versatile crystal contacts.

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.