Detection of trans-cis flips and peptide-plane flips in protein structures

Distance-based global analysis of consistent cis-bonds in protein backbones

Biological polypeptides are known to contain cis-linkage in their main chain as a minor but important feature. Such anomalous connection of amino acids has different structural and functional effects on proteins. Experimental evidence of cis-bonds in proteins is mainly obtained using X-ray crystallography and other methods in the field of structural biology. To date, extensive analyses have been carried out on the experimentally found cis-bonds using the Protein Data Bank (PDB) entry-wise or residue-wise; however, their consistency in each protein has not been examined on a global scale. Data accumulation and advances in computational methodology enable the use of new approaches from a proteomic point of view. Here, we sought to carry out protein-wise analysis and describe a simple procedure for the detection and confirmation of cis-bonds from a set of experimental PDB chains for a protein to discriminate this type of bond from isomerizable and/or misassigned bonds. The resulting set of consistent cis bonds (found at identical positions in multiple chains) provides unprecedented insights into the trend of "high cis content" proteins and the upper limit of consistent cis bonds per polypeptide length. Recognizing such limit would not only be important for a practical check of upcoming structures, but also for the design of novel protein folds beyond the evolutionally-acquired repertoire.

Molecular-dynamics simulation methods for macromolecular crystallography

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein-solvent interface. To address this limitation, a set of MD-MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

Backbone N-Amination Promotes the Folding of β-Hairpin Peptides via a Network of Hydrogen Bonds

Molecular dynamics (MD) simulations have been used to characterize the effects of backbone N-amination of residues in a model β-hairpin peptide. This modification is of considerable interest as N-aminated peptides have been shown to inhibit amyloid-type aggregation. Six derivatives of the β-hairpin peptide, which contain one, two, or four N-aminated residues, have been studied. For each peptide 100 ns MD simulations starting from the folded β-hairpin structure were performed. The effects of the N-amination prove to be very sequence dependent. N-Amination of a residue involved in interstrand hydrogen bonding (Val3) leads to unfolding of the β-hairpin, whereas N-amination of a residue toward the C-terminus (Leu11) gives fraying at the termini of the peptide. In the other derivatives the peptide remains folded, with increasing levels of N-amination reducing the right-handed twist of the β-hairpin and favoring population of a type II' rather than a type I' β-turn. MD simulations (100 ns) have also been run for each peptide starting from an unfolded extended chain. Here, the peptide with four N-aminated residues shows the most folding into the β-hairpin (34%). Analysis of the simulations shows that N-amination favors the population of β (φ, ψ) conformations by the preceding residue due to, at least in part, a network of weak NH₂(i)-CO(i) and NH₂(i)-CO(i-2) hydrogen bonds. It also leads to a reduction of misfolding because of changes in the hydrogen-bonding potential. Both of these features help funnel the peptide to the folded β-hairpin structure. The conformational insights provided through this work give a firm foundation for the design of N-aminated peptide inhibitors for modulating protein-protein interactions and aggregation.

Determination of amino acids that favour the αL region using Ramachandran propensity plots. Implications for α-sheet as the possible amyloid intermediate

In amyloid diseases an insoluble amyloid fibril forms via a soluble oligomeric intermediate. It is this intermediate that mediates toxicity and it has been suggested, somewhat controversially, that it has the α-sheet structure. Nests and α-strands are similar peptide motifs in that alternate residues lie in the α_R and γ_L regions of the Ramachandran plot for nests, or α_R and α_L regions for α-strands. In nests a concavity is formed by the main chain NH atoms whereas in α-strands the main chain is almost straight. Using "Ramachandran propensity plots" to focus on the α_L/γ_L region, it is shown that glycine favours γ_L (82% of amino acids are glycine), but disfavours α_L (3% are glycine). Most charged and polar amino acids favour α_L with asparagine having by far the highest propensity. Thus, glycine favours nests but, contrary to common expectation, should not favour α-sheet. By contrast most charged or polar amino acids should favour α-sheet by their propensity for the α_L conformation, which is more discriminating amongst amino acids than the α_R conformation. Thus, these results suggest the composition of sequences that favour α-sheet formation and point towards effective prediction of α-sheet from sequence.

Intraresidual Correlated Motions in Peptide Chains

We investigate the interresidual and intraresidual correlations between dihedral displacements of adjacent residues within model polyalanine peptides by analyzing extensive molecular dynamics trajectories. Correlations are evaluated individually at different residue conformations covering the whole (ϕ_i,ψ_i)-space. From these, we draw maps that unveil an unprecedented strong intramolecular correlation displaying opposite (correlated/anticorrelated) behaviors at different conformations. Both interresidual and intraresidual correlations arise from the propensity of the peptide to minimize the overall atomic displacements.

Common Mode of Remodeling AAA ATPases p97/CDC48 by Their Disassembling Cofactors ASPL/PUX1

The hexameric ring structure of the type II AAA+ ATPases is considered as stable and permanent. Recently, the UBX domain-containing cofactors Arabidopsis thaliana PUX1 and human alveolar soft part sarcoma locus (ASPL) were reported to bind and disassemble the cognate AAA+ ATPases AtCDC48 and human p97. Here, we present two crystal structures related to these complexes: a truncated AtCDC48 (AtCDC48-ND1) and a hybrid complex containing human p97-ND1 and the UBX domain of plant PUX1 (p97-ND1:PUX1-UBX). These structures reveal close similarity between the human and plant AAA+ ATPases, but also highlight differences between disassembling and non-disassembling AAA+ ATPase cofactors. Based on an AtCDC48 disassembly assay with PUX1 and known crystal structures of the p97-bound human cofactor ASPL, we propose a general ATPase disassembly model. Thus, our structural and biophysical investigations provide detailed insight into the mechanism of AAA+ ATPase disassembly by UBX domain cofactors and suggest a general mode of regulating the cellular activity of these molecular machines.

Molecular Recognition of Lipid II by Lantibiotics: Synthesis and Conformational Studies of Analogues of Nisin and Mutacin Rings A and B

In response to the growing threat posed by antibiotic-resistant bacterial strains, extensive research is currently focused on developing antimicrobial agents that target lipid II, a vital precursor in the biosynthesis of bacterial cell walls. The lantibiotic nisin and related peptides display unique and highly selective binding to lipid II. A key feature of the nisin-lipid II interaction is the formation of a cage-like complex between the pyrophosphate moiety of lipid II and the two thioether-bridged rings, rings A and B, at the N-terminus of nisin. To understand the important structural factors underlying this highly selective molecular recognition, we have used solid-phase peptide synthesis to prepare individual ring A and B structures from nisin, the related lantibiotic mutacin, and synthetic analogues. Through NMR studies of these rings, we have demonstrated that ring A is preorganized to adopt the correct conformation for binding lipid II in solution and that individual amino acid substitutions in ring A have little effect on the conformation. We have also analyzed the turn structures adopted by these thioether-bridged peptides and show that they do not adopt the tight α-turn or β-turn structures typically found in proteins.

Defining a new nomenclature for the structures of active and inactive kinases

Protein kinases play important roles in signaling pathways and are widely studied as drug targets. Their active site exhibits remarkable structural variation as observed in the large number of available crystal structures. We have developed a clustering scheme and nomenclature to categorize and label all the observed conformations in human protein kinases. This has enabled us to clearly define the geometry of the active state and to distinguish closely related inactive states which were previously not characterized. Our classification of kinase conformations will help in better understanding the conformational dynamics of these proteins and the development of inhibitors against them.

Targeting protein kinases is an important strategy for intervention in cancer. Inhibitors are directed at the active conformation or a variety of inactive conformations. While attempts have been made to classify these conformations, a structurally rigorous catalog of states has not been achieved. The kinase activation loop is crucial for catalysis and begins with the conserved DFGmotif. This motif is observed in two major classes of conformations, DFGin—a set of active and inactive conformations where the Phe residue is in contact with the C-helix of the N-terminal lobe—and DFGout—an inactive form where Phe occupies the ATP site exposing the C-helix pocket. We have developed a clustering of kinase conformations based on the location of the Phe side chain (DFGin, DFGout, and DFGinter or intermediate) and the backbone dihedral angles of the sequence X-D-F, where X is the residue before the DFGmotif, and the DFG-Phe side-chain rotamer, utilizing a density-based clustering algorithm. We have identified eight distinct conformations and labeled them based on the Ramachandran regions (A, alpha; B, beta; L, left) of the XDF motif and the Phe rotamer (minus, plus, trans). Our clustering divides the DFGin group into six clusters including BLAminus, which contains active structures, and two common inactive forms, BLBplus and ABAminus. DFGout structures are predominantly in the BBAminus conformation, which is essentially required for binding type II inhibitors. The inactive conformations have specific features that make them unable to bind ATP, magnesium, and/or substrates. Our structurally intuitive nomenclature will aid in understanding the conformational dynamics of kinases and structure-based development of kinase drugs.

Identification and computational characterization of isomers with cis and trans amide bonds in folate and its analogues

Folate and its synthetic analogues, called antifolates, are known to have diverse bio-applications, for example as cell proliferation stimulators or anticancer drugs. Their molecular structure is important for performing the required biological activity. Since all folate-derived ligands contain a peptide-like amide bond, its configuration is one of the key components for the functional fitness of such compounds. During the modelling of folate and three of its derivatives - methotrexate, 5-methyl tetrahydrofolate, and pteroyl ornithine, we registered significant population of the cis isomers along the amide bond. The properties of the cis and trans forms of the ligands in saline are studied in detail by classical atomistic molecular dynamics and by quantum chemical methods. The calculations predict high probability for coexistence of the cis isomers for two of the ligands. The energetic instability of the cis form is explained with a σ-character admixture into the C[double bond, length as m-dash]O(π) bond, while its magnitude is attributed to the pattern of local electron density redistribution. The cis forms of all molecules have markedly slower structural dynamics than the trans ones, which might affect their behavior in vivo.

ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps

This paper introduces ISOLDE, a new software package designed to provide an intuitive environment for high-fidelity interactive remodelling/refinement of macromolecular models into electron-density maps. ISOLDE combines interactive molecular-dynamics flexible fitting with modern molecular-graphics visualization and established structural biology libraries to provide an immersive interface wherein the model constantly acts to maintain physically realistic conformations as the user interacts with it by directly tugging atoms with a mouse or haptic interface or applying/removing restraints. In addition, common validation tasks are accelerated and visualized in real time. Using the recently described 3.8 Å resolution cryo-EM structure of the eukaryotic minichromosome maintenance (MCM) helicase complex as a case study, it is demonstrated how ISOLDE can be used alongside other modern refinement tools to avoid common pitfalls of low-resolution modelling and improve the quality of the final model. A detailed analysis of changes between the initial and final model provides a somewhat sobering insight into the dangers of relying on a small number of validation metrics to judge the quality of a low-resolution model.

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82-84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88-90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction.

An allosteric binding site of the α7 nicotinic acetylcholine receptor revealed in a humanized acetylcholine-binding protein

Nicotinic acetylcholine receptors (nAChRs) belong to the family of pentameric ligand-gated ion channels and mediate fast excitatory transmission in the central and peripheral nervous systems. Among the different existing receptor subtypes, the homomeric α7 nAChR has attracted considerable attention because of its possible implication in several neurological and psychiatric disorders, including cognitive decline associated with Alzheimer's disease or schizophrenia. Allosteric modulators of ligand-gated ion channels are of particular interest as therapeutic agents, as they modulate receptor activity without affecting normal fluctuations of synaptic neurotransmitter release. Here, we used X-ray crystallography and surface plasmon resonance spectroscopy of α7-acetylcholine-binding protein (AChBP), a humanized chimera of a snail AChBP, which has 71% sequence similarity with the extracellular ligand-binding domain of the human α7 nAChR, to investigate the structural determinants of allosteric modulation. We extended previous observations that an allosteric site located in the vestibule of the receptor offers an attractive target for receptor modulation. We introduced seven additional humanizing mutations in the vestibule-located binding site of AChBP to improve its suitability as a model for studying allosteric binding. Using a fragment-based screening approach, we uncovered an allosteric binding site located near the β8-β9 loop, which critically contributes to coupling ligand binding to channel opening in human α7 nAChR. This work expands our understanding of the topology of allosteric binding sites in AChBP and, by extrapolation, in the human α7 nAChR as determined by electrophysiology measurements. Our insights pave the way for drug design strategies targeting nAChRs involved in ion channel-mediated disorders.

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.

Stereochemistry and Validation of Macromolecular Structures

Macromolecular structure is governed by the strict rules of stereochemistry. Several approaches to the validation of the correctness of the interpretation of crystallographic and NMR data that underlie the models deposited in the PDB are utilized in practice. The stereochemical rules applicable to macromolecular structures are discussed in this chapter. Practical, computer-based methods and tools of verification of how well the models adhere to those established structural principles to assure their quality are summarized.

Backbone Dihedral Angle Prediction

More than two decades of research have enabled dihedral angle predictions at an accuracy that makes them an interesting alternative or supplement to secondary structure prediction that provides detailed local structure information for every residue of a protein. The evolution of dihedral angle prediction methods is closely linked to advancements in machine learning and other relevant technologies. Consequently recent improvements in large-scale training of deep neural networks have led to the best method currently available, which achieves a mean absolute error of 19° for phi, and 30° for psi. This performance opens interesting perspectives for the application of dihedral angle prediction in the comparison, prediction, and design of protein structures.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.

Peptide Bond Isomerization in High-Temperature Simulations

Force fields for molecular simulation are generally optimized to model macromolecules such as proteins at ambient temperature and pressure. Nevertheless, elevated temperatures are frequently used to enhance conformational sampling, either during system setup or as a component of an advanced sampling technique such as temperature replica exchange. Because macromolecular force fields are now put upon to simulate temperatures and time scales that greatly exceed their original design specifications, it is appropriate to re-evaluate whether these force fields are up to the task. Here, we quantify the rates of peptide bond isomerization in high-temperature simulations of three octameric peptides and a small fast-folding protein. We show that peptide octamers with and without proline residues undergo cis/trans isomerization every 1-5 ns at 800 K with three classical atomistic force fields (AMBER99SB-ILDN, CHARMM22/CMAP, and OPLS-AA/L). On the low microsecond time scale, these force fields permit isomerization of nonprolyl peptide bonds at temperatures ≥500 K, and the CHARMM22/CMAP force field permits isomerization of prolyl peptide bonds ≥400 K. Moreover, the OPLS-AA/L force field allows chiral inversion about the Cα atom at 800 K. Finally, we show that temperature replica exchange permits cis peptide bonds developed at 540 K to subsequently migrate back to the 300 K ensemble, where cis peptide bonds are present in 2 ± 1% of the population of Trp-cage TC5b, including up to 4% of its folded state. Further work is required to assess the accuracy of cis/trans isomerization in the current generation of protein force fields.

New Biological Insights from Better Structure Models

Structure validation is a key component of all steps in the structure determination process, from structure building, refinement, deposition, and evaluation all the way to post-deposition optimisation of structures in the Protein Data Bank (PDB) by re-refinement and re-building. Today, many aspects of protein structures are understood better than 10years ago, and combined with improved software and more computing power, the automated PDB_REDO procedure can significantly improve about 85% of all X-ray structures ever deposited in the PDB. We review structure validation, structure improvement, and a series of validation resources and facilities that give access to improved PDB files and to reports on the quality of the original and the improved structures. Post-deposition optimisation generally leads to improved protein structures and a series of examples will illustrate how that, in turn, leads to improved or even novel biological insights.