Ultra-high Resolution Protein Structures Research Articles

Introduction of a new scheme for classifying β-turns in protein structures.

Protein β-turn classification remains an area of ongoing development in structural biology research. While the commonly used nomenclature defining type I, type II and type IV β-turns was introduced in the 1970s and 1980s, refinements of β-turn type definitions have been introduced as recently as 2019 by Dunbrack, Jr and co-workers who expanded the number of β-turn types to 18 (Shapovalov et al, PLOS Computat. Biol., 15, e1006844, 2019). Based on their analysis of 13 030 turns from 1074 ultrahigh resolution (≤1.2 Å) protein structures, they used a new clustering algorithm to expand the definitions used to classify protein β-turns and introduced a new nomenclature system. We recently encountered a specific problem when classifying β-turns in crystal structures of pentapeptide repeat proteins (PRPs) determined in our lab that are largely composed of β-turns that often lie close to, but just outside of, canonical β-turn regions. To address this problem, we devised a new scheme that merges the Klyne-Prelog stereochemistry nomenclature and definitions with the Ramachandran plot. The resulting Klyne-Prelog-modified Ramachandran plot scheme defines 1296 distinct potential β-turn classifications that cover all possible protein β-turn space with a nomenclature that indicates the stereochemistry of i + 1 and i+ 2 backbone dihedral angles. The utility of the new classification scheme was illustrated by re-classification of the β-turns in all known protein structures in the PRP superfamily and further assessed using a database of 16 657 high-resolution protein structures (≤1.5Å) from which 522 776 β-turns were identified and classified.

Sub-Atomic Resolution Crystal Structures Reveal Conserved Geometric Outliers at Functional Sites

Myelin protein 2 (P2) is a peripheral membrane protein of the vertebrate nervous system myelin sheath, having possible roles in both lipid transport and 3D molecular organization of the multilayered myelin membrane. We extended our earlier crystallographic studies on human P2 and refined its crystal structure at an ultrahigh resolution of 0.72 Å in perdeuterated form and 0.86 Å in hydrogenated form. Characteristic differences in C–H…O hydrogen bond patterns were observed between extended β strands, kinked or ending strands, and helices. Often, side-chain C–H groups engage in hydrogen bonding with backbone carbonyl moieties. The data highlight several amino acid residues with unconventional conformations, including both bent aromatic rings and twisted guanidinium groups on arginine side chains, as well as non-planar peptide bonds. In two locations, such non-ideal conformations cluster, providing proof of local functional strain. Other ultrahigh-resolution protein structures similarly contain chemical groups, which break planarity rules. For example, in Src homology 3 (SH3) domains, a conserved bent aromatic residue is observed near the ligand binding site. Fatty acid binding protein (FABP) 3, belonging to the same family as P2, has several side chains and peptide bonds bent exactly as those in P2. We provide a high-resolution snapshot on non-ideal conformations of amino acid residues under local strain, possibly relevant to biological function. Geometric outliers observed in ultrahigh-resolution protein structures are real and likely relevant for ligand binding and conformational changes. Furthermore, the deuteration of protein and/or solvent are promising variables in protein crystal optimization.

A new clustering and nomenclature for beta turns derived from high-resolution protein structures.

Protein loops connect regular secondary structures and contain 4-residue beta turns which represent 63% of the residues in loops. The commonly used classification of beta turns (Type I, I’, II, II’, VIa1, VIa2, VIb, and VIII) was developed in the 1970s and 1980s from analysis of a small number of proteins of average resolution, and represents only two thirds of beta turns observed in proteins (with a generic class Type IV representing the rest). We present a new clustering of beta-turn conformations from a set of 13,030 turns from 1074 ultra-high resolution protein structures (≤1.2 Å). Our clustering is derived from applying the DBSCAN and k-medoids algorithms to this data set with a metric commonly used in directional statistics applied to the set of dihedral angles from the second and third residues of each turn. We define 18 turn types compared to the 8 classical turn types in common use. We propose a new 2-letter nomenclature for all 18 beta-turn types using Ramachandran region names for the two central residues (e.g., ‘A’ and ‘D’ for alpha regions on the left side of the Ramachandran map and ‘a’ and ‘d’ for equivalent regions on the right-hand side; classical Type I turns are ‘AD’ turns and Type I’ turns are ‘ad’). We identify 11 new types of beta turn, 5 of which are sub-types of classical beta-turn types. Up-to-date statistics, probability densities of conformations, and sequence profiles of beta turns in loops were collected and analyzed. A library of turn types, BetaTurnLib18, and cross-platform software, BetaTurnTool18, which identifies turns in an input protein structure, are freely available and redistributable from dunbrack.fccc.edu/betaturn and github.com/sh-maxim/BetaTurn18. Given the ubiquitous nature of beta turns, this comprehensive study updates understanding of beta turns and should also provide useful tools for protein structure determination, refinement, and prediction programs.

How planar are planar peptide bonds?

How planar are planar peptide bonds?

Ramachandran analysis of conserved glycyl residues in homologous proteins of known structure

High conservation of glycyl residues in homologous proteins is fairly frequent. It is commonly understood that glycine tends to be highly conserved either because of its unique Ramachandran angles or to avoid steric clash that would arise with a larger side chain. Using a database of aligned 3D structures of homologous proteins we identified conserved Gly in 288 alignment positions from 85 families. Ninety-six of these alignment positions correspond to conserved Gly residue with (φ, ψ) values allowed for non-glycyl residues. Reasons for this observation were investigated by in-silico mutation of these glycyl residues to Ala. We found in 94% of the cases a short contact exists between the C(β) atom of the introduced Ala with the atoms which are often distant in the primary structure. This suggests the lack of space even for a short side chain thereby explaining high conservation of glycyl residues even when they adopt (φ, ψ) values allowed for Ala. In 189 alignment positions, the conserved glycyl residues adopt (φ, ψ) values which are disallowed for Ala. In-silico mutation of these Gly residues to Ala almost always results in steric hindrance involving C(β) atom of Ala as one would expect by comparing Ramachandran maps for Ala and Gly. Rare occurrence of the disallowed glycyl conformations even in ultrahigh resolution protein structures are accompanied by short contacts in the crystal structures and such disallowed conformations are not conserved in the homologues. These observations raise the doubt on the accuracy of such glycyl conformations in proteins.

A fresh look at the Ramachandran plot and the occurrence of standard structures in proteins

The Ramachandran plot is among the most central concepts in structural biology, seen in publications and textbooks alike. However, with the increasing numbers of known protein-structures and greater accuracy of ultra-high resolution protein structures, we are still learning more about the basic principles of protein structure. Here we use high fidelity conformational information to explore novel ways, such a geo-style and wrapped Ramachandran plots, to convey some of the basic aspects of the Ramachandran plot and of protein conformation. We point out the pressing need for a standard nomenclature for peptide conformation and propose such a nomenclature. Finally, we summarize some recent conceptual advances related to the building blocks of protein structure. The results for linear groups imply the need for substantive revisions in how the basics of protein structure are handled.

The role of Buergi‐Dunitz interactions in the structural stability of proteins

Nonbonding interactions are essential for protein stability and maintenance of secondary structure. Their strength, however, is not always experimentally accessible. One example is the stability of collagen, which is in part due to Buergi-Duntiz or n --> pi* interactions between the peptide backbone atoms [DeRider et al., J Am Chem Soc 2002;124:2497-2505]. Here, the overall frequency of n --> pi* interactions in proteins has been investigated. The analysis of a nonredundant set of protein structures showed that 45.1% of all residues have a backbone conformation favoring a n --> pi* nucleophilic attack between the carbonyl oxygen of residue i - 1 and the carbonyl carbon of residue i. These residues form a substantial fraction of right- and left-handed alpha helices, 3(10) helices, pi helices, and hydrogen bonded turns. Simulations showed that there are only four regions in Ramachandran space that favor backbone n(i-1) --> pi(i) (*) interactions and these Phi, Psi combinations are observed with high frequencies in the nonredundant protein structure set. Analysis of carbonyl carbon displacements out of the peptide plane in ultra-high resolution protein structures indeed reveals the presence of the Buergi-Dunitz trajectory. The Buergi-Dunitz interaction thus appears to play an important and general role in protein structure stability that has not hitherto been fully explored.

Conformation dependence of backbone geometry in proteins.

Protein structure determination and predictive modeling have long been guided by the paradigm that the peptide backbone has a single, context-independent ideal geometry. Both quantum-mechanics calculations and empirical analyses have shown this is an incorrect simplification in that backbone covalent geometry actually varies systematically as a function of the phi and Psi backbone dihedral angles. Here, we use a nonredundant set of ultrahigh-resolution protein structures to define these conformation-dependent variations. The trends have a rational, structural basis that can be explained by avoidance of atomic clashes or optimization of favorable electrostatic interactions. To facilitate adoption of this paradigm, we have created a conformation-dependent library of covalent bond lengths and bond angles and shown that it has improved accuracy over existing methods without any additional variables to optimize. Protein structures derived from crystallographic refinement and predictive modeling both stand to benefit from incorporation of the paradigm.

Ultra-high resolution protein structures - Himalayas of protein crystallography

Ultra-high resolution protein structures - Himalayas of protein crystallography

On the occurrence of linear groups in proteins

Linear groups-polypeptide conformations based on a single repeating phi,psi-pair-are a foundational concept in protein structure, yet how they are presented in textbooks is based largely on theoretical studies from the early days of protein structure analysis. Now, ultra-high resolution protein structures provide a resource for an accurate empirical and systematic assessment of the linear groups that truly exist in proteins. Here, a purely conformation-based survey of linear groups shows that only three distinct phi,psi-regions occur: a diverse set of extended conformations mostly present as beta-strands, a broad population of polyproline-II-like spirals, and a tight cluster that includes the highly populated alpha-helix and the conformationally-similar but much less populated 3(10)-helix. Rare, short left-handed alpha-/3(10)-helical turns with repeating phi,psi-angles occur, but none are longer than three residues. Misperceptions dispelled by this study are the existence of 2.2(7)- and pi-helices as linear groups, the existence of specific ideal phi,psi-angles for each linear group, and the existence of a substantive difference in the phi,psi-preferences for parallel versus antiparallel beta-strands. This study provides a concrete basis for updating and enhancing how we think about and teach the basics of protein structure.

All-Atom Contact Model for Understanding Protein Dynamics from Crystallographic B-Factors

An all-atom local contact model is described that can be used to predict protein motions underlying isotropic crystallographic B-factors. It uses a mean-field approximation to represent the motion of an atom in a harmonic potential generated by the surrounding atoms resting at their equilibrium positions. Based on a 400-ns molecular dynamics simulation of ubiquitin in explicit water, it is found that each surrounding atom stiffens the spring constant by a term that on average scales exponentially with the interatomic distance. This model combines features of the local density model by Halle and the local contact model by Zhang and Brüschweiler. When applied to a nonredundant set of 98 ultra-high resolution protein structures, an average correlation coefficient of 0.75 is obtained for all atoms. The systematic inclusion of crystal contact contributions and fraying effects is found to enhance the performance substantially. Because the computational cost of the local contact model scales linearly with the number of protein atoms, it is applicable to proteins of any size for the prediction of B-factors of both backbone and side-chain atoms. The model performs as well as or better than several other models tested, such as rigid-body motional models, the local density model, and various forms of the elastic network model. It is concluded that at the currently achievable level of accuracy, collective intramolecular motions are not essential for the interpretation of B-factors.

A forward-looking suggestion for resolving the stereochemical restraints debate: ideal geometry functions

# 2008 International Union of Crystallography Printed in Singapore – all rights reserved Jaskolski et al. (2007a) initiated a very important discussion (Jaskolski et al., 2007b; Stec, 2007; Tickle, 2007) about the accuracy of ideal geometry targets and the appropriate stringency with which they should be obeyed at various resolutions. All of the discussants agree that protein structures determined at ultra-high resolution, which should be closer to the truth, tend to have larger r.m.s. deviations from ideality. This shows that real deviations from ideality do occur in true protein structures. Another point of agreement is that the real deviations from ideality are to some extent context dependent, so that the single target values used in current refinement programs are a simplification: ‘The N–C –C valence angle has a wide spread and may have a bimodal distribution correlated with secondary structure’, Jaskolski et al. (2007a); ‘Recent results suggest that protein stereochemistry is context-dependent’, Stec (2007); ‘As they point out, the [deviations from ideality] will include real variations arising from the chemical environment’, Tickle (2007); ‘In such a situation, a single target, as used in the refinement programs, will not agree with any of the truly preferred values. This again suggests that the geometrical parameters of protein models should not be too tightly restrained to some predefined values’, Jaskolski et al. (2007b). We point out here that much of the context dependence of stereochemistry can be transformed from a frustrating reality that limits the accuracy of protein modeling to a feature that can instead enhance modeling accuracy. This transformation is possible because much of the context-dependent variation is not random but varies systematically with conformation. This systematic dependence was well documented in the mid-1990s, especially for the N—C —C bond angle, for which the expected value was seen to vary over a range of 10 (Jiang et al.; Karplus, 1996; Schafer et al., 1995). We are now updating these analyses using ultra-high resolution protein structures. These structures not only confirm the highly systematic variation of backbone bond angles with conformation (as illustrated for the N— C —C bond angle in Fig. 1), but they also reveal that the standard deviations are very low. For the N—C —C bond angle, the standard deviations in individual ’, regions vary from 1.0 to 1.7 (Fig. 1b), much lower than the standard deviation of near 2.2 derived for the N—C —C bond angle in the population as a whole (see Table 3 of Jaskolski et al., 2007a). Based on this result, it is clear that no single ideal target value can be appropriate for all of these conformations. However, it is also true that because each mean (or expected value) can be empirically discovered, this feature of protein structure can be accounted for by altering our refinement protocols to allow for ideal geometry targets that are dependent on context. In other words, we propose that more accurate refinement of protein structures at all resolution ranges will be obtained by moving beyond the ‘single ideal value’ paradigm to an ‘ideal geometry function’ paradigm (Schafer et al., 1986) in which each restraint target value varies depending on the local conformation. We are now working to develop a set of empirical conformation-dependent ‘ideal geometry functions’ for backbone bond angles and lengths that can be incorporated into crystallographic refinement software (Berkholz & Karplus, unpublished work).

Advances in charge density studies of ultra high resolution protein structures

Advances in charge density studies of ultra high resolution protein structures

Role of amino acid properties to determine backbone τ(N–Cα–C′) stretching angle in peptides and proteins

The analysis of the basic geometry of amino acid residues of protein structures has demonstrated the invariability of all the bond lengths and bond angles except for τ, the backbone N–Cα–C′ angle. This angle can be widened or contracted significantly from the tetrahedral geometry to accommodate various other strains in the structure. In order to accurately determine the cause for this deviation, a survey is made for the τ angles using the peptide structures and the ultrahigh resolution protein structures. The average deviation of N–Cα–C′ angles from tetrahedral geometry for each amino acid in all the categories were calculated and then correlated with forty-eight physiochemical, energetic and conformational properties of amino acids. Linear and multiple regression analysis were carried out between the amino acid deviation and the 48 properties. This study confirms the deviation of τ angles in both the peptide and protein structures but similar forces do not influence them. The peptide structures are influenced by physical properties whereas as expected the conformational properties influence the protein structures. And it is not any single property that dominates the deviation but the combination of different factors contributes to the τ angle deviation.

Charge density studies of ultra high resolution protein structures

Charge density studies of ultra high resolution protein structures

Experimental evidence for the correlation of bond distances in peptide groups detected in ultrahigh-resolution protein structures.

The structural analysis of a deamidated derivative of ribonuclease A, determined at 0.87 A resolution, reveals a highly significant negative correlation between CN and CO bond distances in peptide groups. This trend, i.e. the CO bond lengthens when the CN bond shortens, is also found in seven out of eight protein structures, determined at ultrahigh resolution (<0.95 A). In five of them the linear correlation is statistically significant at the 95% confidence level. The present findings are consistent with the traditional view of amide resonance and, although already found in small peptide structures, they represent a new and important result. In fact, in a protein structure the fine details of the peptide geometry are only marginally affected by the crystal field and they are mostly produced by intramolecular and solvent interactions. The analysis of very high-resolution protein structures can reveal subtle information about local electronic features of proteins which may be critical to folding, function or ligand binding.