An analysis of side-chain conformation in proteins

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers

Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike image generation or even the closely related problem of protein structure prediction, there are currently no data sources with sufficient breadth to parametrize generative models for conformational ensembles. To enable discovery, a fundamentally different approach to building generative models is required: models should be able to propose rare, albeit physical, conformations that may not arise in even the largest data sets. Here we introduce a modular strategy to generate conformations based on "backmapping" from a fixed protein backbone that (1) maintains conformational diversity of the side chains and (2) couples the side-chain fluctuations using global information about the protein conformation. Our model combines simple statistical models of side-chain conformations based on rotamer libraries with the now ubiquitous transformer architecture to sample with atomistic accuracy. Together, these ingredients provide a strategy for rapid data acquisition and hence a crucial ingredient for scalable physical simulation with generative neural networks.

The peptide NCbz-Val-Tyr-OMe and aromatic π-π interactions

The peptide N-benzyloxycarbonyl-L-valyl-L-tyrosine methyl ester or NCbz-Val-Tyr-OMe (where NCbz is N-benzyloxycarbonyl and OMe indicates the methyl ester), C(23)H(28)N(2)O(6), has an extended backbone conformation. The aromatic rings of the Tyr residue and the NCbz group are involved in various attractive intra- and intermolecular aromatic π-π interactions which stabilize the conformation and packing in the crystal structure, in addition to N-H...O and O-H...O hydrogen bonds. The aromatic π-π interactions include parallel-displaced, perpendicular T-shaped, perpendicular L-shaped and inclined orientations.

Assessment of protein side-chain conformation prediction methods in different residue environments

Computational prediction of side-chain conformation is an important component of protein structure prediction. Accurate side-chain prediction is crucial for practical applications of protein structure models that need atomic-detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side-chain prediction methods in reproducing the side-chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane-spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side-chains at protein interfaces and membrane-spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane-spanning regions as for modeling monomers.

Correlation analysis of the side-chains conformational distribution in bound and unbound proteins

BACKGROUND

Protein interactions play a key role in life processes. Characterization of conformational properties of protein-protein interactions is important for understanding the mechanisms of protein association. The rapidly increasing amount of experimentally determined structures of proteins and protein-protein complexes provides foundation for research on protein interactions and complex formation. The knowledge of the conformations of the surface side chains is essential for modeling of protein complexes. The purpose of this study was to analyze and compare dihedral angle distribution functions of the side chains at the interface and non-interface areas in bound and unbound proteins.

RESULTS

To calculate the dihedral angle distribution functions, the configuration space was divided into grid cells. Statistical analysis showed that the similarity between bound and unbound interface and non-interface surface depends on the amino acid type and the grid resolution. The correlation coefficients between the distribution functions increased with the grid spacing increase for all amino acid types. The Manhattan distance showing the degree of dissimilarity between the distribution functions decreased accordingly. Short residues with one or two dihedral angles had higher correlations and smaller Manhattan distances than the longer residues. Met and Arg had the slowest growth of the correlation coefficient with the grid spacing increase. The correlations between the interface and non-interface distribution functions had a similar dependence on the grid resolution in both bound and unbound states. The interface and non-interface differences between bound and unbound distribution functions, caused by biological protein-protein interactions or crystal contacts, disappeared at the 70° grid spacing for interfaces and 30° for non-interface surface, which agrees with an average span of the side-chain rotamers.

CONCLUSIONS

The two-fold difference in the critical grid spacing indicates larger conformational changes upon binding at the interface than at the rest of the surface. At the same time, transitions between rotamers induced by interactions across the interface or the crystal packing are rare, with most side chains having local readjustments that do not change the rotameric state. The analysis is important for better understanding of protein interactions and development of flexible docking approaches.

Rotamer libraries and probabilities of transition between rotamers for the side chains in protein-protein binding

Conformational changes in the side chains are essential for protein-protein binding. Rotameric states and unbound- to-bound conformational changes in the surface residues were systematically studied on a representative set of protein complexes. The side-chain conformations were mapped onto dihedral angles space. The variable threshold algorithm was developed to cluster the dihedral angle distributions and to derive rotamers, defined as the most probable conformation in a cluster. Six rotamer libraries were generated: full surface, surface noninterface, and surface interface-each for bound and unbound states. The libraries were used to calculate the probabilities of the rotamer transitions upon binding. The stability of amino acids was quantified based on the transition maps. The noninterface residues' stability was higher than that of the interface. Long side chains with three or four dihedral angles were less stable than the shorter ones. The transitions between the rotamers at the interface occurred more frequently than on the noninterface surface. Most side chains changed conformation within the same rotamer or moved to an adjacent rotamer. The highest percentage of the transitions was observed primarily between the two most occupied rotamers. The probability of the transition between rotamers increased with the decrease of the rotamer stability. The analysis revealed characteristics of the surface side-chain conformational transitions that can be utilized in flexible docking protocols.

A protein-dependent side-chain rotamer library

BACKGROUND

Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries.

METHODS

In this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities.

RESULTS

Experimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.

Nitrogen-efficient rice cultivars can reduce nitrate pollution

INTRODUCTION

Environmental pollution by un-utilized nitrogenous fertilizer at the agricultural field is one of the key issues of the day. Rice-based cropping system, the mainstay of Indian agriculture, is one of the main sources of unused N-fertilizer since rice utilizes only 30-40% of total applied N, and the rest goes to waste and creates environmental as well as economic loss.

METHODS

Identification of rice genotypes that can grow and yield well at low nitrogen levels is highly desirable for enhancement of nitrogen use efficiency (NUE). In the present study, we have identified large variability in the NUE of rice cultivars on the basis of plant with low, medium, and high levels of N in nutrient solution. To establish the basis of this wide variability in NUE, nitrate uptake kinetics and enzymes of nitrate assimilation were studied.

RESULTS AND DISCUSSION

The data of nitrate uptake kinetics revealed that the nitrate uptake is mediated by low-affinity transporter system (LATS) in N-inefficient rice cultivars and by both LATS and high-affinity transporter systems (HATS) in N-efficient genotypes. Activities of nitrate reductase, nitrite reductase, glutamine synthetase, glutamate synthase, and the soluble protein content were found to be increased in moderately N-efficient and low N-efficient cultivars with increase in external supply of nitrogen. However, a non-significant decrease in these enzymes was recorded in high N-efficient cultivars with the increase in N supply.

CONCLUSIONS

This study suggests that the HATS, high NR, and glutamine synthetase activity and the soluble protein content distribution have a key role in N efficiency of rice genotypes. These parameters may be considered in breeding and genetic engineering programs for improving the NUE of rice, which might be helpful in reducing the fertilizer loss, hence decreasing environmental degradation and improving crop productivity through improvement of nitrogen utilization efficiency in rice.

From isotropic to anisotropic side chain representations: comparison of three models for residue contact estimation

The criterion to determine residue contact is a fundamental problem in deriving knowledge-based mean-force potential energy calculations for protein structures. A frequently used criterion is to require the side chain center-to-center distance or the -to- atom distance to be within a pre-determined cutoff distance. However, the spatially anisotropic nature of the side chain determines that it is challenging to identify the contact pairs. This study compares three side chain contact models: the Atom Distance criteria (ADC) model, the Isotropic Sphere Side chain (ISS) model and the Anisotropic Ellipsoid Side chain (AES) model using 424 high resolution protein structures in the Protein Data Bank. The results indicate that the ADC model is the most accurate and ISS is the worst. The AES model eliminates about 95% of the incorrectly counted contact-pairs in the ISS model. Algorithm analysis shows that AES model is the most computational intensive while ADC model has moderate computational cost. We derived a dataset of the mis-estimated contact pairs by AES model. The most misjudged pairs are Arg-Glu, Arg-Asp and Arg-Tyr. Such a dataset can be useful for developing the improved AES model by incorporating the pair-specific information for the cutoff distance.

Improved side-chain modeling by coupling clash-detection guided iterative search with rotamer relaxation

MOTIVATION

Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.

RESULTS

We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling.

AVAILABILITY

CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html.

Structural bioinformatics: deriving biological insights from protein structures

Structural bioinformatics can be described as an approach that will help decipher biological insights from protein structures. As an important component of structural biology, this area promises to provide a high resolution understanding of biology by assisting comprehension and interpretation of a large amount of structural data. Biological function of protein molecules can be inferred from their three-dimensional structures by comparing structures, classifying them and transferring function from a related protein or family. It is well known now that the structure space of protein molecules is more conserved than the sequence space, making it important to seek functional associations at the structural level. An added advantage of structural bioinformatics over simpler sequence-based methods is that the former also provides ultimate insights into the mechanisms by which various biological events take place. A bird's eye-view of the different aspects of structural bioinformatics is given here along with various recent advances in the area including how knowledge obtained from structural bioinformatics can be applied in drug discovery.

Side-chain conformational space analysis (SCSA): a multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities

In this article, the concept of multi conformation-based quantitative structure-activity relationship (MCB-QSAR) is proposed, and based upon that, we describe a new approach called the side-chain conformational space analysis (SCSA) to model and predict protein-peptide binding affinities. In SCSA, multi-conformations (rather than traditional single-conformation) have received much attention, and the statistical average information on multi-conformations of side chains is determined using self-consistent mean field theory based upon side chain rotamer library. Thereby, enthalpy contributions (including electrostatic, steric, hydrophobic interaction and hydrogen bond) and conformational entropy effects to the binding are investigated in terms of occurrence probability of residue rotamers. Then, SCSA was applied into the dataset of 419 HLA-A 0201 binding peptides, and nonbonding contributions of each position in peptide ligands are well determined. For the peptides, the hydrogen bond and electrostatic interactions of the two ends are essential to the binding specificity, van der Waals and hydrophobic interactions of all the positions ensure strong binding affinity, and the loss of conformational entropy at anchor positions partially counteracts other favorable nonbonding effects.

Differentiable, multi-dimensional, knowledge-based energy terms for torsion angle probabilities and propensities

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file.

Computing van der Waals energies in the context of the rotamer approximation

The rotamer approximation states that protein side-chain conformations can be described well using a finite set of rotational isomers. This approximation is often applied in the context of computational protein design and structure prediction to reduce the complexity of structural sampling. It is an effective way of reducing the structure space to the most relevant conformations. However, the appropriateness of rotamers for sampling structure space does not imply that a rotamer-based energy landscape preserves any of the properties of the true continuous energy landscape. Specifically, because the energy of a van der Waals interaction can be very sensitive to small changes in atomic separation, meaningful van der Waals energies are particularly difficult to calculate from rotamer-based structures. This presents a problem for computational protein design, where the total energy of a given structure is often represented as a sum of precalculated rigid rotamer self and pair contributions. A common way of addressing this issue is to modify the van der Waals function to reduce its sensitivity to atomic position, but excessive modification may result in a strongly nonphysical potential. Although many different van der Waals modifications have been used in protein design, little is known about which performs best, and why. In this paper, we study 10 ways of computing van der Waals energies under the rotamer approximation, representing four general classes, and compare their performance using a variety of metrics relevant to protein design and native-sequence repacking calculations. Scaling van der Waals radii by anywhere from 85 to 95% gives the best performance. Linearizing and capping the repulsive portion of the potential can give additional improvement, which comes primarily from getting rid of unrealistically large clash energies. On the other hand, continuously minimizing individual rotamer pairs prior to evaluating their interaction works acceptably in native-sequence repacking, but fails in protein design. Additionally, we show that the problem of predicting relevant van der Waals energies from rotamer-based structures is strongly nonpairwise decomposable and hence further modifications of the potential are unlikely to give significant improvement.

Statistical and conformational analysis of the electron density of protein side chains

Protein side chains make most of the specific contacts between proteins and other molecules, and their conformational properties have been studied for many years. These properties have been analyzed primarily in the form of rotamer libraries, which cluster the observed conformations into groups and provide frequencies and average dihedral angles for these groups. In recent years, these libraries have improved with higher resolution structures and using various criteria such as high thermal factors to eliminate side chains that may be misplaced within the crystallographic model coordinates. Many of these side chains have highly non-rotameric dihedral angles. The origin of side chains with high B-factors and/or with non-rotameric dihedral angles is of interest in the determination of protein structures and in assessing the prediction of side chain conformations. In this paper, using a statistical analysis of the electron density of a large set of proteins, it is shown that: (1) most non-rotameric side chains have low electron density compared to rotameric side chains; (2) up to 15% of chi1 non-rotameric side chains in PDB models can clearly be fit to density at a single rotameric conformation and in some cases multiple rotameric conformations; (3) a further 47% of non-rotameric side chains have highly dispersed electron density, indicating potentially interconverting rotameric conformations; (4) the entropy of these side chains is close to that of side chains annotated as having more than one chi(1) rotamer in the crystallographic model; (5) many rotameric side chains with high entropy clearly show multiple conformations that are not annotated in the crystallographic model. These results indicate that modeling of side chains alternating between rotamers in the electron density is important and needs further improvement, both in structure determination and in structure prediction.

Molecular modelling prediction of ligand binding site flexibility

We have investigated the efficacy of generating multiple sidechain conformations using a rotamer library in order to find the experimentally observed ligand binding site conformation of a protein in the presence of a bound ligand. We made use of a recently published algorithm that performs an exhaustive conformational search using a rotamer library to enumerate all possible sidechain conformations in a binding site. This approach was applied to a dataset of proteins whose structures were determined by X-ray and NMR methods. All chosen proteins had two or more structures, generally involving different bound ligands. By taking one of these structures as a reference, we were able in most cases to successfully reproduce the experimentally determined conformations of the other structures, as well as to suggest alternative low-energy conformations of the binding site. In those few cases where this procedure failed, we observed that the bound ligand had induced a high-energy conformation of the binding site. These results suggest that for most proteins that exhibit limited backbone motion, ligands tend to bind to low energy conformations of their binding sites. Our results also reveal that it is possible in most cases to use a rotamer search-based approach to predict alternative low-energy protein binding site conformations that can be used by different ligands. This opens the possibility of incorporating alternative binding site conformations to improve the efficacy of docking and structure-based drug design algorithms.

Side-chain conformation angles of amino acids: effect of temperature factor cut-off

The paper presents the analysis of the side-chain conformation angles of amino acids in 90% non-identical protein structures. The analysis has been carried out using 113,699 residues, which is higher compared to the previous studies. In the present study, one more quality check, namely, temperature factor cut-off, has been introduced in addition to resolution and R-factor cut-offs. Due to this, the present calculation reveals the approximate values for the minimum and the maximum of the three-rotameric states of chi1. In addition, the conformation angles chi2 and chi3 have been addressed with the improved data set. The results reported here could be of use in protein modeling.

The role of carbon-donor hydrogen bonds in stabilizing tryptophan conformations

Although most side-chain torsion angles correspond to low-energy rotameric positions, deviations occur with significant frequency. One striking example arises in Trp residues, which have an important role in stabilizing protein structures because of their size and mixed hydrophobic/hydrophilic character. Ten percent of Trp side-chains have unexplained conformations with chi(2) near 0 degrees instead of the expected 90 degrees. The current work is a structural and energetic analysis of these conformations. It is shown that many Trp residues with these orientations are stabilized by three-center carbon-donor hydrogen bonds of the form C-H...X...H-C, where X is a polar hydrogen-bond acceptor in the environment of the side-chain. The bridging hydrogen bonds occur both within the Trp side-chain and between the side-chain and the local protein backbone. Free energy maps of an isolated Trp residue in an explicit water environment show a minimum corresponding to the off-rotamer peak observed in the crystallographic data. Bridging carbon-donor hydrogen bonds are also shown to stabilize on-rotamer Trp conformations, and similar bridging hydrogen bonds also stabilize some off-rotamer Asp conformations. The present results suggest a previously unrecognized role for three-center carbon-donor hydrogen bonds in protein structures and support the view that the off-rotamer Trp side-chain orientations are real rather than artifacts of crystallographic refinements. Certain of the off-rotamer Trp conformations appear to have a functional role.

Design of peptides with branched beta-carbon dehydro-residues: syntheses, crystal structures and molecular conformations of two peptides, (I) N-Carbobenzoxy-DeltaVal-Ala-Leu-OCH3 and (II) N-Carbobenzoxy-DeltaIle-Ala-Leu-OCH3

Highly specific structures can be designed by inserting dehydro-residues into peptide sequences. The conformational preferences of branched beta-carbon residues are known to be different from other residues. As an implication it was expected that the branched beta-carbon dehydro-residues would also induce different conformations when substituted in peptides. So far, the design of peptides with branched beta-carbon dehydro-residues at (i + 1) position has not been reported. It may be recalled that the nonbranched beta-carbon residues induced beta-turn II conformation when placed at (i + 2) position while branched beta-carbon residues induced beta-turn III conformation. However, the conformation of a peptide with a nonbranched beta-carbon residue when placed at (i + 1) position was not found to be unique as it depended on the stereochemical nature of its neighbouring residues. Therefore, in order to induce predictably unique structures with dehydro-residues at (i + 1) position, we have introduced branched beta-carbon dehydro-residues instead of nonbranched beta-carbon residues and synthesized two peptides: (I) N-Carbobenzoxy-DeltaVal-Ala-Leu-OCH3 and (II) N-Carbobenzoxy-DeltaIle-Ala-Leu-OCH3 with DeltaVal and DeltaIle, respectively. The crystal structures of peptides (I) and (II) have been determined and refined to R-factors of 0.065 and 0.063, respectively. The structures of both peptides were essentially similar. Both peptides adopted type II beta-turn conformations with torsion angles; (I): phi1 = -38.7 (4) degrees, psi1 = 126.0 (3) degrees; phi2 = 91.6 (3) degrees, psi2 = -9.5 (4) degrees and (II): phi1 = -37.0 (6) degrees, psi1 = 123.6 (4) degrees, phi2 = 93.4 (4), psi2 = -11.0(4) degrees respectively. Both peptide structures were stabilized by intramolecular 4-->1 hydrogen bonds. The molecular packing in both crystal structures were stabilized in each by two identical hydrogen bonds N1...O1' (-x, y + 1/2, -z) and N2...O2' (-x + 1, y + 1/2, -z) and van der Waals interactions.

Beyond the rotamer library: genetic algorithm combined with the disturbing mutation process for upbuilding protein side-chains

The disturbing genetic algorithm, incorporating the disturbing mutation process into the genetic algorithm flow, has been developed to extend the searching space of side-chain conformations and to improve the quality of the rotamer library. Moreover, the growing generation amount idea, simulating the real situation of the natural evolution, is introduced to improve the searching speed. In the calculations using the pseudo energy scoring function of the root mean squared deviation, the disturbing genetic algorithm method has been shown to be highly efficient. With the real energy function based on AMBER force field, the program has been applied to rebuilding side-chain conformations of 25 high-quality crystallographic structures of single-protein and protein-protein complexes. The averaged root mean standard deviation of atom coordinates in side-chains and veracities of the torsion angles of chi(1) and chi(1) + chi(2) are 1.165 A, 88.2 and 72.9% for the buried residues, respectively, and 1.493 A, 79.2 and 64.7% for all residues, showing that the method has equal precision to the program SCWRL, whereas it performs better in the prediction of buried residues and protein-protein interfaces. This method has been successfully used in redesigning the interface of the Basnase-Barstar complex, indicating that it will have extensive application in protein design, protein sequence and structure relationship studies, and research on protein-protein interaction.

Rotamer libraries in the 21st century

Rotamer libraries are widely used in protein structure prediction, protein design, and structure refinement. As the size of the structure data base has increased rapidly in recent years, it has become possible to derive well-refined rotamer libraries using strict criteria for data inclusion and for studying dependence of rotamer populations and dihedral angles on local structural features.

Crystal structures of artocarpin, a Moraceae lectin with mannose specificity, and its complex with methyl-alpha-D-mannose: implications to the generation of carbohydrate specificity

The seeds of jack fruit (Artocarpus integrifolia) contain two tetrameric lectins, jacalin and artocarpin. Jacalin was the first lectin found to exhibit the beta-prism I fold, which is characteristic of the Moraceae plant lectin family. Jacalin contains two polypeptide chains produced by a post-translational proteolysis which has been shown to be crucial for generating its specificity for galactose. Artocarpin is a single chain protein with considerable sequence similarity with jacalin. It, however, exhibits many properties different from those of jacalin. In particular, it is specific to mannose. The structures of two crystal forms, form I and form II, of the native lectin have been determined at 2.4 and 2.5 A resolution, respectively. The structure of the lectin complexed with methyl-alpha-mannose, has also been determined at 2.9 A resolution. The structure is similar to jacalin, although differences exist in details. The crystal structures and detailed modelling studies indicate that the following differences between the carbohydrate binding sites of artocarpin and jacalin are responsible for the difference in the specificities of the two lectins. Firstly, artocarpin does not contain, unlike jacalin, an N terminus generated by post-translational proteolysis. Secondly, there is no aromatic residue in the binding site of artocarpin whereas there are four in that of jacalin. A comparison with similar lectins of known structures or sequences, suggests that, in general, stacking interactions with aromatic residues are important for the binding of galactose while such interactions are usually absent in the carbohydrate binding sites of mannose-specific lectins with the beta-prism I fold.

The interrelationships of side-chain and main-chain conformations in proteins

The accurate determination of a large number of protein structures by X-ray crystallography makes it possible to conduct a reliable statistical analysis of the distribution of the main-chain and side-chain conformational angles, how these are dependent on residue type, adjacent residue in the sequence, secondary structure, residue-residue interactions and location at the polypeptide chain termini. The interrelationship between the main-chain (phi, psi) and side-chain (chi 1) torsion angles leads to a classification of amino acid residues that simplify the folding alphabet considerably and can be a guide to the design of new proteins or mutational studies. Analyses of residues occurring with disallowed main-chain conformation or with multiple conformations shed some light on why some residues are less favoured in thermophiles.

Conformational preferences of heterochiral peptides. Crystal structures of heterochiral peptides Boc-(D) Val-(D) Ala-Leu-Ala-OMe and Boc-Val-Ala-Leu-(D) Ala-OMe--enhanced stability of beta-sheet through C-H...O hydrogen bonds

The crystal structures of Boc-(D) Val-(D) Ala-Leu-Ala-OMe (vaLA) and Boc-Val-Ala-Leu-(D) Ala-OMe (VALa) have been determined. vaLA crystallises in space group P2(1),2(1),2(1), with a = 9.401 (4), b = 17.253 (5), c = 36.276 (9)A. V = 5,884 (3) A3, Z = 8, R = 0.086. VALa crystallises in space group P2(1) with a = 9.683 (9), b = 17.355 (7), c = 18.187 (9) A, beta = 95.84 (8) degrees , V = 3,040(4) A3, Z = 4, R = 0.125. There are two molecules in the asymmetric unit in antiparallel beta-sheet arrangement in both the structures. Several of the Calpha hydrogens are in hydrogen bonding contact with the carbonyl oxygen in the adjacent strand. An analysis of the observed conformational feature of D-chiral amino acid residues in oligopeptides, using coordinates of 123 crystal structures selected from the 1998 release of CSD has been carried out. This shows that all the residues except D-isoleucine prefer both extended and alphaL conformation though the frequence of occurence may not be equal. In addition to this, D-leucine, valine, proline and phenylalanine have assumed alphaR conformations in solid state. D-leucine has a strong preference for helical conformation in linear peptides whereas they prefer an extended conformation in cyclic peptides.

Structural and conformational properties of (Z)-beta-(1-naphthyl)- dehydroalanine residue

To understand how chemical structure of beta-substituted alpha, beta-dehydroalanine (particularly size and pi conjugation of beta substituent) affects conformational property, x-ray crystallographic analysis was performed on Boc-Ala-Delta(Z) Nap-Val-OMe [Boc: t-butoxycarbonyl; Delta(Z) Nap: (Z)-beta-(1-naphthyl)dehydroalanine; OMe: methoxy] having the naphthyl group as a bulky beta substituent. Single crystals were grown by slow evaporation from an ethanol solution in the triclinic space group P1 with a = 9.528 (3) A, b = 12.410(4) A, c = 5.975(2) A, alpha = 96.77(3) degrees, beta = 102. 81(2) degrees, gamma = 88.74(3) degrees, V = 684.1(4) A3, and Z = 1. Phase determination was carried out by a direct method (SHELEXS), and the final structure was refined to R = 8.1% and R(w) = 9.0% for 1964 observed reflections. The bond lengths and bond angles of the Delta(Z)Nap residue, characterized by a sp(2) hybridized C(alpha) atom, did not differ from those of other dehydroresidues such as Delta(Z) Phe, Delta(Z) Leu, and DeltaVal essentially. The peptide backbone took a type II beta-turn conformation involving an intramolecular hydrogen bond between CO(Boc) and NH(Val), similar to di- or tripeptides containing a Delta(Z) Phe or Delta(Z) Leu residue in the second positions. Here the naphthyl group was found to be nonplanar [chi(2) = 55(1) degrees ] relative to the C(alpha)==C(beta)==C(gamma) plane. The nonplanarity was supported by conformational energy calculation. The molecular packing was stabilized by two kinds of intermolecular hydrogen bonds and van der Waals interactions. Naphthyl groups were arranged in a partially overlapped face-to-face orientation with a center-to-center distance of 5.97 A. For additional information, peptide Boc-(Ala-Delta(Z) Nap-Leu)(2)-OMe was synthesized and its solution conformation was investigated by (1)H-NMR spectroscopy. The hexapeptide showed the tendency to form a 3(10)-helical conformation in solution essentially. Conformational properties of Delta(Z) Nap residue, characterized by a type II beta-turn and 3(10)-helix, were supported by a conformational energy contour map of the Delta(Z)Nap residue.

Exploring the dynamic information content of a protein NMR structure: comparison of a molecular dynamics simulation with the NMR and X-ray structures of Escherichia coli ribonuclease HI

The multiconformer nature of solution nuclear magnetic resonance (NMR) structures of proteins results from the effects of intramolecular dynamics, spin diffusion and an uneven distribution of structural restraints throughout the molecule. A delineation of the former from the latter two contributions is attempted in this work for an ensemble of 15 NMR structures of the protein Escherichia coli ribonuclease HI (RNase HI). Exploration of the dynamic information content of the NMR ensemble is carried out through correlation with data from two crystal structures and a 1.7-ns molecular dynamics (MD) trajectory of RNase HI in explicit solvent. Assessment of the consistency of the crystal and mean MD structures with nuclear Overhauser effect (NOE) data showed that the NMR ensemble is overall more compatible with the high-resolution (1.48 A) crystal structure than with either the lower-resolution (2.05 A) crystal structure or the MD simulation. Furthermore, the NMR ensemble is found to span more conformational space than the MD simulation for both the backbone and the sidechains of RNase HI. Nonetheless, the backbone conformational variability of both the NMR ensemble and the simulation is especially consistent with NMR relaxation measurements of two loop regions that are putative sites of substrate recognition. Plausible side-chain dynamic information is extracted from the NMR ensemble on the basis of (i) rotamericity and syn-pentane character of variable torsion angles, (ii) comparison of the magnitude of atomic mean-square fluctuations (msf) with those deduced from crystallographic thermal factors, and (iii) comparison of torsion angle conformational behavior in the NMR ensemble and the simulation. Several heterogeneous torsion angles, while adopting non-rotameric/syn-pentane conformations in the NMR ensemble, exist in a unique conformation in the simulation and display low X-ray thermal factors. These torsions are identified as sites whose variability is likely to be an artifact of the NMR structure determination procedure. A number of other torsions show a close correspondence between the conformations sampled in the NMR and MD ensembles, as well as significant correlations among crystallographic thermal factors and atomic msf calculated from the NMR ensemble and the simulation. These results indicate that a significant amount of dynamic information is contained in the NMR ensemble. The relevance of the present findings for the biological function of RNase HI, protein recognition studies, and previous investigations of the motional content of protein NMR structures are discussed.