Analysis of the steric strain in the polypeptide backbone of protein molecules.

The extent to which local strain is present in the polypeptide backbone of folded protein molecules has been examined. The occurrence of steric strain associated with nonproline cis peptide bonds and energetically unfavorable main chain dihedral angles can be identified reliably from the well ordered parts of high resolution, refined crystal structures. The analysis reveals that there are relatively few sterically strained features. Those that do occur are located overwhelmingly in regions concerned with function. We attribute this to the greater precision necessary for ligand binding and catalysis, compared with the requirements of satisfactory folding.     

Modelling of peptide and protein structures

Summary The modelling of protein structures (whether isolated, in solution, or involved in recognition processes) is reviewed, free of any mathematical apparatus, to provide an overview of the concepts as well as leading references. A general feeling for this field of work is first established by a sampling of some impressions on its difficulties and chances of success. Then, the main body of this work examines the information available (databases and parameters), presents the theoretical foundations for the modelling procedures (with emphasis on the potential energy functions), surveys the existing simulation techniques and prediction methods, and discusses the problems still to be faced. For completeness, a representative list of existing software packages is presented in the Appendix.Presented at the Third International Congress on Amino Acids, Vienna, August 23–27, 1993.     

Determination of three-dimensional protein structures from nuclear magnetic resonance data using fragments of known structures

A method to build a three-dimensional protein model from nuclear magnetic resonance (NMR) data using fragments from a data base of crystallographically determined protein structures is presented. The interproton distances derived from the nuclear Overhauser effect (NOE) data are compared to the precalculated distances in the known protein structures. An efficient search algorithm is used, which arranges the distances in matrices akin to a C alpha diagonal distance plot, and compares the NOE distance matrices for short sequential zones of the protein to the data base matrices. After cluster analysis of the fragments found in this way, the structure is built by aligning fragments in overlapping zones. The sequentially long-range NOEs cannot be used in the initial fragments search but are vital to discriminate between several possible combinations of different groups of fragments. The method has been tested on one simulated NOE data set derived from a crystal structure and one experimental NMR data set. The method produces models that have good local structure, but may contain larger global errors. These models can be used as the starting point for further refinement, e.g., by restrained molecular dynamics or interactive graphics.     

Secondary structures without backbone: an analysis of backbone mimicry by polar side chains in protein structures.

Backbone mimicry by the formation of closed-loop C7, C10 and C13 (mimics of gamma-, beta- and alpha-turns) conformations through side chain-main chain hydrogen bonds by polar groups is a frequent observation in protein structures. A data set of 250 non-homologous and high-resolution protein crystal structures was used to analyze these conformations for their characteristic features. Seven out of the nine polar residues (Ser, Thr, Asn, Asp, Gln, Glu and His) have hydrogen bonding groups in their side chains which can participate in such mimicry and as many as 15% of all these polar residues engage in such conformations. The distributions of dihedral angles of these mimics indicate that only certain combinations of the dihedral angles involved aid the formation of these mimics. The observed examples were categorized into various classes based on these combinations, resulting in well defined motifs. Asn and Asp residues show a very high capability to perform such backbone secondary structural mimicry. The most highly mimicked backbone structure is of the C10 conformation by the Asx residues. The mimics formed by His, Ser, Thr and Glx residues are also discussed. The role of such conformations in initiating the formation of regular secondary structures during the course of protein folding seems significant.     

Characterization of novel proteins based on known protein structures

The genome sciences face the challenge to characterize structure and function of a vast number of novel genes. Sequence search techniques are used to infer functional and structural information from similarities to experimentally characterized genes or proteins. The persistent goal is to refine these techniques and to develop alternative and complementary methods to increase the range of reliable inference.Here, we focus on the structural and functional assignments that can be inferred from the known three-dimensional structures of proteins. The study uses all structures in the Protein Data Bank that were known by the end of 1997. The protein structures released in 1998 were then characterized in terms of functional and structural similarity to the previously known structures, yielding an estimate of the maximum amount of information on novel protein sequences that can be obtained from inference techniques.The 147 globular proteins corresponding to 196 domains released in 1998 have no clear sequence similarity to previously known structures. However, 75 % of the domains have extensive structure similarity to previously known folds, and most importantly, in two out of three cases similarity in structure coincides with related function. In view of this analysis, full utilization of existing structure data bases would provide information for many new targets even if the relationship is not accessible from sequence information alone. Currently, the most sophisticated techniques detect of the order of one-third of these relationships.     

Prediction and evaluation of side-chain conformations for protein backbone structures

A common approach to protein modeling is to propose a backbone structure based on homology or threading and then to attempt to build side chains onto this backbone. A fast algorithm using the simple criteria of atomic overlap and overall rotamer probability is proposed for this purpose. The method was first tested in the context of exhaustive searches of side chain configuration space in protein cores and was then applied to all side chains in 49 proteins of known structure, using simulated annealing to sample space. The latter procedure obtains the correct rotamer for 57% and the correct χ₁ value for 74% of the 6751 residues in the sample. When low-temperature Monte-Carlo simulations are initiated from the results of the simulated-annealing processes, consensus configurations are obtained which exhibit slightly more accurate predictions. The Monte-Carlo procedure also allows converged side chain entropies to be calculated for all residues. These prove to be accurate indicators of prediction reliability. For example, the correct rotamer is obtained for 79% and the correct χ₁ value is obtained for 84% of the half of the sample residues exhibiting the lowest entropies. Side chain entropy and predictability are nearly completely uncorrelated with solvent-accessible area. Some precedents for and implications of this observation are discussed. © 1996 Wiley-Liss, Inc.     

Comparison of protein secondary structures based on backbone dihedral angles

In this article, we propose a relatively similar measure to compare protein secondary structures. We first transform a protein secondary structure into a special sequence representation (angle sequence) based on a partition of the backbone φ,ψ-space. Then, pairwise sequence distance is evaluated on the basis of a symbolic sequence complexity. To illustrate our approach, we construct the similarity tree of 24 proteins from PDB.     

TALI: local alignment of protein structures using backbone torsion angles

Torsion angle alignment (TALI) is a novel approach to local structural motif alignment, based on backbone torsion angles (phi, psi) rather than the more traditional atomic distance matrices. Representation of a protein structure in the form of a sequence of torsion angles enables easy integration of sequence and structural information, and adopts mature techniques in sequence alignment to improve performance and alignment quality. We show that TALI is able to match local structural motifs as well as identify global structural similarity. TALI is also compared to other structure alignment methods such as DALI, CE, and SSM, as well as sequence alignment based on PSI-BLAST; TALI is shown to be equally successful as, or more successful than, these other methods when applied to challenging structural alignments. The inference of the evolutionary tree of class II aminoacyl-tRNA synthetase shows the potential for TALI in estimating protein structural evolution and in identifying structural divergence among homologous structures. Availability: http://redcat.cse.sc.edu/index.php/Project:TALI/.     

Pyridoxamine protects protein backbone from oxidative fragmentation

Oxidative damage to proteins is one of the major pathogenic mechanisms in many chronic diseases. Therefore, inhibition of this oxidative damage can be an important part of therapeutic strategies. Pyridoxamine (PM), a prospective drug for treatment of diabetic nephropathy, has been previously shown to inhibit several oxidative and glycoxidative pathways, thus protecting amino acid side chains of the proteins from oxidative damage. Here, we demonstrated that PM can also protect protein backbone from fragmentation induced via different oxidative mechanisms including autoxidation of glucose. This protection was due to hydroxyl radical scavenging by PM and may contribute to PM therapeutic effects shown in clinical trials.     

A unified picture of protein hydration: prediction of hydrodynamic properties from known structures.

Hydration is essential for the structural and functional integrity of globular proteins. How much hydration water is required for that integrity? A number of techniques such as X-ray diffraction, nuclear magnetic resonance (NMR) spectroscopy, calorimetry, infrared spectroscopy, and molecular dynamics (MD) simulations indicate that the hydration level is 0.3-0.5 g of water per gram of protein for medium sized proteins. Hydrodynamic properties, when accounted for by modeling proteins as ellipsoids, appear to give a wide range of hydration levels. In this paper we describe an alternative numerical technique for hydrodynamic calculations that takes account of the detailed protein structures. This is made possible by relating hydrodynamic properties (translational and rotational diffusion constants and intrinsic viscosity) to electrostatic properties (capacitance and polarizability). We show that the use of detailed protein structures in predicting hydrodynamic properties leads to hydration levels in agreement with other techniques. A unified picture of protein hydration emerges. There are preferred hydration sites around a protein surface. These sites are occupied nearly all the time, but by different water molecules at different times. Thus, though a given water molecule may have a very short residence time (approximately 100-500 ps from NMR spectroscopy and MD simulations) in a particular site, the site appears fully occupied in experiments in which time-averaged properties are measured.     

Biodegradability of synthetic branched polypeptide with poly(L-lysine) backbone

A detailed investigation is reported about the biodegradation of poly[Lys(DL-Alam)], m approximately 3, (AK) the common inside area of a branched polypeptide model system developed by our group over the last decade. Enzymatic hydrolysis was carried out by the exopeptidase aminopeptidase M, or the endopeptidase trypsin, or their mixture. Ion-exchange column chromatography, paper electrophoresis and thin-layer chromatography were utilised to achieve separation of metabolites. Breakdown products were identified by the aid of synthetic oligopeptides representing the potential fragments (DL-Ala2, DL-Ala3, Lys(DL-Alam), m = 1-3). The kinetics and the degree of enzymatic degradation were determined. The ratio of peptide/amino acid amounts in the hydrolysate was found to be 1.07 after 24 h treatment with aminopeptidase M, 3.0 with trypsin and 1.3 with aminopeptidase - trypsin mixture. The overall results indicated that the proteolysis of AK by an aminopeptidase M and trypsin mixture proceeds stepwise at multiple sites on the polypeptide chain. The degradation is significantly retarded as compared to that of alpha- or epsilon-polylysine. A mechanism of degradation is suggested based on the experimental results.     

Automated real-space refinement of protein structures using a realistic backbone move set

Crystals of many important biological macromolecules diffract to limited resolution, rendering accurate model building and refinement difficult and time-consuming. We present a torsional optimization protocol that is applicable to many such situations and combines Protein Data Bank-based torsional optimization with real-space refinement against the electron density derived from crystallography or cryo-electron microscopy. Our method converts moderate- to low-resolution structures at initial (e.g., backbone trace only) or late stages of refinement to structures with increased numbers of hydrogen bonds, improved crystallographic R-factors, and superior backbone geometry. This automated method is applicable to DNA-binding and membrane proteins of any size and will aid studies of structural biology by improving model quality and saving considerable effort. The method can be extended to improve NMR and other structures. Our backbone score and its sequence profile provide an additional standard tool for evaluating structural quality.     

Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks

By using an unsupervised cluster analyzer, we have identified a local structural alphabet composed of 16 folding patterns of five consecutive C(alpha) ("protein blocks"). The dependence that exists between successive blocks is explicitly taken into account. A Bayesian approach based on the relation protein block-amino acid propensity is used for prediction and leads to a success rate close to 35%. Sharing sequence windows associated with certain blocks into "sequence families" improves the prediction accuracy by 6%. This prediction accuracy exceeds 75% when keeping the first four predicted protein blocks at each site of the protein. In addition, two different strategies are proposed: the first one defines the number of protein blocks in each site needed for respecting a user-fixed prediction accuracy, and alternatively, the second one defines the different protein sites to be predicted with a user-fixed number of blocks and a chosen accuracy. This last strategy applied to the ubiquitin conjugating enzyme (alpha/beta protein) shows that 91% of the sites may be predicted with a prediction accuracy larger than 77% considering only three blocks per site. The prediction strategies proposed improve our knowledge about sequence-structure dependence and should be very useful in ab initio protein modelling.     

Possible three-dimensional models for the polypeptide backbone structure of alamethicin

Based on an empirical procedure of predicting polypeptide backbone structures of proteins, an attempt was made to construct possible three-dimensional models for the secondary structure of alamethicin. Two chemical properties were used to limit the number of possible models: the presence of seven to eight α-aminoisobutyric acid residues whose conformations were quite restricted, and a covalent bond between the proline residue at position 1 and the glutamic acid residue at position 17. The predicted structures appear very compact and show features in agreement with circular dichroism and optical rotatory dispersion results, nuclear magnetic resonance measurements, and compressed monolayer studies.     

Predicting polypeptide and protein structures from amino acid sequence: Antlion method applied to melittin

This report continues to explore the use of a strategy known as the antlion method for predicting polypeptide and protein structure. The method involves deformation of a biopolymer's potential energy hypersurface in order to retain only a single minimum, near to the native structure. The vexing multiple minimum problem thus is relieved, and the deformed hypersurface constitutes a key element in three-dimensional structure predictions with atomic resolution. In this more demanding pilot study, we provide evidence that the antlion method is capable of dramatically simplifying the surface of polypeptides by successfully predicting the native form of the naturally occurring 26-residue polypeptide melittin. The systematic hypersurface modifications employed in our previous work have been used again for this case, but have been supplemented by the output of a suitable neural network. This neural network involves a new feature: the use of amino acid biophysical scales for improving the secondary structure prediction accuracy of simple perceptrons. © 1993 John Wiley & Sons, Inc.     

Comparison of backbone structures of glucose isomerase from Streptomyces and Arthrobacter

The C alpha backbones of the glucose isomerase molecules of Streptomyces rubiginosus and Arthrobacter have been determined by X-ray crystallography and compared. Each molecule is a tetramer of eight-stranded alpha/beta barrels, and the mode of association of the tetramers is identical in each case. The Arthrobacter electron density shows four additional amino acids at the carboxyl terminus. There is also an insertion of six amino acids at position 277, and two individual insertions at about positions 348 and 357 (numbering according to the Streptomyces structure). There is a close structural homology throughout the whole molecule, which is most accurate up to position 325. The r.m.s. displacement for 315 homologous C alpha positions up to this position is 0.92 A.     

Using convex hulls to extract interaction interfaces from known structures

MOTIVATION: Protein interactions provide an important context for the understanding of function. Experimental approaches have been complemented with computational ones, such as PSIMAP, which computes domain-domain interactions for all multi-domain and multi-chain proteins in the Protein Data Bank (PDB). PSIMAP has been used to determine that superfamilies occurring in many species have many interaction partners, to show examples of convergent evolution through shared interaction partners and to uncover complexes in the interaction map. To determine an interaction, the original PSIMAP algorithm checks all residue pairs of any domain pair defined by classification systems such as SCOP. The computation takes several days for the PDB. The computation of PSIMAP has two shortcomings: first, the original PSIMAP algorithm considers only interactions of residue pairs rather than atom pairs losing information for detailed analysis of contact patterns. At the atomic level the original algorithm would take months. Second, with the superlinear growth of PDB, PSIMAP is not sustainable. RESULTS: We address these two shortcomings by developing a family of new algorithms for the computation of domain-domain interactions based on the idea of bounding shapes, which are used to prune the search space. The best of the algorithms improves on the old PSIMAP algorithm by a factor of 60 on the PDB. Additionally, the algorithms allow a distributed computation, which we carry out on a farm of 80 Linux PCs. Overall, the new algorithms reduce the computation at atomic level from months to 20 min. The combination of pruning and distribution makes the new algorithm scalable and sustainable even with the superlinear growth in PDB.