Does hydrophobic hydration destabilize protein native structures?

Water in the immediate vicinity of a non-polar solute has characteristically low entropy and high heat capacity at 25 degrees C. Common opinion has been that the insolubility of such species is caused by thermodynamic changes associated with the formation of these layers of abnormal water, 'hydrophobic hydration'. Recently, however, it has been proposed instead that hydrophobic hydration favors solution of hydrocarbons, or hydrocarbon sidechains, in water and therefore promotes protein unfolding. It is argued here that available data do not convincingly support this hypothesis.     

Assembly of protein tertiary structures from secondary structures using optimized potentials

We present a simulated annealing-based method for the prediction of the tertiary structures of proteins given knowledge of the secondary structure associated with each amino acid in the sequence. The backbone is represented in a detailed fashion whereas the sidechains and pairwise interactions are modeled in a simplified way, following the LINUS model of Srinivasan and Rose. A perceptron-based technique is used to optimize the interaction potentials for a training set of three proteins. For these proteins, the procedure is able to reproduce the tertiary structures to below 3 A in root mean square deviation (rmsd) from the PDB targets. We present the results of tests on twelve other proteins. For half of these, the lowest energy decoy has a rmsd from the native state below 6 A and, in 9 out of 12 cases, we obtain decoys whose rmsd from the native states are also well below 5 A.     

Spectrum of disease-causing mutations in protein secondary structures

Background  

Most genetic disorders are linked to missense mutations as even minor changes in the size or properties of an amino acid can alter or prevent the function of the protein. Further, the effect of a mutation is also dependent on the sequence and structure context of the alteration.     

Prediction of protein secondary structures from conformational biases

We use LINUS (the "Local Independently Nucleated Units of Structure"), a procedure developed by Srinivasan and Rose, to provide a physical interpretation of and predict the secondary structures of proteins. The secondary structure type at a given site is identified by the largest conformational bias during short simulations. We examine the rate of successful prediction as a function of temperature and the interaction window. At high temperatures, there is a large propensity for the establishment of beta-strands whereas alpha-helices appear only when the temperature is lower than a certain threshold value. It is found that there exists an optimal temperature at which the correct secondary structures are predicted most accurately. We find that this temperature is close to the peak temperature of the specific heat. Changing the interaction window or carrying out longer simulations approaching equilibrium lead to little change in the optimal success rate. Our findings are in accord with the observation by Srinivasan and Rose that the secondary structures are mainly determined by local interactions and appear in the early stage of folding.     

Determining protein topology from skeletons of secondary structures

We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6A cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.     

A model of morphogenesis for protein secondary structures.

This paper proposes a model for the expected probability distribution for a certain class of biological structures. In particular, a model is derived for the distribution of lengths of helices, sheets, turns, and coils as a function of the length of the structure divided by the length of the protein it is contained in. A fit between the derived lognormal function and the structures for some proteins whose three-dimensional structure is known was significant. The fit produces fundamental parameters particular to each structure type that are related to the underlying structure and its morphogenesis. The importance of the result is that a universal mathematical distribution can be used to explain certain protein morphogeneses. Also, these fundamental parameters can be used as an aid in predicting whether a given sequence is a particular secondary structure or not, without a knowledge of its three-dimensional structure.     

Fourier transform infrared spectroscopic analysis of protein secondary structures

Infrared spectroscopy is one of the oldest and well established experimental techniques for the analysis of secondary structure of polypeptides and proteins. It is convenient, non-destructive, requires less sample preparation, and can be used under a wide variety of conditions. This review introduces the recent developments in Fourier transform infrared （FTIR） spectroscopy technique and its applications to protein structural studies. The experimental skills, data analysis, and correlations between the FTIR spectroscopic bands and protein secondary structure components are discussed. The applications of FTIR to the second- ary structure analysis, conformational changes, structural dynamics and stability studies of proteins are also discussed.     

Designed molecules that fold to mimic protein secondary structures

Molecules that fold to mimic protein secondary structures have emerged as important targets of bioorganic chemistry. Recently, a variety of compounds that mimic helices, turns, and sheets have been developed, with notable advances in the design of beta-peptides that mimic each of these structures. These compounds hold promise as a step toward synthetic molecules with protein-like properties and as drugs that block protein-protein interactions.     

Elucidating protein secondary structures using alpha-carbon recurrence quantifications.

Secondary structures of proteins were studied by recurrence quantification analysis (RQA). High-resolution, 3-dimensional coordinates of alpha-carbon atoms comprising a set of 68 proteins were downloaded from the Protein Data Bank. By fine-tuning four recurrence parameters (radius, line, residue, separation), it was possible to establish excellent agreement between percent contribution of alpha-helix and beta-sheet structures determined independently by RQA and that of the DSSP algorithm (Define Secondary Structure of Proteins). These results indicate that there is an equivalency between these two techniques, which are based upon totally different pattern recognition strategies. RQA enhances qualitative contact maps by quantifying the arrangements of recurrent points of alpha carbons close in 3-dimensional space. For example, the radius was systematically increased, moving the analysis beyond local alpha-carbon neighborhoods in order to capture super-secondary and tertiary structures. However, differences between proteins could only be detected within distances up to about 6-11 A, but not higher. This result underscores the complexity of alpha-carbon spacing when super-secondary structures appear at larger distances. Finally, RQA-defined secondary structures were found to be robust against random displacement of alpha carbons upwards of 1 A. This finding has potential import for the dynamic functions of proteins in motion.     

HERA--a program to draw schematic diagrams of protein secondary structures

A program is described which generates hydrogen bonding diagrams of protein structures and optionally helical wheels and helical nets. The program can also beta-strands beta-strands and to automatically extract simple structural motifs such as hairpins or Greek keys. The program greatly reduces the effort required to produce these diagrams and offers considerable flexibility in the information which can be represented. The usefulness of the program is illustrated by several examples including comparing homologous families, correlating protein structure with attributes of individual residues, and extracting all examples of the psi-loop motif from the Brookhaven Data Bank.     

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.     

Molecular dynamics of bending fluctuations in the protein secondary structures

A comparative study of the dynamics of protein secondary structure elements by the example of alpha-helices of myoglobin, barnase, polylysine, and polyglycine and beta-layers of barnase and GFP was carried out by the methods of molecular dynamics. The effective Young's moduli of both free secondary structure elements and those built in the protein globule were determined. A heterogeneity of the elastic properties of the secondary structure elements was found. The melting of myoglobin alpha-helix in a virtual viscous medium was studied.     

Constraint-based assembly of tertiary protein structures from secondary structure elements

A challenge in computational protein folding is to assemble secondary structure elements-helices and strands-into well-packed tertiary structures. Particularly difficult is the formation of beta-sheets from strands, because they involve large conformational searches at the same time as precise packing and hydrogen bonding. Here we describe a method, called Geocore-2, that (1) grows chains one monomer or secondary structure at a time, then (2) disconnects the loops and performs a fast rigid-body docking step to achieve canonical packings, then (3) in the case of intrasheet strand packing, adjusts the side-chain rotamers; and finally (4) reattaches loops. Computational efficiency is enhanced by using a branch-and-bound search in which pruning rules aim to achieve a hydrophobic core and satisfactory hydrogen bonding patterns. We show that the pruning rules reduce computational time by 10(3)- to 10(5)-fold, and that this strategy is computationally practical at least for molecules up to about 100 amino acids long.     

Thermal folding and mechanical unfolding pathways of protein secondary structures

Mechanical stretching of secondary structures is studied through molecular dynamics simulations of a Go-like model. Force versus displacement curves are studied as a function of the stiffness and velocity of the pulling device. The succession of stretching events, as measured by the order in which contacts are ruptured, is compared to the sequencing of events during thermal folding and unfolding. Opposite cross-correlations are found for an alpha-helix and a beta-hairpin structure. In a tandem of two alpha-helices, the two constituent helices unravel nearly simultaneously. A simple condition for simultaneous versus sequential unraveling of repeat units is presented.     

A simple motif for protein recognition in DNA secondary structures

DNA in a single-stranded form (ssDNA) exists transiently within the cell and comprises the telomeres of linear chromosomes and the genomes of some DNA viruses. As with RNA, in the single-stranded state, some DNA sequences are able to fold into complex secondary and tertiary structures that may be recognized by proteins and participate in gene regulation. To better understand how such DNA elements might fold and interact with proteins, and to compare recognition features to those of a structured RNA, we used in vitro selection to identify ssDNAs that bind an RNA-binding peptide from the HIV Rev protein with high affinity and specificity. The large majority of selected binders contain a non-Watson-Crick G.T base-pair and an adjacent C:G base-pair and both are essential for binding. This GT motif can be presented in different DNA contexts, including a nearly perfect duplex and a branched three-helix structure, and appears to be recognized in large part by arginine residues separated by one turn of an alpha-helix. Interestingly, a very similar GT motif is necessary also for protein binding and function of a well-characterized model ssDNA regulatory element from the proenkephalin promoter.     

Analyzing protein circular dichroism spectra for accurate secondary structures.

We have developed an algorithm to analyze the circular dichroism of proteins for secondary structure. Its hallmark is tremendous flexibility in creating the basis set, and it also combines the ideas of many previous workers. We also present a new basis set containing the CD spectra of 22 proteins with secondary structures from high quality X-ray diffraction data. High flexibility is obtained by doing the analysis with a variable selection basis set of only eight proteins. Many variable selection basis sets fail to give a good analysis, but good analyses can be selected without any a priori knowledge by using the following criteria: (1) the sum of secondary structures should be close to 1.0, (2) no fraction of secondary structure should be less than -0.03, (3) the reconstructed CD spectrum should fit the original CD spectrum with only a small error, and (4) the fraction of alpha-helix should be similar to that obtained using all the proteins in the basis set. This algorithm gives a root mean square error for the predicted secondary structure for the proteins in the basis set of 3.3% for alpha-helix, 2.6% for 3(10)-helix, 4.2% for beta-strand, 4.2% for beta-turn, 2.7% for poly(L-proline) II type 3(1)-helix, and 5.1% for other structures when compared with the X-ray structure.     

Temporary secondary structures in tau,an intrinsically disordered protein

The tau protein belongs to the category of intrinsically disordered proteins, which in their native state do not have an average stable structure and fluctuate between many conformations. In its physiological state, tau helps nucleating and stabilising the microtubules in the axons of the neurons. On the other hand, the same tau is involved in the development of Alzheimer disease, when it aggregates in paired helical filaments forming fibrils, which form insoluble tangles. The beginning of the pathological aggregation of tau has been attributed to a local transition of protein portions from random coil to a β-sheet. These structures would very likely be transient; therefore, we performed a molecular dynamics simulation of tau to gather information on the existence of segments of tau endowed with a secondary structure. We combined the results of our simulation with small-angle X-ray scattering experimental data to extract from the dynamics a set of most probable conformations of tau. The analysis of these conformations highlights the presence of transient secondary structures such as turns, β-bridges, β-sheets and α-helices. It also shows that a large segment of the N-terminal region is found near the repeats domain in a globular-like shape.     

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.     

Knowledge-based computational intelligence development for predicting protein secondary structures from sequences

In the postgenomic age, with the avalanche of protein sequences generated and relatively slow progress in determining their structures by experiments, it is important to develop automated methods to predict the structure of a protein from its sequence. The membrane proteins are a special group in the protein family that accounts for approximately 30% of all proteins; however, solved membrane protein structures only represent less than 1% of known protein structures to date. Although a great success has been achieved for developing computational intelligence techniques to predict secondary structures in both globular and membrane proteins, there is still much challenging work in this regard. In this review article, we firstly summarize the recent progress of automation methodology development in predicting protein secondary structures, especially in membrane proteins; we will then give some future directions in this research field.