Position dependence of amino acid intrinsic helical propensities II: non-charged polar residues: Ser, Thr, Asn, and Gln

Mechanistic analysis of thermal stability in a novel thermophilic polygalacturonase MlPG28B derived from the marine fungus Mucor lusitanicus

In this study, heterologous MlPG28B expression was obtained by cloning the Mucor lusitanicus gene screened from a marine environment. The enzyme activity of MlPG28B was maximum at 60 °C, 30 % of the enzyme activity was retained after incubation at 100 °C for 30 min, and enzyme activity was still present after 60 min incubation, one of the best thermostable polygalacturonases characterized until now. The high-purity oligosaccharide standards (DP2-DP7) were prepared with polygalacturonic acid as a substrate. Kinetic parameters showed that MlPG28B at the optimum temperature has a low Km value (3055 ± 1104 mg/L), indicating high substrate affinity. Sequence alignment analysis inferred key residues Cys276, Cys284, Lys107, and Gln237 for MlPG28B thermal stability. Molecular docking and molecular dynamics simulation results indicated that MlPG28B has flexible T1 and T3 loops conducive to substrate recognition, binding, and catalysis and forms a hydrogen bond to the substrate by a highly conserved residue Asn161 in the active-site cleft. Based on site-directed mutation results, the five residues are key in determining MlPG28B thermal stability. Therefore, MlPG28B is a promising candidate for industrial enzymes in feed preparation.

Mechanochemical forces regulate the composition and function of CAT tails

The ribosome-associated quality control (RQC) pathway resolves stalled ribosomes. As part of RQC, stalled nascent polypeptide chains (NCs) are appended with CArboxy-Terminal amino acids (CAT tails) in an mRNA-free, non-canonical elongation process. CAT tail composition includes Ala, Thr, and potentially other residues. The relationship between CAT tail composition and function has remained unknown. Using biochemical approaches in yeast, we discovered that mechanochemical forces on the NC regulate CAT tailing. We propose CAT tailing initially operates in an "extrusion mode" that increases NC lysine accessibility for on-ribosome ubiquitination. Thr in CAT tails enhances NC extrusion by preventing formation of polyalanine, which can form α-helices. After NC ubiquitylation, pulling forces on the NC switch CAT tailing to an Ala-only "release mode" which facilitates nascent chain release from large ribosomal subunits and NC degradation. Failure to switch from extrusion to release mode leads to accumulation of NCs on large ribosomal subunits and proteotoxic aggregation of Thr-rich CAT tails.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Uncovering Streptomyces-Derived Compounds as Cosmeceuticals for the Development of Improved Skin Photoprotection Products: An In Silico Approach to Explore Multi-Targeted Agents

The search for novel photoprotective substances has become a challenge in cosmeceutical research. Streptomyces-derived compounds can serve as a promising source of photoprotective agents to formulate skin photoprotection products, such as sunscreens. This study aimed to identify specialized metabolites with the potential to modulate UV-induced cellular damage in the skin by identifying potential multi-target-directed ligands. Using a combination of ligand- and target-based virtual screening approaches, a public compound library comprising 6524 Streptomyces-derived specialized metabolites was studied for their photoprotective capability. The compounds were initially filtered by safety features and then examined for their ability to interact with key targets in the photodamage pathway by molecular docking. A set of 50 commercially available UV filters was used as the benchmark. The protein–ligand stability of selected Streptomyces-derived compounds was also studied by molecular dynamics (MD) simulations. From the compound library, 1981 compounds were found to meet the safety criteria for topically applied products, such as low skin permeability and low or non-toxicity-alerting substructures. A total of 34 compounds had promising binding scores against crucial targets involved in UV-induced photodamage, such as serotonin-receptor subtype 5-HT2A, platelet-activating factor receptor, IL-1 receptor type 1, epidermal growth factor receptor, and cyclooxygenase-2. Among these compounds, aspergilazine A and phaeochromycin F showed the highest ranked interactions with four of the five targets and triggered complex stabilization over time. Additionally, the predicted UV-absorbing profiles also suggest a UV-filtering effect. Streptomyces is an encouraging biological source of compounds for developing topical products. After in silico protein–ligand interactions, binding mode and stabilization of aspergilazine A and phaeochromycin F led to the discovery of potential candidates as photodamage multi-target inhibitors. Therefore, they can be further explored for the formulation of skin photoprotection products.

Physicochemical Position-Dependent Properties in the Protein Secondary Structures

BACKGROUND

Establishing theories for designing arbitrary protein structures is complicated and depends on understanding the principles for protein folding, which is affected by applied features. Computer algorithms can reach high precision and stability in computationally designed enzymes and binders by applying informative features obtained from natural structures.

METHODS

In this study, a position-specific analysis of secondary structures (α-helix, β-strand, and tight turn) was performed to reveal novel features for protein structure prediction and protein design.

RESULTS

Our results showed that the secondary structures in the N-termini region tend to be more compact than C-termini. Decoying periodicity in length and distribution of amino acids in α-helices is deciphered using the curve-fitting methods. Compared with α-helix, β-strands do not show distinct periodicities in length. Also, significant differences in position-dependent distribution of physicochemical properties are shown in secondary structures.

CONCLUSION

Position-specific propensities in our study underline valuable parameters that could be used by researchers in the field of structural biology, particularly protein design through site-directed mutagenesis.

Design of Stable α-Helical Peptides and Thermostable Proteins in Biotechnology and Biomedicine

α-Helices are the most frequently occurring elements of the secondary structure in water-soluble globular proteins. Their increased conformational stability is among the main reasons for the high thermal stability of proteins in thermophilic bacteria. In addition, α-helices are often involved in protein interactions with other proteins, nucleic acids, and the lipids of cell membranes. That is why the highly stable α-helical peptides used as highly active and specific inhibitors of protein-protein and other interactions have recently found more applications in medicine. Several different approaches have been developed in recent years to improve the conformational stability of α-helical peptides and thermostable proteins, which will be discussed in this review. We also discuss the methods for improving the permeability of peptides and proteins across cellular membranes and their resistance to intracellular protease activity. Special attention is given to the SEQOPT method (http://mml.spbstu.ru/services/seqopt/), which is used to design conformationally stable short α-helices.

The importance of cooperative interactions and a solid-state paradigm to proteins: what Peptide chemists can learn from molecular crystals

Proteins and peptides in solution or in vivo share properties with both liquids and solids. More often than not, they are studied using the liquid paradigm rather than that of a solid. Studies of molecular crystals illustrate how the use of a solid paradigm may change the way that we consider these important molecules. Cooperative interactions, particularly those involving H-bonding, play much more important roles in the solid than in the liquid paradigms, as molecular crystals clearly illustrate. Using the solid rather than the liquid paradigm for proteins and peptides includes these cooperative interactions while application of the liquid paradigm tends to ignore or minimize them. Use of the solid paradigm has important implications for basic principles that are often implied about peptide and protein chemistry, such as the importance of entropy in protein folding and the nature of the hydrophobic effect. Understanding the folded states of peptides and proteins (especially alpha-helices) often requires the solid paradigm, whereas understanding unfolded states does not. Both theoretical and experimental studies of the energetics of protein and peptide folding require comparison to a suitable standard. Our perspective on these energetics depends on the reasonable choice of reference. The use of multiple reference states, particularly that of component amino acids in the gas phase, is proposed.

Molecular dynamics simulation and experimental verification of the interaction between cyclin T1 and HIV-1 Tat proteins

The viral encoded Tat protein is essential for the transcriptional activation of HIV proviral DNA. Interaction of Tat with a cellular transcription elongation factor P-TEFb containing CycT1 is critically required for its action. In this study, we performed MD simulation using the 3D data for wild-type and 4CycT1mutants3D data. We found that the dynamic structural change of CycT1 H2’ helix is indispensable for its activity for the Tat action. Moreover, we detected flexible structural changes of the Tat-recognition cavity in the WT CycT1 comprising of ten AAs that are in contact with Tat. These structural fluctuations in WT were lost in the CycT1 mutants. We also found the critical importance of the hydrogen bond network involving H1, H1’ and H2 helices of CycT1. Since similar AA substitutions of the Tat-CycT1 chimera retained the Tat-supporting activity, these interactions are considered primarily involved in interaction with Tat. These findings described in this paper should provide vital information for the development of effective anti-Tat compound.

Association of polyalanine and polyglutamine coiled coils mediates expansion disease-related protein aggregation and dysfunction

The expansion of homopolymeric glutamine (polyQ) or alanine (polyA) repeats in certain proteins owing to genetic mutations induces protein aggregation and toxicity, causing at least 18 human diseases. PolyQ and polyA repeats can also associate in the same proteins, but the general extent of their association in proteomes is unknown. Furthermore, the structural mechanisms by which their expansion causes disease are not well understood, and these repeats are generally thought to misfold upon expansion into aggregation-prone β-sheet structures like amyloids. However, recent evidence indicates a critical role for coiled-coil (CC) structures in triggering aggregation and toxicity of polyQ-expanded proteins, raising the possibility that polyA repeats may as well form these structures, by themselves or in association with polyQ. We found through bioinformatics screenings that polyA, polyQ and polyQA repeats have a phylogenetically graded association in human and non-human proteomes and associate/overlap with CC domains. Circular dichroism and cross-linking experiments revealed that polyA repeats can form—alone or with polyQ and polyQA—CC structures that increase in stability with polyA length, forming higher-order multimers and polymers in vitro. Using structure-guided mutagenesis, we studied the relevance of polyA CCs to the in vivo aggregation and toxicity of RUNX2—a polyQ/polyA protein associated with cleidocranial dysplasia upon polyA expansion—and found that the stability of its polyQ/polyA CC controls its aggregation, localization and toxicity. These findings indicate that, like polyQ, polyA repeats form CC structures that can trigger protein aggregation and toxicity upon expansion in human genetic diseases.

De novo design of stable α-helices

Recent studies have elucidated key principles governing folding and stability of α-helices in short peptides and globular proteins. In this chapter we review briefly those principles and describe a protocol for the de novo design of highly stable α-helixes using the SEQOPT algorithm. This algorithm is based on AGADIR, the statistical mechanical theory for helix-coil transitions in monomeric peptides, and the tunneling algorithm for global sequence optimization.

Amino acid pair- and triplet-wise groupings in the interior of α-helical segments in proteins

A statistical approach has been applied to analyse primary structure patterns at inner positions of α-helices in proteins. A systematic survey was carried out in a recent sample of non-redundant proteins selected from the Protein Data Bank, which were used to analyse α-helix structures for amino acid pairing patterns. Only residues more than three positions apart from both termini of the α-helix were considered as inner. Amino acid pairings i, i+k (k=1, 2, 3, 4, 5), were analysed and the corresponding 20×20 matrices of relative global propensities were constructed. An analysis of (i, i+4, i+8) and (i, i+3, i+4) triplet patterns was also performed. These analysis yielded information on a series of amino acid patterns (pairings and triplets) showing either high or low preference for α-helical motifs and suggested a novel approach to protein alphabet reduction. In addition, it has been shown that the individual amino acid propensities are not enough to define the statistical distribution of these patterns. Global pair propensities also depend on the type of pattern, its composition and orientation in the protein sequence. The data presented should prove useful to obtain and refine useful predictive rules which can further the development and fine-tuning of protein structure prediction algorithms and tools.

Position-specific propensities of amino acids in the β-strand

Background

Despite the importance of β-strands as main building blocks in proteins, the propensity of amino acid in β-strands is not well-understood as it has been more difficult to determine experimentally compared to α-helices. Recent studies have shown that most of the amino acids have significantly high or low propensity towards both ends of β-strands. However, a comprehensive analysis of the sequence dependent amino acid propensities at positions between the ends of the β-strand has not been investigated.

Results

The propensities of the amino acids calculated from a large non-redundant database of proteins are found to be highly position-specific and vary continuously throughout the length of the β-strand. They follow an unexpected characteristic periodic pattern in inner positions with respect to the cap residues in both termini of β-strands; this periodic nature is markedly different from that of the α-helices with respect to the strength and pattern in periodicity. This periodicity is not only different for different amino acids but it also varies considerably for the amino acids belonging to the same physico-chemical group. Average hydrophobicity is also found to be periodic with respect to the positions from both termini of β-strands.

Conclusions

The results contradict the earlier perception of isotropic nature of amino acid propensities in the middle region of β-strands. These position-specific propensities should be of immense help in understanding the factors responsible for β-strand design and efficient prediction of β-strand structure in unknown proteins.

Design of stable alpha-helices using global sequence optimization

The rational design of peptide and protein helices is not only of practical importance for protein engineering but also is a useful approach in attempts to improve our understanding of protein folding. Recent modifications of theoretical models of helix-coil transitions allow accurate predictions of the helix stability of monomeric peptides in water and provide new possibilities for protein design. We report here a new method for the design of alpha-helices in peptides and proteins using AGADIR, the statistical mechanical theory for helix-coil transitions in monomeric peptides and the tunneling algorithm of global optimization of multidimensional functions for optimization of amino acid sequences. CD measurements of helical content of peptides with optimized sequences indicate that the helical potential of protein amino acids is high enough to allow formation of stable alpha-helices in peptides as short as of 10 residues in length. The results show the maximum achievable helix content (HC) of short peptides with fully optimized sequences at 5 degrees C is expected to be approximately 70-75%. Under certain conditions the method can be a powerful practical tool for protein engineering. Unlike traditional approaches that are often used to increase protein stability by adding a few favorable interactions to the protein structure, this method deals with all possible sequences of protein helices and selects the best one from them.

Statistical mechanical model for helix-sheet-coil transitions in homopolypeptides

In this paper, we propose a simple statistical mechanical model to study the conformation transition between the alpha helix, beta sheet, and random coil in homopolypeptides. In our model, five parameters are introduced to obtain the partition function. There are two factors for helical propagation and initiation, which are the same as those used in the Zimm-Bragg model, and three newly introduced parameters for beta structures: the strand propagation factor for residues in beta strands and two correction factors for the initiation effect of the beta strand and beta sheet. Our model shows that the variation of these parameters may induce conformation transition from alpha helix or random coil to beta sheet. The sharpness of the transition depends on the initiation factors.

Amino acid pairing at the N- and C-termini of helical segments in proteins

A systematic survey was carried out in an unbiased sample of 815 protein chains with a maximum of 20% homology selected from the Protein Data Bank, whose structures were solved at a resolution higher than 1.6 A and with a R-factor lower than 25%. A set of 5556 subsequences with alpha-helix or 3(10)-helix motifs was extracted from the protein chains considered. Global and local propensities were then calculated for all possible amino acid pairs of the type (i, i + 1), (i, i + 2), (i, i + 3), and (i, i + 4), starting at the relevant helical positions N1, N2, N3, C3, C2, C1, and N-int (interior positions), and also at the first nonhelical positions in both termini of the helices, namely, N-cap and C-cap. The statistical analysis of the propensity values has shown that pairing is significantly dependent on the type of the amino acids and on the position of the pair. A few sequences of three and four amino acids were selected and their high prevalence in helices is outlined in this work. The Glu-Lys-Tyr-Pro sequence shows a peculiar distribution in proteins, which may suggest a relevant structural role in alpha-helices when Pro is located at the C-cap position. A bioinformatics tool was developed, which updates automatically and periodically the results and makes them available in a web site.

Improved prediction for N-termini of alpha-helices using empirical information

The prediction of the secondary structure of proteins from their amino acid sequences remains a key component of many approaches to the protein folding problem. The most abundant form of regular secondary structure in proteins is the alpha-helix, in which specific residue preferences exist at the N-terminal locations. Propensities derived from these observed amino acid frequencies in the Protein Data Bank (PDB) database correlate well with experimental free energies measured for residues at different N-terminal positions in alanine-based peptides. We report a novel method to exploit this data to improve protein secondary structure prediction through identification of the correct N-terminal sequences in alpha-helices, based on existing popular methods for secondary structure prediction. With this algorithm, the number of correctly predicted alpha-helix start positions was improved from 30% to 38%, while the overall prediction accuracy (Q3) remained the same, using cross-validated testing. Although the algorithm was developed and tested on multiple sequence alignment-based secondary structure predictions, it was also able to improve the predictions of start locations by methods that use single sequences to make their predictions. Furthermore, the residue frequencies at N-terminal positions of the improved predictions better reflect those seen at the N-terminal positions of alpha-helices in proteins. This has implications for areas such as comparative modeling, where a more accurate prediction of the N-terminal regions of alpha-helices should benefit attempts to model adjacent loop regions. The algorithm is available as a Web tool, located at http://rocky.bms.umist.ac.uk/elephant.

Effect of the N3 residue on the stability of the alpha-helix

N3 is the third position from the N terminus in the alpha-helix with helical backbone dihedral angles. All 20 amino acids have been placed in the N3 position of a synthetic helical peptide (CH(3)CO-[AAX AAAAKAAAAKAGY]-NH(2)) and the helix content measured by circular dichroism spectroscopy at 273 K. The dependence of peptide helicity on N3 residue identity has been used to determine a free energy scale by analysis with a modified Lifson-Roig helix coil theory that includes a parameter for the N3 energy (n3). The most stabilizing residues at N3 in rank order are Ala, Glu, Met/Ile, Leu, Lys, Ser, Gln, Thr, Tyr, Phe, Asp, His, and Trp. Free energies for the most destabilizing residues (Cys, Gly, Asn, Arg, and Pro) could not be fitted. The results correlate with N1, N2, and helix interior energies and not at all with N-cap preferences. This completes our work on studying the structural and energetic preferences of the amino acids for the N-terminal positions of the alpha-helix. These results can be used to rationally modify protein stability, help design helices, and improve prediction of helix location and stability.

Exploration of structural features of monomeric helical peptides designed with a genetic algorithm

A genetic algorithm (GA)-based strategy to dissect the determinants of peptide folding into alpha-helix was developed. The structural information of helical peptides was obtained with respect to patterns of sequence variability. In many previously reported studies the intrinsic alpha-helical propensities of amino acids although sequence-dependent are apparently independent of the amino acid position. In this research, monomeric helical peptides selected from possible sequences produced by a GA-chemical synthesis were analyzed to identify possible influential structural features. These hexadeca-peptides were obtained after four successive generations. A total of 128 synthetic peptides were evaluated via circular dichroism (CD) measurements in aqueous solution, while the mean ellipticity at 222 nm confirmed the monomeric state of the peptides. The results presented here show that our GA-based strategy may be useful in the design of proteins with increased alpha-helix content.

Recent advances in helix-coil theory

Peptide helices in solution form a complex mixture of all helix, all coil or, most frequently, central helices with frayed coil ends. In order to interpret experiments on helical peptides and make theoretical predictions on helices, it is therefore essential to use a helix-coil theory that takes account of this equilibrium. The original Zimm-Bragg and Lifson-Roig helix-coil theories have been greatly extended in the last 10 years to include additional interactions. These include preferences for the N-cap, N1, N2, N3 and C-cap positions, capping motifs, helix dipoles, side chain interactions and 3(10)-helix formation. These have been applied to determine energies for these preferences from experimental data and to predict the helix contents of peptides. This review discusses these newly recognised structural features of helices and how they have been included in helix-coil models.

A critical assessment of the secondary structure alpha-helices and their termini in proteins

Secondary structure prediction from amino acid sequence is a key component of protein structure prediction, with current accuracy at approximately 75%. We analysed two state-of-the-art secondary structure prediction methods, PHD and JPRED, comparing predictions with secondary structure assigned by the algorithms DSSP and STRIDE. The specific focus of our study was alpha-helix N-termini, as empirical free energy scales are available for residue preferences at N-terminal positions. Although these prediction methods perform well in general at predicting the alpha-helical locations and length distributions in proteins, they perform less well at predicting the correct helical termini. For example, although most predicted alpha-helices overlap a real alpha-helix (with relatively few completely missed or extra predicted helices), only one-third of JPRED and PHD predictions correctly identify the N-terminus. Analysis of neighbouring N-terminal sequences to predicted helical N-termini shows that the correct N-terminus is often within one or two residues. More importantly, the true N-terminal motif is, on average, more favourable as judged by our experimentally measured free energies. This suggests a simple, but powerful, strategy to improve secondary structure prediction using empirically derived energies to adjust the predicted output to a more favourable N-terminal sequence.

Amino acid intrinsic alpha-helical propensities III: positional dependence at several positions of C terminus

In this study, we have analyzed experimentally the helical intrinsic propensities of non-charged and non-aromatic residues at different C-terminal positions (C1, C2, C3) of an Ala-based peptide. The effect was found to be complex, resulting in extra stabilization or destabilization, depending on guest amino acid and position under consideration. Polar (Ser, Thr, Cys, Asn, and Gln) amino acids and Gly were found to have significantly larger helical propensities at several C-terminal positions compared with the alpha-helix center (-1.0 kcal/mole in some cases). Some of the nonpolar residues, especially beta-branched ones (Val and Ile) are significantly more favorable at position C3 (-0.3 to -0.4 kcal/mole), although having minor differences at other C-terminal positions compared with the alpha-helix center. Leu has moderate (-0.1 to -0.2 kcal/mole) stabilization effects at position C2 and C3, whereas being relatively neutral at C1. Finally, Met was found to be unfavorable at C1 and C2 ( +0.2 kcal/mole) and favorable at C3 (-0.2 kcal/mole). Thus, significant differences found between the intrinsic helical propensities at the C-terminal positions and those in the alpha-helix center must be accounted for in helix/coil transition theories and in protein design.

New stochastic strategy to analyze helix folding

We propose an alternative stochastic strategy to search secondary structures based on the generalized simulated annealing (GSA) algorithm, by using conformational preferences based on the Ramachandran map. We optimize the search for polypeptide conformational space and apply to peptides considered to be good alpha-helix promoters above a critical number of residues. Our strategy to obtain conformational energies consist in coupling a classical force field (THOR package) with the GSA procedure, biasing the Phi x Psi backbone angles to the allowed regions in the Ramachandran map. For polyalanines we obtained stable alpha-helix structures when the number of residues were equal or exceeded 13 amino acids residues. We also observed that the energy gap between the global minimum and the first local minimum tends to increase with the polypeptide size. These conformations were generated by performing 2880 stochastic molecular optimizations with a continuum medium approach. When compared with molecular dynamics or Monte Carlo methods, GSA can be considered the fastest.

Effect of the N2 residue on the stability of the alpha-helix for all 20 amino acids

N2 is the second position in the alpha-helix. All 20 amino acids were placed in the N2 position of a synthetic helical peptide (CH(3)CO-[AXAAAAKAAAAKAAGY]-NH(2)) and the helix content was measured by circular dichroism spectroscopy at 273K. The dependence of peptide helicity on N2 residue identity has been used to determine a free-energy scale by analysis with a modified Lifson-Roig helix-coil theory that includes a parameter for the N2 energy (n2). The rank order of DeltaDeltaG((relative to Ala)) is Glu(-), Asp(-) > Ala > Glu(0), Leu, Val, Gln, Thr, Ile, Ser, Met, Asp(0), His(0), Arg, Cys, Lys, Phe > Asn, > Gly, His(+), Pro, Tyr. The results correlate very well with N2 propensities in proteins, moderately well with N1 and helix interior preferences, and not at all with N-cap preferences. The strongest energetic effects result from interactions with the helix dipole, which favors negative charges at the helix N terminus. Hydrogen bonds to side chains at N2, such as Gln, Ser, and Thr, are weak, despite occurring frequently in protein crystal structures, in contrast to the N-cap position. This is because N-cap hydrogen bonds are close to linear, whereas N2 hydrogen bonds have poor geometry. These results can be used to modify protein stability rationally, help design helices, and improve prediction of helix location and stability.

Alpha helix capping and the conformation of threonine

The amino acid threonine contains two chiral carbons and thus can exist in four possible conformations. However, only a single conformation (2S, 3R) of threonine is incorporated in proteins by the cellular translation material. The conformation at the alpha carbon (carbon 2) is the same as that of the other amino acids in biological proteins, and there is no explanation for why this enantiomer was selected. Further, there is no explanation for the choice of conformation at the 3 carbon in threonine. Here, I suggest that the preferential ability of (2S, 3R) threonine over the (2S, 3S) enantiomer to participate in alpha helix capping interactions may have led to the selection of the (2S, 3R) conformation.

Effect of the N1 residue on the stability of the alpha-helix for all 20 amino acids

N1 is the first residue in an alpha-helix. We have measured the contribution of all 20 amino acids to the stability of a small helical peptide CH(3)CO-XAAAAQAAAAQAAGY-NH(2) at the N1 position. By substituting every residue into the N1 position, we were able to investigate the stabilizing role of each amino acid in an isolated context. The helix content of each of the 20 peptides was measured by circular dichroism (CD) spectroscopy. The data were analyzed by our modified Lifson-Roig helix-coil theory, which includes the n1 parameter, to find free energies for placing a residue into the N1 position. The rank order for free energies is Asp(-), Ala > Glu(-) > Glu(0) > Trp, Leu, Ser > Asp(0), Thr, Gln, Met, Ile > Val, Pro > Lys(+), Arg, His(0) > Cys, Gly > Phe > Asn, Tyr, His(+). N1 preferences are clearly distinct from preferences for the preceding N-cap and alpha-helix interior. pK(a) values were measured for Asp, Glu, and His, and protonation-free energies were calculated for Asp and Glu. The dissociation of the Asp proton is less favorable than that of Glu, and this reflects its involvement in a stronger stabilizing interaction at the N terminus. Proline is not energetically favored at the alpha-helix N terminus despite having a high propensity for this position in crystal structures. The data presented are of value both in rationalizing mutations at N1 alpha-helix sites in proteins and in predicting the helix contents of peptides.

Rotamer strain energy in protein helices - quantification of a major force opposing protein folding

It is widely believed that the dominant force opposing protein folding is the entropic cost of restricting internal rotations. The energetic changes from restricting side-chain torsional motion are more complex than simply a loss of conformational entropy, however. A second force opposing protein folding arises when a side-chain in the folded state is not in its lowest-energy rotamer, giving rotameric strain. chi strain energy results from a dihedral angle being shifted from the most stable conformation of a rotamer when a protein folds. We calculated the energy of a side-chain as a function of its dihedral angles in a poly(Ala) helix. Using these energy profiles, we quantify conformational entropy, rotameric strain energy and chi strain energy for all 17 amino acid residues with side-chains in alpha-helices. We can calculate these terms for any amino acid in a helix interior in a protein, as a function of its side-chain dihedral angles, and have implemented this algorithm on a web page. The mean change in rotameric strain energy on folding is 0.42 kcal mol-1 per residue and the mean chi strain energy is 0.64 kcal mol-1 per residue. Loss of conformational entropy opposes folding by a mean of 1.1 kcal mol-1 per residue, and the mean total force opposing restricting a side-chain into a helix is 2.2 kcal mol-1. Conformational entropy estimates alone therefore greatly underestimate the forces opposing protein folding. The introduction of strain when a protein folds should not be neglected when attempting to quantify the balance of forces affecting protein stability. Consideration of rotameric strain energy may help the use of rotamer libraries in protein design and rationalise the effects of mutations where side-chain conformations change.

Determination of alpha-helix N1 energies after addition of N1, N2, and N3 preferences to helix/coil theory

Surveys of protein crystal structures have revealed that amino acids show unique structural preferences for the N1, N2, and N3 positions in the first turn of the alpha-helix. We have therefore extended helix-coil theory to include statistical weights for these locations. The helix content of a peptide in this model is a function of N-cap, C-cap, N1, N2, N3, C1, and helix interior (N4 to C2) preferences. The partition function for the system is calculated using a matrix incorporating the weights of the fourth residue in a hexamer of amino acids and is implemented using a FORTRAN program. We have applied the model to calculate the N1 preferences of Gln, Val, Ile, Ala, Met, Pro, Leu, Thr, Gly, Ser, and Asn, using our previous data on helix contents of peptides Ac-XAKAAAAKAAGY-CONH2. We find that Ala has the highest preference for the N1 position. Asn is the most unfavorable, destabilizing a helix at N1 by at least 1.4 kcal mol(-1) compared to Ala. The remaining amino acids all have similar preferences, 0.5 kcal mol(-1) less than Ala. Gln, Asn, and Ser, therefore, do not stabilize the helix when at N1.