Thioesterases: A new perspective based on their primary and tertiary structures

Thioesterases (TEs) are classified into EC 3.1.2.1 through EC 3.1.2.27 based on their activities on different substrates, with many remaining unclassified (EC 3.1.2.–). Analysis of primary and tertiary structures of known TEs casts a new light on this enzyme group. We used strong primary sequence conservation based on experimentally proved proteins as the main criterion, followed by verification with tertiary structure superpositions, mechanisms, and catalytic residue positions, to accurately define TE families. At present, TEs fall into 23 families almost completely unrelated to each other by primary structure. It is assumed that all members of the same family have essentially the same tertiary structure; however, TEs in different families can have markedly different folds and mechanisms. Conversely, the latter sometimes have very similar tertiary structures and catalytic mechanisms despite being only slightly or not at all related by primary structure, indicating that they have common distant ancestors and can be grouped into clans. At present, four clans encompass 12 TE families. The new constantly updated ThYme (Thioester‐active enzYmes) database contains TE primary and tertiary structures, classified into families and clans that are different from those currently found in the literature or in other databases. We review all types of TEs, including those cleaving CoA, ACP, glutathione, and other protein molecules, and we discuss their structures, functions, and mechanisms.     

Acyl carrier protein structural classification and normal mode analysis

All acyl carrier protein primary and tertiary structures were gathered into the ThYme database. They are classified into 16 families by amino acid sequence similarity, with members of the different families having sequences with statistically highly significant differences. These classifications are supported by tertiary structure superposition analysis. Tertiary structures from a number of families are very similar, suggesting that these families may come from a single distant ancestor. Normal vibrational mode analysis was conducted on experimentally determined freestanding structures, showing greater fluctuations at chain termini and loops than in most helices. Their modes overlap more so within families than between different families. The tertiary structures of three acyl carrier protein families that lacked any known structures were predicted as well.     

Carboxylic ester hydrolases: Classification and database derived from their primary,secondary, and tertiary structures

We classified the carboxylic ester hydrolases (CEHs) into families and clans by use of multiple sequence alignments, secondary structure analysis, and tertiary structure superpositions. Our work for the first time has fully established their systematic structural classification. Family members have similar primary, secondary, and tertiary structures, and their active sites and reaction mechanisms are conserved. Families may be gathered into clans by their having similar secondary and tertiary structures, even though primary structures of members of different families are not similar. CEHs were gathered from public databases by use of Basic Local Alignment Search Tool (BLAST) and divided into 91 families, with 36 families being grouped into five clans. Members of one clan have standard α/β‐hydrolase folds, while those of other two clans have similar folds but with different sequences of their β‐strands. The other two clans have members with six‐bladed β‐propeller and three‐α‐helix bundle tertiary structures. Those families not in clans have a large variety of structures or have no members with known structures. At the time of writing, the 91 families contained 321,830 primary structures and 1378 tertiary structures. From these data, we constructed an accessible database: CASTLE (CArboxylic eSTer hydroLasEs, http://www.castle.cbe.iastate.edu ).     

Structural classification of biotin carboxyl carrier proteins

We gathered primary and tertiary structures of acyl-CoA carboxylases from public databases, and established that members of their biotin carboxylase (BC) and biotin carboxyl carrier protein (BCCP) domains occur in one family each and that members of their carboxyl transferase (CT) domains occur in two families. Protein families have members similar in primary and tertiary structure that probably have descended from the same protein ancestor. The BCCP domains complexed with biotin in acyl and acyl-CoA carboxylases transfer bicarbonate ions from BC domains to CT domains, enabling the latter to carboxylate acyl and acyl-CoA moieties. We separated the BCCP domains into four subfamilies based on more subtle primary structure differences. Members of different BCCP subfamilies often are produced by different types of organisms and are associated with different carboxylases.     

Structural classification and properties of ketoacyl synthases

Ketoacyl synthases (KSs) catalyze condensing reactions combining acyl-CoA or acyl-acyl carrier protein (acyl-ACP) with malonyl-CoA to form 3-ketoacyl-CoA or with malonyl-ACP to form 3-ketoacyl-ACP. In each case, the resulting acyl chain is two carbon atoms longer than before, and CO2 and either CoA or ACP are formed. KSs also join other activated molecules in the polyketide synthesis cycle. Our classification of KSs by their primary and tertiary structures instead of by their substrates and the reactions that they catalyze enhances insights into this enzyme group. KSs fall into five families separated by their characteristic primary structures, each having members with the same catalytic residues, mechanisms, and tertiary structures. KS1 members, overwhelmingly named 3-ketoacyl-ACP synthase III or its variants, are produced predominantly by bacteria. Members of KS2 are mainly produced by plants, and they are usually long-chain fatty acid elongases/condensing enzymes and 3-ketoacyl-CoA synthases. KS3, a very large family, is composed of bacterial and eukaryotic 3-ketoacyl-ACP synthases I and II, often found in multidomain fatty acid and polyketide synthases. Most of the chalcone synthases, stilbene synthases, and naringenin-chalcone synthases in KS4 are from eukaryota. KS5 members are all from eukaryota, most are produced by animals, and they are mainly fatty acid elongases. All families except KS3 are split into subfamilies whose members have statistically significant differences in their primary structures. KS1 through KS4 appear to be part of the same clan. KS sequences, tertiary structures, and family classifications are available on the continuously updated ThYme (Thioester-active enzYme) database.     

Non‐native α‐helix formation is not necessary for folding of lipocalin: Comparison of burst‐phase folding between tear lipocalin and β‐lactoglobulin

Tear lipocalin and β‐lactoglobulin are members of the lipocalin superfamily. They have similar tertiary structures but unusually low overall sequence similarity. Non‐native helical structures are formed during the early stage of β‐lactoglobulin folding. To address whether the non‐native helix formation is found in the folding of other lipocalin superfamily proteins, the folding kinetics of a tear lipocalin variant were investigated by stopped‐flow methods measuring the time‐dependent changes in circular dichroism (CD) spectrum and small‐angle X‐ray scattering (SAXS). CD spectrum showed that extensive secondary structures are not formed during a burst‐phase (within a measurement dead time). The SAXS data showed that the radius of gyration becomes much smaller than in the unfolded state during the burst‐phase, indicating that the molecule is collapsed during an early stage of folding. Therefore, non‐native helix formation is not general for folding of all lipocalin family members. The non‐native helix content in the burst‐phase folding appears to depend on helical propensities of the amino acid sequence. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

An amino acid code for irregular and mixed protein packing

To advance our understanding of protein tertiary structure, the development of the knob‐socket model is completed in an analysis of the packing in irregular coil and turn secondary structure packing as well as between mixed secondary structure. The knob‐socket model simplifies packing based on repeated patterns of two motifs: a three‐residue socket for packing within secondary (2°) structure and a four‐residue knob‐socket for tertiary (3°) packing. For coil and turn secondary structure, knob‐sockets allow identification of a correlation between amino acid composition and tertiary arrangements in space. Coil contributes almost as much as α‐helices to tertiary packing. In irregular sockets, Gly, Pro, Asp, and Ser are favored, while in irregular knobs, the preference order is Arg, Asp, Pro, Asn, Thr, Leu, and Gly. Cys, His,Met, and Trp are not favored in either. In mixed packing, the knob amino acid preferences are a function of the socket that they are packing into, whereas the amino acid composition of the sockets does not depend on the secondary structure of the knob. A unique motif of a coil knob with an XYZ β‐sheet socket may potentially function to inhibit β‐sheet extension. In addition, analysis of the preferred crossing angles for strands within a β‐sheet and mixed α‐helice/β‐sheet identifies canonical packing patterns useful in protein design. Lastly, the knob‐socket model abstracts the complexity of protein tertiary structure into an intuitive packing surface topology map. Proteins 2015; 83:2147–2161. © 2015 Wiley Periodicals, Inc.     

An amino acid code to define a protein's tertiary packing surface

One difficult aspect of the protein‐folding problem is characterizing the nonspecific interactions that define packing in protein tertiary structure. To better understand tertiary structure, this work extends the knob‐socket model by classifying the interactions of a single knob residue packed into a set of contiguous sockets, or a pocket made up of 4 or more residues. The knob‐socket construct allows for a symbolic two‐dimensional mapping of pockets. The two‐dimensional mapping of pockets provides a simple method to investigate the variety of pocket shapes to understand the geometry of protein tertiary surfaces. The diversity of pocket geometries can be organized into groups of pockets that share a common core, which suggests that some interactions in pockets are ancillary to packing. Further analysis of pocket geometries displays a preferred configuration that is right‐handed in α‐helices and left‐handed in β‐sheets. The amino acid composition of pockets illustrates the importance of nonpolar amino acids in packing as well as position specificity. As expected, all pocket shapes prefer to pack with hydrophobic knobs; however, knobs are not selective for the pockets they pack. Investigating side‐chain rotamer preferences for certain pocket shapes uncovers no strong correlations. These findings allow a simple vocabulary based on knobs and sockets to describe protein tertiary packing that supports improved analysis, design, and prediction of protein structure. Proteins 2016; 84:201–216. © 2015 Wiley Periodicals, Inc.     

Rules for connectivity of secondary structure elements in protein: Two–layer αβ sandwiches

In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α‐helices and β‐strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two‐layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α‐4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two‐layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β‐strand pairs, two spatially adjacent β‐strands located at discontinuous positions in the amino acid sequence. A two‐dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.     

Biochemical characterization and structural insight into aliphatic β‐amino acid adenylation enzymes IdnL1 and CmiS6

Macrolactam antibiotics such as incednine and cremimycin possess an aliphatic β‐amino acid as a starter unit of their polyketide chain. In the biosynthesis of incednine and cremimycin, unique stand‐alone adenylation enzymes IdnL1 and CmiS6 select and activate the proper aliphatic β‐amino acid as a starter unit. In this study, we describe the enzymatic characterization and the structural basis of substrate specificity of IdnL1 and CmiS6. Functional analysis revealed that IdnL1 and CmiS6 recognize 3‐aminobutanoic acid and 3‐aminononanoic acid, respectively. We solved the X‐ray crystal structures of IdnL1 and CmiS6 to understand the recognition mechanism of these aliphatic β‐amino acids. These structures revealed that IdnL1 and CmiS6 share a common recognition motif that interacts with the β‐amino group of the substrates. However, the hydrophobic side‐chains of the substrates are accommodated differently in the two enzymes. IdnL1 has a bulky Leu220 located close to the terminal methyl group of 3‐aminobutanoate of the trapped acyl‐adenylate intermediate to construct a shallow substrate‐binding pocket. In contrast, CmiS6 possesses Gly220 at the corresponding position to accommodate 3‐aminononanoic acid. This structural observation was supported by a mutational study. Thus, the size of amino acid residue at the 220 position is critical for the selection of an aliphatic β‐amino acid substrate in these adenylation enzymes. Proteins 2017; 85:1238–1247. © 2017 Wiley Periodicals, Inc.     

β‐Bulges: Extensive structural analyses of β‐sheets irregularities

β‐Sheets are quite frequent in protein structures and are stabilized by regular main‐chain hydrogen bond patterns. Irregularities in β‐sheets, named β‐bulges, are distorted regions between two consecutive hydrogen bonds. They disrupt the classical alternation of side chain direction and can alter the directionality of β‐strands. They are implicated in protein‐protein interactions and are introduced to avoid β‐strand aggregation. Five different types of β‐bulges are defined. Previous studies on β‐bulges were performed on a limited number of protein structures or one specific family. These studies evoked a potential conservation during evolution. In this work, we analyze the β‐bulge distribution and conservation in terms of local backbone conformations and amino acid composition. Our dataset consists of 66 times more β‐bulges than the last systematic study (Chan et al. Protein Science 1993, 2:1574–1590). Novel amino acid preferences are underlined and local structure conformations are highlighted by the use of a structural alphabet. We observed that β‐bulges are preferably localized at the N‐ and C‐termini of β‐strands, but contrary to the earlier studies, no significant conservation of β‐bulges was observed among structural homologues. Displacement of β‐bulges along the sequence was also investigated by Molecular Dynamics simulations.     

Evolutionary relationship of NAD(+)-dependent D-lactate dehydrogenase: comparison of primary structure of 2-hydroxy acid dehydrogenases.

A comparison of the primary structures of NAD(+)-dependent D-lactate dehydrogenase with L-lactate dehydrogenase and L-malate dehydrogenase failed to show any sequence similarity. However, D-2-hydroxyisocaproate dehydrogenase from Lactobacillus casei, glycerate dehydrogenase from cucumber, D-3-phosphoglycerate dehydrogenase and erythronate 4-phosphate dehydrogenase from Escherichia coli showed 38%, 24%, 24% and 22% amino acid identity, respectively. The profile analysis of the aligned sequences confirmed their relatedness. The hydropathy profiles of the aligned dehydrogenases were almost identical between residues 100-300 indicating largely preserved folding patterns of their polypeptide chains. The data suggest that L- and D-specific 2-hydroxy acid dehydrogenase genes evolved from two different ancestors and thus represent two different sets of enzyme families.     

An amino acid code for β‐sheet packing structure

To understand the relationship between protein sequence and structure, this work extends the knob‐socket model in an investigation of β‐sheet packing. Over a comprehensive set of β‐sheet folds, the contacts between residues were used to identify packing cliques: sets of residues that all contact each other. These packing cliques were then classified based on size and contact order. From this analysis, the two types of four‐residue packing cliques necessary to describe β‐sheet packing were characterized. Both occur between two adjacent hydrogen bonded β‐strands. First, defining the secondary structure packing within β‐sheets, the combined socket or XY:HG pocket consists of four residues i, i+2 on one strand and j, j+2 on the other. Second, characterizing the tertiary packing between β‐sheets, the knob‐socket XY:H+B consists of a three‐residue XY:H socket (i, i+2 on one strand and j on the other) packed against a knob B residue (residue k distant in sequence). Depending on the packing depth of the knob B residue, two types of knob‐sockets are found: side‐chain and main‐chain sockets. The amino acid composition of the pockets and knob‐sockets reveal the sequence specificity of β‐sheet packing. For β‐sheet formation, the XY:HG pocket clearly shows sequence specificity of amino acids. For tertiary packing, the XY:H+B side‐chain and main‐chain sockets exhibit distinct amino acid preferences at each position. These relationships define an amino acid code for β‐sheet structure and provide an intuitive topological mapping of β‐sheet packing. Proteins 2014; 82:2128–2140. © 2014 Wiley Periodicals, Inc.     

Structural and functional features of the NAD(P) dependent Gfo/Idh/MocA protein family oxidoreductases

The Gfo/Idh/MocA protein family contains a number of different proteins, which almost exclusively consist of NAD(P)‐dependent oxidoreductases that have a diverse set of substrates, typically pyranoses. In this study, to clarify common structural features that would contribute to their function, the available crystal structures of the members of this family have been analyzed. Despite a very low sequence identity, the central features of the three‐dimensional structures of the proteins are surprisingly similar. The members of the protein family have a two‐domain structure consisting of a N‐terminal nucleotide‐binding domain and a C‐terminal α/β‐domain. The C‐terminal domain contributes to the substrate binding and catalysis, and contains a βα‐motif with a central α‐helix carrying common essential amino acid residues. The β‐sheet of the α/β‐domain contributes to the oligomerization in most of the proteins in the family.     

BuildBeta—A system for automatically constructing beta sheets

We describe a method that can thoroughly sample a protein conformational space given the protein primary sequence of amino acids and secondary structure predictions. Specifically, we target proteins with β‐sheets because they are particularly challenging for ab initio protein structure prediction because of the complexity of sampling long‐range strand pairings. Using some basic packing principles, inverse kinematics (IK), and β‐pairing scores, this method creates all possible β‐sheet arrangements including those that have the correct packing of β‐strands. It uses the IK algorithms of ProteinShop to move α‐helices and β‐strands as rigid bodies by rotating the dihedral angles in the coil regions. Our results show that our approach produces structures that are within 4–6 Å RMSD of the native one regardless of the protein size and β‐sheet topology although this number may increase if the protein has long loops or complex α‐helical regions. Proteins 2010. © Published 2009 Wiley‐Liss, Inc.     

Finding the needle in the haystack: towards solving the protein-folding problem computationally

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as “the protein folding problem,” has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.     

Measurements of protein sequence-structure correlations

Correlations between protein structures and amino acid sequences are widely used for protein structure prediction. For example, secondary structure predictors generally use correlations between a secondary structure sequence and corresponding primary structure sequence, whereas threading algorithms and similar tertiary structure predictors typically incorporate interresidue contact potentials. To investigate the relative importance of these sequence-structure interactions, we measured the mutual information among the primary structure, secondary structure and side-chain surface exposure, both for adjacent residues along the amino acid sequence and for tertiary structure contacts between residues distantly separated along the backbone. We found that local interactions along the amino acid chain are far more important than non-local contacts and that correlations between proximate amino acids are essentially uninformative. This suggests that knowledge-based contact potentials may be less important for structure predication than is generally believed.     

Crystal structure and nucleic acid‐binding activity of the CRISPR‐associated protein Csx1 of Pyrococcus furiosus

In many prokaryotic organisms, chromosomal loci known as clustered regularly interspaced short palindromic repeats (CRISPRs) and CRISPR‐associated (CAS) genes comprise an acquired immune defense system against invading phages and plasmids. Although many different Cas protein families have been identified, the exact biochemical functions of most of their constituents remain to be determined. In this study, we report the crystal structure of PF1127, a Cas protein of Pyrococcus furiosus DSM 3638 that is composed of 480 amino acids and belongs to the Csx1 family. The C‐terminal domain of PF1127 has a unique β‐hairpin structure that protrudes out of an α‐helix and contains several positively charged residues. We demonstrate that PF1127 binds double‐stranded DNA and RNA and that this activity requires an intact β‐hairpin and involve the homodimerization of the protein. In contrast, another Csx1 protein from Sulfolobus solfataricus P2 that is composed of 377 amino acids does not have the β‐hairpin structure and exhibits no DNA‐binding properties under the same experimental conditions. Notably, the C‐terminal domain of these two Csx1 proteins is greatly diversified, in contrast to the conserved N‐terminal domain, which appears to play a common role in the homodimerization of the protein. Thus, although P. furiosus Csx1 is identified as a nucleic acid‐binding protein, other Csx1 proteins are predicted to exhibit different individual biochemical activities. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Modelling and mutational evidence identify the substrate binding site and functional elements in APC amino acid transporters

The Amino acid-Polyamine-Organocation (APC) superfamily is the main family of amino acid transporters found in all domains of life and one of the largest families of secondary transporters. Here, using a sensitive homology threading approach and modelling we show that the predicted structure of APC members is extremely similar to the crystal structures of several prokaryotic transporters belonging to evolutionary distinct protein families with different substrate specificities. All of these proteins, despite having no primary amino acid sequence similarity, share a similar structural core, consisting of two V-shaped domains of five transmembrane domains each, intertwined in an antiparallel topology. Based on this model, we reviewed available data on functional mutations in bacterial, fungal and mammalian APCs and obtained novel mutational data, which provide compelling evidence that the amino acid binding pocket is located in the vicinity of the unwound part of two broken helices, in a nearly identical position to the structures of similar transporters. Our analysis is fully supported by the evolutionary conservation and specific amino acid substitutions in the proposed substrate binding domains. Furthermore, it allows predictions concerning residues that might be crucial in determining the specificity profile of APC members. Finally, we show that two cytoplasmic loops constitute important functional elements in APCs. Our work along with different kinetic and specificity profiles of APC members in easily manipulated bacterial and fungal model systems could form a unique framework for combining genetic, in-silico and structural studies, for understanding the function of one of the most important transporter families.     

Analyses of the general rule on residue pair frequencies in local amino acid sequences of soluble,ordered proteins

The amino acid sequences of soluble, ordered proteins with stable structures have evolved due to biological and physical requirements, thus distinguishing them from random sequences. Previous analyses have focused on extracting the features that frequently appear in protein substructures, such as α‐helix and β‐sheet, but the universal features of protein sequences have not been addressed. To clarify the differences between native protein sequences and random sequences, we analyzed 7368 soluble, ordered protein sequences, by inspecting the observed and expected occurrences of 400 amino acid pairs in local proximity, up to 10 residues along the sequence in comparison with their expected occurrence in random sequence. We found the trend that the hydrophobic residue pairs and the polar residue pairs are significantly decreased, whereas the pairs between a hydrophobic residue and a polar residue are increased. This trend was universally observed regardless of the secondary structure content but was not observed in protein sequences that include intrinsically disordered regions, indicating that it can be a general rule of protein foldability. The possible benefits of this rule are discussed from the viewpoints of protein aggregation and disorder, which are both caused by low‐complexity regions of hydrophobic or polar residues.