Analysis and prediction of inter-strand packing distances between beta-sheets of globular proteins

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.

Comparative Protein Structure Modeling Using MODELLER

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc.

The centriolar protein CPAP G-box: an amyloid fibril in a single domain

Centrioles are evolutionarily conserved cylindrical cell organelles with characteristic radial symmetry. Despite their considerable size (400 nm × 200 nm, in humans), genetic studies suggest that relatively few protein components are involved in their assembly. We recently characterized the molecular architecture of the centrosomal P4.1-associated protein (CPAP), which is crucial for controlling the centriolar cylinder length. Here, we review the remarkable architecture of the C-terminal domain of CPAP, termed the G-box, which comprises a single, entirely solvent exposed, antiparallel β-sheet. Molecular dynamics simulations support the stability of the G-box domain even in the face of truncations or amino acid substitutions. The similarity of the G-box domain to amyloids (or amyloid precursors) is strengthened by its oligomeric arrangement to form continuous fibrils. G-box fibrils were observed in crystals as well as in solution and are also supported by simulations. We conclude that the G-box domain may well represent the best analogue currently available for studies of exposed β-sheets, unencumbered by additional structural elements or severe aggregations problems.

Comparative Protein Structure Modeling Using MODELLER

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc.

CYP1B1-mediated Pathobiology of Primary Congenital Glaucoma

CYP1B1 is a dioxin-inducible enzyme belonging to the cytochrome P450 superfamily. It has been observed to be important in a variety of developmental processes including in utero development of ocular structures. Owing to its role in the developmental biology of eye, its dysfunction can lead to ocular developmental defects. This has been found to be true and CYP1B1 mutations have been observed in a majority of primary congenital glaucoma (PCG) patients from all over the globe. Primary congenital glaucoma is an irreversibly blinding childhood disorder (onset at birth or early infancy) typified by anomalous development of trabecular meshwork (TM). How CYP1B1 causes PCG is not known; however, some basic investigations have been reported. Understanding the CYP1B1 mediated etiopathomechanism of PCG is very important to identify targets for therapy and preventive management. In this perspective, we will make an effort to reconstruct the pathomechanism of PCG in the light of already reported information about the disease and the CYP1B1 gene.

How to cite this article: Faiq MA, Dada R, Qadri R, Dada T. CYP1 B1-mediated Pathobiology of Primary Congenital Glaucoma. J Curr Glaucoma Pract 2015;9(3):77-80.

Comparative Protein Structure Modeling Using MODELLER

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

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.

Protein structure modeling in the proteomics era

Structural proteomics aims to understand the structural basis of protein interactions and functions. A prerequisite for this is the availability of 3D protein structures that mediate the biochemical interactions. The explosion in the number of available gene sequences set the stage for the next step in genome-scale projects -- to obtain 3D structures for each protein. To achieve this ambitious goal, the slow and costly structure determination experiments are supplemented with theoretical approaches. The current state and recent advances in structure modeling approaches are reviewed here, with special emphasis on comparative protein structure modeling techniques.

Comparative Modeling of Drug Target Proteins☆

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state-of-the-art by a number of specific examples.

Study on β-sheet packing, stabilized by aromatic interactions in a tri-peptide crystal

The role of unconventional aromatic interactions in the β-sheet packing, inside the crystal, has been highlighted. Crystal structure of terminally blocked tri-peptide, Z-L-Ala-L-Ala-L-Leu-pNA has been determined. There are four different conformers of tri-peptide inside the unit-cell, in space group P1. All the four independent molecules are described by semi-extended backbone conformations which form an anti-parallel β-sheet. The inter β-sheet packing is predominantly stabilized by C—H…π and π…π interactions. In π…π interactions, the center-to-center distance between aromatic rings varies from 3.8 Å to 4.6 Å while the closest distance of approach ranges from 3.4 Å to 3.8 Å. The associations of aromatic-aromatic rings are described by either face-to-face or inclined arrangements.

Comparative protein structure modeling using MODELLER

Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Comparative protein structure modeling using Modeller

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Comparative Modeling of Drug Target Proteins

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state of the art by a number of specific examples.

Disease-causing mutations in proteins: structural analysis of the CYP1B1 mutations causing primary congenital glaucoma in humans

In this communication, we report an in-depth structure-based analysis of the human CYP1b1 protein carrying disease-causing mutations that are discovered in patients suffering from primary congenital glaucoma (PCG). The "wild-type" and the PCG mutant structures of the human CYP1b1 protein obtained from comparative modeling were subjected to long molecular dynamics simulations with an intention of studying the possible impact of these mutations on the protein structure and hence its function. Analysis of time evolution as well as time averaged values of various structural properties--especially of those of the functionally important regions: the heme binding region, substrate binding region, and substrate access channel--gave some insights into the possible structural characteristics of the disease mutant and the wild-type forms of the protein. In a nutshell, compared to the wild-type the core regions in the mutant structures are associated with subtle but significant changes, and the functionally important regions seem to adopt such structures that are not conducive for the wild-type-like functionality.

The role of Phe in the formation of well-ordered oligomers of amyloidogenic hexapeptide (NFGAIL) observed in molecular dynamics simulations with explicit solvent

We observed fast aggregation of partially ordered oligomers in an earlier simulation study of an amyloidogenic hexapeptide NFGAIL. In this work, the nucleation of highly ordered oligomers was further investigated by a combined total of 960 ns molecular dynamics simulations with explicit solvent on NFGAIL and its nonamyloidogenic mutant NAGAIL. In these simulations, four dimer subunits that each was constrained by harmonic forces as a two-strand beta-sheet were used to enhance the rate of formation. It was found that a critical role played by the aromatic residue Phe was to direct the stacking of beta-sheets to form ordered multilayer aggregates. We also found that many molecular arrangements of the peptide satisfied the "cross-beta-structure", a hallmark of amyloid fibrils. The tendency for the peptide to form either parallel or antiparallel beta-sheet was comparable, as was the tendency for the beta-sheets to stack either in parallel or antiparallel orientation. Overall, approximately 85% of the native hexapeptide formed octamers. The fact that only 8% of the octamers were well-ordered species suggests that the dissociation of the disordered oligomers be the rate-limiting step in the formation of highly ordered oligomers. Among the well-ordered subunit pairs, about half was formed by the beta-sheet extension along the main-chain hydrogen-bond direction, whereas the other half was formed by the beta-sheet stacking. Hence, a delicate balance between intersheet and intrasheet interactions appeared to be crucial in the formation of a highly ordered nucleus of amyloid fibrils. The disordered oligomers were mainly stabilized by nonspecific hydrophobic interactions, whereas the well-ordered oligomers were further stabilized by cross-strand hydrogen bonds and favorable side-chain stacking.

The role of geometric complementarity in secondary structure packing: a systematic docking study

A strong similarity between the major aspects of protein folding and protein recognition is one of the emerging fundamental principles in protein science. A crucial importance of steric complementarity in protein recognition is a well-established fact. The goal of this study was to assess the importance of the steric complementarity in protein folding, namely, in the packing of the secondary structure elements. Although the tight packing of protein structures, in general, is a well-known fact, a systematic study of the role of geometric complementarity in the packing of secondary structure elements has been lacking. To assess the role of the steric complementarity, we used a docking procedure to recreate the crystallographically determined packing of secondary structure elements in known protein structures by using the geometric match only. The docking results revealed a significant percentage of correctly predicted packing configurations. Different types of pairs of secondary structure elements showed different degrees of steric complementarity (from high to low: beta-beta, loop-loop, alpha-alpha, and alpha-beta). Interestingly, the relative contribution of the steric match in different types of pairs was correlated with the number of such pairs in known protein structures. This effect may indicate an evolutionary pressure to select tightly packed elements of secondary structure to maximize the packing of the entire structure. The overall conclusion is that the steric match plays an essential role in the packing of secondary structure elements. The results are important for better understanding of principles of protein structure and may facilitate development of better methods for protein structure prediction.

Contributions of residue pairing to beta-sheet formation: conservation and covariation of amino acid residue pairs on antiparallel beta-strands

In an effort to better understand beta-sheet assembly, we have investigated the evolutionary behavior of neighboring residues on adjacent antiparallel beta-strands. Residue pairs were classified according to solvent exposure as well as by whether their backbone NH and C==O groups are hydrogen bonded. The conservation and covariation of 19,241 pairs in 219 sequence alignments was analyzed. Buried pairs were found to be the most conserved, while stronger covariation was detected in the solvent-exposed pairs. However, residues on neighboring strands showed a degree of conservation and covariation similar to that of well-separated residues on the same strand, suggesting that evolutionary pressure to maintain complementarity between pairs on neighboring strands is weak. Moreover, in spite of the preference of certain amino acid pairs to occupy neighboring positions on adjacent strands, such favored pairs are neither more strongly mutually conserved nor covary more strongly than pairs of the same type in non-interacting positions. Although the beta-sheet pairs did not show outstanding evolutionary coupling, in many protein families significant conservation and covariation patterns were detected for some of the residue pairs. Overall, the weak evolutionary conservation and covariation of the beta-sheet pairs indicates that sheet structure is unlikely to be dictated by specific side-chain interactions.

Conserved key amino acid positions (CKAAPs) derived from the analysis of common substructures in proteins

An all-against-all protein structure comparison using the Combinatorial Extension (CE) algorithm applied to a representative set of PDB structures revealed a gallery of common substructures in proteins (http://cl.sdsc.edu/ce.html). These substructures represent commonly identified folds, domains, or components thereof. Most of the subsequences forming these similar substructures have no significant sequence similarity. We present a method to identify conserved amino acid positions and residue-dependent property clusters within these subsequences starting with structure alignments. Each of the subsequences is aligned to its homologues in SWALL, a nonredundant protein sequence database. The most similar sequences are purged into a common frequency matrix, and weighted homologues of each one of the subsequences are used in scoring for conserved key amino acid positions (CKAAPs). We have set the top 20% of the high-scoring positions in each substructure to be CKAAPs. It is hypothesized that CKAAPs may be responsible for the common folding patterns in either a local or global view of the protein-folding pathway. Where a significant number of structures exist, CKAAPs have also been identified in structure alignments of complete polypeptide chains from the same protein family or superfamily. Evidence to support the presence of CKAAPs comes from other computational approaches and experimental studies of mutation and protein-folding experiments, notably the Paracelsus challenge. Finally, the structural environment of CKAAPs versus non-CKAAPs is examined for solvent accessibility, hydrogen bonding, and secondary structure. The identification of CKAAPs has important implications for protein engineering, fold recognition, modeling, and structure prediction studies and is dependent on the availability of structures and an accurate structure alignment methodology. Proteins 2001;42:148-163.