Mechanism of selective release of membrane proteins from human erythrocytes in the presence of liposomes

Incubation of erythrocytes with liposomes results in the release of shed vesicles rich in glycosyl-phosphatidylinositol (GPI)-anchored proteins but poor in transmembranous proteins. We investigated the mechanisms of membrane protein polarization by examining the effect of the interaction between spectrin and membrane proteins on the release of a transmembranous protein, band 3, and a GPI-anchored protein, acetylcholinesterase (AChE), from erythrocyte ghosts. Polymerization of spectrin resulted in a 30-fold decrease in the released amount of band 3 per constant amount of shed vesicles but did not affect the amount of released AChE per constant amount of shed vesicles. On the other hand, the amount of released band 3 per constant amount of shed vesicles increased by cleaving the cytoplasmic part of band 3. Our results first demonstrated that the diffusibility of membrane proteins determined by steric hindrance between membrane proteins and protein mesh primarily determines the ease of localization of membrane proteins into shed vesicles. Taken together with the recent biophysical studies, we built a "fence selection model" that retrograding spectrin mesh sweeps diffusing band 3 molecules from the tip of the membrane crenated area toward the entry of the crenated area, but not AChE molecules. Our study describes a novel method for isolation of a large number of vesicles containing special and intact membrane proteins from cells not by using detergents or organic solvents, but by utilizing the fence effect between the cytoskeleton and membrane proteins.     

The emergence of protein complexes: quaternary structure, dynamics and allostery. Colworth Medal Lecture

All proteins require physical interactions with other proteins in order to perform their functions. Most of them oligomerize into homomers, and a vast majority of these homomers interact with other proteins, at least part of the time, forming transient or obligate heteromers. In the present paper, we review the structural, biophysical and evolutionary aspects of these protein interactions. We discuss how protein function and stability benefit from oligomerization, as well as evolutionary pathways by which oligomers emerge, mostly from the perspective of homomers. Finally, we emphasize the specificities of heteromeric complexes and their structure and evolution. We also discuss two analytical approaches increasingly being used to study protein structures as well as their interactions. First, we review the use of the biological networks and graph theory for analysis of protein interactions and structure. Secondly, we discuss recent advances in techniques for detecting correlated mutations, with the emphasis on their role in identifying pathways of allosteric communication.     

A thermodynamic model of protein structure evolution explains empirical amino acid substitution matrices

Proteins evolve under a myriad of biophysical selection pressures that collectively control the patterns of amino acid substitutions. These evolutionary pressures are sufficiently consistent over time and across protein families to produce substitution patterns, summarized in global amino acid substitution matrices such as BLOSUM, JTT, WAG, and LG, which can be used to successfully detect homologs, infer phylogenies, and reconstruct ancestral sequences. Although the factors that govern the variation of amino acid substitution rates have received much attention, the influence of thermodynamic stability constraints remains unresolved. Here we develop a simple model to calculate amino acid substitution matrices from evolutionary dynamics controlled by a fitness function that reports on the thermodynamic effects of amino acid mutations in protein structures. This hybrid biophysical and evolutionary model accounts for nucleotide transition/transversion rate bias, multi‐nucleotide codon changes, the number of codons per amino acid, and thermodynamic protein stability. We find that our theoretical model accurately recapitulates the complex yet universal pattern observed in common global amino acid substitution matrices used in phylogenetics. These results suggest that selection for thermodynamically stable proteins, coupled with nucleotide mutation bias filtered by the structure of the genetic code, is the primary driver behind the global amino acid substitution patterns observed in proteins throughout the tree of life.     

Use of structural phylogenetic networks for classification of the ferritin-like superfamily

In the postgenomic era, bioinformatic analysis of sequence similarity is an immensely powerful tool to gain insight into evolution and protein function. Over long evolutionary distances, however, sequence-based methods fail as the similarities become too low for phylogenetic analysis. Macromolecular structure generally appears better conserved than sequence, but clear models for how structure evolves over time are lacking. The exponential growth of three-dimensional structural information may allow novel structure-based methods to drastically extend the evolutionary time scales amenable to phylogenetics and functional classification of proteins. To this end, we analyzed 80 structures from the functionally diverse ferritin-like superfamily. Using evolutionary networks, we demonstrate that structural comparisons can delineate and discover groups of proteins beyond the "twilight zone" where sequence similarity does not allow evolutionary analysis, suggesting that considerable and useful evolutionary signal is preserved in three-dimensional structures.     

Networks of coevolving sites in structural and functional domains of serpin proteins

Amino acids do not occur randomly in proteins; rather, their occurrence at any given site is strongly influenced by the amino acid composition at other sites, the structural and functional aspects of the region of the protein in which they occur, and the evolutionary history of the protein. The goal of our research study is to identify networks of coevolving sites within the serpin proteins (serine protease inhibitors) and classify them as being caused by structural-functional constraints or by evolutionary history. To address this, a matrix of pairwise normalized mutual information (NMI) values was computed among amino acid sites for the serpin proteins. The NMI matrix was partitioned into orthogonal patterns of amino acid variability by factor analysis. Each common factor pattern was interpreted as having phylogenetic and/or structural-functional explanations. In addition, we used a bootstrap factor analysis technique to limit the effects of phylogenetic history on our factor patterns. Our results show an extensive network of correlations among amino acid sites in key functional regions (reactive center loop, shutter, and breach). Additionally, we have discovered long-range coevolution for packed amino acids within the serpin protein core. Lastly, we have discovered a group of serpin sites which coevolve in the hydrophobic core region (s5B and s4B) and appear to represent sites important for formation of the "native" instead of the "latent" serpin structure. This research provides a better understanding on how protein structure evolves; in particular, it elucidates the selective forces creating coevolution among protein sites.     

Information and discrimination in pairwise contact potentials

We examine the information-theoretic characteristics of statistical potentials that describe pairwise long-range contacts between amino acid residues in proteins. In our work, we seek to map out an efficient information-based strategy to detect and optimally utilize the structural information latent in empirical data, to make contact potentials, and other statistically derived folding potentials, more effective tools in protein structure prediction. Foremost, we establish fundamental connections between basic information-theoretic quantities (including the ubiquitous Z-score) and contact "energies" or scores used routinely in protein structure prediction, and demonstrate that the informatic quantity that mediates fold discrimination is the total divergence. We find that pairwise contacts between residues bear a moderate amount of fold information, and if optimized, can assist in the discrimination of native conformations from large ensembles of native-like decoys. Using an extensive battery of threading tests, we demonstrate that parameters that affect the information content of contact potentials (e.g., choice of atoms to define residue location and the cut-off distance between pairs) have a significant influence in their performance in fold recognition. We conclude that potentials that have been optimized for mutual information and that have high number of score events per sequence-structure alignment are superior in identifying the correct fold. We derive the quantity "information product" that embodies these two critical factors. We demonstrate that the information product, which does not require explicit threading to compute, is as effective as the Z-score, which requires expensive decoy threading to evaluate. This new objective function may be able to speed up the multidimensional parameter search for better statistical potentials. Lastly, by demonstrating the functional equivalence of quasi-chemically approximated "energies" to fundamental informatic quantities, we make statistical potentials less dependent on theoretically tenuous biophysical formalisms and more amenable to direct bioinformatic optimization.     

Photosynthetic generation of oxygen

The oxygen in the atmosphere is derived from light-driven oxidation of water at a catalytic centre contained within a multi-subunit enzyme known as photosystem II (PSII). PSII is located in the photosynthetic membranes of plants, algae and cyanobacteria and its oxygen-evolving centre (OEC) consists of four manganese ions and a calcium ion surrounded by a highly conserved protein environment. Recently, the structure of PSII was elucidated by X-ray crystallography thus revealing details of the molecular architecture of the OEC. This structural information, coupled with an extensive knowledge base derived from a wide range of biophysical, biochemical and molecular biological studies, has provided a framework for understanding the chemistry of photosynthetic oxygen generation as well as opening up debate about its evolutionary origin.     

Analysis and prediction of functionally important sites in proteins

The rapidly increasing volume of sequence and structure information available for proteins poses the daunting task of determining their functional importance. Computational methods can prove to be very useful in understanding and characterizing the biochemical and evolutionary information contained in this wealth of data, particularly at functionally important sites. Therefore, we perform a detailed survey of compositional and evolutionary constraints at the molecular and biological function level for a large set of known functionally important sites extracted from a wide range of protein families. We compare the degree of conservation across different functional categories and provide detailed statistical insight to decipher the varying evolutionary constraints at functionally important sites. The compositional and evolutionary information at functionally important sites has been compiled into a library of functional templates. We developed a module that predicts functionally important columns (FIC) of an alignment based on the detection of a significant "template match score" to a library template. Our template match score measures an alignment column's similarity to a library template and combines a term explicitly representing a column's residue composition with various evolutionary conservation scores (information content and position-specific scoring matrix-derived statistics). Our benchmarking studies show good sensitivity/specificity for the prediction of functional sites and high accuracy in attributing correct molecular function type to the predicted sites. This prediction method is based on information derived from homologous sequences and no structural information is required. Therefore, this method could be extremely useful for large-scale functional annotation.     

Sequence coevolution between RNA and protein characterized by mutual information between residue triplets

Coevolving residues in a multiple sequence alignment provide evolutionary clues of biophysical interactions in 3D structure. Despite a rich literature describing amino acid coevolution within or between proteins and nucleic acid coevolution within RNA, to date there has been no direct evidence of coevolution between protein and RNA. The ribosome, a structurally conserved macromolecular machine composed of over 50 interacting protein and RNA chains, provides a natural example of RNA/protein interactions that likely coevolved. We provide the first direct evidence of RNA/protein coevolution by characterizing the mutual information in residue triplets from a multiple sequence alignment of ribosomal protein L22 and neighboring 23S RNA. We define residue triplets as three positions in the multiple sequence alignment, where one position is from the 23S RNA and two positions are from the L22 protein. We show that residue triplets with high mutual information are more likely than residue doublets to be proximal in 3D space. Some high mutual information residue triplets cluster in a connected series across the L22 protein structure, similar to patterns seen in protein coevolution. We also describe RNA nucleotides for which switching from one nucleotide to another (or between purines and pyrimidines) results in a change in amino acid distribution for proximal amino acid positions. Multiple crystal structures for evolutionarily distinct ribosome species can provide structural evidence for these differences. For one residue triplet, a pyrimidine in one species is a purine in another, and RNA/protein hydrogen bonds are present in one species but not the other. The results provide the first direct evidence of RNA/protein coevolution by using higher order mutual information, suggesting that biophysical constraints on interacting RNA and protein chains are indeed a driving force in their evolution.     

Models of the structure and voltage-gating mechanism of the shaker K+ channel

In the preceding, accompanying article, we present models of the structure and voltage-dependent gating mechanism of the KvAP bacterial K+ channel that are based on three types of evidence: crystal structures of portions of the KvAP protein, theoretical modeling criteria for membrane proteins, and biophysical studies of the properties of native and mutated voltage-gated channels. Most of the latter experiments were performed on the Shaker K+ channel. Some of these data are difficult to relate directly to models of the KvAP channel's structure due to differences in the Shaker and KvAP sequences. We have dealt with this problem by developing new models of the structure and gating mechanism of the transmembrane and extracellular portions of the Shaker channel. These models are consistent with almost all of the biophysical data. In contrast, much of the experimental data are incompatible with the "paddle" model of gating that was proposed when the KvAP crystal structures were first published. The general folding pattern and gating mechanisms of our current models are similar to some of our earlier models of the Shaker channel.     

Reconstruction of functional beta-propeller lectins via homo-oligomeric assembly of shorter fragments

The modular nature of protein folds suggests that present day proteins evolved via duplication and recombination of smaller functional elements. However, the reconstruction of these putative evolutionary pathways after many millions of years of evolutionary drift has thus far proven difficult, with all attempts to date failing to produce a functional protein. Tachylecin-2 is a monomeric 236 amino acid, five-bladed beta-propeller with five sugar-binding sites. This protein was isolated from a horseshoe crab that emerged ca 500 million years ago. The modular, yet ancient, nature of Tachylectin-2 makes it an excellent model for exploring the evolution of proteins from smaller subunits. To this end, we generated genetically diverse libraries by incremental truncation of the Tachylectin-2 gene and screened them for functional lectins. A number of approximately 100 amino acid residue segments were isolated with the ability to assemble into active homo-pentamers. The topology of most of these segments follows a "hidden" module that differs from the modules observed in wild-type Tachylectin-2, yet their biophysical properties and sugar binding activities resemble the wild-type's. Since the pentamer's molecular mass is twofold higher than the wild-type (approximately 500 amino acid residues), the structure of these oligomeric forms is likely to also differ. Our laboratory evolution experiments highlight the versatility and modularity of the beta-propeller fold, while substantiating the hypothesis that proteins with high internal symmetry, such as beta-propellers, evolved from short, functional gene segments that, at later stages, duplicated, fused, and rearranged, to yield the folds we recognise today.     

Alignment of Helical Membrane Protein Sequences Using AlignMe

Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set.     

The acetylcholinesterase homology region is essential for normal conformational maturation and secretion of thyroglobulin

Secretion of thyroglobulin (Tg, a large homodimeric glycoprotein) is essential to deliver Tg to its site of iodination for thyroxine biosynthesis. An L2263P missense mutation in Tg has been proposed as the molecular defect causing congenital goitrous hypothyroidism in cog/cog mice due to perturbed Tg homodimerization, resulting in its retention within the endoplasmic reticulum. The mutation falls within a carboxyl-terminal region of Tg with high structural similarity to the entirety of acetylcholinesterase (AChE), a secretory protein that also forms homodimers. We provide new evidence that authentic AChE and the cholinesterase-like domain of Tg share a common tertiary structure. Moreover, we find that a Tg truncation, deleted of the cholinesterase-like region (but not a comparably sized deletion of internal Tg regions), blocks Tg export. Appending to this truncation a cDNA encoding authentic AChE results in translation of a chimeric protein in which AChE is present in a native, enzymatically active (albeit latent) conformation, and this fully rescues Tg secretion. Introduction of the cog mutation inhibits AChE enzyme activity, and established denaturing mutations of AChE block secretion of the Tg. Additional studies show that the native structure of the AChE region functions as a "dimerization domain," facilitating intracellular transport of Tg to the site of thyroid hormonogenesis.     

Proportion of solvent-exposed amino acids in a protein and rate of protein evolution

Translational selection, including gene expression, protein abundance, and codon usage bias, has been suggested as the single dominant determinant of protein evolutionary rate in yeast. Here, we show that protein structure is also an important determinant. Buried residues, which are responsible for maintaining protein structure or are located on a stable interaction surface between 2 subunits, are usually under stronger evolutionary constraints than solvent-exposed residues. Our partial correlation analysis shows that, when whole proteins are included, the variance of evolutionary rate explained by the proportion of solvent-exposed residues (P(exposed)) can reach two-thirds of that explained by translational selection, indicating that P(exposed) is the most important determinant of protein evolutionary rate next only to translational selection. Our result suggests that proteins with many residues under selective constraint (e.g., maintaining structure or intermolecular interaction) tend to evolve slowly, supporting the "fitness (functional) density" hypothesis.     

Structural model of the HIV-1 Tat(46-58)-TAR complex

The trans-activator protein (Tat) of human immunodeficiency virus type 1 (HIV-1) binds to an uridine-rich bulge of an RNA target (TAR; trans-activation responsive element) predominantly via its basic sequence domain. The structure of the Tat(46-58)-TAR complex has been determined by a novel modeling approach relying on structural information about one crucial arginine residue and crosslink data. The strategy described here solely uses this experimental data without additional "modeling" assumptions about the structure of the complex in order to avoid human bias. Model building was performed in a fashion similar to structure calculations from nuclear magnetic resonance (NMR)-spectroscopic data using restrained molecular dynamics. The resulting set of structures of Tat(46-58) in its complex with TAR reveals that all models have converged to a common fold, showing a backbone root mean square deviation (RMSD) of 1.36A. Analysis of the calculated structures suggests that HIV-I Tat forms a hairpin loop in its complex with TAR that shares striking similarity to the hairpin formed by the structure of the bovine immunodeficiency virus Tat protein after TAR binding as determined by NMR studies. The outlined approach is not limited to the Tat-TAR complex modeling, but is also applicable to all molecular complexes with sufficient biochemical and biophysical data available.     

An inter‐species protein–protein interaction network across vast evolutionary distance

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical‐versus‐functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an “inter‐interactome” approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter‐interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra‐species networks. Although substantially reduced relative to intra‐species networks, the levels of functional overlap in the yeast–human inter‐interactome network uncover significant remnants of co‐functionality widely preserved in the two proteomes beyond human–yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co‐functionality. Such non‐functional interactions, however, represent a reservoir from which nascent functional interactions may arise.     

Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks

Background

Protein inter-residue contact maps provide a translation and rotation invariant topological representation of a protein. They can be used as an intermediary step in protein structure predictions. However, the prediction of contact maps represents an unbalanced problem as far fewer examples of contacts than non-contacts exist in a protein structure. In this study we explore the possibility of completely eliminating the unbalanced nature of the contact map prediction problem by predicting real-value distances between residues. Predicting full inter-residue distance maps and applying them in protein structure predictions has been relatively unexplored in the past.

Results

We initially demonstrate that the use of native-like distance maps is able to reproduce 3D structures almost identical to the targets, giving an average RMSD of 0.5Å. In addition, the corrupted physical maps with an introduced random error of ±6Å are able to reconstruct the targets within an average RMSD of 2Å. After demonstrating the reconstruction potential of distance maps, we develop two classes of predictors using two-dimensional recursive neural networks: an ab initio predictor that relies only on the protein sequence and evolutionary information, and a template-based predictor in which additional structural homology information is provided. We find that the ab initio predictor is able to reproduce distances with an RMSD of 6Å, regardless of the evolutionary content provided. Furthermore, we show that the template-based predictor exploits both sequence and structure information even in cases of dubious homology and outperforms the best template hit with a clear margin of up to 3.7Å. Lastly, we demonstrate the ability of the two predictors to reconstruct the CASP9 targets shorter than 200 residues producing the results similar to the state of the machine learning art approach implemented in the Distill server.

Conclusions

The methodology presented here, if complemented by more complex reconstruction protocols, can represent a possible path to improve machine learning algorithms for 3D protein structure prediction. Moreover, it can be used as an intermediary step in protein structure predictions either on its own or complemented by NMR restraints.     

Invertebrate acetylcholinesterases: Insights into their evolution and non-classical functions

Acetylcholinesterase (AChE) plays a pivotal role in synaptic transmission by hydrolyzing the neurotransmitter acetylcholine. In addition to the classical function of AChE in synaptic transmission, various non-classical functions have been elucidated. Unlike vertebrates possessing a single AChE gene (ace), invertebrates (nematodes, arachnids, and insects) have multiple ace loci, encoding diverse AChEs with a range of different functions. In the field of toxicology, AChE with synaptic function has long been exploited as the target of organophosphorus and cabarmate pesticides to control invertebrate pests for the past several decades. However, many aspects of the evolution and non-classical roles of invertebrate AChEs are still unclear. Although currently available information on invertebrate AChEs is fragmented, we reviewed the recent findings on their evolutionary status, molecular/biochemical properties, and deduced non-classical (non-neuronal) functions.