Evolution: a guide to perturb protein function and networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Lichtarge O
PROVIDER: S-EPMC2916956 | biostudies-literature | 2010 Jun
REPOSITORIES: biostudies-literature
Publications
Evolution: a guide to perturb protein function and networks.
Lichtarge Olivier O Wilkins Angela A
Current opinion in structural biology 20100503 3
Protein interactions give rise to networks that control cell fate in health and disease; selective means to probe these interactions are therefore of wide interest. We discuss here Evolutionary Tracing (ET), a comparative method to identify protein functional sites and to guide experiments that selectively block, recode, or mimic their amino acid determinants. These studies suggest, in principle, a scalable approach to perturb individual links in protein networks. ...[more]
Similar Datasets
Project description:A wide variety of phytochemicals are consumed for their perceived health benefits. Many of these phytochemicals have been found to alter numerous cell functions, but the mechanisms underlying their biological activity tend to be poorly understood. Phenolic phytochemicals are particularly promiscuous modifiers of membrane protein function, suggesting that some of their actions may be due to a common, membrane bilayer-mediated mechanism. To test whether bilayer perturbation may underlie this diversity of actions, we examined five bioactive phenols reported to have medicinal value: capsaicin from chili peppers, curcumin from turmeric, EGCG from green tea, genistein from soybeans, and resveratrol from grapes. We find that each of these widely consumed phytochemicals alters lipid bilayer properties and the function of diverse membrane proteins. Molecular dynamics simulations show that these phytochemicals modify bilayer properties by localizing to the bilayer/solution interface. Bilayer-modifying propensity was verified using a gramicidin-based assay, and indiscriminate modulation of membrane protein function was demonstrated using four proteins: membrane-anchored metalloproteases, mechanosensitive ion channels, and voltage-dependent potassium and sodium channels. Each protein exhibited similar responses to multiple phytochemicals, consistent with a common, bilayer-mediated mechanism. Our results suggest that many effects of amphiphilic phytochemicals are due to cell membrane perturbations, rather than specific protein binding.
| S-EPMC4136704 | biostudies-literature
Project description:The molecular mechanisms whereby small molecules that contaminate our environment cause physiological effects are largely unknown, in terms of both targets and mechanisms. The essential human enzyme porphobilinogen synthase (HsPBGS, a.k.a. 5-aminolevulinate dehydratase, ALAD) functions in heme biosynthesis. HsPBGS catalytic activity is regulated allosterically via an equilibrium of inactive hexamers and active octamers, and we have shown that certain drugs and drug-like small molecules can inhibit HsPBGS in vitro by stabilizing the hexamer. Here we address whether components of the National Toxicology Program library of environmental contaminants can stabilize the HsPBGS hexamer and inhibit activity in vitro. Native polyacrylamide gel electrophoresis was used to screen the library (1,408 compounds) for components that alter the oligomeric distribution of HsPBGS. Freshly purchased samples of 37 preliminary hits were used to confirm the electrophoretic results and to determine the dose-dependence of the perturbation of oligomeric distribution. Seventeen compounds were identified which alter the oligomeric distribution toward the hexamer and also inhibit HsPBGS catalytic activity, including the most potent HsPBGS inhibitor yet characterized (Mutagen X, IC50 = 1.4 μM). PBGS dysfunction is associated with the inborn error of metabolism know as ALAD porphyria and with lead poisoning. The identified hexamer-stabilizing inhibitors could potentiate these diseases. Allosteric regulation of activity via an equilibrium of alternate oligomers has been proposed for many proteins. Based on the precedent set herein, perturbation of these oligomeric equilibria by small molecules (such as environmental contaminants) can be considered as a mechanism of toxicity.
| S-EPMC4102012 | biostudies-literature
Project description:Expanded runs of consecutive trinucleotide CAG repeats encoding polyglutamine (polyQ) stretches are observed in the genes of a large number of patients with different genetic diseases such as Huntington's and several Ataxias. Protein aggregation, which is a key feature of most of these diseases, is thought to be triggered by these expanded polyQ sequences in disease-related proteins. However, polyQ tracts are a normal feature of many human proteins, suggesting that they have an important cellular function. To clarify the potential function of polyQ repeats in biological systems, we systematically analyzed available information stored in sequence and protein interaction databases. By integrating genomic, phylogenetic, protein interaction network and functional information, we obtained evidence that polyQ tracts in proteins stabilize protein interactions. This happens most likely through structural changes whereby the polyQ sequence extends a neighboring coiled-coil region to facilitate its interaction with a coiled-coil region in another protein. Alteration of this important biological function due to polyQ expansion results in gain of abnormal interactions, leading to pathological effects like protein aggregation. Our analyses suggest that research on polyQ proteins should shift focus from expanded polyQ proteins into the characterization of the influence of the wild-type polyQ on protein interactions.
| S-EPMC3378862 | biostudies-literature
Project description:Although the sequence of a protein largely determines its function, proteins can adopt different folding states in response to changes in the environment, some of which may be deleterious to the organism. All organisms--Bacteria, Archaea and Eukarya--have evolved a protein homeostasis, or proteostasis, network comprising chaperones and folding factors, degradation components, signalling pathways and specialized compartmentalized modules that manage protein folding in response to environmental stimuli and variation. Surveying the origins of proteostasis networks reveals that they have co-evolved with the proteome to regulate the physiological state of the cell, reflecting the unique stresses that different cells or organisms experience, and that they have a key role in driving evolution by closely managing the link between the phenotype and the genotype.
| S-EPMC3718298 | biostudies-literature
Project description:Developmental dynamics in Boolean models of gene networks self-organize, either into point attractors (stable repeating patterns of gene expression) or limit cycles (stable repeating sequences of patterns), depending on the network interactions specified by a genome of evolvable bits. Genome specifications for dynamics that can map specific gene expression patterns in early development onto specific point attractor patterns in later development are essentially impossible to discover by chance mutation alone, even for small networks. We show that selection for approximate mappings, dynamically maintained in the states comprising limit cycles, can accelerate evolution by at least an order of magnitude. These results suggest that self-organizing dynamics that occur within lifetimes can, in principle, guide natural selection across lifetimes.
| S-EPMC6856163 | biostudies-literature
Project description:Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI) networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE), which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.
| S-EPMC5382968 | biostudies-literature
Project description:Domains are the structural, functional and evolutionary units of proteins. They combine to form multidomain proteins. The evolutionary history of this molecular combinatorics has been studied with phylogenomic methods. Here, we construct networks of domain organization and explore their evolution. A time series of networks revealed two ancient waves of structural novelty arising from ancient 'p-loop' and 'winged helix' domains and a massive 'big bang' of domain organization. The evolutionary recruitment of domains was highly modular, hierarchical and ongoing. Domain rearrangements elicited non-random and scale-free network structure. Comparative analyses of preferential attachment, randomness and modularity showed yin-and-yang complementary transition and biphasic patterns along the structural chronology. Remarkably, the evolving networks highlighted a central evolutionary role of cofactor-supporting structures of non-ribosomal peptide synthesis pathways, likely crucial to the early development of the genetic code. Some highly modular domains featured dual response regulation in two-component signal transduction systems with DNA-binding activity linked to transcriptional regulation of responses to environmental change. Interestingly, hub domains across the evolving networks shared the historical role of DNA binding and editing, an ancient protein function in molecular evolution. Our investigation unfolds historical source-sink patterns of evolutionary recruitment that further our understanding of protein architectures and functions.
| S-EPMC8187734 | biostudies-literature
Project description:We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.
| S-EPMC3387198 | biostudies-literature
Project description:Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species.To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms.
| S-EPMC4426845 | biostudies-other
Project description:High throughput techniques produce multiple functional association networks. Integrating these networks can enhance the accuracy of protein function prediction. Many algorithms have been introduced to generate a composite network, which is obtained as a weighted sum of individual networks. The weight assigned to an individual network reflects its benefit towards the protein functional annotation inference. A classifier is then trained on the composite network for predicting protein functions. However, since these techniques model the optimization of the composite network and the prediction tasks as separate objectives, the resulting composite network is not necessarily optimal for the follow-up protein function prediction.We address this issue by modeling the optimization of the composite network and the prediction problems within a unified objective function. In particular, we use a kernel target alignment technique and the loss function of a network based classifier to jointly adjust the weights assigned to the individual networks. We show that the proposed method, called MNet, can achieve a performance that is superior (with respect to different evaluation criteria) to related techniques using the multiple networks of four example species (yeast, human, mouse, and fly) annotated with thousands (or hundreds) of GO terms.MNet can effectively integrate multiple networks for protein function prediction and is robust to the input parameters. Supplementary data is available at https://sites.google.com/site/guoxian85/home/mnet. The Matlab code of MNet is available upon request.
| S-EPMC4331678 | biostudies-literature