Topology is the principal determinant in the folding of a complex all-alpha Greek key death domain from human FADD

Prediction of interactions between cell surface proteins by machine learning

Cells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and, thus, challenging to detect using traditional experimental techniques. Here, we tackle this challenge using a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in the immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells or between proteins on the same cell surface. In practice, we collected all structural data on Ig domain interactions and transformed them into an interface fragment pair library. A high-dimensional profile can then be constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile so that the probability of interaction between the query proteins could be predicted. We tested our models on an experimentally derived dataset that contains 564 cell surface proteins in humans. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in Caenorhabditis elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literature. In conclusion, our computational platform serves as a useful tool to help identify potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study the interactions of proteins in other domain superfamilies.

Prediction of Interactions between Cell Surface Proteins by Machine Learning

Cells detect changes of external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and thus challenging to detect using traditional experimental techniques. Here we tackle this challenge by a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells, or between proteins on the same cell surface. In practice, we collected all structural data of Ig domain interactions and transformed them into an interface fragment pair library. A high dimensional profile can be then constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile, so that the probability of interaction between the query proteins can be predicted. We tested our models to an experimentally derived dataset which contains 564 cell surface proteins in human. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in C elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literatures. In conclusion, our computational platform serves a useful tool to help identifying potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study interactions of proteins in other domain superfamilies.

Slowest-first protein translation scheme: Structural asymmetry and co-translational folding

Proteins are translated from the N to the C terminus, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the Protein Data Bank (PDB). We find remarkable enrichment of α helices at the C terminus and β strands at the N terminus. Furthermore, this α-β asymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the "slowest-first" scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest of the cooperatively folding segments are positioned near the N terminus so they have more time to fold during translation. A phenomenological model predicts that CTF can be accelerated by asymmetry in folding rate, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB predicts that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in secondary structure asymmetry.

Insights into the structure and RNA-binding specificity of Caenorhabditis elegans Dicer-related helicase 3 (DRH-3)

DRH-3 is critically involved in germline development and RNA interference (RNAi) facilitated chromosome segregation via the 22G-siRNA pathway in Caenorhabditis elegans. DRH-3 has similar domain architecture to RIG-I-like receptors (RLRs) and belongs to the RIG-I-like RNA helicase family. The molecular understanding of DRH-3 and its function in endogenous RNAi pathways remains elusive. In this study, we solved the crystal structures of the DRH-3 N-terminal domain (NTD) and the C-terminal domains (CTDs) in complex with 5'-triphosphorylated RNAs. The NTD of DRH-3 adopts a distinct fold of tandem caspase activation and recruitment domains (CARDs) structurally similar to the CARDs of RIG-I and MDA5, suggesting a signaling function in the endogenous RNAi biogenesis. The CTD preferentially recognizes 5'-triphosphorylated double-stranded RNAs bearing the typical features of secondary siRNA transcripts. The full-length DRH-3 displays unique structural dynamics upon binding to RNA duplexes that differ from RIG-I or MDA5. These features of DRH-3 showcase the evolutionary divergence of the Dicer and RLR family of helicases.

Network Connectivity, Centrality and Fragmentation in the Greek-Key Protein Topology

Understanding and computationally predicting the protein folding process remains one of the most challenging scientific problems and has uniquely garnered the interdisciplinary efforts of researchers from both the biological, chemical, physical and computational disciplines. Previous studies have demonstrated the importance of long-range interactions in guiding the native structure. However, predicting how the native long-range interaction network forms to generate a specific topology from among all other conformations remains unresolved. The present research study conducts an exploratory study to identify amino acids and long-range interactions that have the potential to play a key role in building and maintaining the protein topology. Towards this end, the application of network science is utilized and developed to analyze the structures of a group of proteins that share a common Greek-key topology but differ in sequence, secondary structure and function. We investigate the idea that the residues with high betweeness centrality score are potentially significant in maintaining the protein network and in governing the Greek-key topology. This hypothesis is tested by two different computational methods: through a fragmentation test and by the analysis of diameter impacts. In summary, we find a subset of selected residues in similar geographical positions in all model proteins, which demonstrates the role of these specific residues and regions in governing the Greek-key topology from a network perspective.

Prediction of the initial folding sites and the entire folding processes for Ig-like beta-sandwich proteins

Describing the whole story of protein folding is currently the main enigmatic problem in molecular bioinformatics study. Protein folding mechanisms have been intensively investigated with experimental as well as simulation techniques. Since a protein folds into its specific 3D structure from a unique amino acid sequence, it is interesting to extract as much information as possible from the amino acid sequence of a protein. Analyses based on inter-residue average distance statistics and a coarse-grained Gō-model simulation were conducted on Ig and FN3 domains of a titin protein to decode the folding mechanisms from their sequence data and native structure data, respectively. The central region of all domains was predicted to be an initial folding unit, that is, stable in an early state of folding. This common feature coincides well with the experimental results and underscores the significance of the β-sandwich proteins' common structure, namely, the key strands for folding and the Greek-key motif, which is located in the central region. We confirmed that our sequence-based techniques were able to predict the initial folding event just next to the denatured state and that a 3D-based Gō-model simulation can be used to investigate the whole process of protein folding.

Death domain of p75 neurotrophin receptor: a structural perspective on an intracellular signalling hub

The death domain (DD) is a globular protein motif with a signature feature of an all-helical Greek-key motif. It is a primary mediator of a variety of biological activities, including apoptosis, cell survival and cytoskeletal changes, which are related to many neurodegenerative diseases, neurotrauma, and cancers. DDs exist in a wide range of signalling proteins including p75 neurotrophin receptor (p75^NTR ), a member of the tumour necrosis factor receptor superfamily. The specific signalling mediated by p75^NTR in a given cell depends on the type of ligand engaging the extracellular domain and the recruitment of cytosolic interactors to the intracellular domain, especially the DD, of the receptor. In solution, the p75^NTR -DDs mainly form a symmetric non-covalent homodimer. In response to extracellular signals, conformational changes in the p75^NTR extracellular domain (ECD) propagate to the p75^NTR -DD through the disulfide-bonded transmembrane domain (TMD) and destabilize the p75^NTR -DD homodimer, leading to protomer separation and exposure of binding sites on the DD surface. In this review, we focus on recent advances in the study of the structural mechanism of p75^NTR -DD signalling through recruitment of diverse intracellular interactors for the regulation and control of diverse functional outputs.

Prediction of folding mechanisms for Ig-like beta sandwich proteins based on inter-residue average distance statistics methods

To understand the folding mechanism of a protein is one of the goals in bioinformatics study. Nowadays, it is enigmatic and difficult to extract folding information from amino acid sequence using standard bioinformatics techniques or even experimental protocols which can be time consuming. To overcome these problems, we aim to extract the initial folding unit for titin protein (Ig and fnIII domains) by means of inter-residue average distance statistics, Average Distance Map (ADM) and contact frequency analysis (F-value). TI I27 and TNfn3 domains are used to represent the Ig-domain and fnIII-domain, respectively. Beta-strands 2, 3, 5, and 6 are significant for the initial folding processes of TI I27. The central strands of TNfn3 were predicted as a primary folding segment. Known 3D structure and unknown 3D structure domains were investigated by structure or non-structure based multiple sequence alignment, respectively, to learn the conserved hydrophobic residues and predicted compact region relevant to evolution. Our results show good correspondence to experimental data, phi-value and protection factor from H-D exchange experiments. The significance of conserved hydrophobic residues near F-value peaks for structural stability using hydrophobic packing is confirmed. Our prediction methods once again could extract a folding mechanism only knowing the amino acid sequence.

1H, 15N and 13C chemical shift assignments of the C-terminal domain of TRADD

The tumor necrosis factor receptor-associated death domain protein, TRADD, is a multifunctional intracellular molecule participating in divergent signaling pathways, such as NF-κB and apoptosis. TRADD consists of two structurally distinct domains. Its N-terminal domain displays an α-β plaits fold while its C-terminal domain belongs to the death domain (DD) superfamily. TRADD DD is a central component in the tumor necrosis factor receptor 1 signaling. It interacts with other DD-containing proteins through homotypic interactions. TRADD DD is also involved in p75^NTR-mediated signalling in MCF-7 human breast cancer cells. Here we report backbone and sidechain ¹H, ¹³C and ¹⁵N chemical shift assignments of TRADD DD in pure water as a basis for further structural and functional studies.

Structure of the C-terminal domain of TRADD reveals a novel fold in the death domain superfamily

The TNFR1-associated death domain protein (TRADD) is an intracellular adaptor protein involved in various signaling pathways, such as antiapoptosis. Its C-terminal death domain (DD) is responsible for binding other DD-containing proteins including the p75 neurotrophin receptor (p75^NTR). Here we present a solution structure of TRADD DD derived from high-resolution NMR spectroscopy. The TRADD DD comprises two super-secondary structures, an all-helix Greek key motif and a β-hairpin motif flanked by two α helices, which make it unique among all known DD structures. The β-hairpin motif is essential for TRADD DD to fold into a functional globular domain. The highly-charged surface suggests a critical role of electrostatic interactions in TRADD DD-mediated signaling. This novel structure represents a new class within the DD superfamily and provides a structural basis for studying homotypic DD interactions. NMR titration revealed a direct weak interaction between TRADD DD and p75^NTR DD monomers. A binding site next to the p75^NTR DD homodimerization interface indicates that TRADD DD recruitment to p75^NTR requires separation of the p75^NTR DD homodimer, explaining the mechanism of NGF-dependent activation of p75^NTR-TRADD-mediated antiapoptotic pathway in breast cancer cell.

Structural insights of homotypic interaction domains in the ligand-receptor signal transduction of tumor necrosis factor (TNF)

Several members of tumor necrosis factor receptor (TNFR) superfamily that these members activate caspase-8 from death-inducing signaling complex (DISC) in TNF ligand-receptor signal transduction have been identified. In the extrinsic pathway, apoptotic signal transduction is induced in death domain (DD) superfamily; it consists of a hexahelical bundle that contains 80 amino acids. The DD superfamily includes about 100 members that belong to four subfamilies: death domain (DD), caspase recruitment domain (CARD), pyrin domain (PYD), and death effector domain (DED). This superfamily contains key building blocks: with these blocks, multimeric complexes are formed through homotypic interactions. Furthermore, each DD-binding event occurs exclusively. The DD superfamily regulates the balance between death and survival of cells. In this study, the structures, functions, and unique features of DD superfamily members are compared with their complexes. By elucidating structural insights of DD superfamily members, we investigate the interaction mechanisms of DD domains; these domains are involved in TNF ligand-receptor signaling. These DD superfamily members play a pivotal role in the development of more specific treatments of cancer. [BMB Reports 2016; 49(3): 159-166]

Structure and function of legumain in health and disease

The last years have seen a steady increase in our understanding of legumain biology that is driven from two largely uncoupled research arenas, the mammalian and the plant legumain field. Research on legumain, which is also referred to as asparaginyl endopeptidase (AEP) or vacuolar processing enzyme (VPE), is slivered, however. Here we summarise recent important findings and put them into a common perspective. Legumain is usually associated with its cysteine endopeptidase activity in lysosomes where it contributes to antigen processing for class II MHC presentation. However, newly recognized functions disperse previously assumed boundaries with respect to their cellular compartmentalisation and enzymatic activities. Legumain is also found extracellularly and even translocates to the cytosol and the nucleus, with seemingly incompatible pH and redox potential. These different milieus translate into changes of legumain's molecular properties, including its (auto-)activation, conformational stability and enzymatic functions. Contrasting its endopeptidase activity, legumain can develop a carboxypeptidase activity which remains stable at neutral pH. Moreover, legumain features a peptide ligase activity, with intriguing mechanistic peculiarities in plant and human isoforms. In pathological settings, such as cancer or Alzheimer's disease, the proper association of legumain activities with the corresponding cellular compartments is breached. Legumain's increasingly recognized physiological and pathological roles also indicate future research opportunities in this vibrant field.

The response of Greek key proteins to changes in connectivity depends on the nature of their secondary structure

What governs the balance between connectivity and topology in regulating the mechanism of protein folding? We use circular permutation to vary the order of the helices in the all-α Greek key protein FADD (Fas-associated death domain) to investigate this question. Unlike all-β Greek key proteins, where changes in the order of secondary structure cause a shift in the folding nucleus, the position of the nucleus in FADD is unchanged, even when permutation reduces the complexity significantly. We suggest that this is because local helical contacts are so dominant that permutation has little effect on the entropic cost of forming the folding nucleus whereas, in all-β Greek key proteins, all interactions in the nucleus are long range. Thus, the type of secondary structure modulates the sensitivity of proteins to changes in connectivity.

Structures of the NLRP14 pyrin domain reveal a conformational switch mechanism regulating its molecular interactions

The cytosolic tripartite NLR receptors serve as important signalling platforms in innate immunity. While the C-terminal domains act as sensor and activation modules, the N-terminal death-like domain, e.g. the CARD or pyrin domain, is thought to recruit downstream effector molecules by homotypic interactions. Such homotypic complexes have been determined for all members of the death-domain superfamily except for pyrin domains. Here, crystal structures of human NLRP14 pyrin-domain variants are reported. The wild-type protein as well as the clinical D86V mutant reveal an unexpected rearrangement of the C-terminal helix α6, resulting in an extended α5/6 stem-helix. This reordering mediates a novel symmetric pyrin-domain dimerization mode. The conformational switching is controlled by a charge-relay system with a drastic impact on protein stability. How the identified charge relay allows classification of NLRP receptors with respect to distinct recruitment mechanisms is discussed.

The loop hypothesis: contribution of early formed specific non-local interactions to the determination of protein folding pathways

The extremely fast and efficient folding transition (in seconds) of globular proteins led to the search for some unifying principles embedded in the physics of the folding polypeptides. Most of the proposed mechanisms highlight the role of local interactions that stabilize secondary structure elements or a folding nucleus as the starting point of the folding pathways, i.e., a "bottom-up" mechanism. Non-local interactions were assumed either to stabilize the nucleus or lead to the later steps of coalescence of the secondary structure elements. An alternative mechanism was proposed, an "up-down" mechanism in which it was assumed that folding starts with the formation of very few non-local interactions which form closed long loops at the initiation of folding. The possible biological advantage of this mechanism, the "loop hypothesis", is that the hydrophobic collapse is associated with ordered compactization which reduces the chance for degradation and misfolding. In the present review the experiments, simulations and theoretical consideration that either directly or indirectly support this mechanism are summarized. It is argued that experiments monitoring the time-dependent development of the formation of specifically targeted early-formed sub-domain structural elements, either long loops or secondary structure elements, are necessary. This can be achieved by the time-resolved FRET-based "double kinetics" method in combination with mutational studies. Yet, attempts to improve the time resolution of the folding initiation should be extended down to the sub-microsecond time regime in order to design experiments that would resolve the classes of proteins which first fold by local or non-local interactions.

Molecular basis of NF-κB signaling

NF-κB (nuclear factor kappa B) family transcription factors are master regulators of immune and inflammatory processes in response to both injury and infection. In the latent state, NF-κBs are sequestered in the cytosol by their inhibitor IκB (inhibitor of NF-κB) proteins. Upon stimulations of innate immune receptors such as Toll-like receptors and cytokine receptors such as those in the TNF (tumor necrosis factor) receptor superfamily, a series of membrane proximal events lead to the activation of the IKK (IκB kinase). Phosphorylation of IκBs results in their proteasomal degradation and the release of NF-κB for nuclear translocation and activation of gene transcription. Here, we review the plethora of structural studies in these NF-κB activation pathways, including the TRAF (TNF receptor-associated factor) proteins, IKK, NF-κB, ubiquitin ligases, and deubiquitinating enzymes. Although these structures only provide snapshots of isolated processes, an emerging picture is that these signaling cascades coalesce into large oligomeric signaling complexes, or signalosomes, for signal propagation.

Take home lessons from studies of related proteins

The 'Fold Approach' involves a detailed analysis of the folding of several topologically, structurally and/or evolutionarily related proteins. Such studies can reveal determinants of the folding mechanism beyond the gross topology, and can dissect the residues required for folding from those required for stability or function. While this approach has not yet matured to the point where we can predict the native conformation of any polypeptide chain in silico, it has been able to highlight, amongst others, the specific residues that are responsible for nucleation, pathway malleability, kinetic intermediates, chain knotting, internal friction and Paracelsus switches. Some of the most interesting discoveries have resulted from the attempt to explain differences between homologues.

Helical assembly in the death domain (DD) superfamily

Death domain (DD) superfamily members play a central role in apoptotic and inflammatory signaling through formation of oligomeric molecular scaffolds. These scaffolds promote the activation of proinflammatory and apoptotic initiator caspases, as well as Ser/Thr kinases. Interactions between DDs are facilitated by a conserved set of interaction surfaces, type I, type II, and type III. Recently structural information on a ternary complex containing the DDs of MyD88, IRAK4, and IRAK2 and a binary complex containing Fas and FADD DDs has become available. This review will focus on how the three DD interaction surfaces cooperate to facilitate the assembly of these oligomeric signaling complexes.

Folding of an all-helical Greek-key protein monitored by quenched-flow hydrogen-deuterium exchange and NMR spectroscopy

To advance our understanding of the protein folding process, we use stopped-flow far-ultraviolet (far-UV) circular dichroism and quenched-flow hydrogen-deuterium exchange coupled with nuclear magnetic resonance (NMR) spectroscopy to monitor the formation of hydrogen-bonded secondary structure in the C-terminal domain of the Fas-associated death domain (Fadd-DD). The death domain superfamily fold consists of six α-helices arranged in a Greek-key topology, which is shared by the all-β-sheet immunoglobulin and mixed α/β-plait superfamilies. Fadd-DD is selected as our model death domain protein system because the structure of this protein has been solved by NMR spectroscopy, and both thermodynamic and kinetic analysis indicate it to be a stable, monomeric protein with a rapidly formed hydrophobic core. Stopped-flow far-UV circular dichroism spectroscopy revealed that the folding process was monophasic and the rate is 23.4 s(-1). Twenty-two amide hydrogens in the backbone of the helices and two in the backbone of the loops were monitored, and the folding of all six helices was determined to be monophasic with rate constants between 19 and 22 s(-1). These results indicate that the formation of secondary structure is largely cooperative and concomitant with the hydrophobic collapse. This study also provides unprecedented insight into the formation of secondary structure within the highly populated Greek-key fold more generally. Additional insights are gained by calculating the exchange rates of 23 residues from equilibrium hydrogen-deuterium exchange experiments. The majority of protected amide protons are found on helices 2, 4, and 5, which make up core structural elements of the Greek-key topology.

The death-fold superfamily of homotypic interaction motifs

The death-fold superfamily encompasses four structurally homologous subfamilies that engage in homotypic, subfamily-restricted interactions. The Death Domains (DDs), the Death Effector Domains (DEDs), the CAspase Recruitment Domains (CARDs) and the PYrin Domains (PYDs) constitute key building blocks involved in the assembly of multimeric complexes implicated in signaling cascades leading to inflammation and cell death. We review the molecular basis of these homotypic domain-domain interactions in light of their structure, function and evolution. In addition, we elaborate on three distinct types of asymmetric interactions that were recently identified from the crystal structures of three multimeric, death-fold complexes: the MyDDosome, the PIDDosome and the Fas/FADD-DISC. Insights into the mechanisms of interaction of death-fold domains will be useful to design strategies for specific modulation of complex formation and might lead to novel therapeutic applications.

Computational model for protein unfolding simulation

The protein folding problem is one of the fundamental and important questions in molecular biology. However, the all-atom molecular dynamics studies of protein folding and unfolding are still computationally expensive and severely limited by the time scale of simulation. In this paper, a simple and fast protein unfolding method is proposed based on the conformational stability analyses and structure modeling. In this method, two structure-based conditions are considered to identify the unstable regions of proteins during the unfolding processes. The protein unfolding trajectories are mimicked through iterative structure modeling according to conformational stability analyses. Two proteins, chymotrypsin inhibitor 2 (CI2) and α -spectrin SH3 domain (SH3) were simulated by this method. Their unfolding pathways are consistent with the previous molecular dynamics simulations. Furthermore, the transition states of the two proteins were identified in unfolding processes and the theoretical Φ values of these transition states showed significant correlations with the experimental data (the correlation coefficients are >0.8). The results indicate that this method is effective in studying protein unfolding. Moreover, we analyzed and discussed the influence of parameters on the unfolding simulation. This simple coarse-grained model may provide a general and fast approach for the mechanism studies of protein folding.

What lessons can be learned from studying the folding of homologous proteins?

The studies of the folding of structurally related proteins have proved to be a very important tool for investigating protein folding. Here we review some of the insights that have been gained from such studies. Our highlighted studies show just how such an investigation should be designed and emphasise the importance of the synergy between experiment and theory. We also stress the importance of choosing the right system carefully, exploiting the excellent structural and sequence databases at our disposal.

FADD-calmodulin interaction: a novel player in cell cycle regulation

Analyses of knockout and mutant transgenic mice as well as in vitro studies demonstrated a complex role of FADD in the regulation of cell fate. FADD is involved in death receptor induced apoptosis, cell cycle progression and cell proliferation. In a search for mechanisms that might regulate FADD functions, we identified, upon the screening of a lambda-phage cDNA library, calmodulin (CaM) as a novel FADD interacting protein. CaM is a key mediator of signals by the secondary messenger calcium and it is an essential regulator of cell cycle progression and cell survival. Here, we describe the identification and characterization of two calcium dependent CaM binding sites in the alpha helices 8-9 and 10-11 of FADD. Phosphorylation of human FADD at the C-terminal serine 194, by casein kinase I alpha (CKIalpha), has been shown to regulate FADD-dependent non-apoptotic activities. Remarkably, we showed that both FADD and CaM are CKIalpha substrates and that in synchronized HeLa cells, FADD, CaM and CKIalpha co-localize at the mitotic spindle in metaphase and anaphase. Moreover, complementation experiments in Jurkat FADD-/- T cells indicated that: a) cells expressing FADD mutants in the CaM binding sites are protected from Taxol-induced G2/M cell cycle arrest; b) FADD/CaM interaction is not required for Fas receptor-mediated apoptosis although Fas and CaM might compete for binding to FADD. We suggest that the interplay of FADD, CaM and CKIalpha may have an important role in the regulation of cell fate.