Structural Characterization of N-WASP Domain V Using MD Simulations with NMR and SAXS Data

Because of their large conformational heterogeneity, structural characterization of intrinsically disordered proteins (IDPs) is very challenging using classical experimental methods alone. In this study, we use NMR and small-angle x-ray scattering (SAXS) data with multiple molecular dynamics (MD) simulations to describe the conformational ensemble of the fully disordered verprolin homology domain of the neural Aldrich syndrome protein involved in the regulation of actin polymerization. First, we studied several back-calculation software of SAXS scattering intensity and optimized the adjustable parameters to accurately calculate the SAXS intensity from an atomic structure. We also identified the most appropriate force fields for MD simulations of this IDP. Then, we analyzed four conformational ensembles of neural Aldrich syndrome protein verprolin homology domain, two generated with the program flexible-meccano with or without NMR-derived information as input and two others generated by MD simulations with two different force fields. These four conformational ensembles were compared to available NMR and SAXS data for validation. We found that MD simulations with the AMBER-03w force field and the TIP4P/2005s water model are able to correctly describe the conformational ensemble of this 67-residue IDP at both local and global level.     

Exploring the Minimally Frustrated Energy Landscape of Unfolded ACBP

The unfolded state of globular proteins is not well described by a simple statistical coil due to residual structural features, such as secondary structure or transiently formed long-range contacts. The principle of minimal frustration predicts that the unfolded ensemble is biased toward productive regions in the conformational space determined by the native structure. Transient long-range contacts, both native-like and non-native-like, have previously been shown to be present in the unfolded state of the four-helix-bundle protein acyl co-enzyme binding protein (ACBP) as seen from both perturbations in nuclear magnetic resonance (NMR) chemical shifts and structural ensembles generated from NMR paramagnetic relaxation data. To study the nature of the contacts in detail, we used paramagnetic NMR relaxation enhancements, in combination with single-point mutations, to obtain distance constraints for the acid-unfolded ensemble of ACBP. We show that, even in the acid-unfolded state, long-range contacts are specific in nature and single-point mutations affect the free-energy landscape of the unfolded protein. Using this approach, we were able to map out concerted, interconnected, and productive long-range contacts. The correlation between the native-state stability and compactness of the denatured state provides further evidence for native-like contact formation in the denatured state. Overall, these results imply that, even in the earliest stages of folding, ACBP dynamics are governed by native-like contacts on a minimally frustrated energy landscape.     

Dynamic Motion and Communication in the Streptococcal C1 Phage Lysin,PlyC

The growing problem of antibiotic resistance underlies the critical need to develop new treatments to prevent and control resistant bacterial infection. Exogenous application of bacteriophage lysins results in rapid and specific destruction of Gram-positive bacteria and therefore lysins represent novel antibacterial agents. The PlyC phage lysin is the most potent lysin characterized to date and can rapidly lyse Group A, C and E streptococci. Previously, we have determined the X-ray crystal structure of PlyC, revealing a complicated and unique arrangement of nine proteins. The scaffold features a multimeric cell-wall docking assembly bound to two catalytic domains that communicate and work synergistically. However, the crystal structure appeared to be auto-inhibited and raised important questions as to the mechanism underlying its extreme potency. Here we use small angle X-ray scattering (SAXS) and reveal that the conformational ensemble of PlyC in solution is different to that in the crystal structure. We also investigated the flexibility of the enzyme using both normal mode (NM) analysis and molecular dynamics (MD) simulations. Consistent with our SAXS data, MD simulations show rotational dynamics of both catalytic domains, and implicate inter-domain communication in achieving a substrate-ready conformation required for enzyme function. Our studies therefore provide insights into how the domains in the PlyC holoenzyme may act together to achieve its extraordinary potency.     

Crystal structure of human 53BP1 BRCT domains bound to p53 tumour suppressor

The BRCT (BRCA1 C-terminus) is an evolutionary conserved protein-protein interacting module found as single, tandem or multiple repeats in a diverse range of proteins known to play roles in the DNA-damage response. The BRCT domains of 53BP1 bind to the tumour suppressor p53. To investigate the nature of this interaction, we have determined the crystal structure of the 53BP1 BRCT tandem repeat in complex with the DNA-binding domain of p53. The structure of the 53BP1-p53 complex shows that the BRCT tandem repeats pack together through a conserved interface that also involves the inter-domain linker. A comparison of the structure of the BRCT region of 53BP1 with the BRCA1 BRCT tandem repeat reveals that the interdomain interface and linker regions are remarkably well conserved. 53BP1 binds to p53 through contacts with the N-terminal BRCT repeat and the inter-BRCT linker. The p53 residues involved in this binding are mutated in cancer and are also important for DNA binding. We propose that BRCT domains bind to cellular target proteins through a conserved structural element termed the 'BRCT recognition motif'.     

Characterization of Protein Flexibility Using Small-Angle X-Ray Scattering and Amplified Collective Motion Simulations

Large-scale flexibility within a multidomain protein often plays an important role in its biological function. Despite its inherent low resolution, small-angle x-ray scattering (SAXS) is well suited to investigate protein flexibility and determine, with the help of computational modeling, what kinds of protein conformations would coexist in solution. In this article, we develop a tool that combines SAXS data with a previously developed sampling technique called amplified collective motions (ACM) to elucidate structures of highly dynamic multidomain proteins in solution. We demonstrate the use of this tool in two proteins, bacteriophage T4 lysozyme and tandem WW domains of the formin-binding protein 21. The ACM simulations can sample the conformational space of proteins much more extensively than standard molecular dynamics (MD) simulations. Therefore, conformations generated by ACM are significantly better at reproducing the SAXS data than are those from MD simulations.     

Characterization of Protein Flexibility Using Small-Angle X-Ray Scattering and Amplified Collective Motion Simulations

Large-scale flexibility within a multidomain protein often plays an important role in its biological function. Despite its inherent low resolution, small-angle x-ray scattering (SAXS) is well suited to investigate protein flexibility and determine, with the help of computational modeling, what kinds of protein conformations would coexist in solution. In this article, we develop a tool that combines SAXS data with a previously developed sampling technique called amplified collective motions (ACM) to elucidate structures of highly dynamic multidomain proteins in solution. We demonstrate the use of this tool in two proteins, bacteriophage T4 lysozyme and tandem WW domains of the formin-binding protein 21. The ACM simulations can sample the conformational space of proteins much more extensively than standard molecular dynamics (MD) simulations. Therefore, conformations generated by ACM are significantly better at reproducing the SAXS data than are those from MD simulations.     

Targeting disordered-structured domain interactions in Galectin-3 based on NMR and enhanced MD

Intrinsically disordered regions (IDRs) are common and important functional domains in many proteins. However, IDRs are difficult to target for drug development due to the lack of defined structures that would facilitate the identification of possible drug-binding pockets. Galectin-3 is a carbohydrate-binding protein of which overexpression has been implicated in a wide variety of disorders, including cancer and inflammation. Apart from its carbohydrate-recognition/binding domain (CRD), Galectin-3 also contains a functionally important disordered N-terminal domain (NTD) that contacts the C-terminal domain (CTD) and could be a target for drug development. To overcome challenges involved in inhibitor design due to lack of structure and the highly dynamic nature of the NTD, we used a protocol combining nuclear magnetic resonance data from recombinant Galectin-3 with accelerated molecular dynamics (MD) simulations. This approach identified a pocket in the CTD with which the NTD makes frequent contact. In accordance with this model, mutation of residues L131 and L203 in this pocket caused loss of Galectin-3 agglutination ability, signifying the functional relevance of the cavity. In silico screening was used to design candidate inhibitory peptides targeting the newly discovered cavity, and experimental testing of only three of these yielded one peptide that inhibits the agglutination promoted by wild-type Galectin-3. NMR experiments further confirmed that this peptide indeed binds to a cavity in the CTD, not within the actual CRD. Our results show that it is possible to apply a combination of MD simulations and NMR experiments to precisely predict the binding interface of a disordered domain with a structured domain, and furthermore use this predicted interface for designing inhibitors. This procedure can potentially be extended to many other targets in which similar IDR interactions play a vital functional role.     

Long-range information and physicality constraints improve predicted protein contact maps

Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure, but the problem of predicting reliable contact maps is far from solved. One of the main pitfalls of existing contact map predictors is that they generally predict unphysical maps, i.e. maps that cannot be embedded into three-dimensional structures or, at best, violate a number of basic constraints observed in real protein structures, such as the maximum number of contacts for a residue. Here, we focus on the problem of learning to predict more "physical" contact maps. We do so by first predicting contact maps through a traditional system (XXStout), and then filtering these maps by an ensemble of artificial neural networks. The filter is provided as input not only the bare predicted map, but also a number of global or long-range features extracted from it. In a rigorous cross-validation test, we show that the filter greatly improves the predicted maps it is input. CASP7 results, on which we report here, corroborate this finding. Importantly, since the approach we present here is fully modular, it may be beneficial to any other ab initio contact map predictor.     

Three-dimensional folding and functional organization principles of the Drosophila genome

Chromosomes are the physical realization of genetic information and thus form the basis for its readout and propagation. Here we present a high-resolution chromosomal contact map derived from a modified genome-wide chromosome conformation capture approach applied to Drosophila embryonic nuclei. The data show that the entire genome is linearly partitioned into well-demarcated physical domains that overlap extensively with active and repressive epigenetic marks. Chromosomal contacts are hierarchically organized between domains. Global modeling of contact density and clustering of domains show that inactive domains are condensed and confined to their chromosomal territories, whereas active domains reach out of the territory to form remote intra- and interchromosomal contacts. Moreover, we systematically identify specific long-range intrachromosomal contacts between Polycomb-repressed domains. Together, these observations allow for quantitative prediction of the Drosophila chromosomal contact map, laying the foundation for detailed studies of chromosome structure and function in a genetically tractable system.     

Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers

Background

Prediction of long-range inter-residue contacts is an important topic in bioinformatics research. It is helpful for determining protein structures, understanding protein foldings, and therefore advancing the annotation of protein functions.

Results

In this paper, we propose a novel ensemble of genetic algorithm classifiers (GaCs) to address the long-range contact prediction problem. Our method is based on the key idea called sequence profile centers (SPCs). Each SPC is the average sequence profiles of residue pairs belonging to the same contact class or non-contact class. GaCs train on multiple but different pairs of long-range contact data (positive data) and long-range non-contact data (negative data). The negative data sets, having roughly the same sizes as the positive ones, are constructed by random sampling over the original imbalanced negative data. As a result, about 21.5% long-range contacts are correctly predicted. We also found that the ensemble of GaCs indeed makes an accuracy improvement by around 5.6% over the single GaC.

Conclusions

Classifiers with the use of sequence profile centers may advance the long-range contact prediction. In line with this approach, key structural features in proteins would be determined with high efficiency and accuracy.

     

Efficient traversal of beta-sheet protein folding pathways using ensemble models

Molecular dynamics (MD) simulations can now predict ms-timescale folding processes of small proteins; however, this presently requires hundreds of thousands of CPU hours and is primarily applicable to short peptides with few long-range interactions. Larger and slower-folding proteins, such as many with extended β-sheet structure, would require orders of magnitude more time and computing resources. Furthermore, when the objective is to determine only which folding events are necessary and limiting, atomistic detail MD simulations can prove unnecessary. Here, we introduce the program tFolder as an efficient method for modelling the folding process of large β-sheet proteins using sequence data alone. To do so, we extend existing ensemble β-sheet prediction techniques, which permitted only a fixed anti-parallel β-barrel shape, with a method that predicts arbitrary β-strand/β-strand orientations and strand-order permutations. By accounting for all partial and final structural states, we can then model the transition from random coil to native state as a Markov process, using a master equation to simulate population dynamics of folding over time. Thus, all putative folding pathways can be energetically scored, including which transitions present the greatest barriers. Since correct folding pathway prediction is likely determined by the accuracy of contact prediction, we demonstrate the accuracy of tFolder to be comparable with state-of-the-art methods designed specifically for the contact prediction problem alone. We validate our method for dynamics prediction by applying it to the folding pathway of the well-studied Protein G. With relatively very little computation time, tFolder is able to reveal critical features of the folding pathways which were only previously observed through time-consuming MD simulations and experimental studies. Such a result greatly expands the number of proteins whose folding pathways can be studied, while the algorithmic integration of ensemble prediction with Markovian dynamics can be applied to many other problems.     

Structure and dynamics of the quaternary hunchback mRNA translation repression complex

A key regulatory process during Drosophila development is the localized suppression of the hunchback mRNA translation at the posterior, which gives rise to a hunchback gradient governing the formation of the anterior-posterior body axis. This suppression is achieved by a concerted action of Brain Tumour (Brat), Pumilio (Pum) and Nanos. Each protein is necessary for proper Drosophila development. The RNA contacts have been elucidated for the proteins individually in several atomic-resolution structures. However, the interplay of all three proteins during RNA suppression remains a long-standing open question. Here, we characterize the quaternary complex of the RNA-binding domains of Brat, Pum and Nanos with hunchback mRNA by combining NMR spectroscopy, SANS/SAXS, XL/MS with MD simulations and ITC assays. The quaternary hunchback mRNA suppression complex comprising the RNA binding domains is flexible with unoccupied nucleotides functioning as a flexible linker between the Brat and Pum-Nanos moieties of the complex. Moreover, the presence of the Pum-HD/Nanos-ZnF complex has no effect on the equilibrium RNA binding affinity of the Brat RNA binding domain. This is in accordance with previous studies, which showed that Brat can suppress mRNA independently and is distributed uniformly throughout the embryo.     

Inter-domain movements in polyketide synthases: a molecular dynamics study

Insights into the structure and dynamics of modular polyketide synthases (PKS) are essential for understanding the mechanistic details of the biosynthesis of a large number of pharmaceutically important secondary metabolites. The crystal structures of the KS-AT di-domain from erythromycin synthase have revealed the relative orientation of various catalytic domains in a minimal PKS module. However, the relatively large distance between catalytic centers of KS and AT domains in the static structure has posed certain intriguing questions regarding mechanistic details of substrate transfer during polyketide biosynthesis. In order to investigate the role of inter-domain movements in substrate channeling, we have carried out a series of explicit solvent MD simulations for time periods ranging from 10 to 15 ns on the KS-AT di-domain and its sub-fragments. Analyses of these MD trajectories have revealed that both the catalytic domains and the structured inter-domain linker region remain close to their starting structures. Inter-domain movements at KS-linker and linker-AT interfaces occur around hinge regions which connect the structured linker region to the catalytic domains. The KS-linker interface was found to be more flexible compared to the linker-AT interface. However, inter-domain movements observed during the timescale of our simulations do not significantly reduce the distance between catalytic centers of KS and AT domains for facilitating substrate channeling. Based on these studies and prediction of intrinsic disorder we propose that the intrinsically unstructured linker stretch preceding the ACP domain might be facilitating movement of ACP domains to various catalytic centers.     

Self‐assembling study of sarcolipin and its mutants in multiple molecular dynamic simulations

The Sarcolipin (SLN) is a single trans‐membrane protein that can self‐assembly to dimer and oligomer for playing importantphysiological function. In this work, we addressed the dimerization of wild type SLN (wSLN) and its mutants (mSLNs) – I17A and I20A, using both coarse‐grained (CG) and atomistic (AT) molecular dynamics (MD) simulations. Our results demonstrated that wSLN homodimer assembled as a left‐handed helical complex, while mSLNs heterodimers assembled as right‐handed complexes. Analysis of residue‐residue contacts map indicated that isoleucine (Ile)‐leucione (Leu) zipper domain played an important role in dimerization. The potential of mean force (PMF) demonstrated that wSLN homodimer was more stable than mSLNs heterodimers. Meanwhile, the mSLNs heterodimers preferred right‐handed rather than left‐handed helix. AT‐MD simulations for wSLN and mSLNs were also in line with CG‐MD simulations. These results provided the insights for understanding the mechanisms of SLNs self‐assembling. Proteins 2017; 85:1065–1077. © 2017 Wiley Periodicals, Inc.     

Intrinsically disordered regions have specific functions in mitochondrial and nuclear proteins

Proteins in general consist not only of globular structural domains (SDs), but also of intrinsically disordered regions (IDRs), i.e. those that do not assume unique three-dimensional structures by themselves. Although IDRs are especially prevalent in eukaryotic proteins, the functions are mostly unknown. To elucidate the functions of IDRs, we first divided eukaryotic proteins into subcellular localizations, identified IDRs by the DICHOT system that accurately divides entire proteins into SDs and IDRs, and examined charge and hydropathy characteristics. On average, mitochondrial proteins have IDRs more positively charged than SDs. Comparison of mitochondrial proteins with orthologous prokaryotic proteins showed that mitochondrial proteins tend to have segments attached at both N and C termini, high fractions of which are IDRs. Segments added to the N-terminus of mitochondrial proteins contain not only signal sequences but also mature proteins and exhibit a positive charge gradient, with the magnitude increasing toward the N-terminus. This finding is consistent with the notion that positively charged residues are added to the N-terminus of proteobacterial proteins so that the extended proteins can be chromosomally encoded and efficiently transported to mitochondria after translation. By contrast, nuclear proteins generally have positively charged SDs and negatively charged IDRs. Among nuclear proteins, DNA-binding proteins have enhanced charge tendencies. We propose that SDs in nuclear proteins tend to be positively charged because of the need to bind to negatively charged nucleotides, while IDRs tend to be negatively charged to interact with other proteins or other regions of the same proteins to avoid premature proteasomal degradation.