Systematic evaluation of CS-Rosetta for membrane protein structure prediction with sparse NOE restraints

We critically test and validate the CS-Rosetta methodology for de novo structure prediction of α-helical membrane proteins (MPs) from NMR data, such as chemical shifts and NOE distance restraints. By systematically reducing the number and types of NOE restraints, we focus on determining the regime in which MP structures can be reliably predicted and pinpoint the boundaries of the approach. Five MPs of known structure were used as test systems, phototaxis sensory rhodopsin II (pSRII), a subdomain of pSRII, disulfide binding protein B (DsbB), microsomal prostaglandin E2 synthase-1 (mPGES-1), and translocator protein (TSPO). For pSRII and DsbB, where NMR and X-ray structures are available, resolution-adapted structural recombination (RASREC) CS-Rosetta yields structures that are as close to the X-ray structure as the published NMR structures if all available NMR data are used to guide structure prediction. For mPGES-1 and Bacillus cereus TSPO, where only X-ray crystal structures are available, highly accurate structures are obtained using simulated NMR data. One main advantage of RASREC CS-Rosetta is its robustness with respect to even a drastic reduction of the number of NOEs. Close-to-native structures were obtained with one randomly picked long-range NOEs for every 14, 31, 38, and 8 residues for full-length pSRII, the pSRII subdomain, TSPO, and DsbB, respectively, in addition to using chemical shifts. For mPGES-1, atomically accurate structures could be predicted even from chemical shifts alone. Our results show that atomic level accuracy for helical membrane proteins is achievable with CS-Rosetta using very sparse NOE restraint sets to guide structure prediction. Proteins 2017; 85:812-826. © 2016 Wiley Periodicals, Inc.

Regulatory Implications of Non-Trivial Splicing: Isoform 3 of Rab1A Shows Enhanced Basal Activity and Is Not Controlled by Accessory Proteins

Alternative splicing often affects structured and highly conserved regions of proteins, generating so called non-trivial splicing variants of unknown structure and cellular function. The human small G-protein Rab1A is involved in the regulation of the vesicle transfer from the ER to Golgi. A conserved non-trivial splice variant lacks nearly 40% of the sequence of the native Rab1A, including most of the regulatory interaction sites. We show that this variant of Rab1A represents a stable and folded protein, which is still able to bind nucleotides and co-localizes with membranes. Nevertheless, it should be mentioned that compared to other wild-typeRabGTPases, the measured nucleotide binding affinities are dramatically reduced in the variant studied. Furthermore, the Rab1A variant forms hetero-dimers with wild-type Rab1A and its presence in the cell enhances the efficiency of alkaline phosphatase secretion. However, this variant shows no specificity for GXP nucleotides, a constantly enhanced GTP hydrolysis activity and is no longer controlled by GEF or GAP proteins, indicating a new regulatory mechanism for the Rab1A cycle via alternative non-trivial splicing.

Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction

Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

Recently, a breakthrough has been achieved in modeling the atomic 3D structures of proteins from their sequence alone without requiring any experimental work on the protein itself. To achieve this goal, a database of evolutionary related sequences is analyzed to find co-evolving residues, giving insight into which residues are in close proximity to each other. These residue-residue contacts can help to drive a computer simulation with an atomic-scale physical model of the protein structure from a random starting conformation to a native-like 3D conformation. Although much effort is being put into the improvement of residue-residue contact predictions, their accuracy will always be limited. Therefore, structure prediction protocols with a high tolerance against incorrect distance restraints are needed. Here, we present a structure prediction protocol that combines evolutionary information with the iterative sampling approach of the molecular modeling suite Rosetta, called RASREC. RASREC has been shown to converge faster to near-native models and to be more robust against incorrect distance restraints than standard prediction protocols. It is therefore perfectly suited for restraints obtained from predicted residue-residue contacts with limited accuracy. We show that our protocol outperforms other currently published structure prediction methods and is able to achieve accurate structures, even if the accuracy of predicted contacts is low.

A Framework to Simplify Combined Sampling Strategies in Rosetta

A core task in computational structural biology is the search of conformational space for low energy configurations of a biological macromolecule. Because conformational space has a very high dimensionality, the most successful search methods integrate some form of prior knowledge into a general sampling algorithm to reduce the effective dimensionality. However, integrating multiple types of constraints can be challenging. To streamline the incorporation of diverse constraints, we developed the Broker: an extension of the Rosetta macromolecular modeling suite that can express a wide range of protocols using constraints by combining small, independent modules, each of which implements a different set of constraints. We demonstrate expressiveness of the Broker through several code vignettes. The framework enables rapid protocol development in both biomolecular design and structural modeling tasks and thus is an important step towards exposing the rich functionality of Rosetta's core libraries to a growing community of users addressing a diverse set of tasks in computational biology.

Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta

The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.

Side-binding proteins modulate actin filament dynamics

Actin filament dynamics govern many key physiological processes from cell motility to tissue morphogenesis. A central feature of actin dynamics is the capacity of filaments to polymerize and depolymerize at their ends in response to cellular conditions. It is currently thought that filament kinetics can be described by a single rate constant for each end. In this study, using direct visualization of single actin filament elongation, we show that actin polymerization kinetics at both filament ends are strongly influenced by the binding of proteins to the lateral filament surface. We also show that the pointed-end has a non-elongating state that dominates the observed filament kinetic asymmetry. Estimates of flexibility as well as effects on fragmentation and growth suggest that the observed kinetic diversity arises from structural alteration. Tuning elongation kinetics by exploiting the malleability of the filament structure may be a ubiquitous mechanism to generate a rich variety of cellular actin dynamics.

DOI:http://dx.doi.org/10.7554/eLife.04599.001

Actin is one of the most abundant proteins in cells. It forms networks of filaments that provide structural support and generate the forces needed for cell movement, division, and many other processes in cells.

Filaments of actin continuously change in length as actin molecules are added or removed at the ends. One end of an actin filament—called the barbed-end—grows much faster than the other, known as the pointed-end. Many other proteins also help the actin filaments to form. Some of these proteins bind to the ends of the filaments, where they directly control the growth of the filaments. Other proteins bind along the length of the filaments, but how these ‘side-binding’ proteins influence the growth of filaments is not clear.

In this study, Crevenna et al. used a technique called ‘total internal reflection fluorescence (TIRF) microscopy’ to study how several side-binding proteins affect the growth of actin filaments in an artificial system. The growth of the barbed-ends was strongly influenced by which side-binding protein was interacting with the filament. For example, the barbed-end grew rapidly when a protein called VASP was present but grew more slowly in the presence of the protein α-actinin. Although the growth at the pointed-end was generally slow and sporadic, the side-binding proteins also had noticeable effects.

Crevenna et al. found that when the side-binding proteins were present at low levels, filament growth was similar for all proteins studied. It was only when the proteins were present at higher levels that the growth of the actin filaments was altered depending on the specific side-binding protein present. One side-binding protein called α-actinin also altered the shape of the actin filament so that when it was present at high levels, the filaments curved in a particular direction. Together, these results suggest that the growth, structure, and flexibility of actin filaments can be strongly influenced by the various proteins that bind along the length of the filaments.

The next challenges are to understand the precise details of how these side-binding proteins are able to alter the growth and shape of actin and investigate how they influence other processes that control the structure of actin networks in cells.

DOI:http://dx.doi.org/10.7554/eLife.04599.002

A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta

Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.

Access to Cα backbone dynamics of biological solids by 13C T1 relaxation and molecular dynamics simulation

We introduce a labeling scheme for magic angle spinning (MAS) solid-state NMR that is based on deuteration in combination with dilution of the carbon spin system. The labeling strategy achieves spectral editing by simplification of the HαCα and aliphatic side chain spectral region. A reduction in both proton and carbon spin density in combination with fast spinning (≥50 kHz) is essential to retrieve artifact-free (13)C-R1 relaxation data for aliphatic carbons. We obtain good agreement between the NMR experimental data and order parameters extracted from a molecular dynamics (MD) trajectory, which indicates that carbon based relaxation parameters can yield complementary information on protein backbone as well as side chain dynamics.

Site-specific analysis of heteronuclear Overhauser effects in microcrystalline proteins

Relaxation parameters such as longitudinal relaxation are susceptible to artifacts such as spin diffusion, and can be affected by paramagnetic impurities as e.g. oxygen, which make a quantitative interpretation difficult. We present here the site-specific measurement of [(1)H](13)C and [(1)H](15)N heteronuclear rates in an immobilized protein. For methyls, a strong effect is expected due to the three-fold rotation of the methyl group. Quantification of the [(1)H](13)C heteronuclear NOE in combination with (13)C-R 1 can yield a more accurate analysis of side chain motional parameters. The observation of significant [(1)H](15)N heteronuclear NOEs for certain backbone amides, as well as for specific asparagine/glutamine sidechain amides is consistent with MD simulations. The measurement of site-specific heteronuclear NOEs is enabled by the use of highly deuterated microcrystalline protein samples in which spin diffusion is reduced in comparison to protonated samples.

Automatic NOESY assignment in CS-RASREC-Rosetta

We have developed an approach for simultaneous structure calculation and automatic Nuclear Overhauser Effect (NOE) assignment to solve nuclear magnetic resonance (NMR) structures from unassigned NOESY data. The approach, autoNOE-Rosetta, integrates Resolution Adapted Structural RECombination (RASREC) Rosetta NMR calculations with algorithms for automatic NOE assignment. The method was applied to two proteins in the 15-20 kDa size range for which both, NMR and X-ray data, is available. The autoNOE-Rosetta calculations converge for both proteins and yield accurate structures with an RMSD of 1.9 Å to the X-ray reference structures. The method greatly expands the radius of convergence for automatic NOE assignment, and should be broadly useful for NMR structure determination.

Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta

We have developed a novel and robust approach for automatic and unsupervised simultaneous nuclear Overhauser effect (NOE) assignment and structure determination within the CS-Rosetta framework. Starting from unassigned peak lists and chemical shift assignments, autoNOE-Rosetta determines NOE cross-peak assignments and generates structural models. The approach tolerates incomplete and raw NOE peak lists as well as incomplete or partially incorrect chemical shift assignments, and its performance has been tested on 50 protein targets ranging from 50 to 200 residues in size. We find a significantly improved performance compared to established programs, particularly for larger proteins and for NOE data obtained on perdeuterated protein samples. X-ray crystallographic structures allowed comparison of Rosetta and conventional, PDB-deposited, NMR models in 20 of 50 test cases. The unsupervised autoNOE-Rosetta models were often of significantly higher accuracy than the corresponding expert-supervised NMR models deposited in the PDB. We also tested the method with unrefined peak lists and found that performance was nearly as good as for refined peak lists. Finally, demonstrating our method's remarkable robustness against problematic input data, we provided correct models for an incorrect PDB-deposited NMR solution structure.

A mechanism for the auto-inhibition of hyperpolarization-activated cyclic nucleotide-gated (HCN) channel opening and its relief by cAMP

Hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels control neuronal and cardiac electrical rhythmicity. There are four homologous isoforms (HCN1-4) sharing a common multidomain architecture that includes an N-terminal transmembrane tetrameric ion channel followed by a cytoplasmic "C-linker," which connects a more distal cAMP-binding domain (CBD) to the inner pore. Channel opening is primarily stimulated by transmembrane elements that sense membrane hyperpolarization, although cAMP reduces the voltage required for HCN activation by promoting tetramerization of the intracellular C-linker, which in turn relieves auto-inhibition of the inner pore gate. Although binding of cAMP has been proposed to relieve auto-inhibition by affecting the structure of the C-linker and CBD, the nature and extent of these cAMP-dependent changes remain limitedly explored. Here, we used NMR to probe the changes caused by the binding of cAMP and of cCMP, a partial agonist, to the apo-CBD of HCN4. Our data indicate that the CBD exists in a dynamic two-state equilibrium, whose position as gauged by NMR chemical shifts correlates with the V½ voltage measured through electrophysiology. In the absence of cAMP, the most populated CBD state leads to steric clashes with the activated or "tetrameric" C-linker, which becomes energetically unfavored. The steric clashes of the apo tetramer are eliminated either by cAMP binding, which selects for a CBD state devoid of steric clashes with the tetrameric C-linker and facilitates channel opening, or by a transition of apo-HCN to monomers or dimer of dimers, in which the C-linker becomes less structured, and channel opening is not facilitated.

Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker

A new fragment picker has been developed for CS-Rosetta that combines beneficial features of the original fragment picker, MFR, used with CS-Rosetta, and the fragment picker, NNMake, that was used for purely sequence based fragment selection in the context of ROSETTA de-novo structure prediction. Additionally, the new fragment picker has reduced sensitivity to outliers and other difficult to match data points rendering the protocol more robust and less likely to introduce bias towards wrong conformations in cases where data is bad, missing or inconclusive. The fragment picker protocol gives significant improvements on 6 of 23 CS-Rosetta targets. An independent benchmark on 39 protein targets, whose NMR data sets were published only after protocol optimization had been finished, also show significantly improved performance for the new fragment picker (van der Schot et al. in J Biomol NMR, 2013).

Improving 3D structure prediction from chemical shift data

We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 Å RMSD from the reference).

Replica exchange improves sampling in low-resolution docking stage of RosettaDock

Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied.

Blind testing of routine, fully automated determination of protein structures from NMR data

The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent "blind" assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.

Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation

Recent work has shown that NMR structures can be determined by integrating sparse NMR data with structure prediction methods such as Rosetta. The experimental data serve to guide the search for the lowest energy state towards the deep minimum at the native state which is frequently missed in Rosetta de novo structure calculations. However, as the protein size increases, sampling again becomes limiting; for example, the standard Rosetta protocol involving Monte Carlo fragment insertion starting from an extended chain fails to converge for proteins over 150 amino acids even with guidance from chemical shifts (CS-Rosetta) and other NMR data. The primary limitation of this protocol—that every folding trajectory is completely independent of every other—was recently overcome with the development of a new approach involving resolution-adapted structural recombination (RASREC). Here we describe the RASREC approach in detail and compare it to standard CS-Rosetta. We show that the improved sampling of RASREC is essential in obtaining accurate structures over a benchmark set of 11 proteins in the 15-25 kDa size range using chemical shifts, backbone RDCs and H^N-H^N NOE data; in a number of cases the improved sampling methodology makes a larger contribution than incorporation of additional experimental data. Experimental data are invaluable for guiding sampling to the vicinity of the global energy minimum, but for larger proteins, the standard Rosetta fold-from-extended-chain protocol does not converge on the native minimum even with experimental data and the more powerful RASREC approach is necessary to converge to accurate solutions.

Structure of the BamC two-domain protein obtained by Rosetta with a limited NMR data set

The CS-RDC-NOE Rosetta program was used to generate the solution structure of a 27-kDa fragment of the Escherichia coli BamC protein from a limited set of NMR data. The BamC protein is a component of the essential five-protein β-barrel assembly machine in E. coli. The first 100 residues in BamC were disordered in solution. The Rosetta calculations showed that BamC₁₀₁₋₃₄₄ forms two well-defined domains connected by an ~18-residue linker, where the relative orientation of the domains was not defined. Both domains adopt a helix-grip fold previously observed in the Bet v 1 superfamily. ¹⁵N relaxation data indicated a high degree of conformational flexibility for the linker connecting the N-terminal domain and the C-terminal domain in BamC. The results here show that CS-RDC-NOE Rosetta is robust and has a high tolerance for misassigned nuclear Overhauser effect restraints, greatly simplifying NMR structure determinations.

Determination of the structures of symmetric protein oligomers from NMR chemical shifts and residual dipolar couplings

Symmetric protein dimers, trimers, and higher-order cyclic oligomers play key roles in many biological processes. However, structural studies of oligomeric systems by solution NMR can be difficult due to slow tumbling of the system and the difficulty in identifying NOE interactions across protein interfaces. Here, we present an automated method (RosettaOligomers) for determining the solution structures of oligomeric systems using only chemical shifts, sparse NOEs, and domain orientation restraints from residual dipolar couplings (RDCs) without a need for a previously determined structure of the monomeric subunit. The method integrates previously developed Rosetta protocols for solving the structures of monomeric proteins using sparse NMR data and for predicting the structures of both nonintertwined and intertwined symmetric oligomers. We illustrated the performance of the method using a benchmark set of nine protein dimers, one trimer, and one tetramer with available experimental data and various interface topologies. The final converged structures are found to be in good agreement with both experimental data and previously published high-resolution structures. The new approach is more readily applicable to large oligomeric systems than conventional structure-determination protocols, which often require a large number of NOEs, and will likely become increasingly relevant as more high-molecular weight systems are studied by NMR.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

Scrutinizing molecular mechanics force fields on the submicrosecond timescale with NMR data

Protein dynamics on the atomic level and on the microsecond timescale has recently become accessible from both computation and experiment. To validate molecular dynamics (MD) at the submicrosecond timescale against experiment we present microsecond MD simulations in 10 different force-field configurations for two globular proteins, ubiquitin and the gb3 domain of protein G, for which extensive NMR data is available. We find that the reproduction of the measured NMR data strongly depends on the chosen force field and electrostatics treatment. Generally, particle-mesh Ewald outperforms cut-off and reaction-field approaches. A comparison to measured J-couplings across hydrogen bonds suggests that there is room for improvement in the force-field description of hydrogen bonds in most modern force fields. Our results show that with current force fields, simulations beyond hundreds of nanoseconds run an increased risk of undergoing transitions to nonnative conformational states or will persist within states of high free energy for too long, thus skewing the obtained population frequencies. Only for the AMBER99sb force field have such transitions not been observed. Thus, our results have significance for the interpretation of data obtained with long MD simulations, for the selection of force fields for MD studies and for force-field development. We hope that this comprehensive benchmark based on NMR data applied to many popular MD force fields will serve as a useful resource to the MD community. Finally, we find that for gb3, the force-field AMBER99sb reaches comparable accuracy in back-calculated residual dipolar couplings and J-couplings across hydrogen bonds to ensembles obtained by refinement against NMR data.

Estimating absolute configurational entropies of macromolecules: the minimally coupled subspace approach

We develop a general minimally coupled subspace approach (MCSA) to compute absolute entropies of macromolecules, such as proteins, from computer generated canonical ensembles. Our approach overcomes limitations of current estimates such as the quasi-harmonic approximation which neglects non-linear and higher-order correlations as well as multi-minima characteristics of protein energy landscapes. Here, Full Correlation Analysis, adaptive kernel density estimation, and mutual information expansions are combined and high accuracy is demonstrated for a number of test systems ranging from alkanes to a 14 residue peptide. We further computed the configurational entropy for the full 67-residue cofactor of the TATA box binding protein illustrating that MCSA yields improved results also for large macromolecular systems.

NMR structure determination for larger proteins using backbone-only data

Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.

Adaptive anisotropic kernels for nonparametric estimation of absolute configurational entropies in high-dimensional configuration spaces

The quasiharmonic approximation is the most widely used estimate for the configurational entropy of macromolecules from configurational ensembles generated from atomistic simulations. This method, however, rests on two assumptions that severely limit its applicability, (i) that a principal component analysis yields sufficiently uncorrelated modes and (ii) that configurational densities can be well approximated by Gaussian functions. In this paper we introduce a nonparametric density estimation method which rests on adaptive anisotropic kernels. It is shown that this method provides accurate configurational entropies for up to 45 dimensions thus improving on the quasiharmonic approximation. When embedded in the minimally coupled subspace framework, large macromolecules of biological interest become accessible, as demonstrated for the 67-residue coldshock protein.

Self-consistent residual dipolar coupling based model-free analysis for the robust determination of nanosecond to microsecond protein dynamics

Residual dipolar couplings (RDCs) provide information about the dynamic average orientation of inter-nuclear vectors and amplitudes of motion up to milliseconds. They complement relaxation methods, especially on a time-scale window that we have called supra-tau(c) (tau(c) < supra-tau(c) < 50 micros). Here we present a robust approach called Self-Consistent RDC-based Model-free analysis (SCRM) that delivers RDC-based order parameters-independent of the details of the structure used for alignment tensor calculation-as well as the dynamic average orientation of the inter-nuclear vectors in the protein structure in a self-consistent manner. For ubiquitin, the SCRM analysis yields an average RDC-derived order parameter of the NH vectors <S2(rdc)>0.72 +/- 0.02 compared to <S2(LS)> = 0.778 +/- 0.003 for the Lipari-Szabo order parameters, indicating that the inclusion of the supra-tau(c) window increases the averaged amplitude of mobility observed in the sub-supra-tau(c) window by about 34%. For the beta-strand spanned by residues Lys48 to Leu50, an alternating pattern of backbone NH RDC order parameter S2(rdc)(NH) = (0.59, 0.72, 0.59) was extracted. The backbone of Lys48, whose side chain is known to be involved in the poly-ubiquitylation process that leads to protein degradation, is very mobile on the supra-tau(c) time scale (S2(rdc)(NH) = 0.59 +/- 0.03), while it is inconspicuous (S2(LS)(NH)= 0.82) on the sub-tau(c) as well as on micros-ms relaxation dispersion time scales. The results of this work differ from previous RDC dynamics studies of ubiquitin in the sense that the results are essentially independent of structural noise providing a much more robust assessment of dynamic effects that underlie the RDC data.

Full correlation analysis of conformational protein dynamics

Correlated motions in biomolecules are often essential for their function, for example, allosteric signal transduction or mechanical/thermodynamic energy transport. Principal component analysis (PCA) is a widely used method to extract functionally relevant collective motions from a molecular dynamics (MD) trajectory. Being based on the covariance matrix, however, PCA detects only linear correlations. Here we present a new method, full correlation analysis (FCA), which is based on mutual information and thus quantifies all correlations, including nonlinear and higher order correlations. For comparison, we applied both, PCA and FCA, to approximately 100 ns MD trajectories of T4 lysozyme and the hexapeptide neurotensin. For both systems, FCA yielded better resolved conformational substates and aligned its modes more often with actual transition pathways. This improved resolution is shown to be due to a strongly increased anharmonicity of FCA modes as compared to the respective PCA modes. The high anharmonicity further suggests that the motions extracted by FCA are functionally more relevant than those captured by PCA. In summary, FCA should provide improved collective degrees of freedom for dimension-reduced descriptions of macromolecular dynamics.

Flooding in GROMACS: accelerated barrier crossings in molecular dynamics

The major bottleneck of today's atomistic molecular dynamics (MD) simulations is that because of the enormous computational effort involved, only processes at nanoseconds to microseconds time scales or faster can be studied directly. Unfortunately, apart from a few exceptions, relevant processes, such as chemical reactions or many large scale conformational transitions in proteins, occur at slower time scales and therefore are currently far out of reach for conventional MD. The flooding technique addresses this problem by inclusion of a flooding potential into the force field. This flooding potential locally destabilizes the educt state and thereby significantly accelerates the escape from the initial energy well without affecting the reaction pathway. Here, we summarize the theory and method for the computational chemistry community and detail the implementation within the official version 3.3 of the freely available MD program package GROMACS. Two examples shall demonstrate the application of flooding to accelerate conformational transitions and chemical reactions. The second example was carried out within a QM/MM framework.

Collective Langevin dynamics of conformational motions in proteins

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150 ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (approximately 50 ns) was much longer than the 1 ns molecular dynamics simulation from which the memory kernel was extracted.

Can principal components yield a dimension reduced description of protein dynamics on long time scales?

The suitability of principal component analysis (PCA) to yield slow collective coordinates for use within a dimension reduced description of conformational motions in proteins is evaluated. Two proteins are considered, T4 lysozyme and crambin. We present a quantitative evaluation of the convergence of conformational coordinates obtained with principal component analysis. Detailed analyses of (>200 ns) molecular dynamics trajectories and crystallographic data suggests that simulations of a few nanoseconds should generally provide a stable and statistically reliable definition of the essential and near constraints subspaces. Moreover, a systematic assessment of the density of states of the dynamics of all principal components showed that for an optimal separation of time scales it is crucial to include also side chain atoms in the PCA.

Generalized correlation for biomolecular dynamics

Correlated motions in biomolecules are often essential for their function, e.g., allosteric signal transduction or mechanical/thermodynamic energy transport. Because correlated motions in biomolecules remain difficult to access experimentally, molecular dynamics (MD) simulations are particular useful for their analysis. The established method to quantify correlations from MD simulations via calculation of the covariance matrix, however, is restricted to linear correlations and therefore misses part of the correlations in the atomic fluctuations. Herein, we propose a general statistical mechanics approach to detect and quantify any correlated motion from MD trajectories. This generalized correlation measure is contrasted with correlations obtained from covariance matrices for the B1 domain of protein G and T4 lysozyme. The new method successfully quantifies correlations and provides a valuable global overview over the functionally relevant collective motions of lysozyme. In particular, correlated motions of helix 1 together with the two main lobes of lysozyme are detected, which are not seen by the conventional covariance matrix. Overall, the established method misses more than 50% of the correlation. This failure is attributed to both, an interfering and unnecessary dependence on mutual orientations of the atomic fluctuations and, to a lesser extent, attributed to nonlinear correlations. Our generalized correlation measure overcomes these problems and, moreover, allows for an improved understanding of the conformational dynamics by separating linear and nonlinear contributions of the correlation.

Palliative radio-chemotherapy with ifosfamide and BCNU for breast cancer patients with cerebral metastases. A 5-year experience

Between January 1983 and April 1989, 61 patients with brain metastases of primary breast cancer were treated in the Robert Janker Clinic. To optimize the overall response rates, a simultaneous combination of radiation and chemotherapy was used. The patients median age was 49 (range, 30-67) years and the median performance score, 1 (0-2). The average interval between the diagnosis of the primary tumour and the brain metastases was 38 (range, 3-144) months. A total of 82% of the patients had multiple cerebral metastases. All patients had been pretreated with primary surgery; 79%, with radiation; 74%, with chemotherapy; and 64%, with hormones. Radiotherapy was given using a cobalt 60 machine. The whole brain was irradiated in daily fractions of 1.5 Gy, up to a total dose of 45 Gy. Using a split-course technique, this dose was given in three courses simultaneously with the chemotherapy. The chemotherapeutic regimen consisted of ifosfamide given daily for 5 days at 2 g/m2 and the nitrosourea derivative carmustine (BCNU) given at 30 mg/m2 on 3 days. The toxicity of the treatment was moderate; no haemotological or gastro-intestinal complications occurred. Complete and mostly irreversible alopecia occurred in all cases. All patients received a cranial computerized tomographic (CT) scan prior to and after treatment. According to the criteria of the International Union Against Cancer (UICC), there was a complete remission (CR) in 20% of the patients and a partial remission (PR) in 45%; 20% had a minor remission (MR) and 7% showed no change (NC) in the tumour. Another 7% of the patients experienced a progression of their metastases (PD). The median survival was 8 months for all patients and 12 months for those showing a CR.

Palliative chemo-radiotherapy with ifosfamide and epirubicin as first-line treatment for high-risk metastatic breast cancer. Results of a prospective multicenter trial

From June 1986 to December 1988, 107 patients (median age, 49 years; median performance score, 1) with haematogeneous metastases from breast carcinoma were treated with concomitant radiation and chemotherapy. Overall, 97% of the patients had been pretreated with surgery; 65%, with radiation; and 56%, with hormones. In all, 38% had received adjuvant chemotherapy. Patients with prior palliative chemotherapy were excluded from the study. All patients fulfilled at least two high-risk criteria. Chemotherapy was given according to the EI protocol (4-epirubicin and ifosfamide), and all patients simultaneously received radiation to the main tumour sites. Gastro-intestinal toxicity was moderate (11.1%, WHO grade 4), and bone marrow depression was marked in all cases. After three treatment courses, the overall response rate was 67% [21% complete response (CR), 46% partial response (PR)]. In all, 28% had stable disease (NC) and the rate of progressive disease (PD) was 5%. The median duration of tumour response was 8 months, with 12 months for CRs, 9 months for PRs and 6 months for NCs. The median survival was 13.5 months.

Interferon-gamma treatment of metastasized malignant melanoma

Between 1-1-85 and 6-30-86, 17 patients suffering from metastatic malignant melanoma received total doses of 30-40 I.U. IFN-gamma given i.v. in a daily fractionation of 1.0-2.6 X 10(6) I.U. The only side effect was fever grade I-II (WHO). In four of these patients a regression of the disease was obtained (two complete remissions and two partial remissions, according to UICC criteria). Thus, the overall response rate was 23.5%. The average duration of remission was 8.9 months (range from 1.5 to 21 + months), the average survival time 12.4 months (range from 1.5 to 21 + months, also). Two other patients showed no change lasting for two and five months respectively. In all, systemic interferon-gamma treatment applied in the manner described seems to be able to induce remissions in single cases without showing severe toxicity.

Simultaneous radio- and chemotherapy of inoperable brain tumours

Between January 1980 and May 1985, 102 patients (68 men, 34 women, median age 47 years) with malignant brain tumours (35% glioblastoma multiforme, 30% astrocytoma grade III, 21% oligodendroglioma grade III) have been treated in our clinic. All tumours were inoperable because of their size and/or location. The diagnosis was confirmed histopathologically (stereotactic biopsy or subtotal resection). Seventy-five patients without previous radiotherapy received three courses of a concomitant radio- and chemotherapy with free intervals of 5 weeks between the courses of the therapy. Using lateral opposing fields the whole brain was irradiated with 60Co in daily fractions of 1.5 Gy up to 15 Gy per course of the treatment. Simultaneously, all patients received ifosfamide on five consecutive days in a dosage of 1.2 g/sqm body surface each day i.v. On days 1, 3 and 5, BCNU was given additionally in a daily dosage of 30 mg/sqm body surface i.v. After three courses, a total radiation dose of 45 Gy was administered to the whole brain. Directly after the last cycle of the combined treatment the primary tumour was boosted up to 50-60 Gy using smaller portals. Seventy-one of the 75 patients were amenable to statistical analysis. The overall tolerance was good. No severe haematological or gastrointestinal complications occurred. According to the criteria of the UICC, 12 complete remissions (CR) (i.e. 16.9%) and 35 partial remissions (PR) (i.e. 49.3%) were achieved. In 21 cases (i.e. 29.6%), the progression of the tumour could be stopped. Depending on the histopathological classification of the malignancies survival rates between 64.3% and 87.5% were achieved for one year.(ABSTRACT TRUNCATED AT 250 WORDS)

[Initial experiences with simultaneous combined radiation and cytostatic chemotherapy in the modification of intractable pain by inoperable tumor growth in the ENT area]

Patients with malignant tumours of the ENT, who show signs of tumour progression after operation, radiation and chemotherapy, could be treated with a new combined therapy. We present a patient who was successfully treated by combined radiation and chemotherapy with Cisplatin, Ifosfamid, and BCNU. This therapy offers a chance of tumour reduction even for repeatedly treated patients. The relief of pain proves the success of the therapy.