Monte Carlo simulations of protein folding. II. Application to protein A, ROP, and crambin

The hierarchy of lattice Monte Carlo models described in the accompanying paper (Kolinski, A., Skolnick, J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme. Proteins 18:338-352, 1994) is applied to the simulation of protein folding and the prediction of 3-dimensional structure. Using sequence information alone, three proteins have been successfully folded: the B domain of staphylococcal protein A, a 120 residue, monomeric version of ROP dimer, and crambin. Starting from a random expanded conformation, the model proteins fold along relatively well-defined folding pathways. These involve a collection of early intermediates, which are followed by the final (and rate-determining) transition from compact intermediates closely resembling the molten globule state to the native-like state. The predicted structures are rather unique, with native-like packing of the side chains. The accuracy of the predicted native conformations is better than those obtained in previous folding simulations. The best (but by no means atypical) folds of protein A have a coordinate rms of 2.25 A from the native C alpha trace, and the best coordinate rms from crambin is 3.18 A. For ROP monomer, the lowest coordinate rms from equivalent C alpha s of ROP dimer is 3.65 A. Thus, for two simple helical proteins and a small alpha/beta protein, the ability to predict protein structure from sequence has been demonstrated.     

Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures

For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-Calpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 A.     

Genesis of residency programs in dental public health: reflections of the first dental public health resident?

BACKGROUND: Combinatorial methods based on binary patterning of polar and nonpolar residues have been used to generate large libraries of de novo alpha-helical proteins. Within such libraries, the ability to find structures that resemble natural proteins requires a rapid method to sort through large collections of proteins and detect those possessing 'native-like' features. The current paper presents such a method and applies it to an initial collection of de novo proteins. RESULTS: We present a method to identify proteins with native-like properties from libraries of de novo sequences expressed in vivo. A novel 'rapid prep' freeze/thaw procedure was used to prepare samples; chromatographic purification was not required. The semi-crude samples were analyzed for native-like features by one-dimensional 1H NMR spectroscopy. Using this method, we demonstrate that native-like features can readily be observed for several proteins among a collection of sequences designed by binary patterning of polar and nonpolar amino acids. CONCLUSIONS: Native-like properties can be detected using a method that requires neither isotopic enrichment nor chromatographic purification. The method is inexpensive, rapid, and suitable for parallel processing. It can therefore be employed to screen for native-like properties among large collections of de novo sequences. Using this method, we demonstrate that although the binary code strategy does not explicitly design tertiary packing, it can nonetheless generate proteins that possess native-like properties. The use of combinatorial methods to produce large collections of proteins coupled with the availability of a rapid assay for detecting native-like properties will facilitate the design and isolation of novel proteins with desirable properties.     

Prediction of the three-dimensional structure of proteins using the electrostatic screening model and hierarchic condensation

We describe a method for predicting the three-dimensional (3-D) structure of proteins from their sequence alone. The method is based on the electrostatic screening model for the stability of the protein main-chain conformation. The free energy of a protein as a function of its conformation is obtained from the potentials of mean force analysis of high-resolution x-ray protein structures. The free energy function is simple and contains only 44 fitted coefficients. The minimization of the free energy is performed by the torsion space Monte Carlo procedure using the concept of hierarchic condensation. The Monte Carlo minimization procedure is applied to predict the secondary, super-secondary, and native 3-D structures of 12 proteins with 28-110 amino acids. The 3-D structures of the majority of local secondary and super-secondary structures are predicted accurately. This result suggests that control in forming the native-like local structure is distributed along the entire protein sequence. The native 3-D structure is predicted correctly for 3 of 12 proteins composed mainly from the alpha-helices. The method fails to predict the native 3-D structure of proteins with a predominantly beta secondary structure. We suggest that the hierarchic condensation is not an appropriate procedure for simulating the folding of proteins made up primarily from beta-strands. The method has been proved accurate in predicting the local secondary and super-secondary structures in the blind ab initio 3-D prediction experiment.     

Nativelike topology assembly of small proteins using predicted restraints in Monte Carlo folding simulations

By incorporating predicted secondary and tertiary restraints derived from multiple sequence alignments into ab initio folding simulations, it has been possible to assemble native-like tertiary structures for a test set of 19 nonhomologous proteins ranging from 29 to 100 residues in length and representing all secondary structural classes. Secondary structural restraints are provided by the PHD secondary structure prediction algorithm that incorporates multiple sequence information. Multiple sequence alignments also provide predicted tertiary restraints via a two-step process: First, seed side chain contacts are selected from a correlated mutation analysis, and then an inverse folding algorithm expands these seed contacts. The predicted secondary and tertiary restraints are incorporated into a lattice-based, reduced protein model for structure assembly and refinement. The resulting native-like topologies exhibit a coordinate root-mean-square deviation from native for the whole chain between 3.1 and 6.7 A, with values ranging from 2.6 to 4.1 A over approximately 80% of the structure. Overall, this study suggests that the use of restraints derived from multiple sequence alignments combined with a fold assembly algorithm is a promising approach to the prediction of the global topology of small proteins.     

Exploring the folding funnel of a polypeptide chain by biophysical studies on protein fragments

We are examining possible roles of native and non-native interactions in early events in protein folding by a systematic analysis of the structures of fragments of proteins whose folding pathways are well characterised. Seven fragments of the 110-residue protein barnase, corresponding to the progressive elongation from its N terminus, have been characterised by a battery of biophysical and spectroscopic methods. Barnase is a multi-modular protein that folds via an intermediate in which the C-terminal region of its major alpha-helix (alpha-helix1, residues Thr6-His18) is substantially formed as is also its anti-parallel beta-sheet, centred around a beta-hairpin (residues Ser92-Leu95). Fragments up to, and including, residues 1-95 (fragment B95), appeared to be mainly disordered, although a small amount of helical secondary structure in each was inferred from far-UV CD experiments, and fluorescence studies indicated some native-like tertiary interactions in B95. The largest fragment (residues 1-105, B105) is compactly folded. The secondary structure in alpha-helix1 in the seven fragments was found by NMR to increase with increasing chain length faster than the build-up of tertiary interactions, indicating that alpha-helix1 is being stabilised by non-native interactions. This behaviour contrasts with that in fragments of the 64-residue chymotrypsin inhibitor 2 (CI2), in which tertiary and secondary structures build up in parallel with increasing length. CI2 consists of a single module of structure that folds without a detectable intermediate. The largest fragment of barnase, B105, has interactions that resemble its folding intermediate, whereas one of the largest fragments of CI2 (residues 1-60) resembles the folding transition state. The folding pathways of both proteins are consistent with a scheme in which there are low levels of native-like secondary structure in the denatured state that become stabilised by long-range interactions as folding proceeds. Neither protein forms a stable fold when lacking the last ten residues at the C terminus. Since at least 20 amino acid residues are bound to the ribosome during protein biosynthesis, these small proteins do not fold until they have left the ribosome, and so the studies of the folding of such proteins in vitro may be relevant to their folding in vivo, especially as the molecular chaperone GroEL binds only weakly to denatured CI2 and does not discernibly alter the folding mechanism of barnase.     

High-resolution solution NMR structure of the minimal active domain of the human immunodeficiency virus type-2 nucleocapsid protein

The retroviral nucleocapsid (NC) protein is a multifunctional protein essential for RNA genome packaging and viral infectivity. The NC protein, NCp8, of the human immunodeficiency virus type-II (HIV-2) is a 49 amino acid peptide containing two zinc fingers, of the type C-X2-C-X4-H-X4-C, connected by seven amino acid residues, called the "basic amino acid cluster." It has been shown that the N-terminal zinc finger flanked by the basic amino acid cluster is the minimal active domain for the specific binding to viral RNA and other functions. However, the structure-activity relationships of NCp8 have not been investigated in detail. In the present study, the three-dimensional structure of a 29 amino acid peptide, including the minimal active domain (NCp8-fl), was determined by two-dimensional 1H NMR spectroscopy with simulated annealing calculations. A total of 15 converged structures of NCp8-fl were obtained on the basis of 355 experimental constraints, including 343 distance constraints obtained from nuclear Overhauser effect connectivities, 12 torsion angle (phi, chi1) constraints, and four constraints for zinc binding. The root-mean-square deviation of the 15 converged structures was 0.29 +/- 0.04 A for the backbone atoms (N, C(alpha), C) and 1.27 +/- 0.13 A for all heavy atoms. Interestingly, the basic amino acid cluster itself was defined well, with a loop-like conformation in which three arginine residues in the cluster and one arginine residue in the zinc finger are located approximately in the same plane of the molecule and are exposed to the solvent. The structure-activity relationships are discussed on the basis of the comparison of this well-defined structure with those of other NC proteins.     

New scoring schemes for protein fold recognition based on Voronoi contacts

MOTIVATION: The genome projects produce a wealth of protein sequences. Theoretical methods to predict possible structures and functions are needed for screening purposes, large-scale comparisons and in-depth analysis to identify worthwhile targets for further experimental research. Sequence-structure alignment is a basic tool for the identification of model folds for protein sequences and the construction of crude structural models. Empirical contact potentials (potentials of mean force) are used to optimize and evaluate such alignments. RESULTS: We propose new scoring schemes based on a contact definition derived from Voronoi decompositions of the three-dimensional coordinates of protein structures. We demonstrate that Voronoi potentials are superior to pure distance-based contact potentials with respect to recognition rate and significance for native folds. Moreover, the scoring scheme has the potential to provide a reasonable balance of detail and ion such that it is also useful for the recognition of distantly related (both homologous and non-homologous) proteins. This is demonstrated here on a set of structural alignments showing much better correspondence of native and model scores for the Voronoi potentials as compared to conventional distance-based potentials. AVAILABILITY: The potentials are made available via the program system ToPLign (URL: http://cartan.gmd.de/ToPLign.html). CONTACT: Ralf.Zimmer,Ralf.Thiele@gmd.de     

Ultracentrifugal analysis of factor VIII and von Willebrand factor in therapeutic preparations

The X-ray structures of the maltose bound forms of two insertion/deletion mutants of the Escherichia coli maltodextrin binding protein, MalE322 and MalE178, have been determined and refined. MalE322 involves a one residue deletion, two residue insertion in a hinge segment connecting the two (N and C) domains of the protein, an area already identified as being critical for the correct functioning of the protein. MalE178 involves a nine residue deletion and two residue insertion in a helix at the periphery of the C-domain. The function of both mutant proteins is similar to the wild-type, although MalE322 increases the ability to transport maltose and maltodextrin whilst inhibiting the ability of the cell to grow on dextrins. Both proteins exhibit very localized and conservative conformational changes due to their mutations. The structure of MalE322 shows some deformation of the third hinge strand, indicating the likely cause of change in its biochemistry. MalE178 is stable and its activity virtually unchanged from the wild-type. This is most likely due to the long distance of the mutation from the binding site and conservation of the number of interactions between the area around the deletion site and the main body of the protein.     

Prediction of the antigenic sites of the cystic fibrosis transmembrane conductance regulator protein by molecular modelling

Antibodies are powerful tools for studying the in situ localization and physiology of proteins. The prediction of epitopes by molecular modelling has been used successfully for the papilloma virus, and valuable antibodies have been raised [Müller et al. (1990) J. Gen. Virol., 71, 2709-2717]. We have improved the modelling approach to allow us to predict epitopes from the primary sequences of the cystic fibrosis transmembrane conductance regulator. The procedure involves searching for fragments of primary sequences likely to make amphipathic secondary structures, which are hydrophilic enough to be at the surface of the folded protein and thus accessible to antibodies. Amphipathic helices were predicted using the methods of Berzofsky, Eisenberg and J?hnig. Their hydrophobic-hydrophilic interface was calculated and drawn, and used to predict the orientation of the helices at the surface of the native protein. Amino acids involved in turns were selected using the algorithm of Eisenberg. Tertiary structures were calculated using 'FOLDING', a software developed by R. Brasseur for the prediction of small protein structures [Brasseur (1995) J. Mol. Graphics, in press]. We selected sequences that folded as turns with at least five protruding polar residues. One important property of antibodies is selectivity. To optimize the selectivity of the raised antibodies, each sequence was screened for similarity (FASTA) to the protein sequence from several databanks. Ubiquitous sequences were discarded. This approach led to the identification of 13 potential epitopes in the cystic fibrosis transmembrane conductance regulator: seven helices and six loops.     

De novo design of the hydrophobic core of ubiquitin

We have previously reported the development and evaluation of a computational program to assist in the design of hydrophobic cores of proteins. In an effort to investigate the role of core packing in protein structure, we have used this program, referred to as Repacking of Cores (ROC), to design several variants of the protein ubiquitin. Nine ubiquitin variants containing from three to eight hydrophobic core mutations were constructed, purified, and characterized in terms of their stability and their ability to adopt a uniquely folded native-like conformation. In general, designed ubiquitin variants are more stable than control variants in which the hydrophobic core was chosen randomly. However, in contrast to previous results with 434 cro, all designs are destabilized relative to the wild-type (WT) protein. This raises the possibility that beta-sheet structures have more stringent packing requirements than alpha-helical proteins. A more striking observation is that all variants, including random controls, adopt fairly well-defined conformations, regardless of their stability. This result supports conclusions from the cro studies that non-core residues contribute significantly to the conformational uniqueness of these proteins while core packing largely affects protein stability and has less impact on the nature or uniqueness of the fold. Concurrent with the above work, we used stability data on the nine ubiquitin variants to evaluate and improve the predictive ability of our core packing algorithm. Additional versions of the program were generated that differ in potential function parameters and sampling of side chain conformers. Reasonable correlations between experimental and predicted stabilities suggest the program will be useful in future studies to design variants with stabilities closer to that of the native protein. Taken together, the present study provides further clarification of the role of specific packing interactions in protein structure and stability, and demonstrates the benefit of using systematic computational methods to predict core packing arrangements for the design of proteins.     

Role of glutamine 17 of the bovine papillomavirus E5 protein in platelet-derived growth factor beta receptor activation and cell transformation

The bovine papillomavirus E5 protein is a small, homodimeric transmembrane protein that forms a stable complex with the cellular platelet-derived growth factor (PDGF) beta receptor through transmembrane and juxtamembrane interactions, resulting in receptor activation and cell transformation. Glutamine 17 in the transmembrane domain of the 44-amino-acid E5 protein is critical for complex formation and receptor activation, and we previously proposed that glutamine 17 forms a hydrogen bond with threonine 513 of the PDGF beta receptor. We have constructed and analyzed mutant E5 proteins containing all possible amino acids at position 17 and examined the ability of these proteins to transform C127 fibroblasts, which express endogenous PDGF beta receptor. Although several position 17 mutants were able to transform cells, mutants containing amino acids with side groups that were unable to participate in hydrogen bonding interactions did not form a stable complex with the PDGF beta receptor or transform cells, in agreement with the proposed interaction between position 17 of the E5 protein and threonine 513 of the receptor. The nature of the residue at position 17 also affected the ability of the E5 proteins to dimerize. Overall, there was an excellent correlation between the ability of the various E5 mutant proteins to bind the PDGF beta receptor, lead to receptor tyrosine phosphorylation, and transform cells. Similar results were obtained in Ba/F3 hematopoietic cells expressing exogenous PDGF beta receptor. In addition, treatment of E5-transformed cells with a specific inhibitor of the PDGF receptor tyrosine kinase reversed the transformed phenotype. These results confirm the central importance of the PDGF beta receptor in mediating E5 transformation and highlight the critical role of the residue at position 17 of the E5 protein in the productive interaction with the PDGF beta receptor. On the basis of molecular modeling analysis and the known chemical properties of the amino acids, we suggest a structural basis for the role of the residue at position 17 in E5 dimerization and in complex formation between the E5 protein and the PDGF beta receptor.     

Probing the molecular basis of allergy. three-dimensional structure of the bovine lipocalin allergen Bos d 2

The three-dimensional structure of the major bovine allergen Bos d 2 has been determined by using x-ray diffraction at 1.8-A resolution. Structurally Bos d 2 is a member of the lipocalin family comprising proteins with transport functions. There is a flat small cavity inside the Bos d 2 protein core suitable for ligand binding, and it is possible that Glu115 and Asn37 inside the core are able to make hydrogen bonds with the ligand. Many allergens from different animals belong to the lipocalin family. The amino acid residue similarities between these lipocalins indicate putative regions for IgE binding. Comparison with the available allergen structures from other sources suggests that these allergens are roughly the same size and that their shape is more spherical than elliptical.     

Dopamine and the mechanisms of cognition: Part I. A neural network model predicting dopamine effects on selective attention

BACKGROUND: Dopamine affects neural information processing, cognition, and behavior; however, the mechanisms through which these three levels of function are affected have remained unspecified. We present a parallel-distributed processing model of dopamine effects on neural ensembles that accounts for effects on human performance in a selective attention task. METHODS: Task performance is stimulated using principles and mechanisms that capture salient aspects of information processing in neural ensembles. Dopamine effects are simulated as a change in gain of neural assemblies in the area of release. RESULTS: The model leads to different predictions as a function of the hypothesized location of dopamine effects. Motor system effects are simulated as a change in gain over the response layer of the model. This induces speeding of reaction times but an impairment of accuracy. Cognitive attentional effects are simulated as a change in gain over the attention layer. This induces a speeding of reaction times and an improvement of accuracy, especially at very fast reaction times and when processing of the stimulus requires selective attention. CONCLUSIONS: A computer simulation using widely accepted principles of processing in neural ensembles can account for reaction time distributions and time-accuracy curves in a selective attention task. The simulation can be used to generate predictions about the effects of dopamine agonists on performance. An empirical study evaluating these predictions is described in a companion paper.     

CATH--a hierarchic classification of protein domain structures

BACKGROUND: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structure-based classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can also be assigned. The ever increasing number of known protein structures is too large to classify all proteins manually, therefore, automatic methods are needed for fast evaluation of protein structures. RESULTS: We present a semi-automatic procedure for deriving a novel hierarchical classification of protein domain structures (CATH). The four main levels of our classification are protein class (C), architecture (A), topology (T) and homologous superfamily (H). Class is the simplest level, and it essentially describes the secondary structure composition of each domain. In contrast, architecture summarises the shape revealed by the orientations of the secondary structure units, such as barrels and sandwiches. At the topology level, sequential connectivity is considered, such that members of the same architecture might have quite different topologies. When structures belonging to the same T-level have suitably high similarities combined with similar functions, the proteins are assumed to be evolutionarily related and put into the same homologous superfamily. CONCLUSIONS: Analysis of the structural families generated by CATH reveals the prominent features of protein structure space. We find that nearly a third of the homologous superfamilies (H-levels) belong to ten major T-levels, which we call superfolds, and furthermore that nearly two-thirds of these H-levels cluster into nine simple architectures. A database of well-characterised protein structure families, such as CATH, will facilitate the assignment of structure-function/evolution relationships to both known and newly determined protein structures.     

Modeling protein-induced configurational changes in DNA minicircles

A method is offered for obtaining minimum energy configurations of DNA minicircles constrained by one or more DNA-binding proteins. The minicircles are modeled as elastic rods, while the presence of bound protein is implied by rigidly fixing portions of these chains. The configurations of the geometrically constrained circular rods are sampled stochastically and optimized according to a simple elastic energy model of nicked DNA. The shapes of the minimum energy structures identified after a simulated annealing process are analyzed in terms of relative protein orientation and writhing number. The procedure is applied to minicircles 500 base pairs in length, bound to two evenly spaced DNA-wrapping proteins. The presence of histone octamers is suggested by rigidly fixing the two protein-bound portions of each minicircle as small superhelices similar in dimension to nucleosomal DNA. The folded minimum energy forms of sample chains with different degrees of protein wrapping are noteworthy in themselves in that they offer a new resolution to the well-known minichromosome linking number paradox and point to future minicircle simulations of possible import.     

An evolutionary approach to folding small alpha-helical proteins that uses sequence information and an empirical guiding fitness function

Three short protein sequences have been guided by computer to folds resembling their crystal structures. Initially, peptide fragment conformations ranging in size from 9 to 25 residues were selected from a database of known protein structures. A fragment was selected if it was compatible with a segment of the sequence to be folded, as judged by three-dimensional profile scores. By linking the selected fragment conformations together, hundreds of trial structures were generated of the same length and sequence as the protein to be folded. These starting trial structures were then improved by an evolutionary algorithm. Selection pressure for improving the structures was provided by an energy function that was designed to guide the conformational search procedure toward the correct structure. We find that by evolution of only 400 structures for fewer than 1400 generations, the overall fold of some small helical proteins can be computed from the sequence, with deviations from observed structures of 2.5-4.0 A for C alpha atoms.     

Molecular docking of superantigens with class II major histocompatibility complex proteins

The molecular recognition of two superantigens with class II major histocompatibility complex molecules was simulated by using protein-protein docking. Superantigens studied were staphylococcal enterotoxin B (SEB) and toxic shock syndrome toxin-1 (TSST-1) in their crystallographic assemblies with HLA-DR1. Rigid-body docking was performed sampling configurational space of the interfacial surfaces by employing a strategy of partitioning the contact regions on HLA-DR1 into separate molecular recognition units. Scoring of docked conformations was based on an electrostatic continuum model evaluated with the finite-difference Poisson-Boltzmann method. Estimates of nonpolar contributions were derived from the buried molecular surface areas. We found for both superantigens that docking the HLA-DR1 surface complementary with the SEB and TSST-1 contact regions containing a homologous hydrophobic surface loop provided sufficient recognition for the reconstitution of native-like conformers exhibiting the highest-scoring free energies. For the SEB complex, the calculations were successful in reproducing the total association free energy. A comparison of the free-energy determinants of the conserved hydrophobic contact residue indicates functional similarity between the two proteins for this interface. Though both superantigens share a common global association mode, differences in binding topology distinguish the conformational specificities underlying recognition.     

Search for low-energy conformations of a neurotoxic protein by means of predictive rules, tests for hard-sphere overlaps, and energy minimization

A method to obtain models for the three-dimensional structure of the neurotoxin alpha from Naja nigricollis from its amino acid sequence is explored here. Empirical predictive rules were used to estimate the positions of helices, extended structures and bends; advantage was taken of the availability of 14 homologous sequences for the neurotoxins in an attempt to increase the reliability of these predictions. Unassigned residues were allowed to take up several possible conformations determined from the frequencies of occurrence of each type of conformation of that residue in x-ray structures of many proteins. The conformational space of the molecule was explored initially by testing for hard-sphere overlaps and approximate closure of disulfide loops with the aid of a computer; this procedure yielded a limited number of conformations, whose conformational energies were then determined and minimized by optimizing the backbone and side-chain dihedral angles of each residue. Five compact conformations with low energy were found for this neurotoxin. The procedure used here provides an illustration as to how empirical protein algorithms may be used to limit the conformational space, in which energy minimization has to be carried out.