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M J Sippl

Publications and source records attributed to M J Sippl.

At least 19 recordsLinked to original sources
PubMed2001

Assessment of the CASP4 fold recognition category.

We present the assessment of the CASP4 fold recognition category. The tasks we had to execute include the splitting of multidomain targets into single domains, the classification of target domains in terms of prediction categories, the numerical evaluation of predictions, the mapping of numerical scores to quality indices, the ranking of predictors, the selection of top-performing groups, and the analysis and critical discussion of the state of the art in this field. The 125 fold recognition groups were assessed by a total score that summarizes their performance over all targets and a quality score reflecting the average quality of the submitted models. Most of the top-performing groups achieved respectable results on both scores simultaneously. Several groups submitted models that were much closer to the respective target structures than any of the known folds in the Protein Data Bank. The CASP4 assessment included the automated servers of the parallel CAFASP experiment. For the total score, the highest rank achieved by a fully automated server is 12. Two thirds of the predictors have rather low scores.

Computer Simulation↗
PubMed2000

The role of protein structure in genomics.

The genome projects produce an enormous amount of sequence data that needs to be annotated in terms of molecular structure and biological function. These tasks have triggered additional initiatives like structural genomics. The intention is to determine as many protein structures as possible, in the most efficient way, and to exploit the solved structures for the assignment of biological function to hypothetical proteins. We discuss the impact of these developments on protein classification, gene function prediction, and protein structure prediction.

Databases, Factual↗
PubMed2000

Structure-based evaluation of sequence comparison and fold recognition alignment accuracy.

The biological role, biochemical function, and structure of uncharacterized protein sequences is often inferred from their similarity to known proteins. A constant goal is to increase the reliability, sensitivity, and accuracy of alignment techniques to enable the detection of increasingly distant relationships. Development, tuning, and testing of these methods benefit from appropriate benchmarks for the assessment of alignment accuracy.Here, we describe a benchmark protocol to estimate sequence-to-sequence and sequence-to-structure alignment accuracy. The protocol consists of structurally related pairs of proteins and procedures to evaluate alignment accuracy over the whole set. The set of protein pairs covers all the currently known fold types. The benchmark is challenging in the sense that it consists of proteins lacking clear sequence similarity. Correct target alignments are derived from the three-dimensional structures of these pairs by rigid body superposition. An evaluation engine computes the accuracy of alignments obtained from a particular algorithm in terms of alignment shifts with respect to the structure derived alignments. Using this benchmark we estimate that the best results can be obtained from a combination of amino acid residue substitution matrices and knowledge-based potentials.

Algorithms↗
PubMed2000

Characterization of novel proteins based on known protein structures.

The genome sciences face the challenge to characterize structure and function of a vast number of novel genes. Sequence search techniques are used to infer functional and structural information from similarities to experimentally characterized genes or proteins. The persistent goal is to refine these techniques and to develop alternative and complementary methods to increase the range of reliable inference.Here, we focus on the structural and functional assignments that can be inferred from the known three-dimensional structures of proteins. The study uses all structures in the Protein Data Bank that were known by the end of 1997. The protein structures released in 1998 were then characterized in terms of functional and structural similarity to the previously known structures, yielding an estimate of the maximum amount of information on novel protein sequences that can be obtained from inference techniques. The 147 globular proteins corresponding to 196 domains released in 1998 have no clear sequence similarity to previously known structures. However, 75 % of the domains have extensive structure similarity to previously known folds, and most importantly, in two out of three cases similarity in structure coincides with related function. In view of this analysis, full utilization of existing structure data bases would provide information for many new targets even if the relationship is not accessible from sequence information alone. Currently, the most sophisticated techniques detect of the order of one-third of these relationships.

Amino Acid Sequence↗
PubMed2000

ProSup: a refined tool for protein structure alignment.

We investigated and optimized a method for structure comparison which is based on rigid body superimposition. The method maximizes the number of structurally equivalent residues while keeping the root mean square deviation constant. The resulting number of equivalent residues then provides an adequate similarity measure, which is easy to interpret. We demonstrate that the approach is able to detect remote structural similarity. We show that the number of equivalent residues is a suitable measure for ranking database searches and that the results are in good agreement with expert knowledge protein structure classification. Structure comparison frequently has multiple solutions. The approach that we use provides a range of alternative alignments rather a single solution. We discuss the nature of alternative solutions on several examples.

Algorithms↗
PubMed2000

Structure-derived substitution matrices for alignment of distantly related sequences.

Sequence alignment is a standard method to infer evolutionary, structural, and functional relationships among sequences. The quality of alignments depends on the substitution matrix used. Here we derive matrices based on superimpositions from protein pairs of similar structure, but of low or no sequence similarity. In a performance test the matrices are compared with 12 other previously published matrices. It is found that the structure-derived matrices are applicable for comparisons of distantly related sequences. We investigate the influence of evolutionary relationships of protein pairs on the alignment accuracy.

Models, Molecular↗
PubMed1999

Who solved the protein folding problem?

For the third time, techniques for the prediction of three-dimensional structures of proteins were critically assessed in a worldwide blind test. Steady progress is undeniable. How did this happen and what are the implications?

Algorithms↗
PubMed1999

An attempt to analyse progress in fold recognition from CASP1 to CASP3.

The Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment has been conducted for the third time. An obvious question is whether there has been progress from CASP1 to CASP3. An analysis depends on many variables, including prediction category, number and difficulty of targets, methods used to evaluate prediction success, and the rules for submission. It also depends on whether progress is measured in terms of all predictions submitted or in terms of the best predictions for each target. The progress made by individual groups is another interesting issue. In view of this complexity and the limited amount of data, an objective estimate of progress is difficult to obtain. Despite such difficulties, some estimate of progress is desirable. Here, we present an attempt to quantify progress in the fold-recognition category from CASP1 to CASP3. The numbers indicate clear progress from CASP1 to CASP2 but no improvement from CASP2 to CASP3. However, we argue that the targets in CASP3 are more difficult compared with CASP2, which translates into better performance of CASP3 over CASP2.

Autoantigens↗
PubMed1999

Automated large scale evaluation of protein structure predictions.

Evaluation and assessment are critical issues in CASP experiments. Automated procedures are necessary to compare a large number of predictions with the target folds. The evaluation has to reveal the maximum extent of similarity between predictions and targets, it should be applicable across prediction categories, and it should be transparent and accessible to a wide community. Here we present an automated evaluation scheme which is an attempt to meet these requirements. In the implementation and execution of this scheme we had to solve or circumvent problems of convergence, where algorithms fail to find optimum solutions, problems of ambiguity where no unique optimum solution exists, and problems in ranking and interpretation. Key features of this implementation are (1) the root mean square deviation of structure superimposition is kept close to a constant value throughout the evaluation and (2) all structural matches found between two folds are taken into account. We discuss these points in detail and describe the numerical criteria used in the CASP3 evaluation.

Algorithms↗
PubMed1999

Sustained performance of knowledge-based potentials in fold recognition.

We describe the results obtained using fold recognition techniques in our third participation in the CASP experiment. The approach relies on knowledge-based potentials for alignment production and fold identification. As indicated by the increase in alignment quality and fold identification reliability, the predictions improved from CASP1 to CASP3. In particular, we identified structural relationships in which no known evolutionary link exists. Our predictions are based on single sequences rather than multiple sequence alignments. Additionally, we voluntarily submitted only a single model for each target because, in our view, submission of a single model is the most stringent test. We describe the methods used, the strategy adopted in the predictions, and the prediction results and discuss future work.

Algorithms↗
PubMed1998

Knowledge-based potentials--back to the roots.

Applications of knowledge-based quantities in protein structure theory are well established but their theoretical foundation, physical interpretation, and range of applicability seems unclear or even controversial. Moreover, the current literature contains terms like "pseudo-energy", "energy-like quantity", or "true energy" which are vague and unclear and terms like "mean-force potential" corresponding to well defined concepts. Seemingly contradictory results are often caused by inconsistent terminology. Often such problems are resolved when the physical nature of the involved quantities is properly defined. We summarize the fundamental principles of mean-force potentials and radial distribution functions as defined in statistical mechanics and put these into perspective with the term "knowledge-based potential".

Databases, Factual↗
PubMed1997

Protein folds from pair interactions: a blind test in fold recognition.

We submitted nine predictions to CASP2 using our fold recognition program ProFIT. Two of these structures were still unsolved by the end of the experiment, six had a recognizable fold, and one fold was new. Four predictions of the six recognizable folds were correct. Two models were excellent in terms of alignment quality (T0031, T0004): in one the alignment was partially correct (T0014), and one fold was correctly identified (T0038). We discuss improvements of the program and analyze the prediction results.

Aldose-Ketose Isomerases↗
PubMed1997

Neutral networks in protein space: a computational study based on knowledge-based potentials of mean force.

BACKGROUND: Many protein sequences, often unrelated, adopt similar folds. Sequences folding into the same shape thus form subsets of sequence space. The shape and the connectivity of these sets have implications for protein evolution and de novo design. RESULTS: We investigate the topology of these sets for some proteins with known three-dimensional structure using inverse folding techniques. First, we find that sequences adopting a given fold do not cluster in sequence space and that there is no detectable sequence homology among them. Nevertheless, these sequences are connected in the sense that there exists a path such that every sequence can be reached from every other sequence while the fold remains unchanged. We find similar results for restricted amino acid alphabets in some cases (e. g. ADLG). In other cases, it seems impossible to find sequences with native-like behavior (e.g. QLR). These findings seem to be independent of the particular structure considered. CONCLUSIONS: Amino acid sequences folding into a common shape are distributed homogeneously in sequence space. Hence, the connectivity of the set of these sequences implies the existence of very long neutral paths on all examined protein structures. Regarding protein design, these results imply that sequences with more or less arbitrary chemical properties can be attached to a given structural framework. But we also observe that designability varies significantly among native structures. These features of protein sequence space are similar to what has been found for nucleic acids.

Amino Acids↗
PubMed1996

Helmholtz free energy of peptide hydrogen bonds in proteins.

We estimate the Helmholtz free energy of peptide hydrogen bonds in native protein structures as a function of spatial separation between donor and acceptor atoms. The resulting potential function has a deep narrow well at H-bond contact but bond formation is hindered by a barrier and the net change in free energy is close to zero. The barrier provides a molecular lock mechanism acting as a kinetic trap. Once formed, H-bonds keep protein chains in a precise orientation. However, bond formation requires energy input and opposes protein folding. In contrast, the free energy functions of most side-chain interactions have no energy barriers. They lack spatial precision but free energy differences of contact formation are substantial. These interactions drive folding and stabilize structures but precision is mediated and maintained by H-bonds.

Arginine↗
PubMed1996

Optimum superimposition of protein structures: ambiguities and implications.

BACKGROUND: Techniques for comparison and optimum superimposition of protein structures are indispensable tools, providing the basis for statistical analysis, modeling, prediction and classification of protein folds. Observed similarity of structures is frequently interpreted as an indication of evolutionary relatedness. A variety of advanced techniques are available, but so far the important issue of uniqueness of structural superimposition has been largely neglected. We set out to investigate this issue by implementing an efficient algorithm for structure superimposition enabling routine searches for alternative alignments. RESULTS: The algorithm is based on optimum superimposition of structures and dynamic programming. The implementation is tested and validated using published results. In particular, an automatic classification of all protein folds in a recent release of the protein data bank is performed. The results obtained are closely related to published data. Surprisingly, for many protein pairs alternative alignments are obtained. These alignments are indistinguishable in terms of number of equivalent residues and root mean square error of superimposition, but the respective sets of equivalent residue pairs are completely distinct. Alternative alignments are observed for all protein architectures, including mixed alpha/beta folds. CONCLUSIONS: Superimposition of protein folds is frequently ambiguous. This has several implications on the interpretation of structural similarity with respect to evolutionary relatedness and it restricts the range of applicability of superimposed structures in statistical analysis. In particular, studies based on the implicit assumption that optimum superimposition of structures is unique are bound to be misleading.

Algorithms↗
PubMed1996

Helmholtz free energies of atom pair interactions in proteins.

BACKGROUND: Proteins fold to unique three-dimensional structures, but how they achieve this transition and how they maintain their native folds is controversial. Information on the functional form of molecular interactions is required to address these issues. The basic building blocks are the free energies of atom pair interactions in dense protein solvent systems. In a dense medium, entropic effects often dominate over internal energies but free energy estimates are notoriously difficult to obtain. A prominent example is the peptide hydrogen bond (H-bond). It is still unclear to what extent H-bonds contribute to protein folding and stability of native structures. RESULTS: Radial distribution functions of atom pair interactions are compiled from a database of known protein folds. The functions are transformed to Helmholtz free energies using a recipe from the statistical mechanics of dense interacting systems. In particular we concentrate on the features of the free energy functions of peptide H-bonds. Differences in Helmholtz free energies correspond to the reversible work required or gained when the distance between two particles is changed. Consequently, the functions directly display the energetic features of the respective thermodynamic process, such as H-bond formation or disruption. CONCLUSIONS: In the H-bond potential, a high barrier isolates a deep narrow minimum at H-bond contact from large distances, but the free energy difference between H-bond contact and large distances is close to zero. The energy barrier plays an intriguing role in H-bond formation and disruption: both processes require activation energy in the order of 2kT. H-bond formation opposes folding to compact states, but once formed, H-bonds act as molecular locks and a network of such bonds keeps polypeptide chains in a precise spatial configuration. On the other hand, peptide H-bonds do not contribute to the thermodynamic stability of native folds, because the energy balance of H-bond formation is close to zero.

Drug Stability↗
PubMed1995

Progress in fold recognition.

The prediction experiment reveals that fold recognition has become a powerful tool in structural biology. We applied our fold recognition technique to 13 target sequences. In two cases, replication terminating protein and prosequence of subtilisin, the predicted structures are very similar to the experimentally determined folds. For the first time, in a public blind test, the unknown structures of proteins have been predicted ahead of experiment to an accuracy approaching molecular detail. In two other cases the approximate folds have been predicted correctly. According to the assessors there were 12 recognizable folds among the target proteins. In our postprediction analysis we find that in 7 cases our fold recognition technique is successful. In several of the remaining cases the predicted folds have interesting features in common with the experimental results. We present our procedure, discuss the results, and comment on several fundamental and technical problems encountered in fold recognition.

Algorithms↗