Biomedical subjects

P Lackner

Publications and source records attributed to P Lackner.

7 recordsLinked to original sources

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↗

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↗

PubMed1992

Assembly of polypeptide and protein backbone conformations from low energy ensembles of short fragments: development of strategies and construction of models for myoglobin, lysozyme, and thymosin beta 4.

Recently we developed methods for the construction of knowledge-based mean fields from a data base of known protein structures. As shown previously, this approach can be used to calculate ensembles of probable conformations for short fragments of polypeptide chains. Here we develop procedures for the assembly of short fragments to complete three-dimensional models of polypeptide chains. The amino acid sequence of a given protein is decomposed into all possible overlapping fragments of a given length, and an ensemble of probable conformations is calculated for each fragment. The fragments are assembled to a complete model by choosing appropriate conformations from the individual ensembles and by averaging over equivalent angles. Finally a consistent model is obtained by rebuilding the conformation from the average angles. From the average angles the local variability of the structure can be calculated, which is a useful criterion for the reliability of the model. The procedure is applied to the calculation of the local backbone conformations of myoglobin and lysozyme whose structures have been solved by X-ray analysis and thymosin beta 4, a polypeptide of 43 amino acid residues whose structure was recently investigated by NMR spectroscopy. We demonstrate that substantial fractions of the calculated local backbone conformations are similar to the experimentally determined structures.

Amino Acid Sequence↗

PubMed1990

Identification of native protein folds amongst a large number of incorrect models. The calculation of low energy conformations from potentials of mean force.

We present an approach that is able to detect native folds amongst a large number of non-native conformations. The method is based on the compilation of potentials of mean force of the interactions of the C beta atoms of all amino acid pairs from a database of known three-dimensional protein structures. These potentials are used to calculate the conformational energy of amino acid sequences in a number of different folds. For a substantial number of proteins we find that the conformational energy of the native state is lowest amongst the alternatives. Exceptions are proteins containing large prosthetic groups, Fe-S clusters or polypeptide chains that do not adopt globular folds. We discuss briefly potential applications in various fields of protein structural research.

Animals↗