Biomedical subjects

A Elofsson

Publications and source records attributed to A Elofsson.

26 records · Page 2Linked to original sources

PubMed1997

Prediction of transmembrane alpha-helices in prokaryotic membrane proteins: the dense alignment surface method.

A new, simple method for predicting transmembrane segments in integral membrane proteins has been developed. It is based on low-stringency dot-plots of the query sequence against a collection of non-homologous membrane proteins using a previously derived scoring matrix [Cserzö et al., 1994, J. Mol. Biol., 243, 388-396]. This so-called dense alignment surface (DAS) method is shown to perform on par with earlier methods that require extra information in the form of multiple sequence alignments or the distribution of positively charged residues outside the transmembrane segments, and thus improves prediction abilities when only single-sequence information is available or for classes of membrane proteins that do not follow the 'positive inside' rule.

Cell Membrane↗

PubMed1996

A study of combined structure/sequence profiles.

BACKGROUND: For genome sequencing projects to achieve their full impact on biology and medicine, each protein sequence must be identified with its three-dimensional structure. Fold assignment methods (also called profile and threading methods) attempt to assign sequences to known protein folds by computing the compatibility of sequence to fold. RESULTS: We have extended profile methods for the detection of protein folds having structural similarity but low sequence similarity to sequence probes. Our extension combines sequence substitution tables with structural properties to form a combined profile. The structural properties used in this study include distances between residues, exposed areas, areas buried by polar atoms, and properties of the original three-dimensional profile method. We compared the performance of these combined profiles with different sequence matrices and with the original three-dimensional profile method. To determine the optimal gap penalties and weights used with these profiles, we employed a genetic algorithm. The performance of these combined profiles was tested by cross validation using independent test and training sets. CONCLUSIONS: These studies show that the combined profiles perform better than profiles based on either structural or sequence information alone.

Algorithms↗

PubMed1996

Assessing the performance of fold recognition methods by means of a comprehensive benchmark.

Recently there has been an explosion of methods for fold recognition. These methods seek to align a protein sequence to a three-dimensional structure and measure the compatibility of the sequence to the structure. In this work, we present a benchmark to assess the performance of such methods. The benchmark consists of a set of protein sequences matched by superposition to known structures. This set covers a wide range of protein families, and includes matching proteins with insignificant sequence similarity. To demonstrate the usefulness of this benchmark, we apply it here to compare different fold-recognition methods developed through the years in our group as well as several sequence-sequence substitution matrices. The results show that "global-local" alignments are superior to either local or global alignments. The most effective sequence-sequence matching matrix is the Gonnet table. The best performance overall is obtained by a method which combines the 3D-1D profiles of Bowie et al. with a substitution matrix and takes into account residue pairwise interactions.

Amino Acid Sequence↗

PubMed1995

Local moves: an efficient algorithm for simulation of protein folding.

We have enhanced genetic algorithms and Monte Carlo methods for simulation of protein folding by introducing "local moves" in dihedral space. A local move consists of changes in backbone dihedral angles in a sequential window while the positions of all atoms outside the window remain unchanged. We find three advantages of local moves: (1) For some energy functions, protein conformations of lower energy are found; (2) these low energy conformations are found in fewer steps; and (3) the simulations are less sensitive to the details of the annealing protocol. To distinguish the effectiveness of local move algorithm from the complexity of the energy function, we have used several different energy functions. These energy functions include the Profile score (Bowie et al., Science 253:164-170, 1991), the knowledge-based energy function used by Bowie and Eisenberg 1994 (Proc. Natl. Acad. Sci. U.S.A. 91:4434-4440, 1994), two energy terms developed as suggested by Sippl and coworkers (Hendlich et al., J. Mol. Biol. 216:167-180, 1990), and AMBER (Weiner and Kollman, J. Comp. Chem. 2:287-303, 1981). Besides these energy functions we have used three energy functions that include knowledge of the native structures: the RMSD from the native structure, the distance matrix error, and an energy term based on the distance between different residue types called DBIN. In some of these simulations the main advantage of local moves is the reduced dependence on the details of the annealing schedule. In other simulations, local moves are superior to other algorithms as structures with lower energy are found.

Algorithms↗

PubMed1993

How consistent are molecular dynamics simulations? Comparing structure and dynamics in reduced and oxidized Escherichia coli thioredoxin.

In this study we have examined several parameters that can be used for checking the consistency and accuracy of protein structures and molecular dynamics simulations. This is done by comparing: (1) three X-ray structures of oxidized Escherichia coli thioredoxin (Trx-S2); (2) 14 NMR structures of reduced E. coli thioredoxin (Trx-(SH)2); and (3) 30 different simulations, 15 of Trx-S2 and 15 of Trx-(SH)2. The energy, the agreement with NOE data, the root-mean-square deviation between structures, and the surface characteristics of all these structures are analyzed. The 30 simulations, four water simulations, 20 standard vacuum simulations and six alternative vacuum simulations, are examined with respect to mobility, temperature factors and aromatic side-chain mobility. It is shown that although vacuum simulations may reproduce some parameters, all the features of a water simulation cannot be reproduced in any of these simulations. Several of the parameters described above are shown to be good for discriminating between an accurate and an inaccurate simulation. It is also shown that 100 ps is too short a time to obtain statistically certain temperature factors and correlation functions of aromatic side-chain motions. The results also suggest that performing ten 100 ps simulations spans the conformation space better than one 1 ns simulation.

Computer Simulation↗

PubMed1993

Site specific point mutation changes specificity: a molecular modeling study by free energy simulations and enzyme kinetics of the thermodynamics in ribonuclease T1 substrate interactions.

We have theoretically and experimentally studied the binding of two different ligands to wild-type ribonuclease T1 (RNT1) and to a mutant of RNT1 with Glu-46 replaced by Gln. The binding of the natural substrate 3'-GMP has been compared with the binding of a fluorescent probe, 2-aminopurine 3'-monophosphate (2AP), and relative free energies of binding of these ligands to the mutant and the wild-type (wt) enzyme have been calculated by free energy perturbation methods. The free energy perturbations predict that the mutant RNT1-Gln-46 binds 2AP better than 3'GMP, in agreement with experiments on dinucleotides. Four free energy perturbations, forming a closed loop, have been performed to allow the detection of systematic errors in the simulation procedure. Because of the larger number of atoms involved, it was necessary to use a much longer simulation time for the change in the protein, i,e., the perturbation from Glu to Gln, than in the perturbation from 3'-GMP to 2AP. Finally the structure of the binding site is analyzed for understanding differences in catalytic speed and binding strength.

2-Aminopurine↗

PubMed1991

Motion of aromatic side chains, picosecond fluorescence, and internal energy transfer in Escherichia coli thioredoxin studied by site-directed mutagenesis, time-resolved fluorescence spectroscopy, and molecular dynamics simulations.

We have determined the picosecond fluorescence of the four aromatic amino acid residues (W28, W31, Y49, and Y70) in wild-type Escherichia coli thioredoxin (wt Trx) and a mutant Trx with W31 replaced by phenylalanine, Trx-W28-W31F. The internal motions of the four aromatic side chains were also analyzed. We examined the possibility of using internal energy transfer from tyrosine to tryptophan as a measure of long-range distances. The major features of the lifetime distribution of tryptophan fluorescence were unchanged in the W31F mutation, indicating that the environment of W28 is similar in both wt Trx and Trx-W28-W31F. However, the mutation of W31F changed the mobility of W28, situated close to the active-site disulfide/dithiol, but not the mobility of two tyrosines, Y49 and Y70, situated on the other side of the molecule. The mobility of the two tyrosine residues increased upon reduction of the active-site disulfide, indicating a looser structure with reduction. This increased motion could also be seen from molecular dynamics simulations. The change in energy transfer rates, as judged by tyrosine fluorescence lifetimes, was in agreement with energy transfer rates calculated from the molecular dynamics simulations. The anisotropy of tryptophan and tyrosine fluorescence could be separated in three parts: (I) overall rotation of the protein (10(-9)s), (II) internal mobility of side chains (10(-10)s), and (III) a very fast relaxation (10(-12)s). We can only experimentally detect this very fast relaxation when the internal motion is not present.

Amino Acids↗

PubMed1990

Studies on somatostatin with time-resolved spectroscopy and molecular dynamics simulations.

Somatostatin was studied by time-resolved fluorescence spectroscopy and by molecular dynamics simulations. The results obtained indicate the existence of mainly one conformation in DMSO, and the existence of several conformations in other solvents. Molecular dynamics simulations showed that the most important region for activity (residue 7-9) is also the most flexible region in the peptide.

Computer Simulation↗