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School of Biological Sciences

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https://hdl.handle.net/1853/70750

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Organizational Unit

College of Sciences

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Organizational Unit

Center for the Study of Systems Biology

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1131

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Publication Search Results

Now showing 1 - 9 of 9

Unfolding of globular proteins: monte carlo dynamics of a realistic reduced model

(Georgia Institute of Technology, 2003-11) Kolinski, Andrzej ; Klein, Piotr ; Romiszowski, Piotr ; Skolnick, Jeffrey

Reduced lattice models of proteins and Monte Carlo dynamics were used to simulate the initial stages of the unfolding of several proteins of various structural types, and the results were compared to experiment. The models semiquantitatively reproduce the approximate order of events of unfolding as well as subtle mutation effects and effects resulting from differences in sequences of similar folds. The short-time mobility of particular residues, observed in simulations, correlates with the crystallographic temperature factor. The main factor controlling unfolding is the native state topology, with sequence playing a less important role. The correlation with various experiments, especially for sequence-specific effects, strongly suggests that properly designed reduced models of proteins can be used for qualitative studies (or prediction) of protein unfolding pathways
TOUCHSTONE II: a new approach to ab initio protein structure prediction

(Georgia Institute of Technology, 2003-08) Zhang, Yang ; Kolinski, Andrzej ; Skolnick, Jeffrey

We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting Ca atoms, with attached Cb atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical analysis of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30 3 60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36 ; 120 residues) with predicted structures having a RMSD from native below 6.5 A˚ in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36 ; 174 residues) with structures having a RMSD to native below 6.5 A˚ in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, especially when the accuracy of side-chain contact prediction is [20%. For native fold selection, we introduce quantities dependent on the cluster density and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.
A minimal physically realistic protein-like lattice model: designing an energy landscape that ensures all-or-none folding to a unique native state

(Georgia Institute of Technology, 2003-03) Pokarowski, Piotr ; Kolinski, Andrzej ; Skolnick, Jeffrey

A simple protein model restricted to the face-centered cubic lattice has been studied. The model interaction scheme includes attractive interactions between hydrophobic (H) residues, repulsive interactions between hydrophobic and polar (P) residues, and orientation-dependent P-P interactions. Additionally, there is a potential that favors extended b-type conformations. A sequence has been designed that adopts a native structure, consisting of an antiparallel, six-member Greekkey b-barrel with protein-like structural degeneracy. It has been shown that the proposed model is a minimal one, i.e., all the above listed types of interactions are necessary for cooperative (all-or-none) type folding to the native state. Simulations were performed via the Replica Exchange Monte Carlo method and the numerical data analyzed via a multihistogram method.
Development of unified statistical potentials describing protein-protein interactions

(Georgia Institute of Technology, 2003-03) Lu, Hui ; Lu, Long ; Skolnick, Jeffrey

A residue-based and a heavy atom-based statistical pair potential are developed for use in assessing the strength of protein-protein interactions. To ensure the quality of the potentials, a nonredundant, high-quality dimer database is constructed. The protein complexes in this dataset are checked by a literature search to confirm that they form multimers, and the pairwise amino acid preference to interact across a protein-protein interface is analyzed and pair potentials constructed. The performance of the residue-based potentials is evaluated by using four jackknife tests and by assessing the potentials’ ability to select true protein-protein interfaces from false ones. Compared to potentials developed for monomeric protein structure prediction, the interdomain potential performs much better at distinguishing protein-protein interactions. The potential developed from homodimer interfaces is almost the same as that developed from heterodimer interfaces with a correlation coefficient of 0.92. The residue-based potential is well suited for genomic scale protein interaction prediction and analysis, such as in a recently developed threading-based algorithm, MULTIPROSPECTOR. However, the more time-consuming atom-based potential performs better in identifying near-native structures from docking generated decoys.
Numerical study of the entropy loss of dimerization and the folding thermodynamics of the GCN4 leucine zipper

(Georgia Institute of Technology, 2002-11) Viñals, Jorge ; Kolinski, Andrzej ; Skolnick, Jeffrey

A lattice-based model of a protein and the Monte Carlo simulation method are used to calculate the entropy loss of dimerization of the GCN4 leucine zipper. In the representation used, a protein is a sequence of interaction centers arranged on a cubic lattice, with effective interaction potentials that are both of physical and statistical nature. The Monte Carlo simulation method is then used to sample the partition functions of both the monomer and dimer forms as a function of temperature. A method is described to estimate the entropy loss upon dimerization, a quantity that enters the free energy difference between monomer and dimer, and the corresponding dimerization reaction constant. As expected, but contrary to previous numerical studies, we find that the entropy loss of dimerization is a strong function of energy (or temperature), except in the limit of large energies in which the motion of the two dimer chains becomes largely uncorrelated. At the monomer-dimer transition temperature we find that the entropy loss of dimerization is approximately five times smaller than the value that would result from ideal gas statistics, a result that is qualitatively consistent with a recent experimental determination of the entropy loss of dimerization of a synthetic peptide that also forms a two-stranded -helical coiled coil.
Parallel-hat tempering: A Monte Carlo search scheme for the identification of low-energy structures

(Georgia Institute of Technology, 2001-09-15) Zhang, Yang ; Skolnick, Jeffrey

A new parallel-hat tempering algorithm has been developed for Monte Carlo simulations, in which a composite ensemble of noninteracting replicas of the molecule system at different temperatures is simulated, and the Markov process of each replica is driven by a hatlike weight factor with exponentially enhanced probability in both low- and high-energy regions. To test the algorithm, the methodology is applied to a homopolymeric protein chain located on a face-centered cubic lattice. We demonstrate that the ability of the current approach to search for low-energy molecule structures is significantly better than other Monte Carlo techniques found in the literature.
Computational studies of protein folding

(Georgia Institute of Technology, 2001-09) Skolnick, Jeffrey ; Kolinski, Andrzej

The authors describe the state of the art in the field of protein structure prediction. They also introduce Prospector, a newly developed, iterative threading algorithm for protein structure prediction that can also be applied to ab initio protein folding, and discuss the promising results of its large-scale application.
Sequence evolution and the mechanism of protein folding

(Georgia Institute of Technology, 2000-10) Ortiz, Angel R. ; Skolnick, Jeffrey

The impact on protein evolution of the physical laws that govern folding remains obscure. Here, by analyzing in silico-evolved sequences subjected to evolutionary pressure for fast folding, it is shown that: First, a subset of residues in the thermodynamic folding nucleus is mainly responsible for modulating the protein folding rate. Second and most important, the protein topology itself is of paramount importance in determining the location of these residues in the structure. Further stabilization of the interactions in this nucleus leads to fast folding sequences. Third, these nucleation points restrict the sequence space available to the protein during evolution. Correlated mutations between positions around these hot spots arise in a statistically significant manner, and most involve contacting residues. When a similar analysis is carried out on real proteins, qualitatively similar results are obtained.
Comparison of three Monte Carlo conformational search strategies for a proteinlike homopolymer model: Folding thermodynamics and identification of low-energy structures

(Georgia Institute of Technology, 2000-09-22) Gront, Dominik ; Kolinski, Andrzej ; Skolnick, Jeffrey

Entropy sampling Monte Carlo, the replica method, and the classical Metropolis scheme were applied in numerical studies of the collapse transition in a simple face-centered cubic lattice polymer. The force field of the model consists of pairwise, contact-type, long-range interactions and a short-range potential based on the β -sheet definition assumed in the model. The ability to find the lowest energy conformation by various Monte Carlo methods and the computational cost associated with each was examined. It is shown that all of the methods generally provide the same picture of the collapse transition. However, the most complete thermodynamic description of the transition derives from the results of entropy sampling Monte Carlo simulations, but this is the most time-consuming method. The replica method is shown to be the most effective and efficient in searching for the lowest energy conformation. The possible consequences of these findings for the development of simulation strategies for the folding of model proteins are discussed briefly.