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Teresa Head-Gordon

Publications and source records attributed to Teresa Head-Gordon.

8 recordsLinked to original sources
PubMed2003

Coarse-grained sequences for protein folding and design.

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the alpha/beta ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design.

Amino Acid Sequence↗
PubMed2003

Cool walking: a new Markov chain Monte Carlo sampling method.

Effective relaxation processes for difficult systems like proteins or spin glasses require special simulation techniques that permit barrier crossing to ensure ergodic sampling. Numerous adaptations of the venerable Metropolis Monte Carlo (MMC) algorithm have been proposed to improve its sampling efficiency, including various hybrid Monte Carlo (HMC) schemes, and methods designed specifically for overcoming quasi-ergodicity problems such as Jump Walking (J-Walking), Smart Walking (S-Walking), Smart Darting, and Parallel Tempering. We present an alternative to these approaches that we call Cool Walking, or C-Walking. In C-Walking two Markov chains are propagated in tandem, one at a high (ergodic) temperature and the other at a low temperature. Nonlocal trial moves for the low temperature walker are generated by first sampling from the high-temperature distribution, then performing a statistical quenching process on the sampled configuration to generate a C-Walking jump move. C-Walking needs only one high-temperature walker, satisfies detailed balance, and offers the important practical advantage that the high and low-temperature walkers can be run in tandem with minimal degradation of sampling due to the presence of correlations. To make the C-Walking approach more suitable to real problems we decrease the required number of cooling steps by attempting to jump at intermediate temperatures during cooling. We further reduce the number of cooling steps by utilizing "windows" of states when jumping, which improves acceptance ratios and lowers the average number of cooling steps. We present C-Walking results with comparisons to J-Walking, S-Walking, Smart Darting, and Parallel Tempering on a one-dimensional rugged potential energy surface in which the exact normalized probability distribution is known. C-Walking shows superior sampling as judged by two ergodic measures.

Journal Article↗
PubMed2003

Minimalist models for protein folding and design.

Protein folding research during the past decade has emphasized the dominant role of native state topology in determining the speed and mechanism of folding for small proteins; this has been illustrated by simulations using minimalist protein models. The advantages of minimalist protein models lie in their ability to rapidly collect meaningful statistics about folding pathways and kinetics, their ease of characterization with coarse-grained order parameters and their concentration on the essential physics of the problem to connect with experimental observables for a target protein. The maturation of experimental protein folding has driven the need for more quantitative protein simulations to better understand the balance between sequence details and fold topology. In the past year, we have seen the emergence of more complex minimalist models, ranging from all-atom Gō potentials to coarse-grained bead models in which Gō interactions are replaced or supplemented by more physically motivated potentials. The reduced computational cost at the coarse-grained level of abstraction will potentially enable both folding studies on a genomic scale and systematic application in protein design.

Bacterial Proteins↗
PubMed2002

Toward minimalist models of larger proteins: a ubiquitin-like protein.

Our recently developed off-lattice bead model capable of simulating protein structures with mixed alpha/beta content has been extended to model the folding of a ubiquitin-like protein and provides a means for examining the more complex kinetics involved in the folding of larger proteins. Using trajectories generated from constant-temperature Langevin dynamics simulations and sampling with the multiple multi-histogram method over five-order parameters, we are able to characterize the free energy landscape for folding and find evidence for folding through compact intermediates. Our model reproduces the observation that the C-terminus loop structure in ubiquitin is the last to fold in the folding process and most likely plays a spectator role in the folding kinetics. The possibility of a productive metastable intermediate along the folding pathway consisting of collapsed states with no secondary structure, and of intermediates or transition structures involving secondary structural elements occurring early in the sequence, is also supported by our model. The kinetics of folding remain multi-exponential below the folding temperature, with glass-like kinetics appearing at T/T(f) approximately 0.86. This new physicochemical model, designed to be predictive, helps validate the value of modeling protein folding at this level of detail for genomic-scale studies, and motivates further studies of other protein topologies and the impact of more complex energy functions, such as the addition of solvation forces.

Amino Acid Sequence↗
PubMed2002

Modeling chemical bonding effects for protein electron crystallography: the transferable fragmental electrostatic potential (TFESP) method.

This paper addresses the problem of determining the electrostatic potential of large proteins by the superposition of potentials calculated for small fragments. The use of different atomic and molecular fragments is considered for reproducing the molecular electrostatic potential of different conformations of N-acetylalanine methylamide (NAAMA) with an acceptable degree of error as measured by conventional R factors used in crystallographic structure refinement. Three different divisions of NAAMA are tested, producing fragments that incorporate increasingly more complete descriptions of molecular bonding with diminishing accuracy in geometric fit to the parent molecule: single atoms in molecules, bonded atoms in molecules and selected functional groups, such as the backbone peptide moiety, or the alpha-carbon, beta-carbon and their associated H atoms. In the resolution range 2.5-25A, the fairly straightforward use of single atoms in molecules reduces the calculated R factors by 5-15% over a free-atom superposition. No significant further improvement was found at the lowest resolutions with a superposition of single bonds in molecules and R factors were found to degrade with larger fragments at higher resolutions because of poor geometry fits to the atoms of the parent molecule. Because the potential distribution even for single atoms depends on the environment, the best accuracy will be obtained by using a library of fragment potentials calculated for each type of atom as a function of important protein conformations.

Algorithms↗
PubMed2002

A physical approach to protein structure prediction.

We describe our global optimization method called Stochastic Perturbation with Soft Constraints (SPSC), which uses information from known proteins to predict secondary structure, but not in the tertiary structure predictions or in generating the terms of the physics-based energy function. Our approach is also characterized by the use of an all atom energy function that includes a novel hydrophobic solvation function derived from experiments that shows promising ability for energy discrimination against misfolded structures. We present the results obtained using our SPSC method and energy function for blind prediction in the 4th Critical Assessment of Techniques for Protein Structure Prediction competition, and show that our approach is more effective on targets for which less information from known proteins is available. In fact our SPSC method produced the best prediction for one of the most difficult targets of the competition, a new fold protein of 240 amino acids.

Algorithms↗
PubMed2002

Protein engineering study of protein L by simulation.

We examine the ability of our recently introduced minimalist protein model to reproduce experimentally measured thermodynamic and kinetic changes upon sequence mutation in the well-studied immunoglobulin-binding protein L. We have examined five different sequence mutations of protein L that are meant to mimic the same mutation type studied experimentally: two different mutations which disrupt the natural preference in the beta-hairpin #1 and beta-hairpin #2 turn regions, two different helix mutants where a surface polar residue in the alpha-helix has been mutated to a hydrophobic residue, and a final mutant to further probe the role of nonnative hydrophobic interactions in the folding process. These simulated mutations are analyzed in terms of various kinetic and thermodynamic changes with respect to wild type, but in addition we evaluate the structure-activity relationship of our model protein based on the phi-value calculated from both the kinetic and thermodynamic perspectives. We find that the simulated thermodynamic phi-values reproduce the experimental trends in the mutations studied and allow us to circumvent the difficult interpretation of the complicated kinetics of our model. Furthermore, the level of resolution of the model allows us to directly predict what experiments seek in regard to protein engineering studies of protein folding--namely the residues or portions of the polypeptide chain that contribute to the crucial step in the folding of the wild-type protein.

Bacterial Proteins↗