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Biomedical subjects

K A Dill

Publications and source records attributed to K A Dill.

At least 19 recordsLinked to original sources
PubMed2001

Stabilization of proteins in confined spaces.

We present theory showing that confining a protein to a small inert space (a "cage") should stabilize the protein against reversible unfolding. Examples of such spaces might include the pores within chromatography columns, the Anfinsen cage in chaperonins, the interiors of ribosomes, or regions of steric occlusion inside cells. Confinement eliminates some expanded configurations of the unfolded chain, shifting the equilibrium from the unfolded state toward the native state. The partition coefficient for a protein in a confined space is predicted to decrease significantly when the solvent is changed from native to denaturing conditions. Small cages are predicted to increase the stability of the native state by as much as 15 kcal/mol. Confinement may also increase the rates of protein or RNA folding.

Chaperonins↗
PubMed2001

Are proteins well-packed?

The average packing density inside proteins is as high as in crystalline solids. Does this mean proteins are well-packed? We go beyond average densities, and look at the full distribution functions of free volumes inside proteins. Using a new and rigorous Delaunay triangulation method for parsing space into empty and filled regions, we introduce formal definitions of interior and surface packing densities. Although proteins look like organic crystals by the criterion of average density, they look more like liquids and glasses by the criterion of their free volume distributions. The distributions are broad, and the scalings of volume-to-surface, volume-to-cluster-radius, and numbers of void versus volume show that the interiors of proteins are more like randomly packed spheres near their percolation threshold than like jigsaw puzzles. We find that larger proteins are packed more loosely than smaller proteins. And we find that the enthalpies of folding (per amino acid) are independent of the packing density of a protein, indicating that van der Waals interactions are not a dominant component of the folding forces.

Computer Simulation↗
PubMed2001

Transition states and the meaning of Phi-values in protein folding kinetics.

What is the mechanism of two-state protein folding? The rate-limiting step is typically explored through a Phi-value, which is the mutation-induced change in the transition state free energy divided by the change in the equilibrium free energy of folding. Phi-values ranging from 0 to 1 have been interpreted as meaning the transition state is denatured-like (0), native-like (1) or in-between. But there is no classical interpretation for the experimental Phi-values that are negative or >1. Using a rigorous method to identity transition states via an exact lattice model, we find that nonclassical Phi-values can arise from parallel microscopic flow processes, such as those in funnel-shaped energy landscapes. Phi < 0 results when a mutation destabilizes a slow flow channel, causing a backflow into a faster flow channel. Phi > 1 implies the reverse: a backflow from a fast channel into a slow one. Using a 'landscape mapping' method, we find that Phi correlates with the acceleration/deceleration of folding induced by mutations, rather than with the degree of nativeness of the transition state.

Kinetics↗
PubMed2000

RNA folding energy landscapes.

Using a statistical mechanical treatment, we study RNA folding energy landscapes. We first validate the theory by showing that, for the RNA molecules we tested having only secondary structures, this treatment (i) predicts about the same native structures as the Zuker method, and (ii) qualitatively predicts the melting curve peaks and shoulders seen in experiments. We then predict thermodynamic folding intermediates. For one hairpin sequence, unfolding is a simple unzipping process. But for another sequence, unfolding is more complex. It involves multiple stable intermediates and a rezipping into a completely non-native conformation before unfolding. The principle that emerges, for which there is growing experimental support, is that although protein folding tends to involve highly cooperative two-state thermodynamic transitions, without detectable intermediates, the folding of RNA secondary structures may involve rugged landscapes, often with more complex intermediate states.

Base Sequence↗
PubMed2000

A method for parameter optimization in computational biology.

Models in computational biology, such as those used in binding, docking, and folding, are often empirical and have adjustable parameters. Because few of these models are yet fully predictive, the problem may be nonoptimal choices of parameters. We describe an algorithm called ENPOP (energy function parameter optimization) that improves-and sometimes optimizes-the parameters for any given model and for any given search strategy that identifies the stable state of that model. ENPOP iteratively adjusts the parameters simultaneously to move the model global minimum energy conformation for each of m different molecules as close as possible to the true native conformations, based on some appropriate measure of structural error. A proof of principle is given for two very different test problems. The first involves three different two-dimensional model protein molecules having 12 to 37 monomers and four parameters in common. The parameters converge to the values used to design the model native structures. The second problem involves nine bumpy landscapes, each having between 4 and 12 degrees of freedom. For the three adjustable parameters, the globally optimal values are known in advance. ENPOP converges quickly to the correct parameter set.

Algorithms↗
PubMed2000

Constraint-based assembly of tertiary protein structures from secondary structure elements.

A challenge in computational protein folding is to assemble secondary structure elements-helices and strands-into well-packed tertiary structures. Particularly difficult is the formation of beta-sheets from strands, because they involve large conformational searches at the same time as precise packing and hydrogen bonding. Here we describe a method, called Geocore-2, that (1) grows chains one monomer or secondary structure at a time, then (2) disconnects the loops and performs a fast rigid-body docking step to achieve canonical packings, then (3) in the case of intrasheet strand packing, adjusts the side-chain rotamers; and finally (4) reattaches loops. Computational efficiency is enhanced by using a branch-and-bound search in which pruning rules aim to achieve a hydrophobic core and satisfactory hydrogen bonding patterns. We show that the pruning rules reduce computational time by 10(3)- to 10(5)-fold, and that this strategy is computationally practical at least for molecules up to about 100 amino acids long.

Algorithms↗
PubMed1999

Designing polymers that mimic biomolecules.

A new field is emerging. Chemists are beginning to synthesize polymers with properties that are similar to those of proteins and RNA. Recent studies have identified oligomer backbones that form stable secondary structures. It is now possible to assemble specific sequences of diverse monomer sets into chain lengths that are nearly sufficient for tertiary structure formation. Such molecules will teach us how natural biopolymers fold; they will also enable us to design synthetic heteropolymers with novel structures and desirable functions.

Antibodies↗
PubMed1999

Predicting the structures of 18 peptides using Geocore.

We describe an extensive test of Geocore, an ab initio peptide folding algorithm. We studied 18 short molecules for which there are structures in the Protein Data Bank; chains are up to 31 monomers long. Except for the very shortest peptides, an extremely simple energy function is sufficient to discriminate the true native state from more than 10(8) lowest energy conformations that are searched explicitly for each peptide. A high incidence of native-like structures is found within the best few hundred conformations generated by Geocore for each amino acid sequence. Predictions improve when the number of discrete phi/psi choices is increased.

Algorithms↗
PubMed1999

The effect of multiple binding modes on empirical modeling of ligand docking to proteins.

A popular approach to the computational modeling of ligand/receptor interactions is to use an empirical free energy like model with adjustable parameters. Parameters are learned from one set of complexes, then used to predict another set. To improve these empirical methods requires an independent way to study their inherent errors. We introduce a toy model of ligand/receptor binding as a workbench for testing such errors. We study the errors incurred from the two state binding assumption--the assumption that a ligand is either bound in one orientation, or unbound. We find that the two state assumption can cause large errors in free energy predictions, but it does not affect rank order predictions significantly. We show that fitting parameters using data from high affinity ligands can reduce two state errors; so can using more physical models that do not use the two state assumption. We also find that when using two state models to predict free energies, errors are more severe on high affinity ligands than low affinity ligands. And we show that two state errors can be diagnosed by systematically adding new binding modes when predicting free energies: if predictions worsen as the modes are added, then the two state assumption in the fitting step may be at fault.

Computer Simulation↗
PubMed1999

Polymer principles and protein folding.

This paper surveys the emerging role of statistical mechanics and polymer theory in protein folding. In the polymer perspective, the folding code is more a solvation code than a code of local phipsi propensities. The polymer perspective resolves two classic puzzles: (1) the Blind Watchmaker's Paradox that biological proteins could not have originated from random sequences, and (2) Levinthal's Paradox that the folded state of a protein cannot be found by random search. Both paradoxes are traditionally framed in terms of random unguided searches through vast spaces, and vastness is equated with impossibility. But both processes are partly guided. The searches are more akin to balls rolling down funnels than balls rolling aimlessly on flat surfaces. In both cases, the vastness of the search is largely irrelevant to the search time and success. These ideas are captured by energy and fitness landscapes. Energy landscapes give a language for bridging between microscopics and macroscopics, for relating folding kinetics to equilibrium fluctuations, and for developing new and faster computational search strategies.

Biopolymers↗
PubMed1999

Predicting conformational switches in proteins.

We describe a new computational technique to predict conformationally switching elements in proteins from their amino acid sequences. The method, called ASP (Ambivalent Structure Predictor), analyzes results from a secondary structure prediction algorithm to identify regions of conformational ambivalence. ASP identifies ambivalent regions in 16 test protein sequences for which function involves substantial backbone rearrangements. In the test set, all sites previously described as conformational switches are correctly predicted to be structurally ambivalent regions. No such regions are predicted in three negative control protein sequences. ASP may be useful as a guide for experimental studies on protein function and motion in the absence of detailed three-dimensional structural data.

Adenylyl Cyclases↗
PubMed1998

Sequence-specific polypeptoids: a diverse family of heteropolymers with stable secondary structure.

We have synthesized and characterized a family of structured oligo-N-substituted-glycines (peptoids) up to 36 residues in length by using an efficient solid-phase protocol to incorporate chemically diverse side chains in a sequence-specific fashion. We investigated polypeptoids containing side chains with a chiral center adjacent to the main chain nitrogen. Some of these sequences have stable secondary structure, despite the achirality of the polymer backbone and its lack of hydrogen bond donors. In both aqueous and organic solvents, peptoid oligomers as short as five residues give rise to CD spectra that strongly resemble those of peptide alpha-helices. Differential scanning calorimetry and CD measurements show that polypeptoid secondary structure is highly stable and that unfolding is reversible and cooperative. Thermodynamic parameters obtained for unfolding are similar to those obtained for the alpha-helix to coil transitions of peptides. This class of biomimetic polymers may enable the design of self-assembling macromolecules with novel structures and functions.

Circular Dichroism↗
PubMed1998

NMR determination of the major solution conformation of a peptoid pentamer with chiral side chains.

Polymers of N-substituted glycines ("peptoids") containing chiral centers at the alpha position of their side chains can form stable structures in solution. We studied a prototypical peptoid, consisting of five para-substituted (S)-N-(1-phenylethyl)glycine residues, by NMR spectroscopy. Multiple configurational isomers were observed, but because of extensive signal overlap, only the major isomer containing all cis-amide bonds was examined in detail. The NMR data for this molecule, in conjunction with previous CD spectroscopic results, indicate that the major species in methanol is a right-handed helix with cis-amide bonds. The periodicity of the helix is three residues per turn, with a pitch of approximately 6 A. This conformation is similar to that anticipated by computational studies of a chiral peptoid octamer. The helical repeat orients the amide bond chromophores in a manner consistent with the intensity of the CD signal exhibited by this molecule. Many other chiral polypeptoids have similar CD spectra, suggesting that a whole family of peptoids containing chiral side chains is capable of adopting this secondary structure motif. Taken together, our experimental and theoretical studies of the structural properties of chiral peptoids lay the groundwork for the rational design of more complex polypeptoid molecules, with a variety of applications, ranging from nanostructures to nonviral gene delivery systems.

Circular Dichroism↗
PubMed1998

Protein folding in the landscape perspective: chevron plots and non-Arrhenius kinetics.

We use two simple models and the energy landscape perspective to study protein folding kinetics. A major challenge has been to use the landscape perspective to interpret experimental data, which requires ensemble averaging over the microscopic trajectories usually observed in such models. Here, because of the simplicity of the model, this can be achieved. The kinetics of protein folding falls into two classes: multiple-exponential and two-state (single-exponential) kinetics. Experiments show that two-state relaxation times have "chevron plot" dependences on denaturant and non-Arrhenius dependences on temperature. We find that HP and HP+ models can account for these behaviors. The HP model often gives bumpy landscapes with many kinetic traps and multiple-exponential behavior, whereas the HP+ model gives more smooth funnels and two-state behavior. Multiple-exponential kinetics often involves fast collapse into kinetic traps and slower barrier climbing out of the traps. Two-state kinetics often involves entropic barriers where conformational searching limits the folding speed. Transition states and activation barriers need not define a single conformation; they can involve a broad ensemble of the conformations searched on the way to the native state. We find that unfolding is not always a direct reversal of the folding process.

Animals↗
PubMed1998

Native protein fluctuations: the conformational-motion temperature and the inverse correlation of protein flexibility with protein stability.

We study the fluctuations of native proteins by exact enumeration using the HP lattice model. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This prediction is consistent with the observation by Tilton et al. [R. F. Tilton, Jr., J. C. Dewan, and G. A. Petsko, Biochemistry 31, 2469 (1992)], that the thermal motions of ribonuclease A increase sharply above about 200 K. We also explore protein "flexibility" as defined by Debye-Waller-like factors and solvent accessibilities of core residues to hydrogen exchange. We find that proteins having greater stability tend to have fewer large fluctuations, and hence lower flexibilities. If flexibility is necessary for enzyme catalysis, this could explain why proteins from thermophilic organisms, which are exceptionally stable, may be catalytically inactive at normal temperatures.

Enzymes↗
PubMed1997

Ligand binding to proteins: the binding landscape model.

Models of ligand binding are often based on four assumptions: (1) steric fit: that binding is determined mainly by shape complementarity; (2) native binding: that ligands mainly bind to native states; (3) locality: that ligands perturb protein structures mainly at the binding site; and (4) continuity: that small changes in ligand or protein structure lead to small changes in binding affinity. Using a generalization of the 2D HP lattice model, we study ligand binding and explore these assumptions. We first validate the model by showing that it reproduces typical binding behaviors. We observe ligand-induced denaturation, ANS and heme-like binding, and "lock-and-key" and "induced-fit" specific binding behaviors characterized by Michaelis-Menten or more cooperative types of binding isotherms. We then explore cases where the model predicts violations of the standard assumptions. For example, very different binding modes can result from two ligands of identical shape. Ligands can sometimes bind highly denatured states more tightly than native states and yet have Michaelis-Menten isotherms. Even low-population binding to denatured states can cause changes in global stability, hydrogen-exchange rates, and thermal B-factors, contrary to expectations, but in agreement with experiments. We conclude that ligand binding, similar to protein folding, may be better described in terms of energy landscapes than in terms of simpler mass-action models.

Hemeproteins↗