Restriction versus guidance in protein structure prediction

Abstract

Conformational restriction by fragment assembly and guidance in molecular dynamics are alternate conformational search strategies in protein structure prediction. We examine both approaches using a version of the associative memory Hamiltonian that incorporates the influence of water-mediated interactions (AMW). For short proteins (<70 residues), fragment assembly, while searching a restricted space, compares well to molecular dynamics and is often sufficient to fold such proteins to near-native conformations (4Å) via simulated annealing. Longer proteins encounter kinetic sampling limitations in fragment assembly not seen in molecular dynamics which generally samples more native-like conformations. We also present a fragment enriched version of the standard AMW energy function, AMW-FME, which incorporates the local sequence alignment derived fragment libraries from fragment assembly directly into the energy function. This energy function, in which fragment information acts as a guide not a restriction, is found by molecular dynamics to improve on both previous approaches.fragment assembly ͉ associative memory Hamiltonian ͉ protein folding ͉ annealing ͉ molecular dynamics I t is useful to categorize protein structure prediction schemes into two classes: template-based modeling and de novo prediction. Template-based modeling depends on the existence, and identification of, at least one experimentally-solved structure with significant global structural similarity to the target to be predicted, usually a sequence homolog. The identification can be made either by a global sequence-sequence alignment or a global sequencestructure alignment (1). Finding the proper template is a search problem but unlike folding, a search highly restricted to a relatively modest number of possibilities. After finding a template, the homolog structure acts as a global constraint which again severely restricts the remainder of the relevant conformational space to be searched. This leads overall to a much simpler optimization problem to solve. Various energy functions can be used which often lead to successful predictions defined by significant improvement relative to input homolog information (2).However, modeling a protein structure when no experimentallydetermined homologs exist to match the structures globally (or none are recognized to exist) is quite challenging. Such de novo structure prediction can employ all-atom molecular mechanics or hybrid models. Molecular mechanics methods are based on physico-chemical interactions such as van der Waals, electrostatics, hydrogen bonding, solvation energy, and basic backbone steric constraints (covalent bond lengths and angles and torsion angle preferences). Model parameters are generally inferred from experimental measurements and/or quantum chemical calculations on small organic molecules (3, 4). Based on such data, one can generate a transferable energy function (5). The resulting energy function can be used in a variety of search procedures, including template-based modeling. Ultimately, a...

Learning To Fold Proteins Using Energy Landscape Theory

“…The process of folding a protein is inherently coupled to collapse. Monte Carlo search, which requires large fragments to remain rigid during moves, suffers from an inability of simple moves to rearrange in the collapsed state resulting in an inability to avoid steric clashes [47]. Then sampling even a well-funneled landscape in this way can be problematic for large structures if a simple move set is used.…”

PEST Control of Molecular Stripping of NFκB from DNA Transcription Sites

“…Although the C-terminus of IκBα extends to residue 317, previous experimental evidence had suggested that the sequence PESEDEE (residues 281–287) was necessary and sufficient for full NFκB-binding and DNA molecular stripping activity 14–15, 18 . To more fully explore the role of the PEST sequence in molecular stripping, in this paper we present simulations in which the full distribution of conformers adopted by residues 281–292 in IκBα is explored using the multiple fragment memory approach which takes a somewhat agnostic view of the PEST structure treating it as if there were no direct crystal structure information available 19–20 . In addition, we use the same protocol to analyze a charge-neutralized version of the PEST sequence.…”

The role of atomic level steric effects and attractive forces in protein folding

“…While fully accurate protein structures can be used to predict folding kinetics quite well 29 , do lower resolution models like those obtained by homology modeling 30,31,32 or ab initio structure prediction 33,34,35 suffice for kinetic modeling? Here we show that if sufficient predictive accuracy is available short range attractive models can be used and direct transit to the folded state (like that usually found experimentally near T F ) will occur in the simulation and mechanisms near the folding midpoint properly delineated.…”