Crowding-induced protein destabilization in the absence of soft attractions.

It is generally assumed that volume exclusion by macromolecular crowders universally stabilizes the native states of proteins and destabilization suggests soft attractions between crowders and protein. Here we show that proteins can be destabilized even by crowders that are purely repulsive. With a coarse-grained sequence-based model, we study the folding thermodynamics of two sequences with different native folds, a helical hairpin and a β-barrel, in a range of crowder volume fractions, φ.

Effects of Topology and Sequence in Protein Folding Linked via Conformational Fluctuations.

Experiments have compared the folding of proteins with different amino acid sequences but the same basic structure, or fold. Results indicate that folding is robust to sequence variations for proteins with some nonlocal folds, such as all-β, whereas the folding of more local, all-α proteins typically exhibits a stronger sequence dependence. Here, we use a coarse-grained model to systematically study how variations in sequence perturb the folding energy landscapes of three model sequences with 3α, 4β + α, and β-barrel folds, respectively.

Binding Specificity Profiles from Computational Peptide Screening.

The computational peptide screening method is a Monte Carlo-based procedure to systematically characterize the specificity of a peptide-binding site. The method is based on a generalized-ensemble algorithm in which the peptide sequence has become a dynamic variable, i.e.

Smooth functional transition along a mutational pathway with an abrupt protein fold switch.

Recent protein design experiments have demonstrated that proteins can migrate between folds through the accumulation of substitution mutations without visiting disordered or nonfunctional points in sequence space. To explore the biophysical mechanism underlying such transitions we use a three-letter continuous protein model with seven atoms per amino acid to provide realistic sequence-structure and sequence-function mappings through explicit simulation of the folding and interaction of model sequences. We start from two 16-amino-acid sequences folding into an α-helix and a β-hairpin, respectively, each of which has a preferred binding partner with 35 amino acids.

Aggregate geometry in amyloid fibril nucleation.

We present and study a minimal structure-based model for the self-assembly of peptides into ordered β-sheet-rich fibrils. The peptides are represented by unit-length sticks on a cubic lattice and interact by hydrogen bonding and hydrophobicity forces. Using Monte Carlo simulations with >10(5) peptides, we show that fibril formation occurs with sigmoidal kinetics in the model.

In silico peptide-binding predictions of passerine MHC class I reveal similarities across distantly related species, suggesting convergence on the level of protein function.

The major histocompatibility complex (MHC) genes are the most polymorphic genes found in the vertebrate genome, and they encode proteins that play an essential role in the adaptive immune response. Many songbirds (passerines) have been shown to have a large number of transcribed MHC class I genes compared to most mammals. To elucidate the reason for this large number of genes, we compared 14 MHC class I alleles (α1-α3 domains), from great reed warbler, house sparrow and tree sparrow, via phylogenetic analysis, homology modelling and in silico peptide-binding predictions to investigate their functional and genetic relationships.

Epitope-specificity of recombinant antibodies reveals promiscuous peptide-binding properties.

Protein-peptide interactions are a common occurrence and essential for numerous cellular processes, and frequently explored in broad applications within biology, medicine, and proteomics. Therefore, understanding the molecular mechanism(s) of protein-peptide recognition, specificity, and binding interactions will be essential. In this study, we report the first detailed analysis of antibody-peptide interaction characteristics, by combining large-scale experimental peptide binding data with the structural analysis of eight human recombinant antibodies and numerous peptides, targeting tryptic mammalian and eukaryote proteomes.

Binding of two intrinsically disordered peptides to a multi-specific protein: a combined Monte Carlo and molecular dynamics study.

The unique ability of intrinsically disordered proteins (IDPs) to fold upon binding to partner molecules makes them functionally well-suited for cellular communication networks. For example, the folding-binding of different IDP sequences onto the same surface of an ordered protein provides a mechanism for signaling in a many-to-one manner. Here, we study the molecular details of this signaling mechanism by applying both Molecular Dynamics and Monte Carlo methods to S100B, a calcium-modulated homodimeric protein, and two of its IDP targets, p53 and TRTK-12.

All-atom Monte Carlo approach to protein-peptide binding.

We develop a procedure for exploring the free energy landscape of protein-peptide binding at atomic detail and apply it to PDZ domain-peptide interactions. The procedure involves soft constraints on receptor proteins providing limited chain flexibility, including backbone motions. Peptide chains are left fully flexible and kept in spatial proximity of the protein through periodic boundary conditions.

The folding mechanics of a knotted protein.

An increasing number of proteins are being discovered with a remarkable and somewhat surprising feature, a knot in their native structures. How the polypeptide chain is able to "knot" itself during the folding process to form these highly intricate protein topologies is not known. Here we perform a computational study on the 160-amino-acid homodimeric protein YibK, which, like other proteins in the SpoU family of MTases, contains a deep trefoil knot in its C-terminal region.