Antibody binding increases the flexibility of the prion protein

Prion diseases are associated with the conversion of the cellular prion protein (PrP) into a pathogenic conformer (PrPSc). A proposed therapeutic approach to avoid the pathogenic transformation is to develop antibodies that bind to PrP and stabilize its structure. POM1 and POM6 are two monoclonal antibodies that bind the globular domain of PrP and have different biological responses, i.e., trigger neurotoxicity mimicking prion infections (POM1) or prevent neurotoxicity (POM6). The crystal structures of PrP in complex with the two antibodies show similar epitopes which seems inconsistent with the opposite phenotypes. Here, we investigate the influence of the POM1 and POM6 antibodies on the flexibility of the mouse PrP by molecular dynamics simulations. The simulations reveal that the POM6/PrP interface is less stable than the POM1/PrP interface, ascribable to localized polar mismatches at the interface, despite the former complex having a larger epitope than the latter. In the presence of any of the two antibodies, the flexibility of the globular domain increases everywhere except for the β1-α1 loop in the POM1/PrP complex which suggests the involvement of this loop in the pathological conversion. The secondary structure of PrP is preserved whereas the polar interactions involving residues Glu146, Arg156 and Arg208 are modified upon antibody binding

Spiking burstiness and working memory in the human medial temporal lobe

Persistent activity has commonly been considered to be a hallmark of working memory (WM). Recent evidence indicates that neuronal discharges in the medial temporal lobe (MTL) are compatible with WM neural patterns observed in cortical areas. However, the characterization of this activity rarely consists of measurements other than firing rates of single neurons. Moreover, a varied repertoire of firing dynamics has been reported in the MTL regions, which motivate the more detailed examination of the relationships between WM processes and discharge patterns undertaken here. Specifically, we investigate' at different resolution levels, firing irregularities in electrode recordings from the hippocampus, amygdala, and the entorhinal cortex of epileptic patients during a WM task. We show that some types of (ir)regularities predict response times of the patients depending on the trial periods under consideration. Prominent burst activity at the population level is observed in the amygdala and entorhinal cortex during memory retrieval. In general, regular and bursty neurons contribute to the decoding of the memory load, yet they display important differences across the three anatomical areas. Our results suggest that nonrandom (non-Poisson) patterns are relevant for WM, which calls for the development and use of statistics complementary to mere spike counts

Estimation of protein folding probability from equilibrium simulations

The assumption that similar structures have similar folding probabilities ($p_{fold}$) leads naturally to a procedure to evaluate $p_{fold}$ for every snapshot saved along an equilibrium folding-unfolding trajectory of a structured peptide or protein. The procedure utilizes a structurally homogeneous clustering and does not require any additional simulation. It can be used to detect multiple folding pathways as shown for a three-stranded antiparallel $\beta$-sheet peptide investigated by implicit solvent molecular dynamics simulations.Comment: 7 pages, 4 figures, supplemetary material

Domino Effect in Allosteric Signaling of Peptide Binding

While being a thoroughly studied model of dynamic allostery in a small protein, the pathway of signal transduction in the PDZ3 domain has not been fully determined. Here, we investigate peptide binding to the PDZ3 domain by conventional and fully data-driven analyses of molecular dynamics simulations. First, we identify isoleucine 37 as a key residue by widely used computational procedures such as cross-correlation and community network analysis. Simulations of the Ile37Ala mutant show disruption of the coordinated movements of spatially close regular elements of secondary structure. Then, we employ a recently developed unsupervised, data-driven procedure to determine an optimized reaction coordinate (slowest-relaxation eigenvector) of peptide binding. We use this reaction coordinate to improve sampling by restarting additional simulations from the transition state region. Significant differences in the distributions of some of the pairwise residue distances in the bound and unbound states emerge from the projection onto the optimized reaction coordinate. The unsupervised analysis shows that allosteric signaling is transduced from the β2 strand, which forms part of the peptide binding site, to the spatially adjacent β3 and β4 strands, and from there to the α3 helix. The domino-like transmission of a (peptide binding) signal along β strands and α helices that are close in three-dimensional space is likely to be a general mechanism of allostery in single-domain proteins

Multistep greedy algorithm identifies community structure in real-world and computer-generated networks

We have recently introduced a multistep extension of the greedy algorithm for modularity optimization. The extension is based on the idea that merging l pairs of communities (l>1) at each iteration prevents premature condensation into few large communities. Here, an empirical formula is presented for the choice of the step width l that generates partitions with (close to) optimal modularity for 17 real-world and 1100 computer-generated networks. Furthermore, an in-depth analysis of the communities of two real-world networks (the metabolic network of the bacterium E. coli and the graph of coappearing words in the titles of papers coauthored by Martin Karplus) provides evidence that the partition obtained by the multistep greedy algorithm is superior to the one generated by the original greedy algorithm not only with respect to modularity but also according to objective criteria. In other words, the multistep extension of the greedy algorithm reduces the danger of getting trapped in local optima of modularity and generates more reasonable partitions.Comment: 17 pages, 2 figure

Local modularity measure for network clusterizations

Many complex networks have an underlying modular structure, i.e., structural subunits (communities or clusters) characterized by highly interconnected nodes. The modularity $Q$ has been introduced as a measure to assess the quality of clusterizations. $Q$ has a global view, while in many real-world networks clusters are linked mainly \emph{locally} among each other (\emph{local cluster-connectivity}). Here, we introduce a new measure, localized modularity $LQ$, which reflects local cluster structure. Optimization of $Q$ and $LQ$ on the clusterization of two biological networks shows that the localized modularity identifies more cohesive clusters, yielding a complementary view of higher granularity.Comment: 5 pages, 4 figures, RevTex4; Changed conten

Kinase selectivity potential for inhibitors targeting the ATP binding site: a network analysis

Motivation and method: Small-molecule inhibitors targeting the adenosine triphosphate (ATP) binding pocket of the catalytic domain of protein kinases have potential to become drugs devoid of (major) side effects, particularly if they bind selectively. Here, the sequences of the 518 human kinases are first mapped onto the structural alignment of 116 kinases of known three-dimensional structure. The multiple structure alignment is then used to encode the known strategies for developing selective inhibitors into a fingerprint. Finally, a network analysis is used to partition the kinases into clusters according to similarity of their fingerprints, i.e. physico-chemical characteristics of the residues responsible for selective binding. Results: For each kinase the network analysis reveals the likelihood to find selective inhibitors targeting the ATP binding site. Systematic guidelines are proposed to develop selective inhibitors. Importantly, the network analysis suggests that the tyrosine kinase EphB4 has high selectivity potential, which is consistent with the selectivity profile of two novel EphB4 inhibitors. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Wordom: a program for efficient analysis of molecular dynamics simulations

Summary: Wordom is a versatile program for manipulation of molecular dynamics trajectories and efficient analysis of simulations. Original tools in Wordom include a procedure to evaluate significance of sampling for principal component analysis as well as modules for clustering multiple conformations and evaluation of order parameters for folding and aggregation. The program was developed with special emphasis on user-friendliness, effortless addition of new modules and efficient handling of large sets of trajectories. Availability: The Wordom program is distributed with full source code (in the C language) and documentation for usage and further development as a platform-independent package under a GPL license from http://www.biochem-caflisch.unizh.ch/wordom/ Contact: [email protected]