Stability of graph communities across time scales

The complexity of biological, social and engineering networks makes it desirable to find natural partitions into communities that can act as simplified descriptions and provide insight into the structure and function of the overall system. Although community detection methods abound, there is a lack of consensus on how to quantify and rank the quality of partitions. We show here that the quality of a partition can be measured in terms of its stability, defined in terms of the clustered autocovariance of a Markov process taking place on the graph. Because the stability has an intrinsic dependence on time scales of the graph, it allows us to compare and rank partitions at each time and also to establish the time spans over which partitions are optimal. Hence the Markov time acts effectively as an intrinsic resolution parameter that establishes a hierarchy of increasingly coarser clusterings. Within our framework we can then provide a unifying view of several standard partitioning measures: modularity and normalized cut size can be interpreted as one-step time measures, whereas Fiedler's spectral clustering emerges at long times. We apply our method to characterize the relevance and persistence of partitions over time for constructive and real networks, including hierarchical graphs and social networks. We also obtain reduced descriptions for atomic level protein structures over different time scales.Comment: submitted; updated bibliography from v

Uncovering allosteric pathways in caspase-1 with Markov transient analysis and multiscale community detection

Allosteric regulation at distant sites is central to many cellular processes. In particular, allosteric sites in proteins are a major target to increase the range and selectivity of new drugs, and there is a need for methods capable of identifying intra-molecular signalling pathways leading to allosteric effects. Here, we use an atomistic graph-theoretical approach that exploits Markov transients to extract such pathways and exemplify our results in an important allosteric protein, caspase-1. Firstly, we use Markov Stability community detection to perform a multiscale analysis of the structure of caspase-1 which reveals that the active conformation has a weaker, less compartmentalised large-scale structure as compared to the inactive conformation, resulting in greater intra-protein coherence and signal propagation. We also carry out a full computational point mutagenesis and identify that only a few residues are critical to such structural coherence. Secondly, we characterise explicitly the transients of random walks originating at the active site and predict the location of a known allosteric site in this protein quantifying the contribution of individual bonds to the communication pathway between the active and allosteric sites. Several of the bonds we find have been shown experimentally to be functionally critical, but we also predict a number of as yet unidentified bonds which may contribute to the pathway. Our approach offers a computationally inexpensive method for the identification of allosteric sites and communication pathways in proteins using a fully atomistic description.Comment: 14 pages, 8 figure

Protein multi-scale organization through graph partitioning and robustness analysis: Application to the myosin-myosin light chain interaction

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding.Comment: 13 pages, 7 Postscript figure

Driving current through single organic molecules

We investigate electronic transport through two types of conjugated molecules. Mechanically controlled break-junctions are used to couple thiol endgroups of single molecules to two gold electrodes. Current-voltage characteristics (IVs) of the metal-molecule-metal system are observed. These IVs reproduce the spatial symmetry of the molecules with respect to the direction of current flow. We hereby unambigously detect an intrinsic property of the molecule, and are able to distinguish the influence of both the molecule and the contact to the metal electrodes on the transport properties of the compound system.Comment: 4 pages, 5 figure

Current-Driven Conformational Changes, Charging and Negative Differential Resistance in Molecular Wires

We introduce a theoretical approach based on scattering theory and total energy methods that treats transport non-linearities, conformational changes and charging effects in molecular wires in a unified way. We apply this approach to molecular wires consisting of chain molecules with different electronic and structural properties bonded to metal contacts. We show that non-linear transport in all of these systems can be understood in terms of a single physical mechanism and predict that negative differential resistance at high bias should be a generic property of such molecular wires.Comment: 9 pages, 4 figure

ab initio modeling of open systems: charge transfer, electron conduction, and molecular switching of a C_{60} device

We present an {\it ab initio} analysis of electron conduction through a $C_{60}$ molecular device. Charge transfer from the device electrodes to the molecular region is found to play a crucial role in aligning the lowest unoccupied molecular orbital (LUMO) of the $C_{60}$ to the Fermi level of the electrodes. This alignment induces a substantial device conductance of $\sim 2.2 \times (2e^2/h)$. A gate potential can inhibit charge transfer and introduce a conductance gap near $E_F$, changing the current-voltage characteristics from metallic to semi-conducting, thereby producing a field effect molecular current switch

Fullerene-based molecular nanobridges: A first-principles study

Building upon traditional quantum chemistry calculations, we have implemented an {\em ab-initio} method to study the electrical transport in nanocontacts. We illustrate our technique calculating the conductance of C$_{60}$ molecules connected in various ways to Al electrodes characterized at the atomic level. Central to a correct estimate of the electrical current is a precise knowledge of the local charge transfer between molecule and metal which, in turn, guarantees the correct positioning of the Fermi level with respect to the molecular orbitals. Contrary to our expectations, ballistic transport seems to occur in this system.Comment: 4 pages in two-column forma