Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/.
We present a simple method, using constant pinnings, to suppress spatiotemporal chaos and achieve global control in coupled map lattice models under different situations, e.g., for uniform pinning, nonuniform pinning with regular or random distributions, and lattices with spatial heterogeneity in local dynamics and coupling strength. The method is easy to implement and does not require any a priori information of the system dynamics or explicit changes in its parameters. This method can also be used for local control of spatiotemporal dynamics, an aspect that has crucial importance in many natural systems. [S0031-9007(98)06896-3] PACS numbers: 05.45. + b, 05.50. + q, 47.20.Ky, Spatially extended systems are commonly described using coupled map lattice (CML) models which exhibit a wide variety of novel and complex spatiotemporal behaviors including spatiotemporal chaos (STC) for different levels of spatial coupling and nonlinearity in the local dynamics [1]. Along with physicochemical systems such as plasma devices, laser systems, and chemical reactions, the CMLs are also being increasingly used in modeling spatially extensive excitable media in biology, such as the cardiac, neural, or retinal tissue, and metapopulations in ecology, where the coupled discrete nature of the media and the resulting spatiotemporal dynamics has significance in both physical and biological functions [2]. Alterations in the normal functions in these systems lead to pathological conditions, and thus control of spatiotemporal dynamics has major implications in biological functions. However, only a few methods have been proposed for controlling such spatially extended systems [3][4][5].The dynamical control of spatially extended systems can have two different motivations: (a) control of the full system by manipulating all or parts of the system, and (b) controlling only a localized spatial region, leaving the rest of the system unperturbed. The first is needed when one desires to exert global control over the system in the event of its exhibiting undesirable dynamics, e.g., instabilities in coupled chemical reactors, or in arrays of Josephson junctions, etc. The second is extremely useful in situations where local control is required without interfering with other parts of the system, viz., suppressing activities of an ectopic node in the heart, or introducing localized alterations in neural tissues.In this Letter we propose a novel and simple method to control the spatiotemporal dynamics in CMLs by applying constant pinning in the spatial domain. The STC in the lattice can be suppressed by pinning all sites uniformly, and the high dimensional system can thus be stabilized in any desired periodic state on appropriately varying the pinning strengths in few time steps (ϳ50). Global suppression of STC (as measured by negative maximum Lyapunov exponent, l max ) can also be achieved by this method by the application of regularly spaced or randomly distributed nonuniform pinnings. The major advantage of the method is that, unlike other feedback ...
Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein–protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein–nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein–protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.