The strength of intraprotein interactions or contact network is one of the dominant factors determining the thermodynamic stabilities of proteins. The nature and the extent of connectivity of this network also play a role in allosteric signal propagation characteristics upon ligand binding to a protein domain. Here, we develop a server for rapid quantification of the strength of an interaction network by employing an experimentally consistent perturbation approach previously validated against a large data set of 375 mutations in 19 different proteins. The web server can be employed to predict the extent of destabilization of proteins arising from mutations in the protein interior in experimentally relevant units. Moreover, coupling distancesa measure of the extent of percolation on perturbationand overall perturbation magnitudes are predicted in a residue-specific manner, enabling a first look at the distribution of energetic couplings in a protein or its changes upon ligand binding. We show specific examples of how the server can be employed to probe for the distribution of local stabilities in a protein, to examine changes in side chain orientations or packing before and after ligand binding, and to predict changes in stabilities of proteins upon mutations of buried residues. The web server is freely available at http://pbl. biotech.iitm.ac.in/pPerturb and supports recent versions of all major browsers.
Microbial consortia exhibit spatial patterning across diverse environments. Since probing the self-organization of natural microbial communities is limited by their inherent complexity, synthetic models have emerged as attractive alternatives. In this study, we develop novel frameworks of bacterial communication and explore the emergent spatiotemporal organization of microbes. Specifically, we built quorum sensing-mediated models of microbial growth that are utilized to characterize the dynamics of communities from arbitrary initial configurations and establish the effectiveness of our communication strategies in coupling the growth rates of microbes. Our simulations indicate that the behavior of quorum sensing-coupled consortia can be most effectively modulated by the rates of secretion of acyl homoserine lactones. Such a mechanism of control enables the construction of desired relative populations of constituent species in spatially organized populations. Our models accurately recapitulate previous experiments that have investigated pattern formation in synthetic multi-cellular systems. Additionally, our software tool enables the easy implementation and analysis of our frameworks for a variety of initial configurations and simplifies the development of sophisticated gene circuits facilitating distributed computing. Overall, we demonstrate the potential of spatial organization as a tunable parameter in synthetic biology by introducing a communication paradigm based on the location and strength of coupling of microbial strains.
G-protein-coupled receptors (GPCRs) are ubiquitous integral membrane proteins involved in diverse cellular signaling processes. Here, we carry out a large-scale ensemble thermodynamic study of 45 ligand-free GPCRs employing a structure-based statistical mechanical framework. We find that multiple partially structured states co-exist in the GPCR native ensemble, with the TM helices 1, 6 and 7 displaying varied folding status, and shaping the conformational landscape. Strongly coupled residues are anisotropically distributed, accounting for only 13% of the residues, illustrating that a large number of residues are inherently dynamic. Active-state GPCRs are characterized by reduced conformational heterogeneity with altered coupling-patterns distributed throughout the structural scaffold. In silico alanine-scanning mutagenesis reveals that extra- and intra-cellular faces of GPCRs are coupled thermodynamically, highlighting an exquisite structural specialization and the fluid nature of the intramolecular interaction network. The ensemble-based perturbation methodology presented here lays the foundation for understanding allosteric mechanisms and the effects of disease-causing mutations in GCPRs.
Microbial consortia exhibit spatial patterning in several environments. However, the study of such patterning is limited by the inherent complexity of natural systems. An attractive alternative to study such systems involves the use of model synthetic microbial communities, which are convenient frameworks that allow the reuse of circuit components by eliminating cross-talk through compartmentalization of modules in genetic circuits. Computational models facilitate the understanding of how spatial organization can be harnessed as a tunable parameter in 2D cultures. We propose a Quorum Sensing-Mediated Model to engineer communication between strains in a consortium. This is implemented using a cellular automaton. We further analyze the properties of this model and compare them with those of the traditionally used Metabolite Mediated Model. Our studies indicate that modulating the rate of secretion of quorum sensing molecules is the most effective means of regulating community behavior. The models and codes are available from https://github.com/RamanLab/picCASO.
G-protein-coupled receptors (GPCRs) are ubiquitous integral membrane proteins involved in diverse cellular signaling processes and consequently serve as crucial drug targets. Here, we carry out the first large-scale ensemble thermodynamic study of 45 different ligand-free GPCRs employing a structure-based statistical mechanical framework and identify extensive conformational plasticity encompassing the seven transmembrane (TM) helices. Multiple partially structured states or intermediates co-exist in equilibrium in the native ensemble, with the TM helices 1, 6 and 7 displaying varied degrees of structure, and TM3 exhibiting the maximal stability. Active state GPCRs are characterized by reduced conformational heterogeneity with altered coupling-patterns distributed not just locally but throughout the structural scaffold. Strongly coupled residues are distributed across the structure in an anisotropic manner accounting for only 13% of the residues, highlighting that a large number of residues in GPCRs are inherently dynamic to enable structural motions critical for function. Our work thus uncovers the thermodynamic hallmarks of GPCR structure and activation, and how differences quantifiable only via higher-order coupling free energies provide insights into their exquisite structural specialization and the fluid nature of the intramolecular interaction network. The intricate landscapes and perturbation methodologies presented here lay the foundation for understanding allosteric mechanisms in GPCRs, location of structural-functional hot-spots, and effects of disease-causing mutations.
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