Search PubMed⌕ Search

Biomedical subjects

Rama Ranganathan

Publications and source records attributed to Rama Ranganathan.

12 recordsLinked to original sources
PubMed2006

Signal transduction pathway of TonB-dependent transporters.

Transcription of the ferric citrate import system is regulated by ferric citrate binding to the outer membrane transporter FecA. A signal indicating transporter occupancy is relayed across the outer membrane to energy-transducing and regulatory proteins embedded in the cytoplasmic membrane. Because transcriptional activation is not coupled to ferric citrate import, an allosteric mechanism underlies this complex signaling mechanism. Using evolution-based statistical analysis we have identified a sparse but structurally connected network of residues that links distant functional sites in FecA. Functional analyses of these positions confirm their involvement in the mechanism that regulates transcriptional activation in response to ferric citrate binding at the cell surface. This mechanism appears to be conserved and provides the structural basis for the allosteric signaling of TonB-dependent transporters.

Bacterial Proteins↗
PubMed2006

Knowledge-based potentials in protein design.

Knowledge-based potentials are statistical parameters derived from databases of known protein properties that empirically capture aspects of the physical chemistry of protein structure and function. These potentials play a key role in protein design by improving the accuracy of physics-based models of interatomic interactions and enhancing the computational efficiency of the design process by limiting the complexity of searching sequence space. Recently, knowledge-based potentials (in isolation or in combination with physics-based potentials) have been applied to the modification of existing protein function, the redesign of natural protein folds and the complete design of a non-natural protein fold. In addition, knowledge-based potentials appear to be providing important information about the global topology of amino acid interactions in natural proteins. A detailed study of the methods and products of these protein design efforts promises to greatly expand our understanding of proteins and the evolutionary process that created them.

Databases, Protein↗
PubMed2006

A global analysis of cross-talk in a mammalian cellular signalling network.

Cellular information processing requires the coordinated activity of a large network of intracellular signalling pathways. Cross-talk between pathways provides for complex non-linear responses to combinations of stimuli, but little is known about the density of these interactions in any specific cell. Here, we have analysed a large-scale survey of pathway interactions carried out by the Alliance for Cellular Signalling (AfCS) in RAW 264.7 macrophages. Twenty-two receptor-specific ligands were studied, both alone and in all pairwise combinations, for Ca2+ mobilization, cAMP synthesis, phosphorylation of many signalling proteins and for cytokine production. A large number of non-additive interactions are evident that are consistent with known mechanisms of cross-talk between pathways, but many novel interactions are also revealed. A global analysis of cross-talk suggests that many external stimuli converge on a relatively small number of interaction mechanisms to provide for context-dependent signalling.

Animals↗
PubMed2005

Natural-like function in artificial WW domains.

Protein sequences evolve through random mutagenesis with selection for optimal fitness. Cooperative folding into a stable tertiary structure is one aspect of fitness, but evolutionary selection ultimately operates on function, not on structure. In the accompanying paper, we proposed a model for the evolutionary constraint on a small protein interaction module (the WW domain) through application of the SCA, a statistical analysis of multiple sequence alignments. Construction of artificial protein sequences directed only by the SCA showed that the information extracted by this analysis is sufficient to engineer the WW fold at atomic resolution. Here, we demonstrate that these artificial WW sequences function like their natural counterparts, showing class-specific recognition of proline-containing target peptides. Consistent with SCA predictions, a distributed network of residues mediates functional specificity in WW domains. The ability to recapitulate natural-like function in designed sequences shows that a relatively small quantity of sequence information is sufficient to specify the global energetics of amino acid interactions.

Amino Acid Sequence↗
PubMed2005

Evolutionary information for specifying a protein fold.

Classical studies show that for many proteins, the information required for specifying the tertiary structure is contained in the amino acid sequence. Here, we attempt to define the sequence rules for specifying a protein fold by computationally creating artificial protein sequences using only statistical information encoded in a multiple sequence alignment and no tertiary structure information. Experimental testing of libraries of artificial WW domain sequences shows that a simple statistical energy function capturing coevolution between amino acid residues is necessary and sufficient to specify sequences that fold into native structures. The artificial proteins show thermodynamic stabilities similar to natural WW domains, and structure determination of one artificial protein shows excellent agreement with the WW fold at atomic resolution. The relative simplicity of the information used for creating sequences suggests a marked reduction to the potential complexity of the protein-folding problem.

Algorithms↗
PubMed2004

Structural determinants of allosteric ligand activation in RXR heterodimers.

Allosteric communication underlies ligand-dependent transcriptional responses mediated by nuclear receptors. While studies have elucidated many of the components involved in this process, the energetic architecture within the receptor protein that mediates allostery remains unknown. Using a sequence-based method designed to detect coevolution of amino acids in a protein, termed the statistical coupling analysis (SCA), we identify a network of energetically coupled residues that link the functional surfaces of nuclear receptor ligand binding domains. Functional analysis of these predicted residues demonstrates their participation in an allosteric network that governs the ability of heterodimeric receptors to activate transcription in response to ligand binding by either partner. Interestingly, mutation of a single network residue can discriminate between receptor activation by endocrine, dietary, and synthetic agonists. These results reveal a structural network required for RXR heterodimer allosteric communication and suggest that the specificity of ligand response and permissivity coevolved to enable signal discrimination.

Allosteric Regulation↗
PubMed2003

Local complexity of amino acid interactions in a protein core.

Atomic resolution structures of proteins indicate that the core is typically well packed, suggesting a densely connected network of interactions between amino acid residues. The combinatorial complexity of energetic interactions in such a network could be enormous, a problem that limits our ability to relate structure and function. Here, we report a case study of the complexity of amino acid interactions in a localized region within the core of the GFP, a particularly stable and tightly packed molecule. Mutations at three sites within the chromophore-binding pocket display an overlapping pattern of conformational change and are thermodynamically coupled, seemingly consistent with the dense network model. However, crystallographic and energetic analyses of coupling between mutations paint a different picture; pairs of mutations couple through independent "hotspots" in the region of structural overlap. The data indicate that, even in highly stable proteins, the core contains sufficient plasticity in packing to uncouple high-order energetic interactions of residues, a property that is likely general in proteins.

Amino Acids↗
PubMed2003

Allosteric determinants in guanine nucleotide-binding proteins.

Members of the G protein superfamily contain nucleotide-dependent switches that dictate the specificity of their interactions with binding partners. Using a sequence-based method termed statistical coupling analysis (SCA), we have attempted to identify the allosteric core of these proteins, the network of amino acid residues that couples the domains responsible for nucleotide binding and protein-protein interactions. One-third of the 38 residues identified by SCA were mutated in the G protein Gs alpha, and the interactions of guanosine 5'-3-O-(thio)triphosphate- and GDP-bound mutant proteins were tested with both adenylyl cyclase (preferential binding to GTP-Gs alpha) and the G protein beta gamma subunit complex (preferential binding to GDP-Gs alpha). A two-state allosteric model predicts that mutation of residues that control the equilibrium between GDP- and GTP-bound conformations of the protein will cause the ratio of affinities of these species for adenylyl cyclase and G beta gamma to vary in a reciprocal fashion. Observed results were consistent with this prediction. The network of residues identified by the SCA appears to comprise a core allosteric mechanism conferring nucleotide-dependent switching; the specific features of different G protein family members are built on this core.

Allosteric Site↗
PubMed2003

Evolutionarily conserved networks of residues mediate allosteric communication in proteins.

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which signals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Here, we describe a sequence-based statistical method for quantitatively mapping the global network of amino acid interactions in a protein. Application of this method for three structurally and functionally distinct protein families (G protein-coupled receptors, the chymotrypsin class of serine proteases and hemoglobins) reveals a surprisingly simple architecture for amino acid interactions in each protein family: a small subset of residues forms physically connected networks that link distant functional sites in the tertiary structure. Although small in number, residues comprising the network show excellent correlation with the large body of mechanistic data available for each family. The data suggest that evolutionarily conserved sparse networks of amino acid interactions represent structural motifs for allosteric communication in proteins.

Allosteric Regulation↗
PubMed2002

Overview of the Alliance for Cellular Signaling.

The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells--B lymphocytes (the cells of the immune system) and cardiac myocytes--to facilitate quantitative modelling. One goal is to catalyse complementary research in individual laboratories; to facilitate this, all alliance data are freely available for use by the entire research community.

B-Lymphocytes↗
PubMed2002

Knowledge-based potential functions in protein design.

Predicting protein sequences that fold into specific native three-dimensional structures is a problem of great potential complexity. Although the complete solution is ultimately rooted in understanding the physical chemistry underlying the complex interactions between amino acid residues that determine protein stability, recent work shows that empirical information about these first principles is embedded in the statistics of protein sequence and structure databases. This review focuses on the use of 'knowledge-based' potentials derived from these databases in designing proteins. In addition, the data suggest how the study of these empirical potentials might impact our fundamental understanding of the energetic principles of protein structure.

Amino Acid Sequence↗