Browsing by Subject "Protein Interaction Domains and Motifs"
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Item Decomposition of Proteins into Functionally and Evolutionarily Independent Cooperative Units(2009-06-17) Halabi, Najeeb Maroof; Ranganathan, RamaUnderstanding cooperative interactions within proteins is an important goal because cooperativity underlies protein functions such as catalysis, allostery, ligand binding and folding. Cooperative units within proteins can be revealed via an evolution based method called statistical coupling analysis that quantifies the correlations between positions in a multiple sequence alignment of a protein family. In this work, coupling analysis and experimental studies were used to analyze two protein families - the TonB dependent receptors and the S1A serine proteases. The TonB dependent receptor family members are membrane bound siderophore transporters. Ligand binding on the extracellular side of the transporter transmits a signal to the periplasmic side where another protein (TonB) provides the energy for transport. Coupling analysis, based on a diverse alignment of 541 family members revealed a network of physically contiguous positions extending close to 50 angstroms from the ligand binding pocket to the putative periplasmic interaction sites. A mutational analysis of FecA, a representative member of this family, confirmed the functional significance of the coupled positions. The S1A serine protease family members are involved in diverse functions such as digestion, coagulation, immunity and reproduction. Coupling analysis on 1470 serine proteases revealed at least three sets of independently evolving positions. Each set of positions is called a sector. Structural analysis revealed that each sector is physically contiguous suggesting mechanical independence. Extensive data in the literature on this protein family allowed the assignment of function to two of the sectors. One sector comprised positions making up the catalytic machinery, while another sector comprised positions important for substrate binding. To determine the function of the sector with unknown function, mutations were done on positions making up this sector and tested for catalytic and stability effects on proteins. The data showed that the positions in the unknown function sector affected stability but not catalysis. Each sector therefore performs a different and independent cooperative function: one sector for catalysis, one for substrate binding and one for fold stability.Item Evolutionary Constraints Specifying Protein Folding and Function(2007-08-04) Larson, Christopher; Ranganathan, RamaProteins are complex macromolecules that carry out biological functions while under constant mutational load and selective pressure during evolution. Consequently, evolution has generated protein families by exploring the set of sequences able to carry out a particular biological activity, maintaining sequence motifs critical for function while varying the rest of the protein. Statistical coupling analysis of a protein family examines an alignment of such sequences and detects the evolutionarily preserved interresidue interactions critical for the proteins' selective fitness. This set of information has provided a sufficiently detailed description of evolutionary design constraints to allow the design of novel WW domain sequences that fold and function like natural proteins. This work expands the initial investigations, and probes the minimal information content necessary to specify the WW domain fold, as well as the effect of increasing the coupling constraints in the design process. This work also evaluates the ability of coupling information to design larger and more complex protein folds and to specify their biological functions. Experimental expression and characterization of WW domains designed with varying levels of coupling information indicates that incorporating even small amounts of coupling information has a notable impact on these proteins' ability to fold. Moreover, different coupling-based design approaches produce results robust to details of how coupling information is incorporated. Similar experiments with designed PDZ domains and in vivo characterization of designed G-protein coupled receptors show that, to the extent studied, this design approach is successful with these larger and more complex proteins as well. This indicates that the typically sparse matrices of coupling values observed for a protein family capture the core evolutionary constraints on the proteins in sufficient detail to generate even complex proteins with natural-like folds and functions.Item Logic and Mechanism of an Evolutionarily Conserved Interaction in PDZ Domain(2006-05-15) Sharma, Rohit; Ranganathan, RamaProteins are beautiful materials evolved to channel specific energetic perturbations into particular functions. At the core of virtually every biological process are two features of a protein: the energetic architecture and the mechanisms of energy propagation. Structural, dynamics, and mutagenesis experiments have revealed that anisotropy and cooperativity are common features of the energy propagation in proteins; however, a complete understanding of the patterns and mechanisms of energy propagation remain unclear from these studies. Previous work in our lab developed a methodology, termed the Statistical Coupling Analysis (SCA), to estimate energetic interactions between residues in a protein from their statistical co-variation through evolution. The results of this algorithm revealed a small subset of the residues in a protein have significant energetic interactions and form a connected substructure in proteins and show excellent agreement with mutagenesis data in several systems. Using the same fundamental concepts of the original SCA, we have developed an improved version of SCA. This new algorithm provides, for the first time, a global map of the co-evolutionary interactions between residues in a protein from a multiple sequence alignment. The results of the new SCA are consistent with the original method but produce values for all pairs of positions. We then used the energetic map provided by SCA to understand the physical basis of specificity in the PDZ domain. The co-evolutionary energetic map of the PDZ domain predicts a long range interaction between position 372, a known specificity determinant that directly interacts with ligand, and position 322. Thermodynamic measurements in one PDZ domain reveal that position 322 modulates the specificity-determining interaction between 372 and its ligand contact. Structural studies show that flexibility at 322 is tuned to make conformational change on one side of the binding pocket sensitive to interactions at the distant specificity-determining contact. This designed mechanical coupling allows the domain to have AND gate-like behavior in screening for specific binding interactions. Understanding the logic and mechanism of a co-evolved interaction gives confidence in the ability of SCA to identify the functionally critical interactions in a protein, even when not structurally obvious. Given the functional and structural relevance of SCA predictions, we next addressed the topology of the energetic map in proteins. Analysis of several structurally and functionally diverse proteins revealed several common striking features in their energetic maps. First, the highly co-evolved positions in a protein show a high degree of mutual co-evolution so that, together, they form a nearly completely co-evolved sub-cluster. Secondly, the pattern of energetic interactions in proteins is highly heterogeneous, and fit a power-law distribution where most residues have very few co-evolutionary links with other residues and a few residues have many co-evolutionary links. The data is very consistent with extensive mutagenesis studies in several systems. Together, these experiments begin to demonstrate that the contiguous networks identified by SCA reflect structural regions capable of cooperatively channeling energy to produce functionality.