Coevolution study of tau and a-synuclein suggests a connection between their normal interaction in neurons and the Parkinson's disease-associated mutation A53T

Alpha-synuclein lies at the center of Parkinson’s disease etiology, and polymorphisms in the gene for the microtubule-associated protein tau are risk factors for getting the disease. Tau and a-synuclein interact in vitro, and a-synuclein can also compete with tau binding to microtubules. To test whether these interactions might be part of their natural biological functions, a correlated mutation analysis was performed between tau and a-synuclein, looking for evidence of coevolution. For comparison, analyses were also performed between tau and b- and g-synuclein. In addition, analyses were performed between tau and the synuclein proteins and the neuronal tubulin proteins. Potential correlated mutations were detected between tau and a-synuclein, one involving an a-synuclein residue known to interact with tau in vitro, Asn122, and others involving the Parkinson’s disease-associated mutation A53T. No significant correlated mutations were seen between tau and b- and g-synuclein. Tau showed potential correlated mutations with the neuron-specific bIII-tubulin protein, encoded by the TUBB3 gene. No convincing correlated mutations were seen between the synuclein and tubulin proteins, with the possible exception of b-synuclein with bIVa-tubulin, encoded by the TUBB4A gene. While the correlated mutations between tau and a-synuclein suggest the two proteins have coevolved, additional study will be needed to confirm that their interaction is part of their normal biological function in cells.

Distant Non-Obvious Mutations Influence the Activity of a Hyperthermophilic Pyrococcus furiosus Phosphoglucose Isomerase

The cupin-type phosphoglucose isomerase (PfPGI) from the hyperthermophilic archaeon Pyrococcus furiosus catalyzes the reversible isomerization of glucose-6-phosphate to fructose-6-phosphate. We investigated PfPGI using protein-engineering bioinformatics tools to select functionally-important residues based on correlated mutation analyses. A pair of amino acids in the periphery of PfPGI was found to be the dominant co-evolving mutation. The position of these selected residues was found to be non-obvious to conventional protein engineering methods. We designed a small smart library of variants by substituting the co-evolved pair and screened their biochemical activity, which revealed their functional relevance. Four mutants were further selected from the library for purification, measurement of their specific activity, crystal structure determination, and metal cofactor coordination analysis. Though the mutant structures and metal cofactor coordination were strikingly similar, variations in their activity correlated with their fine-tuned dynamics and solvent access regulation. Alternative, small smart libraries for enzyme optimization are suggested by our approach, which is able to identify non-obvious yet beneficial mutations.

Improving intermolecular contact prediction through protein-protein interaction prediction using coevolutionary analysis with expectation-maximization

Predicting residue-residue contacts between interacting proteins is an important problem in bioinformatics. The growing wealth of sequence data can be used to infer these contacts through correlated mutation analysis on multiple sequence alignments of interacting homologs of the proteins of interest. This requires correct identification of pairs of interacting proteins for many species, in order to avoid introducing noise (i.e. non-interacting sequences) in the analysis that will decrease predictive performance. We have designed Ouroboros, a novel algorithm to reduce such noise in intermolecular contact prediction. Our method iterates between weighting proteins according to how likely they are to interact based on the correlated mutations signal, and predicting correlated mutations based on the weighted sequence alignment. We show that this approach accurately discriminates between protein interaction versus noninteraction and simultaneously improves the prediction of intermolecular contact residues compared to a naive application of correlated mutation analysis. Furthermore, the method relaxes the assumption of one-to-one interaction of previous approaches, allowing for the study of many-to-many interactions. Source code and test data are available at www.bif.wur.nl/

Protein sites with more coevolutionary connections tend to evolve slower, while more variable protein families acquire higher coevolutionary connections

Background: Correlated mutation or coevolution of positions in a protein is tightly linked with the protein’s respective evolutionary rate. It is essential to investigate the intricate relationship between the extent of coevolution and the evolutionary variability exerted at individual protein sites, as well as the whole protein. Methods: In this study, we have used a reliable set of coevolutionary connections (sites within 10Å spatial distance) and investigated their correlation with the evolutionary diversity within the respective protein sites. Results: Based on our observations, we propose an interesting hypothesis that higher numbers of coevolutionary connections are associated with lesser evolutionary variable protein sites, while higher numbers of the coevolutionary connections can be observed for a protein family that has higher evolutionary variability. Our findings also indicate that highly coevolved sites located in a solvent accessible state tend to be less evolutionary variable. This relationship reverts at the whole protein level where cytoplasmic and extracellular proteins show moderately higher anti-correlation between the number of coevolutionary connections and the average evolutionary conservation of the whole protein. Conclusions: Observations and hypothesis presented in this study provide intriguing insights towards understanding the critical relationship between coevolutionary and evolutionary changes observed within proteins. Our observations encourage further investigation to find out the reasons behind subtle variations in the relationship between coevolutionary connectivity and evolutionary diversity for proteins located at various cellular localizations and/or involved in different molecular-biological functions.

Structure and mechanism of the ATP synthase membrane motor inferred from quantitative integrative modeling

Two subunits within the transmembrane domain of the ATP synthase—the c-ring and subunit a—energize the production of 90% of cellular ATP by transducing an electrochemical gradient of H+ or Na+ into rotational motion. The nature of this turbine-like energy conversion mechanism has been elusive for decades, owing to the lack of definitive structural information on subunit a or its c-ring interface. In a recent breakthrough, several structures of this complex were resolved by cryo–electron microscopy (cryo-EM), but the modest resolution of the data has led to divergent interpretations. Moreover, the unexpected architecture of the complex has cast doubts on a wealth of earlier biochemical analyses conducted to probe this structure. Here, we use quantitative molecular-modeling methods to derive a structure of the a–c complex that is not only objectively consistent with the cryo-EM data, but also with correlated mutation analyses of both subunits and with prior cross-linking and cysteine accessibility measurements. This systematic, integrative approach reveals unambiguously the topology of subunit a and its relationship with the c-ring. Mapping of known Cd2+ block sites and conserved protonatable residues onto the structure delineates two noncontiguous pathways across the complex, connecting two adjacent proton-binding sites in the c-ring to the space on either side of the membrane. The location of these binding sites and of a strictly conserved arginine on subunit a, which serves to prevent protons from hopping between them, explains the directionality of the rotary mechanism and its strict coupling to the proton-motive force. Additionally, mapping of mutations conferring resistance to oligomycin unexpectedly reveals that this prototypical inhibitor may bind to two distinct sites at the a–c interface, explaining its ability to block the mechanism of the enzyme irrespective of the direction of rotation of the c-ring. In summary, this study is a stepping stone toward establishing the mechanism of the ATP synthase at the atomic level.

Codon-level information improves predictions of inter-residue contacts in proteins by correlated mutation analysis

Methods for analysing correlated mutations in proteins are becoming an increasingly powerful tool for predicting contacts within and between proteins. Nevertheless, limitations remain due to the requirement for large multiple sequence alignments (MSA) and the fact that, in general, only the relatively small number of top-ranking predictions are reliable. To date, methods for analysing correlated mutations have relied exclusively on amino acid MSAs as inputs. Here, we describe a new approach for analysing correlated mutations that is based on combined analysis of amino acid and codon MSAs. We show that a direct contact is more likely to be present when the correlation between the positions is strong at the amino acid level but weak at the codon level. The performance of different methods for analysing correlated mutations in predicting contacts is shown to be enhanced significantly when amino acid and codon data are combined.