Similarity Measures for Protein Ensembles

Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations. However, instead of examining individual conformations it is in many cases more relevant to analyse ensembles of conformations that have been obtained either through experiments or from methods such as molecular dynamics simulations. We here present three approaches that can be used to compare conformational ensembles in the same way as the root mean square deviation is used to compare individual pairs of structures. The methods are based on the estimation of the probability distributions underlying the ensembles and subsequent comparison of these distributions. We first validate the methods using a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single-molecule refinement.     

Comparison of the transition state ensembles for folding of Im7 and Im9 determined using all-atom molecular dynamics simulations with phi value restraints

Delineation of the structural properties of transition states is key to deriving models for protein folding. Here we describe the structures of the transition states of the bacterial immunity proteins Im7 and Im9 obtained by all-atom molecular dynamics simulations with phi value restraints derived from protein engineering experiments. This pair of proteins is of special interest because, at pH 7 and 10 degrees C, Im7 folds via an intermediate while Im9 folds with a two-state transition. The structures of the transition states for Im7 and Im9, together with their radii of gyration and distances from the native state, are similar. The typical distance between any two members of the transition state ensemble of both proteins is large, with that of Im9 nearly twice that of Im7. Thus, a broad range of structures make up the transition state ensembles of these proteins. The ensembles satisfy the set of rather low phi values and yet are consistent with high beta(T) values (> 0.85 for both proteins). For both Im7 and Im9 the inter-helical angles are highly variable in the transition state ensembles, although the native contacts between helices I and IV are well conserved. By measuring the distribution of the accessible surface area for each residue we show that the hydrophobic residues that are buried in the native state remain buried in the transition state, corresponding to a hydrophobic collapse to a relatively ordered globule. The data provide new insights into the structural properties of the transition states of these proteins at an atomic level of detail and show that molecular dynamics simulations with phi value restraints can significantly enhance the knowledge of the transition state ensembles (TSE) provided by the experimental phi values alone.     

Taphonomy in the light of intrinsic shell properties and life habits: Marine bivalves from the Eemian of northern Russia

A taphonomic analysis of the bivalvesArctica islandica (Arcticidae),Astarte borealis (Astartidae),Mytilus edulis (Mytilidae), andSpisula elliptica (Mactridae) from shallow-marine last interglacial Sediments exposed along the Pyoza river, Arkhangelsk region, shows that they differ in preservation, probably because of differences in shell shape, shell structures, and life habits. The Shells indicate that the temporal sequence of taphonomic processes was as follows: (1) pre-mortem bioerosion and dissolution; (2) post-mortem bioerosion; (3) abrasion, disarticulation, and fragmentation; and (4) dissolution. A new graphic Illustration, the taphonomic constituent diagram (TCD), is proposed to illustrate the sequences of taphonomic processes. It is inspired by the ichnofabric constituent diagram used in ichnology and integrates the shell surface coverage of different taphonomic features by graphically plotting them against relative time. The taphonomic constituent diagram may display differences in the Chronologie order of paleoenvironmental processes. Also, the diagram enables a combination of both microscopic and macroscopic taphonomic features, and eases comparative studies of fossil assemblages.      

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges.     

Upper Campanian–Maastrichtian chronostratigraphy of the Skælskør‐1 core,Denmark: correlation at the basinal and global scale and implications for changes in sea‐surface temperatures

The lithostratigraphy, calcareous nannofossil biostratigraphy, carbon‐ and oxygen‐isotope stratigraphy and gamma‐ray profile are presented for the Skælskør‐1 core, eastern Denmark. The correlation of carbon isotopes to Gubbio (Italy) and ODP Site 762C (Indian Ocean) provides the chronostratigrahical framework of the core through a tie to magnetostratigraphy. Two new carbon‐isotope excursions are defined for the uppermost Maastrichtian of the core and prove useful for long‐distance correlation. Twenty stratigraphic tie‐points are used for correlation of the upper Campanian–Maastrichtian interval by combining carbon‐isotope and gamma‐ray variations. Significant dissimilarities in the gamma‐ray profiles of the Danish Basin cores preclude the sole use of this tool for basin‐scale correlations. Bulk oxygen‐isotopes and semi‐quantitative abundance changes in the warm‐water calcareous nannofossil Watznaueria barnesiae and the cool‐water Kamptnerius magnificus highlight the following past changes in sea‐surface temperatures (SSTs): relatively warm late Campanian SSTs, cooling across the Campanian–Maastrichtian boundary and through the early Maastrichtian, warming across the early–late Maastrichtian transition, cooling in the late Maastrichtian, intense warming in the latest Maastrichtian chron C29r, followed by a very short episode of cooling immediately before the Cretaceous–Palaeogene boundary. The late Campanian–Maastrichtian evolution in sea water temperatures inferred from the Danish Basin is similar to that delineated at tropical latitude oceanic sites.     

Understanding the Origins of Loss of Protein Function by Analyzing the Effects of Thousands of Variants on Activity and Abundance

Understanding and predicting how amino acid substitutions affect proteins are keys to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analyzed 6,749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyze the structural and mechanistic origins of loss of function and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.