Construction of analytical many body wave functions for correlated bosons in a harmonic trap

We develop an analytical many-body wave function to accurately describe the crossover of a one-dimensional bosonic system from weak to strong interactions in a harmonic trap. The explicit wave function, which is based on the exact two-body states, consists of symmetric multiple products of the corresponding parabolic cylinder functions, and respects the analytically known limits of zero and infinite repulsion for arbitrary number of particles. For intermediate interaction strengths we demonstrate, that the energies, as well as the reduced densities of first and second order, are in excellent agreement with large scale numerical calculations.Comment: 4 pages, 2 Figure

3D-Fun: predicting enzyme function from structure

The ‘omics’ revolution is causing a flurry of data that all needs to be annotated for it to become useful. Sequences of proteins of unknown function can be annotated with a putative function by comparing them with proteins of known function. This form of annotation is typically performed with BLAST or similar software. Structural genomics is nowadays also bringing us three dimensional structures of proteins with unknown function. We present here software that can be used when sequence comparisons fail to determine the function of a protein with known structure but unknown function. The software, called 3D-Fun, is implemented as a server that runs at several European institutes and is freely available for everybody at all these sites. The 3D-Fun servers accept protein coordinates in the standard PDB format and compare them with all known protein structures by 3D structural superposition using the 3D-Hit software. If structural hits are found with proteins with known function, these are listed together with their function and some vital comparison statistics. This is conceptually very similar in 3D to what BLAST does in 1D. Additionally, the superposition results are displayed using interactive graphics facilities. Currently, the 3D-Fun system only predicts enzyme function but an expanded version with Gene Ontology predictions will be available soon. The server can be accessed at http://3dfun.bioinfo.pl/ or at http://3dfun.cmbi.ru.nl/

Explicitly correlated trial wave functions in Quantum Monte Carlo calculations of excited states of Be and Be-

We present a new form of explicitly correlated wave function whose parameters are mainly linear, to circumvent the problem of the optimization of a large number of non-linear parameters usually encountered with basis sets of explicitly correlated wave functions. With this trial wave function we succeeded in minimizing the energy instead of the variance of the local energy, as is more common in quantum Monte Carlo methods. We applied this wave function to the calculation of the energies of Be 3P (1s22p2) and Be- 4So (1s22p3) by variational and diffusion Monte Carlo methods. The results compare favorably with those obtained by different types of explicitly correlated trial wave functions already described in the literature. The energies obtained are improved with respect to the best variational ones found in literature, and within one standard deviation from the estimated non-relativistic limitsComment: 19 pages, no figures, submitted to J. Phys.

Reflexive adaptation for resilient water services: lessons for theory and practice

‘Adaptive management’ concern attempts to manage complex social-ecological and socio-technical systems in nimble ways to enhance their resilience. In this paper, three forms of adaptive management are identified, ‘scientific’ forms focused on collation of scientific data in response to management experiments, but more recent developments adding processes of collaboration as well as emphasising the need for reflexivity, that is, conscious processes of opening up debates to different perspectives and values. While reflexive adaptive management has been increasingly discussed in theory, there is a lack of examples of what its application means in practice. As a response, this paper examines an ‘Adaptive Planning Process’ (APP), seeking to apply reflexive adaptive management as a means to improve climate resilience in the UK water sector. The APP’s three inter linked workshops – Aspiration, Scenario and Roadmapping – were co-developed and trialled in a water utility. By describing and justifying the choices made in the development of the APP, the paper aims to reveal some of the challenges that arise when trying to design processes that achieve reflexive adaptation. The paper concludes that, if applied to planning for climate change, reflexive adaptation has the potential to explore multiple value positions, highlight different potential futures and acknowledge (and hence, partly address) power differentials, and therefore to offer the possibility of real change. On the basis of the trial, we argue that through tapping the depth and breadth of internal knowledge the APP process created the potential for decision making to be joined up across different parts of the utility, and hence offering new strategies and routes for addressing uncertainties and delivering more resilient water services

Expanding the set of rhodococcal Baeyer–Villiger monooxygenases by high-throughput cloning, expression and substrate screening

To expand the available set of Baeyer–Villiger monooxygenases (BVMOs), we have created expression constructs for producing 22 Type I BVMOs that are present in the genome of Rhodococcus jostii RHA1. Each BVMO has been probed with a large panel of potential substrates. Except for testing their substrate acceptance, also the enantioselectivity of some selected BVMOs was studied. The results provide insight into the biocatalytic potential of this collection of BVMOs and expand the biocatalytic repertoire known for BVMOs. This study also sheds light on the catalytic capacity of this large set of BVMOs that is present in this specific actinomycete. Furthermore, a comparative sequence analysis revealed a new BVMO-typifying sequence motif. This motif represents a useful tool for effective future genome mining efforts.

Island method for estimating the statistical significance of profile-profile alignment scores

<p>Abstract</p> <p>Background</p> <p>In the last decade, a significant improvement in detecting remote similarity between protein sequences has been made by utilizing alignment profiles in place of amino-acid strings. Unfortunately, no analytical theory is available for estimating the significance of a gapped alignment of two profiles. Many experiments suggest that the distribution of local profile-profile alignment scores is of the Gumbel form. However, estimating distribution parameters by random simulations turns out to be computationally very expensive.</p> <p>Results</p> <p>We demonstrate that the background distribution of profile-profile alignment scores heavily depends on profiles' composition and thus the distribution parameters must be estimated independently, for each pair of profiles of interest. We also show that accurate estimates of statistical parameters can be obtained using the "island statistics" for profile-profile alignments.</p> <p>Conclusion</p> <p>The island statistics can be generalized to profile-profile alignments to provide an efficient method for the alignment score normalization. Since multiple island scores can be extracted from a single comparison of two profiles, the island method has a clear speed advantage over the direct shuffling method for comparable accuracy in parameter estimates.</p

Automated functional classification of experimental and predicted protein structures

BACKGROUND: Proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural similarity. RESULTS: We analyzed experimental structures belonging to the Structural Classification of Proteins (SCOP) database and showed that about half of them belong to multi-functional fold families for which protein similarity alone is not adequate to assign function. We also analyzed predicted structures from the LiveBench and the PDB-CAFASP experiments and showed that accurate homology-based functional assignments cannot be achieved approximately one third of the time, when the protein is a member of a multi-functional fold family. We then conducted extended performance evaluation and comparisons on both experimental and predicted structures using our Functional Signatures from Structural Alignments (FSSA) algorithm that we previously developed to handle the problem of classifying proteins belonging to multi-functional fold families. CONCLUSION: The results indicate that the FSSA algorithm has better accuracy when compared to homology-based approaches for functional classification of both experimental and predicted protein structures, in part due to its use of local, as opposed to global, information for classifying function. The FSSA algorithm has also been implemented as a webserver and is available at

Evaluation of 3D-Jury on CASP7 models

<p>Abstract</p> <p>Background</p> <p>3D-Jury, the structure prediction consensus method publicly available in the Meta Server <url>http://meta.bioinfo.pl/</url>, was evaluated using models gathered in the 7^{<it>th </it>}round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers.</p> <p>Results</p> <p>The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models.</p> <p>Conclusion</p> <p>The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature <url>http://meta.bioinfo.pl/compare_your_model_example.pl</url> available in the Meta Server.</p

Considering scores between unrelated proteins in the search database improves profile comparison

<p>Abstract</p> <p>Background</p> <p>Profile-based comparison of multiple sequence alignments is a powerful methodology for the detection remote protein sequence similarity, which is essential for the inference and analysis of protein structure, function, and evolution. Accurate estimation of statistical significance of detected profile similarities is essential for further development of this methodology. Here we analyze a novel approach to estimate the statistical significance of profile similarity: the explicit consideration of background score distributions for each database template (subject).</p> <p>Results</p> <p>Using a simple scheme to combine and analytically approximate query- and subject-based distributions, we show that (i) inclusion of background distributions for the subjects increases the quality of homology detection; (ii) this increase is higher when the distributions are based on the scores to all known non-homologs of the subject rather than a small calibration subset of the database representatives; and (iii) these all known non-homolog distributions of scores for the subject make the dominant contribution to the improved performance: adding the calibration distribution of the query has a negligible additional effect.</p> <p>Conclusion</p> <p>The construction of distributions based on the complete sets of non-homologs for each subject is particularly relevant in the setting of structure prediction where the database consists of proteins with solved 3D structure (PDB, SCOP, CATH, etc.) and therefore structural relationships between proteins are known. These results point to a potential new direction in the development of more powerful methods for remote homology detection.</p