What Can We Learn from the Evolution of Protein-Ligand Interactions to Aid the Design of New Therapeutics?

Efforts to increase affinity in the design of new therapeutic molecules have tended to lead to greater lipophilicity, a factor that is generally agreed to be contributing to the low success rate of new drug candidates. Our aim is to provide a structural perspective to the study of lipophilic efficiency and to compare molecular interactions created over evolutionary time with those designed by humans. We show that natural complexes typically engage in more polar contacts than synthetic molecules bound to proteins. The synthetic molecules also have a higher proportion of unmatched heteroatoms at the interface than the natural sets. These observations suggest that there are lessons to be learnt from Nature, which could help us to improve the characteristics of man-made molecules. In particular, it is possible to increase the density of polar contacts without increasing lipophilicity and this is best achieved early in discovery while molecules remain relatively small.     

Within- and between-species patterns of allocation to pulp and seed in vertebrate dispersed plants

Non-uniform scaling of pulp and seed mass has been shown to alter dispersal probabilities in vertebrate dispersed species. Since dispersal in tropical forests is strongly linked to establishment success, processes determining allocation to pulp and seed are likely to impact on parental fitness, and therefore should be under the control of natural selection. In this study I examine size-dependent dry mass allocation pattern to pulp and seed mass both among and within 20 fruit-producing plant species of tropical rainforest in northeast Queensland, Australia. Reduced major axis analyses using mean values for each species showed significant isometry, indicating that at the community level, plant species that employ vertebrates as a means of seed dispersal tend to allocate an equivalent mean relative proportion of the overall dry weight investment in fruit to pulp. However, identical analyses conducted for each species separately revealed that relationships within individual species do not reflect the inter-specific relationship. These results imply two influences on dry mass allocation to fruit components; the first (within-species allometry) determines how fruits vary within each species. The second (between-species allometry) operates in a similar manner across species to produce equal ratios of mean pulp and seed mass independent of within-species allometries.     

Population Level Inference for Multivariate MEG Analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation.     

Partial characterization of protein kinase-catalyzed phosphorylation of low molecular weight proteins in purified preparations of pigeon heart sarcolemma and sarcoplasmic reticulum

Pigeon heart microsomes contain three minor size protein kinase substrates of minimal molecular weights of 22 000, 15 000, and 11 500, as estimated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. When the microsomes were partially loaded with calcium oxalate and subjected to rate zonal and isopynic centrifugations in sucrose density gradient columns, the 22 000 and the 15 000 dalton proteins settled in the heaviest fraction, which was composed mainly of vesicles of sarcoplasmic reticular membranes; the 11 500 dalton protein was concentrated in the lightest fractions, which consisted chiefly of vesicles of sarcolemmal origin. During incubation of the membrane fractions with Mg[γ-³²P]ATP significant amounts of ³²P were incorporated into all these proteins. Incorporation of ³²P into the 15 000 dalton protein was moderately and ³²P incorporation into the 22 000 dalton protein was markedly enhanced in the presence of exogenous soluble cyclic AMP-dependent protein kinase and cyclic AMP. The phosphorylation of the three proteins was virtually unaffected by CA²⁺ concentrations up to 0.1 mM and by ethyleneglycol-bis(β-aminoethylether)-N,N′-tetraacetic acid in the absence of added Ca²⁺.Phosphorylation of the 22 000 and the 11 500 dalton proteins occurred mainly at serine residues. In the 15 000 dalton protein threonine residues were the main site of endogenous phosphorylation. Nearly equal amounts of [³²P]-phosphate were incorporated into threonine and serine residues of this protein when phosphorylation was supported by exogenous cyclic AMP-dependent protein kinase and cyclic AMP.The 15 000 dalton protein could be removed from its membrane attachment by extraction with an acidic chloroform/methanol mixture. This step opens the way for the purification of this membrane-bound protein kinase substrate.     

CRISPRmap: an automated classification of repeat conservation in prokaryotic adaptive immune systems

Central to Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Cas systems are repeated RNA sequences that serve as Cas-protein–binding templates. Classification is based on the architectural composition of associated Cas proteins, considering repeat evolution is essential to complete the picture. We compiled the largest data set of CRISPRs to date, performed comprehensive, independent clustering analyses and identified a novel set of 40 conserved sequence families and 33 potential structure motifs for Cas-endoribonucleases with some distinct conservation patterns. Evolutionary relationships are presented as a hierarchical map of sequence and structure similarities for both a quick and detailed insight into the diversity of CRISPR-Cas systems. In a comparison with Cas-subtypes, I-C, I-E, I-F and type II were strongly coupled and the remaining type I and type III subtypes were loosely coupled to repeat and Cas1 evolution, respectively. Subtypes with a strong link to CRISPR evolution were almost exclusive to bacteria; nevertheless, we identified rare examples of potential horizontal transfer of I-C and I-E systems into archaeal organisms. Our easy-to-use web server provides an automated assignment of newly sequenced CRISPRs to our classification system and enables more informed choices on future hypotheses in CRISPR-Cas research: http://rna.informatik.uni-freiburg.de/CRISPRmap.