EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

Functional analysis and structural modeling of human APOBEC3G reveal the role of evolutionarily conserved elements in the inhibition of human immunodeficiency virus type 1 infection and Alu transposition.

Retroelements are important evolutionary forces but can be deleterious if left uncontrolled. Members of the human APOBEC3 family of cytidine deaminases can inhibit a wide range of endogenous, as well as exogenous, retroelements. These enzymes are structurally organized in one or two domains comprising a zinc-coordinating motif. APOBEC3G contains two such domains, only the C terminal of which is endowed with editing activity, while its N-terminal counterpart binds RNA, promotes homo-oligomerization, and is necessary for packaging into human immunodeficiency virus type 1 (HIV-1) virions. Here, we performed a large-scale mutagenesis-based analysis of the APOBEC3G N terminus, testing mutants for (i) inhibition of vif-defective HIV-1 infection and Alu retrotransposition, (ii) RNA binding, and (iii) oligomerization. Furthermore, in the absence of structural information on this domain, we used homology modeling to examine the positions of functionally important residues and of residues found to be under positive selection by phylogenetic analyses of primate APOBEC3G genes. Our results reveal the importance of a predicted RNA binding dimerization interface both for packaging into HIV-1 virions and inhibition of both HIV-1 infection and Alu transposition. We further found that the HIV-1-blocking activity of APOBEC3G N-terminal mutants defective for packaging can be almost entirely rescued if their virion incorporation is forced by fusion with Vpr, indicating that the corresponding region of APOBEC3G plays little role in other aspects of its action against this pathogen. Interestingly, residues forming the APOBEC3G dimer interface are highly conserved, contrasting with the rapid evolution of two neighboring surface-exposed amino acid patches, one targeted by the Vif protein of primate lentiviruses and the other of yet-undefined function.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Identification of structural variation in mouse genomes.

Structural variation is variation in structure of DNA regions affecting DNA sequence length and/or orientation. It generally includes deletions, insertions, copy-number gains, inversions, and transposable elements. Traditionally, the identification of structural variation in genomes has been challenging. However, with the recent advances in high-throughput DNA sequencing and paired-end mapping (PEM) methods, the ability to identify structural variation and their respective association to human diseases has improved considerably. In this review, we describe our current knowledge of structural variation in the mouse, one of the prime model systems for studying human diseases and mammalian biology. We further present the evolutionary implications of structural variation on transposable elements. We conclude with future directions on the study of structural variation in mouse genomes that will increase our understanding of molecular architecture and functional consequences of structural variation.

Fitness, inclusive fitness, and optimization

Individual-as-maximizing agent analogies result in a simple understanding of the functioning of the biological world. Identifying the conditions under which individuals can be regarded as fitness maximizing agents is thus of considerable interest to biologists. Here, we compare different concepts of fitness maximization, and discuss within a single framework the relationship between Hamilton's (J Theor Biol 7: 1-16, 1964) model of social interactions, Grafen's (J Evol Biol 20: 1243-1254, 2007a) formal Darwinism project, and the idea of evolutionary stable strategies. We distinguish cases where phenotypic effects are additive separable or not, the latter not being covered by Grafen's analysis. In both cases it is possible to define a maximand, in the form of an objective function phi(z), whose argument is the phenotype of an individual and whose derivative is proportional to Hamilton's inclusive fitness effect. However, this maximand can be identified with the expression for fecundity or fitness only in the case of additive separable phenotypic effects, making individual-as-maximizing agent analogies unattractive (although formally correct) under general situations of social interactions. We also feel that there is an inconsistency in Grafen's characterization of the solution of his maximization program by use of inclusive fitness arguments. His results are in conflict with those on evolutionary stable strategies obtained by applying inclusive fitness theory, and can be repaired only by changing the definition of the problem.

Structure-function characterization and optimization of a plant-derived antibacterial peptide.

Crushed seeds of the Moringa oleifera tree have been used traditionally as natural flocculants to clarify drinking water. We previously showed that one of the seed peptides mediates both the sedimentation of suspended particles such as bacterial cells and a direct bactericidal activity, raising the possibility that the two activities might be related. In this study, the conformational modeling of the peptide was coupled to a functional analysis of synthetic derivatives. This indicated that partly overlapping structural determinants mediate the sedimentation and antibacterial activities. Sedimentation requires a positively charged, glutamine-rich portion of the peptide that aggregates bacterial cells. The bactericidal activity was localized to a sequence prone to form a helix-loop-helix structural motif. Amino acid substitution showed that the bactericidal activity requires hydrophobic proline residues within the protruding loop. Vital dye staining indicated that treatment with peptides containing this motif results in bacterial membrane damage. Assembly of multiple copies of this structural motif into a branched peptide enhanced antibacterial activity, since low concentrations effectively kill bacteria such as Pseudomonas aeruginosa and Streptococcus pyogenes without displaying a toxic effect on human red blood cells. This study thus identifies a synthetic peptide with potent antibacterial activity against specific human pathogens. It also suggests partly distinct molecular mechanisms for each activity. Sedimentation may result from coupled flocculation and coagulation effects, while the bactericidal activity would require bacterial membrane destabilization by a hydrophobic loop.

Evolution of the P-type II ATPase gene family in the fungi and presence of structural genomic changes among isolates of Glomus intraradices.

BACKGROUND: The P-type II ATPase gene family encodes proteins with an important role in adaptation of the cell to variation in external K+, Ca2+ and Na2+ concentrations. The presence of P-type II gene subfamilies that are specific for certain kingdoms has been reported but was sometimes contradicted by discovery of previously unknown homologous sequences in newly sequenced genomes. Members of this gene family have been sampled in all of the fungal phyla except the arbuscular mycorrhizal fungi (AMF; phylum Glomeromycota), which are known to play a key-role in terrestrial ecosystems and to be genetically highly variable within populations. Here we used highly degenerate primers on AMF genomic DNA to increase the sampling of fungal P-Type II ATPases and to test previous predictions about their evolution. In parallel, homologous sequences of the P-type II ATPases have been used to determine the nature and amount of polymorphism that is present at these loci among isolates of Glomus intraradices harvested from the same field. RESULTS: In this study, four P-type II ATPase sub-families have been isolated from three AMF species. We show that, contrary to previous predictions, P-type IIC ATPases are present in all basal fungal taxa. Additionally, P-Type IIE ATPases should no longer be considered as exclusive to the Ascomycota and the Basidiomycota, since we also demonstrate their presence in the Zygomycota. Finally, a comparison of homologous sequences encoding P-type IID ATPases showed unexpectedly that indel mutations among coding regions, as well as specific gene duplications occur among AMF individuals within the same field. CONCLUSION: On the basis of these results we suggest that the diversification of P-Type IIC and E ATPases followed the diversification of the extant fungal phyla with independent events of gene gains and losses. Consistent with recent findings on the human genome, but at a much smaller geographic scale, we provided evidence that structural genomic changes, such as exonic indel mutations and gene duplications are less rare than previously thought and that these also occur within fungal populations.

Evolutionary footprint of coevolving positions in genes.

MOTIVATION: The analysis of molecular coevolution provides information on the potential functional and structural implication of positions along DNA sequences, and several methods are available to identify coevolving positions using probabilistic or combinatorial approaches. The specific nucleotide or amino acid profile associated with the coevolution process is, however, not estimated, but only known profiles, such as the Watson-Crick constraint, are usually considered a priori in current measures of coevolution. RESULTS: Here, we propose a new probabilistic model, Coev, to identify coevolving positions and their associated profile in DNA sequences while incorporating the underlying phylogenetic relationships. The process of coevolution is modeled by a 16 × 16 instantaneous rate matrix that includes rates of transition as well as a profile of coevolution. We used simulated, empirical and illustrative data to evaluate our model and to compare it with a model of 'independent' evolution using Akaike Information Criterion. We showed that the Coev model is able to discriminate between coevolving and non-coevolving positions and provides better specificity and specificity than other available approaches. We further demonstrate that the identification of the profile of coevolution can shed new light on the process of dependent substitution during lineage evolution.