Wordom update 2: A user-friendly program for the analysis of molecular structures and conformational ensembles

We present the second update of Wordom, a user-friendly and efficient program for manipulation and analysis of conformational ensembles from molecular simulations. The actual update expands some of the existing modules and adds 21 new modules to the update 1 published in 2011. The new adds can be divided into three sets that: 1) analyze atomic fluctuations and structural communication; 2) explore ion-channel conformational dynamics and ionic translocation; and 3) compute geometrical indices of structural deformation. Set 1 serves to compute correlations of motions, find geometrically stable domains, identify a dynamically invariant core, find changes in domain-domain separation and mutual orientation, perform wavelet analysis of large-scale simulations, process the output of principal component analysis of atomic fluctuations, perform functional mode analysis, infer regions of mechanical rigidity, analyze overall fluctuations, and perform the perturbation response scanning. Set 2 includes modules specific for ion channels, which serve to monitor the pore radius as well as water or ion fluxes, and measure functional collective motions like receptor twisting or tilting angles. Finally, set 3 includes tools to monitor structural deformations by computing angles, perimeter, area, volume, β-sheet curvature, radial distribution function, and center of mass. The ring perception module is also included, helpful to monitor supramolecular self-assemblies. This update places Wordom among the most suitable, complete, user-friendly, and efficient software for the analysis of biomolecular simulations. The source code of Wordom and the relative documentation are available under the GNU general public license at http://wordom.sf.net

Catching Functional Modes and Structural Communication in Dbl Family Rho Guanine Nucleotide Exchange Factors

Computational approaches such as Principal Component Analysis (PCA) and Elastic Network Model-Normal Mode Analysis (ENM-NMA) are proving to be of great value in investigating relevant biological problems linked to slow motions with no demand in computer power. In this study, these approaches have been coupled to the graph theory-based Protein Structure Network (PSN) analysis to dissect functional dynamics and structural communication in the Dbl family of Rho Guanine Nucleotide Exchange Factors (RhoGEFs). They are multidomain proteins whose common structural feature is a DH-PH tandem domain deputed to the GEF activity that makes them play a central role in cell and cancer biology. While their common GEF action is accomplished by the DH domain, their regulatory mechanisms are highly variegate and depend on the PH and the additional domains as well as on interacting proteins. Major evolutionary-driven deformations as inferred from PCA concern the alpha6 helix of DH that dictates the orientation of the PH domain. Such deformations seem to depend on the mechanisms adopted by the GEF to prevent Rho binding, i.e. functional specialization linked to autoinhibition. In line with PCA, ENM-NMA indicates alpha6 and the linked PH domain as the portions of the tandem domain holding almost the totality of intrinsic and functional dynamics, with the alpha6/beta1 junction acting as a hinge point for the collective motions of PH. In contrast, the DH domain holds a static scaffolding and hub behavior, with structural communication playing a central role in the regulatory actions by other domains/proteins. Possible allosteric communication pathways involving essentially DH were indeed found in those RhoGEFs acting as effectors of small or heterotrimeric RasGTPases. The employed methodology is suitable for deciphering structure/dynamics relationships in large sets of homologous or analogous proteins

Understanding Structure and Dynamics of PTEN and its Possible Genotype-Phenotype Correlations in Endometriosis and Cancer

The phosphatase and tensin homolog deleted on chromosome 10, (PTEN) gene encodes a tumor suppressor phosphatase frequently mutated in various human cancers. Somatic missense mutations of PTEN have recently been found in patients with endometriosis, endometrial cancer, and ovarian cancer. Here we present the first computational analysis of 13 somatic missense PTEN mutations to assess a possible genotype-phenotype correlation in endometriosis and cancer. We posit PTEN’s active site defines a possible mutation-driven allosteric region wherein a subset of mutations correlate with endometriosis, endometrial cancer, and ovarian cancer. Our data suggest that mutations within the active site disrupt the structural stability, electrostatic interaction, global dynamics and the structural communication pathway, likely contributing to the aforementioned phenotypes. Multiple in silico prediction methods were utilized to calculate protein structural stability changes produced by each mutation; decreases in protein structure stability were seen in each mutation with an increase in dynamics across the phosphatase-C2 domain interface of R130G/L/Q and R173C/H mutations. To assess the impact on intrinsic and global dynamics, elastic network models (ENMs) were employed demonstrating changes from wild-type “hinge-bending” to “zipper-like” global motions induced by each mutation. All-atom molecular dynamics (MD) simulations revealed large conformational changes that affect the global dynamics of the active site loops and the CBR3 loop in the C2 domain. Interestingly, mutations G36E/R, C124S, G129R, R130L/Q, R173C/H, and V191A dramatically affected the principal motions of the active site loops and inter-domain interface. Overall, the global dynamics induced by each mutation effects reveal unique long-range perturbations that may impair PTEN’s function. We further investigated structural communication within each mutant system using protein structure network (PSN) analysis and found that R130 and R173 play critical roles in controlling salient communication pathways suggesting a compelling interplay between the two positions involving a potential mutation-driven allosteric interface. The results of this research provide a greater understanding of the mechanistic role of mutated PTEN associated with endometriosis and cancer. It is our hope that these results will aid in a better clinical-molecular classification of the resulting phenotypes allowing for translation into improved diagnostic and therapeutic approaches.Biology and Biochemistry, Department o