Study of SV40 large T antigen nucleotide specificity for DNA unwinding.

BACKGROUND: Simian Virus 40 (SV40) Large Tumor Antigen (LT) is an essential enzyme that plays a vital role in viral DNA replication in mammalian cells. As a replicative helicase and initiator, LT assembles as a double-hexamer at the SV40 origin to initiate genomic replication. In this process, LT converts the chemical energy from ATP binding and hydrolysis into the mechanical work required for unwinding replication forks. It has been demonstrated that even though LT primarily utilizes ATP to unwind DNA, other NTPs can also support low DNA helicase activity. Despite previous studies on specific LT residues involved in ATP hydrolysis, no systematic study has been done to elucidate the residues participating in the selective usage of different nucleotides by LT. In this study, we performed a systematic mutational analysis around the nucleotide pocket and identified residues regulating the specificity for ATP, TTP and UTP in LT DNA unwinding. METHODS: We performed site-directed mutagenesis to generate 16 LT nucleotide pocket mutants and characterized each mutant's ability to unwind double-stranded DNA, oligomerize, and bind different nucleotides using helicase assays, size-exclusion chromatography, and isothermal titration calorimetry, respectively. RESULTS: We identified four residues in the nucleotide pocket of LT, cS430, tK419, cW393 and cL557 that selectively displayed more profound impact on using certain nucleotides for LT DNA helicase activity. CONCLUSION: Little is known regarding the mechanisms of nucleotide specificity in SV40 LT DNA unwinding despite the abundance of information available for understanding LT nucleotide hydrolysis. The systematic residue analysis performed in this report provides significant insight into the selective usage of different nucleotides in LT helicase activity, increasing our understanding of how LT may structurally prefer different energy sources for its various targeted cellular activities.

StructMap: Elastic Distance Analysis of Electron Microscopy Maps for Studying Conformational Changes.

Single-particle electron microscopy (EM) has been shown to be very powerful for studying structures and associated conformational changes of macromolecular complexes. In the context of analyzing conformational changes of complexes, distinct EM density maps obtained by image analysis and three-dimensional (3D) reconstruction are usually analyzed in 3D for interpretation of structural differences. However, graphic visualization of these differences based on a quantitative analysis of elastic transformations (deformations) among density maps has not been done yet due to a lack of appropriate methods. Here, we present an approach that allows such visualization. This approach is based on statistical analysis of distances among elastically aligned pairs of EM maps (one map is deformed to fit the other map), and results in visualizing EM maps as points in a lower-dimensional distance space. The distances among points in the new space can be analyzed in terms of clusters or trajectories of points related to potential conformational changes. The results of the method are shown with synthetic and experimental EM maps at different resolutions.

Efficient initial volume determination from electron microscopy images of single particles.

MOTIVATION: Structural information of macromolecular complexes provides key insights into the way they carry out their biological functions. The reconstruction process leading to the final 3D map requires an approximate initial model. Generation of an initial model is still an open and challenging problem in single-particle analysis. RESULTS: We present a fast and efficient approach to obtain a reliable, low-resolution estimation of the 3D structure of a macromolecule, without any a priori knowledge, addressing the well-known issue of initial volume estimation in the field of single-particle analysis. The input of the algorithm is a set of class average images obtained from individual projections of a biological object at random and unknown orientations by transmission electron microscopy micrographs. The proposed method is based on an initial non-lineal dimensionality reduction approach, which allows to automatically selecting representative small sets of class average images capturing the most of the structural information of the particle under study. These reduced sets are then used to generate volumes from random orientation assignments. The best volume is determined from these guesses using a random sample consensus (RANSAC) approach. We have tested our proposed algorithm, which we will term 3D-RANSAC, with simulated and experimental data, obtaining satisfactory results under the low signal-to-noise conditions typical of cryo-electron microscopy. AVAILABILITY: The algorithm is freely available as part of the Xmipp 3.1 package [http://xmipp.cnb.csic.es]. CONTACT: jvargas@cnb.csic.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.