Decrypting the Information Exchange Pathways across the Spliceosome Machinery

Abstract

Intron splicing of a nascent mRNA transcript by spliceosome (SPL) is a hallmark of gene regulation in eukaryotes. SPL is a majestic molecular machine composed of an entangled network of proteins and RNAs that meticulously promotes intron splicing through the formation of eight intermediate complexes. Cross-communication among the critical distal proteins of the SPL assembly is pivotal for fast and accurate directing of the compositional and conformational readjustments necessary to achieve high splicing fidelity. Here, molecular dynamics (MD) simulations of an 800 000 atom model of SPL C complex from yeast Saccharomyces cerevisiae and community network analysis enabled us to decrypt the complexity of this huge molecular

Network Theory Reveals Principles of Spliceosome Structure and Dynamics

“…A recent study calculated network betweenness of spliceosome C complex factors and supported a well-established function of Prp8 as key communication conduit within spliceosome (Brow, 2002;Saltalamacchia et al, 2020). Our analysis provides further insights.…”

“…However, these studies are difficult to interpret with respect to molecular mechanisms since snRNAs are not part of the STRING database and without structural data the intermolecular contacts that cause changes in biological function are unclear. Recently, network theory analysis of a spliceosome structure combined with molecular dynamic simulations were used to identify putative information exchange pathways among splicing machinery components (Clf1, Cwc2, and Prp8) in the yeast C complex spliceosome (Saltalamacchia et al, 2020; Shao et al, 2020b). It is not clear, though, how the C complex structural network is assembled or changes during splicing.…”

Distant Residues Modulate Conformational Opening in SARS-CoV-2 Spike Protein

“…In it, the C α atoms of each amino acid are the nodes and the correlation between them are the edges connecting the nodes. The number of nodes in our system is N=3438, which makes it one of the largest systems studied previously with this method (60–65)(Comparable to the work by Saltalamacchia et al on a splicosome complex involving 4804 C α atomd and 270 phosphorus atoms in the network (69)). We then calculated the betweenness centrality (BC), a graph theoretical measure that provides a way to quantify the amount of information that flows via the nodes and edges of a network.…”

Allosteric Cross-Talk Among SARS-CoV-2 Spike’s Receptor-Binding Domain Mutations Triggers an Effective Hijacking of Human Cell Receptor

“…Due to the strategic location of K417, halfway of L1/4 and L3 in the RBM, tweezing the α1helix@ACE2, we computed the cross-correlation matrices based on the Pearson's correlation coefficient and the per-residue sum of the Cross-Correlation coefficient (CCc) for the residues at the RBM/ACE2 interface (Figure S3). [26][27] Stunningly, SA RBD/ACE2 and K417 RBD/ACE2 exhibit the largest CCcs all over the RBM, with the difference of SA RBD/ACE2 being more marked at the L1/4 and L3 regions.…”

“…Since an allosteric communication among SARS-CoV-2 mutations has been recently speculated, [28][29][30] we then applied dynamical NetWork theory Analysis (NWA) to decrypt the information-exchange pathways underlying the observed RBD functional dynamics and to decode whether RBD mutants can enhance the allosteric cross-talk between critical RDB's structural elements. 26,31 In NWA, the protein is represented as a correlation-based weighted network. The nodes (the residues' center of mass) are connected by edges whose numerical value (weight) indicates the correlation-strength between residues pairs (i.e.…”