Biology subjects

Razban, R.

Publications and source records attributed to Razban, R..

3 recordsLinked to original sources

bioRxiv2024

Modeling brain signaling as Markovian helps explain its structure-function relationship

Structure determines function. However, this universal theme in biology has been surprisingly difficult to observe in human brain neuroimaging data. Here, we link structure to function by hypothesizing that brain signals propagate as a Markovian process on an underlying structure. We focus on a metric called commute time: the average number of steps for a random walker to go from region A to B and then back to A. Commute times based on white matter tracts from diffusion MRI exhibit an average {+/-} standard deviation Spearman correlation of -0.26 {+/-} 0.08 with functional MRI connectivity data across 434 UK Biobank individuals and -0.24 {+/-} 0.06 across 400 HCP Young Adult brain scans. The correlation increases to -0.36 {+/-} 0.14 and to -0.32 {+/-} 0.12 when the principal contributions of both commute time and functional connectivity are compared for both datasets. The correlations are stronger by 33% compared to broadly used communication measures such as search information and communicability. The difference further widens to a factor of 5 when commute times are correlated to the principal mode of functional connectivity from its eigenvalue decomposition. Overall, the study points to the utility of commute time to account for the role of polysynaptic (indirect) connectivity underlying brain function by assuming that signals randomly traverse along the underlying brain structure.

neuroscience↗

bioRxiv2019

Conformational catalysis of cataract-associated aggregation by interacting intermediates in a human eye lens crystallin

Human {gamma}D-crystallin (H{gamma}D) is an abundant and highly stable two-domain protein in the core region of the eye lens. Destabilizing mutations and post-translational modifications in this protein are linked to onset of aggregation that causes cataract disease (lens turbidity). Wild-type H{gamma}D greatly accelerates aggregation of the cataract-related W42Q variant, without itself aggregating. The mechanism of this \"inverse prion\" catalysis of aggregation remained unknown. Here we provide evidence that an early unfolding intermediate with an opened domain interface enables transient dimerization of the C-terminal domains of wild-type and mutant, or mutant and mutant, H{gamma}D molecules, which deprives the mutants N-terminal domain of intramolecular stabilization by the native domain interface and thus accelerates its misfolding to a distinct, aggregation-prone intermediate. A detailed kinetic model predicts universal power-law scaling relationships for lag time and rate of the resulting aggregation, which are in excellent agreement with the data. The mechanism reported here, which we term interface stealing, can be generalized to explain how common domain-domain interactions can have surprising consequences, such as conformational catalysis of unfolding, in multidomain proteins.\n\nSignificanceMost known proteins in nature consist of multiple domains. Interactions between domains may lead to unexpected folding and misfolding phenomena. This study of human {gamma}D-crystallin, a two-domain protein in the eye lens, revealed one such surprise: conformational catalysis of misfolding via intermolecular domain interface \"stealing.\" An intermolecular interface between the more stable domains outcompetes the native intramolecular domain interface. Loss of the native interface in turn promotes misfolding and subsequent aggregation, especially in cataract-related {gamma}D-crystallin variants. This phenomenon is likely a contributing factor in the development of cataract disease, the leading worldwide cause of blindness. However, interface stealing likely occurs in many proteins composed of two or more interacting domains.

biophysics↗

bioRxiv2017

ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms’ proteomes

MotivationProtein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the S. cerevisiae and E. coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution is studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level.\n\nResultsWe demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S. cerevisiae and E. coli oPCUGs are scale-free with scaling constants of 1.78 and 1.50, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution (Dokholyan et al., 2002). Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.51 (p-value<10-10) and -0.46 (p-value<10-10) for S. cerevisiae and E. coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant (Zhang and Yang, 2015).\n\nAvailabilityProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu/proteomevis/.\n\nContactshakhnovich@chemistry.harvard.edu\n\nSupplementary informationAvailable to download on bioRxiv.

evolutionary biology↗