The blobulator: a webtool for identification and visual exploration of hydrophobic modularity in protein sequences.

Motivation: Clusters of hydrophobic residues are known to promote structured protein stability and drive protein aggregation. Recent work has shown that identifying contiguous hydrophobic residue clusters (termed "blobs") has proven useful in both intrinsically disordered protein (IDP) simulation and human genome studies. However, a graphical interface was unavailable.

A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships.

Background: Chromatin contacts are essential for gene-expression regulation; however, obtaining a high-resolution genome-wide chromatin contact map is still prohibitively expensive owing to large genome sizes and the quadratic scale of pairwise data. Chromosome conformation capture (3C)-based methods such as Hi-C have been extensively used to obtain chromatin contacts. However, since the sparsity of these maps increases with an increase in genomic distance between contacts, long-range or trans-chromatin contacts are especially challenging to sample.

Contiguously hydrophobic sequences are functionally significant throughout the human exome.

Hydrophobic interactions have long been established as essential for stabilizing struc-tured proteins as well as drivers of aggregation, but the impact of hydrophobicity on thefunctional significance of sequence variants has rarely been considered in a genome-wide context. Here we test the role of hydrophobicity on functional impact across70,000 disease- and non–disease-associated single-nucleotide polymorphisms (SNPs),using enrichment of disease association as an indicator of functionality. We find thatfunctional impact is uncorrelated with hydrophobicity of the SNP itself and only weaklycorrelated with the average local hydrophobicity, but is strongly correlated with boththe size and minimum hydrophobicity of the contiguously hydrophobic sequence (or“blob”) that contains the SNP.

Characterization of intrinsically disordered regions in proteins informed by human genetic diversity.

All proteomes contain both proteins and polypeptide segments that don't form a defined three-dimensional structure yet are biologically active-called intrinsically disordered proteins and regions (IDPs and IDRs). Most of these IDPs/IDRs lack useful functional annotation limiting our understanding of their importance for organism fitness. Here we characterized IDRs using protein sequence annotations of functional sites and regions available in the UniProt knowledgebase ("UniProt features": active site, ligand-binding pocket, regions mediating protein-protein interactions, etc.

Sequence specificity despite intrinsic disorder: How a disease-associated Val/Met polymorphism rearranges tertiary interactions in a long disordered protein.

The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) in precursor brain-derived neurotrophic factor (BDNF) is one of the earliest SNPs to be associated with neuropsychiatric disorders, and the underlying molecular mechanism is unknown. Here we report on over 250 μs of fully-atomistic, explicit solvent, temperature replica-exchange molecular dynamics (MD) simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence.

A Streamlined, General Approach for Computing Ligand Binding Free Energies and Its Application to GPCR-Bound Cholesterol.

The theory of receptor-ligand binding equilibria has long been well-established in biochemistry, and was primarily constructed to describe dilute aqueous solutions. Accordingly, few computational approaches have been developed for making quantitative predictions of binding probabilities in environments other than dilute isotropic solution. Existing techniques, ranging from simple automated docking procedures to sophisticated thermodynamics-based methods, have been developed with soluble proteins in mind.

Comparative metagenome analysis of an Alaskan glacier.

The temperature in the Arctic region has been increasing in the recent past accompanied by melting of its glaciers. We took a snapshot of the current microbial inhabitation of an Alaskan glacier (which can be considered as one of the simplest possible ecosystems) by using metagenomic sequencing of 16S rRNA recovered from ice/snow samples. Somewhat contrary to our expectations and earlier estimates, a rich and diverse microbial population of more than 2,500 species was revealed including several species of Archaea that has been identified for the first time in the glaciers of the Northern hemisphere.