Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays.

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS.

Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand.

RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial 'low-resolution' docking step.

In silico analysis and experimental verification of OSR1 kinase - Peptide interaction.

The oxidative-stress-responsive kinase 1 (OSR1) and the STE20/SPS1-related proline/alanine-rich kinase (SPAK) are key enzymes in a signaling cascade regulating the activity of Na(+)-K(+)-2Cl(-) cotransporters (NKCC1-2) and Na(+)-Cl(-) cotransporter (NCC). Both kinases have a conserved carboxyl-terminal (CCT) domain, which recognizes a unique peptide motif present in OSR1- and SPAK-activating kinases (with-no-lysine kinase 1 (WNK1) and WNK4) as well as their substrates (NKCC1, NKCC2, and NCC). Utilizing various modalities of the Rosetta Molecular Modeling Software Suite including flexible peptide docking and protein design, we comprehensively explored the sequence space recognized by the CCT domain.

Small-molecule ligand docking into comparative models with Rosetta.

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable.

Human germline antibody gene segments encode polyspecific antibodies.

Structural flexibility in germline gene-encoded antibodies allows promiscuous binding to diverse antigens. The binding affinity and specificity for a particular epitope typically increase as antibody genes acquire somatic mutations in antigen-stimulated B cells. In this work, we investigated whether germline gene-encoded antibodies are optimal for polyspecificity by determining the basis for recognition of diverse antigens by antibodies encoded by three VH gene segments.

Design of native-like proteins through an exposure-dependent environment potential.

We hypothesize that the degree of surface exposure of amino acid side chains within a globular, soluble protein has been optimized in evolution, not only to minimize the solvation free energy of the monomeric protein but also to prevent protein aggregation. This effect needs to be taken into account when engineering proteins de novo. We test this hypothesis through addition of a knowledge-based, exposure-dependent energy term to the RosettaDesign solvation potential [Lazaridis, T.

Practically useful: what the Rosetta protein modeling suite can do for you.

The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol.