Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.

The packaging and organization of genomic DNA into chromatin represents an additional regulatory layer of gene expression, with specific nucleosome positions that restrict the accessibility of regulatory DNA elements. The mechanisms that position nucleosomes in vivo are thought to depend on the biophysical properties of the histones, sequence patterns, like phased di-nucleotide repeats and the architecture of the histone octamer that folds DNA in 1.65 tight turns. Comparative studies of human and P. falciparum histones reveal that the latter have a strongly reduced ability to recognize internal sequence dependent nucleosome positioning signals. In contrast, the nucleosomes are positioned by AT-repeat sequences flanking nucleosomes in vivo and in vitro. Further, the strong sequence variations in the plasmodium histones, compared to other mammalian histones, do not present adaptations to its AT-rich genome. Human and parasite histones bind with higher affinity to GC-rich DNA and with lower affinity to AT-rich DNA. However, the plasmodium nucleosomes are overall less stable, with increased temperature induced mobility, decreased salt stability of the histones H2A and H2B and considerable reduced binding affinity to GC-rich DNA, as compared with the human nucleosomes. In addition, we show that plasmodium histone octamers form the shortest known nucleosome repeat length (155bp) in vitro and in vivo. Our data suggest that the biochemical properties of the parasite histones are distinct from the typical characteristics of other eukaryotic histones and these properties reflect the increased accessibility of the P. falciparum genome.

Straka MM, Schmitz S, Lim HH. Response features across the auditory midbrain reveal an organization consistent with a dual lemniscal pathway. J Neurophysiol 112: 981-998, 2014. First published May 14, 2014 doi:10.1152/jn.00008.2014.-The central auditory system has traditionally been divided into lemniscal and nonlemniscal pathways leading from the midbrain through the thalamus to the cortex. This view has served as an organizing principle for studying, modeling, and understanding the encoding of sound within the brain. However, there is evidence that the lemniscal pathway could be further divided into at least two subpathways, each potentially coding for sound in different ways. We investigated whether such an interpretation is supported by the spatial distribution of response features in the central nucleus of the inferior colliculus (ICC), the part of the auditory midbrain assigned to the lemniscal pathway. We recorded responses to pure tone stimuli in the ICC of ketamine-xylazineanesthetized guinea pigs and used three-dimensional brain reconstruction techniques to map the location of the recording sites. Compared with neurons in caudal-and-medial regions within an isofrequency lamina of the ICC, neurons in rostral-and-lateral regions responded with shorter first-spike latencies with less spiking jitter, shorter durations of spiking responses, a higher proportion of spikes occurring near the onset of the stimulus, lower thresholds, and larger local field potentials with shorter latencies. Further analysis revealed two distinct clusters of response features located in either the caudal-and-medial or the rostral-and-lateral parts of the isofrequency laminae of the ICC. Thus we report substantial differences in coding properties in two regions of the ICC that are consistent with the hypothesis that the lemniscal pathway is made up of at least two distinct subpathways from the midbrain up to the cortex. functional organization; inferior colliculus; lemniscal; medial geniculate; auditory cortex THE ASCENDING AUDITORY PATHWAY has traditionally been separated into two pathways, the lemniscal "core" pathway and the nonlemniscal pathway (Andersen et al. 1980;Ehret and Romand 1997;Rauschecker and Romanski 2011;Rouiller 1997). The lemniscal pathway includes neurons in the central nucleus of the inferior colliculus (ICC), the ventral division of the medial geniculate body (MGV), and core auditory cortex regions (ACC). Neurons within the lemniscal pathway are tonotopically organized and primarily code for auditory information. Within the ICC and MGV, the tonotopicity derives from an arrangement of isofrequency laminae, where each lamina is a two-dimensional sheet formed by the dendritic arbors of neurons that respond optimally to similar "best frequencies" (Cetas et al. 2001;Imig and Morel 1985;Malmierca et al. 1993;Winer and Schreiner 2005). In contrast, neurons within the nonlemniscal pathway include regions outside of ICC, MGV, and ACC, have poor or no tonotopic organization, code for multimodal information, and are tho...

Background: Deficiency in the leptin-leptin receptor (LEPR) axis leads to severe, and potentially treatable, obesity in humans. To guide clinical decision-making, the functional relevance of variants in the LEPR gene needs to be carefully investigated. Cases and methods: We characterized the functional impact of LEPR variants identified in two patients with severe early-onset obesity (1: compound heterozygous for the novel variant p.Tyr411del and p.Trp664Arg; 2: heterozygous for p.Arg612His) by investigating leptin-mediated signaling, leptin binding, receptor expression on cell surfaces, and receptor dimerization and activation for either wild-type and/or mutant LEPR. Results: Leptin-induced STAT3-phosphorylation was blunted the novel p.Tyr411del or the p.Trp664Arg variant and mildly reduced with the p.Arg612His variant. Computational structure prediction suggested impaired leptin binding for all three LEPR variants. Experimentally, reduced leptin binding of all mutant proteins was due to diminished LEPR expression on the cell surface, with the p.Trp664Arg mutations being the most affected. Considering the heterozygosity in our patients, we assessed the heterodimerization capacity with the wild-type LEPR, which was retained for the p.Tyr411del and p.Arg612His variants. Finally, mimicking (compound) heterozygosity, we confirmed abolished STAT3-phosphorylation for the variant combination [p.Tyr411del + p.Trp664Arg] as found in patient 1, whereas it was retained for [p.Arg612His + wilde type] as found in patient 2. Conclusions: The novel p.Tyr411del mutation causes complete loss of function alone (and combined with p. Trp664Arg) and is likely the cause for the early onset obesity, qualifying the patient for pharmacologic treatment. Heterozygosity for the p.Arg612His variant, however, appears unlikely to be solely responsible for the phenotype.

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Background: Recent advances in DNA sequencing technologies have enabled significant leaps in capacity to generate large volumes of DNA sequence data, which has spurred a rapid growth in the use of bioinformatics as a means of interrogating antibody variable gene repertoires. Common tools used for annotation of antibody sequences are often limited in functionality, modularity and usability. Results: We have developed PyIR, a Python wrapper and library for IgBLAST, which offers a minimal setup CLI and API, FASTQ support, file chunking for large sequence files, JSON and Python dictionary output, and built-in sequence filtering. Conclusions: PyIR offers improved processing speed over multithreaded IgBLAST (version 1.14) when spawning more than 16 processes on a single computer system. Its customizable filtering and data encapsulation allow it to be adapted to a wide range of computing environments. The API allows for IgBLAST to be used in customized bioinformatics workflows.

The antibody (Ab) germline gene rearrangement of variable (V), diversity (D), and joining (J) gene segments, as well as somatic hypermutation, give rise to the human Ab variable gene sequence repertoire. It is common to characterize single nucleotide frequencies of the variable region by alignment to species-specific wildtype germline genes. The increasing application of next-generation sequencing to immune repertoire studies has led to the compilation of increasing large adaptive immunome receptor repertoire datasets. We have developed a method that maps the sequence of a target Ab onto an immunome dataset of 326 million human Ab sequences. For this purpose, we created a position-and gene-specific scoring matrix (PGSSM) and its corresponding antibody similarity score. We characterized our PGSSM score and found that it strongly correlated with the phylogenetic distance of 181,355 Ab sequences from GenBank across 20 species. The most likely human nucleotide back-translation was obtained given only PGSSMs and the amino acid sequence of an Ab achieving a nucleotide sequence recovery of 95.9% and 97.2% for human heavy and light chains, respectively. In conclusion, the scoring of our back-translation is a valuable estimate for the similarity of an Ab sequence to the natural human repertoire. As expected, Ab therapeutic molecules developed from a human source showed a higher similarity to the repertoire than engineered Abs. Thus, the PGSSM metric introduced here can be used to engineer human-like Ab therapeutics.

Computational protein design has the ambitious goal of crafting novel proteins that address challenges in biology and medicine. To overcome these challenges, the computational protein modeling suite Rosetta has been tailored to address various protein design tasks. Recently, statistical methods have been developed that identify correlated mutations between residues in a multiple sequence alignment of homologous proteins. These subtle inter-dependencies in the occupancy of residue positions throughout evolution are crucial for protein function, but we found that three current Rosetta design approaches fail to recover these co-evolutionary couplings. Thus, we developed the Rosetta method ResCue (residue-coupling enhanced) that leverages co-evolutionary information to favor sequences which recapitulate correlated mutations, as observed in nature. To assess the protocols via recapitulation designs, we compiled a benchmark of ten proteins each represented by two, structurally diverse states. We could demonstrate that ResCue designed sequences with an average sequence recovery rate of 70%, whereas three other protocols reached not more than 50%, on average. Our approach had higher recovery rates also for functionally important residues, which were studied in detail. This improvement has only a minor negative effect on the fitness of the designed sequences as assessed by Rosetta energy. In conclusion, our findings support the idea that informing protocols with co-evolutionary signals helps to design stable and native-like proteins that are compatible with the different conformational states required for a complex function.