New in protein structure and function annotation: Hotspots, single nucleotide polymorphisms and the 'Deep Web'

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation

Comprehensive functional characterization of SGCB coding variants predicts pathogenicity in limb-girdle muscular dystrophy type R4/2E

Genetic testing is essential for patients with a suspected hereditary myopathy. More than 50% of patients clinically diagnosed with a myopathy carry a variant of unknown significance in a myopathy gene, often leaving them without a genetic diagnosis. Limb-girdle muscular dystrophy (LGMD) type R4/2E is caused by mutations in β-sarcoglycan (SGCB). Together, β-, α-, γ-, and δ-sarcoglycan form a 4-protein transmembrane complex (SGC) that localizes to the sarcolemma. Biallelic loss-of-function mutations in any subunit can lead to LGMD. To provide functional evidence for the pathogenicity of missense variants, we performed deep mutational scanning of SGCB and assessed SGC cell surface localization for all 6,340 possible amino acid changes. Variant functional scores were bimodally distributed and perfectly predicted pathogenicity of known variants. Variants with less severe functional scores more often appeared in patients with slower disease progression, implying a relationship between variant function and disease severity. Amino acid positions intolerant to variation mapped to points of predicted SGC interactions, validated in silico structural models, and enabled accurate prediction of pathogenic variants in other SGC genes. These results will be useful for clinical interpretation of SGCB variants and improving diagnosis of LGMD; we hope they enable wider use of potentially life-saving gene therapy

Towards Prediction of Metabolic Products of Polyketide Synthases: An In Silico Analysis

Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products

Fold Family-Regularized Bayesian Optimization for Directed Protein Evolution

Directed Evolution (DE) is a technique for protein engineering that involves iterative rounds of mutagenesis and screening to search for sequences that optimize a given property (ex. binding affinity to a specified target). Unfortunately, the underlying optimization problem is under-determined, and so mutations introduced to improve the specified property may come at the expense of unmeasured, but nevertheless important properties (ex. subcellular localization). We seek to address this issue by incorporating a fold-specific regularization factor into the optimization problem. The regularization factor biases the search towards designs that resemble sequences from the fold family to which the protein belongs. We applied our method to a large library of protein GB1 mutants with binding affinity measurements to IgG-Fc. Our results demonstrate that the regularized optimization problem produces more native-like GB1 sequences with only a minor decrease in binding affinity. Specifically, the log-odds of our designs under a generative model of the GB1 fold family are between 41-45% higher than those obtained without regularization, with only a 7% drop in binding affinity. Thus, our method is capable of making a trade-off between competing traits. Moreover, we demonstrate that our active-learning driven approach reduces the wet-lab burden to identify optimal GB1 designs by 67%, relative to recent results from the Arnold lab on the same data

Signal Transduction and Pathogenic Modifications at the Melanocortin-4 Receptor: A Structural Perspective

The melanocortin-4 receptor (MC4R) can be endogenously activated by binding of melanocyte-stimulating hormones (MSH), which mediates anorexigenic effects. In contrast, the agouti-related peptide (AgRP) acts as an endogenous inverse agonist and suppresses ligand-independent basal signaling activity (orexigenic effects). Binding of ligands to MC4R leads to the activation of different G-protein subtypes or arrestin and concomitant signaling pathways. This receptor is a key protein in the hypothalamic regulation of food intake and energy expenditure and naturally-occurring inactivating MC4R variants are the most frequent cause of monogenic obesity. In general, obesity is a growing problem on a global scale and is of social, medical, and economic relevance. A significant goal is to develop optimized pharmacological tools targeting MC4R without adverse effects. To date, this has not been achieved because of inter alia non-selective ligands across the five functionally different MCR subtypes (MC1-5R). This motivates further investigation of (i) the three-dimensional MC4R structure, (ii) binding mechanisms of various ligands, and (iii) the molecular transfer process of signal transduction, with the aim of understanding how structural features are linked with functional-physiological aspects. Unfortunately, experimentally elucidated structural information is not yet available for theMC receptors, a group of class A G-protein coupled receptors (GPCRs). We, therefore, generated MC4R homology models and complexes with interacting partners to describe approximate structural properties associated with signaling mechanisms. In addition, molecular insights from pathogenic mutations were incorporated to discriminate more precisely their individual malfunction of the signal transfer mechanism

High-resolution mutagenesis of the linker domain of archaeal basal transcription factor TFIIB

TFIIB is a component of the minimal eukaryotic as well as the archaeal transcriptional machinery that is essential for promoter-directed transcription. The flexible linker domain of the protein engages in an intimate association with the RNA polymerase surface. Early structural data suggested that the linker forms a finger-like structure (the ‘B-finger’) within the RNA exit channel projecting into the active centre. Biochemical data indicated a contribution of the archaeal ‘B-finger’ domain to the catalytic mechanism by stimulating abortive transcription. The path of the linker within the RNA polymerase catalytic centre has recently been re-assessed and residues of the original Bfinger were re-assigned to structural elements named ‘B-reader helix’ and ‘B-reader loop’. Novel high-throughput tools, in combination with a comprehensive mutagenesis screen of residues E78 to A95, facilitated the biochemical evaluation of structural-functional relationships of the M. jannaschii TFIIB linker – RNAP interface at a single residue resolution. The performance of such point mutants during abortive initiation and RNA polymerase recruitment was interpreted in light of structural information. The tip region of the ‘B-finger’ that was predicted to be closest to the active site was insensitive to mutations in abortive initiation assays, thus disproving the original model. Individual residues, forming part of the B-reader helix and the C-terminal half of the Breader loop, were found to engage in abortive transcription. Three-residue deletions within the N-terminal half of the B-reader loop resulted in super-stimulation of abortive transcription. Individual point mutations within the B-reader loop led to enhanced recruitment of RNA polymerase. A functional role of the loop in stabilizing TFIIBRNA polymerase-DNA complexes in both the absence and presence of TBP seems feasible. The combined data provide a detailed view of biochemical functions of individual residues of the TFIIB linker favouring the ‘B-reader’ model over the ‘B-finger’ model

Porphyrin Binding to Gun4 Protein, Facilitated by a Flexible Loop, Controls Metabolite Flow through the Chlorophyll Biosynthetic Pathway.

In oxygenic phototrophs, chlorophylls, hemes, and bilins are synthesized by a common branched pathway. Given the phototoxic nature of tetrapyrroles, this pathway must be tightly regulated, and an important regulatory role is attributed to magnesium chelatase enzyme at the branching between the heme and chlorophyll pathway. Gun4 is a porphyrin-binding protein known to stimulate in vitro the magnesium chelatase activity, but how the Gun4-porphyrin complex acts in the cell was unknown. To address this issue, we first performed simulations to determine the porphyrin-docking mechanism to the cyanobacterial Gun4 structure. After correcting crystallographic loop contacts, we determined the binding site for magnesium protoporphyrin IX. Molecular modeling revealed that the orientation of α6/α7 loop is critical for the binding, and the magnesium ion held within the porphyrin is coordinated by Asn-211 residue. We also identified the basis for stronger binding in the Gun4-1 variant and for weaker binding in the W192A mutant. The W192A-Gun4 was further characterized in magnesium chelatase assay showing that tight porphyrin binding in Gun4 facilitates its interaction with the magnesium chelatase ChlH subunit. Finally, we introduced the W192A mutation into cells and show that the Gun4-porphyrin complex is important for the accumulation of ChlH and for channeling metabolites into the chlorophyll biosynthetic pathway

Discovery of unusual dimeric piperazyl cyclopeptides encoded by a Lentzea flaviverrucosa DSM 44664 biosynthetic supercluster

Rare actinomycetes represent an underexploited source of new bioactive compounds. Here, we report the use of a targeted metabologenomic approach to identify piperazyl compounds in the rare actinomycete Lentzea flaviverrucosa DSM 44664. These efforts to identify molecules that incorporate piperazate building blocks resulted in the discovery and structural elucidation of two dimeric biaryl-cyclohexapeptides, petrichorins A and B. Petrichorin B is a symmetric homodimer similar to the known compound chloptosin, but petrichorin A is unique among known piperazyl cyclopeptides because it is an asymmetric heterodimer. Due to the structural complexity of petrichorin A, solving its structure required a combination of several standard chemical methods plus in silico modeling, strain mutagenesis, and solving the structure of its biosynthetic intermediate petrichorin C for confident assignment. Furthermore, we found that the piperazyl cyclopeptides comprising each half of the petrichorin A heterodimer are made via two distinct nonribosomal peptide synthetase (NRPS) assembly lines, and the responsible NRPS enzymes are encoded within a contiguous biosynthetic supercluster on the L. flaviverrucosa chromosome. Requiring promiscuous cytochrome p450 crosslinking events for asymmetric and symmetric biaryl production, petrichorins A and B exhibited potent in vitro activity against A2780 human ovarian cancer, HT1080 fibrosarcoma, PC3 human prostate cancer, and Jurkat human T lymphocyte cell lines with IC50 values at low nM levels. Cyclic piperazyl peptides and their crosslinked derivatives are interesting drug leads, and our findings highlight the potential for heterodimeric bicyclic peptides such as petrichorin A for inclusion in future pharmaceutical design and discovery programs.Fil: Li, Chunshun. University Of Hawaii; Estados UnidosFil: Hu, Yifei. University Of Hawaii; Estados Unidos. Washington University in St. Louis; Estados UnidosFil: Wu, Xiaohua. University Of Hawaii; Estados UnidosFil: Stumpf, Spencer D.. Washington University in St. Louis; Estados UnidosFil: Qi, Yunci. Washington University in St. Louis; Estados UnidosFil: D'Alessandro, John M.. Washington University in St. Louis; Estados UnidosFil: Nepal, Keshav K.. Washington University in St. Louis; Estados UnidosFil: Sarotti, Ariel Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Cao, Shugeng. University Of Hawaii; Estados UnidosFil: Blodgett, Joshua A.V.. Washington University in St. Louis; Estados Unido

Directed Evolution of (R)-2-Hydroxyglutarate Dehydrogenase Improves 2-Oxoadipate Reduction by 2 Orders of Magnitude

Pathway engineering is commonly employed to improve the production of various metabolites but may incur in bottlenecks due to the low catalytic activity of a particular reaction step. The reduction of 2-oxoadipate to (R)-2-hydroxyadipate is a key reaction in metabolic pathways that exploit 2-oxoadipate conversion via α-reduction to produce adipic acid, an industrially important platform chemical. Here, we engineered (R)-2-hydroxyglutarate dehydrogenase from Acidaminococcus fermentans (Hgdh) with the aim of improving 2-oxoadipate reduction. Using a combination of computational analysis, saturation mutagenesis, and random mutagenesis, three mutant variants with a 100-fold higher catalytic efficiency were obtained. As revealed by rational analysis of the mutations found in the variants, this improvement could be ascribed to a general synergistic effect where mutation A206V played a key role since it boosted the enzyme\u27s activity by 4.8-fold. The Hgdh variants with increased activity toward 2-oxoadipate generated within this study pave the way for the bio-based production of adipic acid