<i>Gene Composer</i>in a structural genomics environment

Lorimer, Don; Raymond, Amy; Mixon, Mark B.; Burgin, Alex B.; Staker, Bart L.; Stewart, Lance

doi:10.1107/s1744309111027424

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…Multiple crystallization efforts with native sequence BpML1 constructs with tags removed failed to yield crystals. Therefore, to obtain alternative crystal forms not dependent on the cleavage site sequence interaction with the protein, a series of BpML1 point mutations was designed using GeneComposer software (31,32,52). Via GeneComposer, specific residues were identified that could alter the crystal lattice while minimizing the impact on binding site topology, based on crystal contacts observed in the apo form of the BpML1 structure.…”

Section: Resultsmentioning

confidence: 99%

A Structural Biology Approach Enables the Development of Antimicrobials Targeting Bacterial Immunophilins

Begley¹,

Fox²,

Jenner

et al. 2014

Antimicrob Agents Chemother

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f Macrophage infectivity potentiators (Mips) are immunophilin proteins and essential virulence factors for a range of pathogenic organisms. We applied a structural biology approach to characterize a Mip from Burkholderia pseudomallei (BpML1), the causative agent of melioidosis. Crystal structure and nuclear magnetic resonance analyses of BpML1 in complex with known macrocyclics and other derivatives led to the identification of a key chemical scaffold. This scaffold possesses inhibitory potency for BpML1 without the immunosuppressive components of related macrocyclic agents. Biophysical characterization of a compound series with this scaffold allowed binding site specificity in solution and potency determinations for rank ordering the set. The best compounds in this series possessed a low-micromolar affinity for BpML1, bound at the site of enzymatic activity, and inhibited a panel of homologous Mip proteins from other pathogenic bacteria, without demonstrating toxicity in human macrophages. Importantly, the in vitro activity of BpML1 was reduced by these compounds, leading to decreased macrophage infectivity and intracellular growth of Burkholderia pseudomallei. These compounds offer the potential for activity against a new class of antimicrobial targets and present the utility of a structure-based approach for novel antimicrobial drug discovery.

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Section: Resultsmentioning

confidence: 99%

A Structural Biology Approach Enables the Development of Antimicrobials Targeting Bacterial Immunophilins

Begley¹,

Fox²,

Jenner

et al. 2014

Antimicrob Agents Chemother

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“…Starting from the amino-acid sequences for these two PDF proteins, gene sequences were designed for expression in E. coli using Gene Composer (Emerald BioSystems, Bainbridge Island, WA, USA) (Lorimer et al , 2009; Lorimer et al , 2011). Back-translation of the amino-acid sequences employed a Universal Codon Usage Table designed to accommodate expression in E. coli with a minimum usage threshold of 2%.…”

Section: Methodsmentioning

confidence: 99%

Structure and function of a cyanophage-encoded peptide deformylase

Frank

Lorimer²,

Youle³

et al. 2013

The ISME Journal

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Bacteriophages encode auxiliary metabolic genes that support more efficient phage replication. For example, cyanophages carry several genes to maintain host photosynthesis throughout infection, shuttling the energy and reducing power generated away from carbon fixation and into anabolic pathways. Photodamage to the D1/D2 proteins at the core of photosystem II necessitates their continual replacement. Synthesis of functional proteins in bacteria requires co-translational removal of the N-terminal formyl group by a peptide deformylase (PDF). Analysis of marine metagenomes to identify phage-encoded homologs of known metabolic genes found that marine phages carry PDF genes, suggesting that their expression during infection might benefit phage replication. We identified a PDF homolog in the genome of Synechococcus cyanophage S-SSM7. Sequence analysis confirmed that it possesses the three absolutely conserved motifs that form the active site in PDF metalloproteases. Phylogenetic analysis placed it within the Type 1B subclass, most closely related to the Arabidopsis chloroplast PDF, but lacking the C-terminal α-helix characteristic of that group. PDF proteins from this phage and from Synechococcus elongatus were expressed and characterized. The phage PDF is the more active enzyme and deformylates the N-terminal tetrapeptides from D1 proteins more efficiently than those from ribosomal proteins. Solution of the X-ray/crystal structures of those two PDFs to 1.95 Å resolution revealed active sites identical to that of the Type 1B Arabidopsis chloroplast PDF. Taken together, these findings show that many cyanophages encode a PDF with a D1 substrate preference that adds to the repertoire of genes used by phages to maintain photosynthetic activities.

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“…Genes were designed for optimal expression in E. coli using Gene Composer (Emerald BioSystems, Bainbridge Island WA) [76] – [77] . Amino acid sequences were back-translated using an E. coli codon usage table with a minimum usage cutoff of 2%.…”

Section: Methodsmentioning

confidence: 99%

Artificial Neural Networks Trained to Detect Viral and Phage Structural Proteins

et al. 2012

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Phages play critical roles in the survival and pathogenicity of their hosts, via lysogenic conversion factors, and in nutrient redistribution, via cell lysis. Analyses of phage- and viral-encoded genes in environmental samples provide insights into the physiological impact of viruses on microbial communities and human health. However, phage ORFs are extremely diverse of which over 70% of them are dissimilar to any genes with annotated functions in GenBank. Better identification of viruses would also aid in better detection and diagnosis of disease, in vaccine development, and generally in better understanding the physiological potential of any environment. In contrast to enzymes, viral structural protein function can be much more challenging to detect from sequence data because of low sequence conservation, few known conserved catalytic sites or sequence domains, and relatively limited experimental data. We have designed a method of predicting phage structural protein sequences that uses Artificial Neural Networks (ANNs). First, we trained ANNs to classify viral structural proteins using amino acid frequency; these correctly classify a large fraction of test cases with a high degree of specificity and sensitivity. Subsequently, we added estimates of protein isoelectric points as a feature to ANNs that classify specialized families of proteins, namely major capsid and tail proteins. As expected, these more specialized ANNs are more accurate than the structural ANNs. To experimentally validate the ANN predictions, several ORFs with no significant similarities to known sequences that are ANN-predicted structural proteins were examined by transmission electron microscopy. Some of these self-assembled into structures strongly resembling virion structures. Thus, our ANNs are new tools for identifying phage and potential prophage structural proteins that are difficult or impossible to detect by other bioinformatic analysis. The networks will be valuable when sequence is available but in vitro propagation of the phage may not be practical or possible.

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Gene Composerin a structural genomics environment

Cited by 4 publications

References 10 publications

A Structural Biology Approach Enables the Development of Antimicrobials Targeting Bacterial Immunophilins

A Structural Biology Approach Enables the Development of Antimicrobials Targeting Bacterial Immunophilins

Structure and function of a cyanophage-encoded peptide deformylase

Artificial Neural Networks Trained to Detect Viral and Phage Structural Proteins

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