Molecular basis of sulfonylurea herbicide inhibition of acetohydroxyacid synthase

Acetohydroxyacid synthase (AHAS) (acetolactate synthase, EC ) catalyzes the first step in branched-chain amino acid biosynthesis and is the target for sulfonylurea and imidazolinone herbicides. These compounds are potent and selective inhibitors, but their binding site on AHAS has not been elucidated. Here we report the 2.8 A resolution crystal structure of yeast AHAS in complex with a sulfonylurea herbicide, chlorimuron ethyl. The inhibitor, which has a K(i) of 3.3 nm, blocks access to the active site and contacts multiple residues where mutation results in herbicide resistance. The structure provides a starting point for the rational design of further herbicidal compounds.     

Twenty thousand ORFan microbial protein families for the biologist?

The genomes of most newly sequenced organisms contain a significant fraction of ORFs (open reading frames) that match no other sequence in the databases. We refer to these singleton ORFs as sequence ORFans. Because little can be learned about ORFans by homology, the origin and functions of ORFans remain a mystery. However, in this era of full genome sequencing, it seems that ORFans have been underemphasized. In this minireview, we draw attention to the increasing number of ORFans and to the consequences of this growth to biological research in the postgenomic era.     

Transfection of liver in vivo by biolistic particle delivery

We describe the delivery of reporter gene constructs to rat liver through the use of the Helios Gene Gun system. The effectiveness of this transfection method is illustrated by describing its use for determining in vivo the role of a DNA element that regulates cytochrome P450 2B1 (CYP2B1) gene expression in response to xenobiotics. DNA was delivered to the liver of an anesthetized animal via DNA-coated gold microcarriers. The highest level of reporter gene expression was obtained about six hours posttransfection; however, at this time endogenous CYP2B1 mRNA is transiently induced by the anesthetic treatment. The optimal time for investigating expression of a reporter gene under the control of CYP2B1 regulatory elements was 24 h after transfection, by which time the inductive effect of the anesthetic had ceased. Reporter gene expression subsequently declined rapidly to a low level by 48 h. In the transfected liver the heterologous SV40 promoter was about eight-fold stronger than the minimal CYP2B1 promoter. However, when attached to the phenobarbital response element both promoters give the same fold-induction of reporter activity in response to phenobarbital.     

A synthetic weak neurotoxin binds with low affinity to Torpedo and chicken alpha7 nicotinic acetylcholine receptors.

Weak neurotoxins from snake venom are small proteins with five disulfide bonds, which have been shown to be poor binders of nicotinic acetylcholine receptors. We report on the cloning and sequencing of four cDNAs encoding weak neurotoxins from Naja sputatrix venom glands. The protein encoded by one of them, Wntx-5, has been synthesized by solid-phase synthesis and characterized. The physicochemical properties of the synthetic toxin (sWntx-5) agree with those anticipated for the natural toxin. We show that this toxin interacts with relatively low affinity (K(d) = 180 nm) with the muscular-type acetylcholine receptor of the electric organ of T. marmorata, and with an even weaker affinity (90 microm) with the neuronal alpha7 receptor of chicken. Electrophysiological recordings using isolated mouse hemidiaphragm and frog cutaneous pectoris nerve-muscle preparations revealed no blocking activity of sWntx-5 at microm concentrations. Our data confirm previous observations that natural weak neurotoxins from cobras have poor affinity for nicotinic acetylcholine receptors.     

Improved microarray methods for profiling the Yeast Knockout strain collection

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens.     

Functional profiling of recombinant NS3 proteases from all four serotypes of dengue virus using tetrapeptide and octapeptide substrate libraries

Regulated proteolysis by the two-component NS2B/NS3 protease of dengue virus is essential for virus replication and the maturation of infectious virions. The functional similarity between the NS2B/NS3 proteases from the four genetically and antigenically distinct serotypes was addressed by characterizing the differences in their substrate specificity using tetrapeptide and octapeptide libraries in a positional scanning format, each containing 130,321 substrates. The proteases from different serotypes were shown to be functionally homologous based on the similarity of their substrate cleavage preferences. A strong preference for basic amino acid residues (Arg/Lys) at the P1 positions was observed, whereas the preferences for the P2-4 sites were in the order of Arg > Thr > Gln/Asn/Lys for P2, Lys > Arg > Asn for P3, and Nle > Leu > Lys > Xaa for P4. The prime site substrate specificity was for small and polar amino acids in P1' and P3'. In contrast, the P2' and P4' substrate positions showed minimal activity. The influence of the P2 and P3 amino acids on ground state binding and the P4 position for transition state stabilization was identified through single substrate kinetics with optimal and suboptimal substrate sequences. The specificities observed for dengue NS2B/NS3 have features in common with the physiological cleavage sites in the dengue polyprotein; however, all sites reveal previously unrecognized suboptimal sequences.     

Prediction of RNA-binding proteins from primary sequence by a support vector machine approach

Elucidation of the interaction of proteins with different molecules is of significance in the understanding of cellular processes. Computational methods have been developed for the prediction of protein-protein interactions. But insufficient attention has been paid to the prediction of protein-RNA interactions, which play central roles in regulating gene expression and certain RNA-mediated enzymatic processes. This work explored the use of a machine learning method, support vector machines (SVM), for the prediction of RNA-binding proteins directly from their primary sequence. Based on the knowledge of known RNA-binding and non-RNA-binding proteins, an SVM system was trained to recognize RNA-binding proteins. A total of 4011 RNA-binding and 9781 non-RNA-binding proteins was used to train and test the SVM classification system, and an independent set of 447 RNA-binding and 4881 non-RNA-binding proteins was used to evaluate the classification accuracy. Testing results using this independent evaluation set show a prediction accuracy of 94.1%, 79.3%, and 94.1% for rRNA-, mRNA-, and tRNA-binding proteins, and 98.7%, 96.5%, and 99.9% for non-rRNA-, non-mRNA-, and non-tRNA-binding proteins, respectively. The SVM classification system was further tested on a small class of snRNA-binding proteins with only 60 available sequences. The prediction accuracy is 40.0% and 99.9% for snRNA-binding and non-snRNA-binding proteins, indicating a need for a sufficient number of proteins to train SVM. The SVM classification systems trained in this work were added to our Web-based protein functional classification software SVMProt, at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi. Our study suggests the potential of SVM as a useful tool for facilitating the prediction of protein-RNA interactions.