Will my protein crystallize? A sequence‐based predictor

We propose a machine-learning approach to sequence-based prediction of protein crystallizability in which we exploit subtle differences between proteins whose structures were solved by X-ray analysis [or by both X-ray and nuclear magnetic resonance (NMR) spectroscopy] and those proteins whose structures were solved by NMR spectroscopy alone. Because the NMR technique is usually applied on relatively small proteins, sequence length distributions of the X-ray and NMR datasets were adjusted to avoid predictions biased by protein size. As feature space for classification, we used frequencies of mono-, di-, and tripeptides represented by the original 20-letter amino acid alphabet as well as by several reduced alphabets in which amino acids were grouped by their physicochemical and structural properties. The classification algorithm was constructed as a two-layered structure in which the output of primary support vector machine classifiers operating on peptide frequencies was combined by a second-level Naive Bayes classifier. Due to the application of metamethods for cost sensitivity, our method is able to handle real datasets with unbalanced class representation. An overall prediction accuracy of 67% [65% on the positive (crystallizable) and 69% on the negative (noncrystallizable) class] was achieved in a 10-fold cross-validation experiment, indicating that the proposed algorithm may be a valuable tool for more efficient target selection in structural genomics. A Web server for protein crystallizability prediction called SECRET is available at http://webclu.bio.wzw.tum.de:8080/secret.     

Structural behavior of RNA-binding proteins in the free state and in complex with RNA: <Emphasis Type="Italic">Escherichia coli</Emphasis> ribosomal protein L25 and 5S rRNA

A novel approach was proposed to evaluate the steadiness of polar clusters containing the RNA-binding sites on the protein surface. The degree of clustering of RNA-binding polar residues was used as a measure of the steadiness of the corresponding polar clusters. Escherichia coli ribosomal protein L25 utilizes two binding sites, S1 and S2, to complexate with a 5S rRNA fragment. The cluster distribution of RNA-contacting polar residues on the protein surface was studied using the structural data on the complex (in crystal and in solution) and the free state (in solution). The degree of polar residue clustering in S1 and S2 in crystal was estimated at 71.4 and 100%, respectively. For the free state in solution, the degree of clustering of the two sites was 22.8 and 68.6%, respectively. Thus, the steadiness was quantitatively estimated for the RNA-binding sites of two different types, one preexisting in the protein and the other induced by the RNA structure upon complexation. The difference between the protein structures in crystal and in solution was found to be functionally significant. The results can be extrapolated to numerous complexes of proteins with double-stranded RNA and DNA.     

From cancer genomes to cancer models: bridging the gaps

Cancer genome projects are now being expanded in an attempt to provide complete landscapes of the mutations that exist in tumours. Although the importance of cataloguing genome variations is well recognized, there are obvious difficulties in bridging the gaps between high‐throughput resequencing information and the molecular mechanisms of cancer evolution. Here, we describe the current status of the high‐throughput genomic technologies, and the current limitations of the associated computational analysis and experimental validation of cancer genetic variants. We emphasize how the current cancer‐evolution models will be influenced by the high‐throughput approaches, in particular through efforts devoted to monitoring tumour progression, and how, in turn, the integration of data and models will be translated into mechanistic knowledge and clinical applications.     

Photoactivation of Electrogenic Activity in Chloroplasts and Its Relation to Photoinduced Swelling of Thylakoids

In patch-clamp experiments on isolated chloroplasts of Peperomia metallica Lind. et Rodig. (Piperaceae), the replacement of 50 mM KCl in a medium with 50 mM NH₄Cl strongly influenced the parameters of photocurrent known to reflect the generation of electric potential in thylakoids. The addition of NH⁺ ₄to the medium modified the induction curves of the photocurrent as well as the currents induced by single-turnover flashes in preilluminated chloroplasts. Under the action of a prolonged light pulse (1 s), the steady-state current was much higher in the ammonium-containing medium than in the presence of K⁺. Preillumination of a dark-adapted chloroplast with a 1-s light pulse suppressed the current induced by a single-turnover flash (6 s) in the presence of K⁺ but caused an elevation (by 50–150%) of the flash-induced current and shortening of its relaxation time in the presence of NH⁺ ₄. The origin of different induction kinetics for the photocurrent in K⁺ and NH⁺ ₄ media is partly clear, because ammonium prevents generation of the pH gradient and, subsequently, eliminates the pH-dependent suppression of the electron transport rate. However, this does not explain the origin of NH⁺ ₄-dependent photostimulation of the current generated by single-turnover flashes. This phenomenon arises from the thylakoid swelling caused by the accumulation of NH⁺ ₄ in the lumen and from the respective changes in the network resistances. The network element most sensitive to thylakoid swelling is the lateral resistance of the lumen: it decreases upon enlargement of the cross-section area. Stimulation of the flash-induced current by preillumination in the presence of NH⁺ ₄ was accompanied by accelerated relaxation of the current, indicating that the phenomena observed are caused by the reduction of network resistance involved in the discharge of the membrane capacity. Thus, the light-induced structural changes in the thylakoid system have a marked effect on the currents measured with the patch-clamp technique.     

Adiabatic compressibility and intrinsic viscosity studies on peptide aggregates

Density and sound velocity measurements and ¹H NMR investigations were carried out in aqueous solution at various temperatures for determining the adiabatic compressibility () and hydration of the tetrapeptide, TFA. Tyr-Gly-Phe-Ala-Obz I. The present investigation showed changes in the temperature coefficient of adiabatic compressibility at 40 °C. ¹H NMR studies indicated the inverse temperature transition in the concentration range studied.     

Protein biophysical properties that correlate with crystallization success in Thermotoga maritima: maximum clustering strategy for structural genomics

Cost and time reduction are two of the driving forces in the development of new strategies for protein crystallization and subsequent structure determination. Here, we report the analysis of the Thermotoga maritima proteome, in which we compare the proteins that were successfully expressed, purified and crystallized versus the rest of the proteome. This set of almost 500 proteins represents one of the largest, internally consistent, protein expression and crystallization datasets available. The analysis shows that individual parameters, such as isoelectric point, sequence length, average hydropathy, low complexity regions (SEG), and combinations of these biophysical properties for crystallized proteins define a distinct subset of the T. maritima proteome. The distribution profiles of the various biophysical properties in the expression/crystallization set are then used to extract rules to improve target selection and improve the efficiency and output of structural genomics, as well as general structural biology efforts.     

Development of an Undergraduate Bioinformatics Degree Program at a Liberal Arts College

The highly interdisciplinary field of bioinformatics has emerged as a powerful modern science. There has been a great demand for undergraduate- and graduate-level trained bioinformaticists in the industry as well in the academia. In order to address the needs for trained bioinformaticists, its curriculum must be offered at the undergraduate level, especially at four-year colleges, where a majority of the United States gets its education. There are many challenges in developing an undergraduate-level bioinformatics program that needs to be carefully designed as a well-integrated and cohesive interdisciplinary curriculum that prepares the students for a wide variety of career options. This article describes the challenges of establishing a highly interdisciplinary undergraduate major, the development of an undergraduate bioinformatics degree program at Ramapo College of New Jersey, and lessons learned in the last 10 years during its management.