En route to new inhibitors: The binding of Zn2+ cyclen to the human Ras protein stabilizes a protein conformation that has a weak affinity for effectors. Consequently this complex is a lead structure for inhibition studies on the Ras–effector interaction. The picture shows the NMR structure of Ras⋅Mg2+⋅GppNHp complexed to Zn2+ cyclen.

C3 exoenzymes from bacterial pathogens ADP-ribosylate and inactivate low-molecular-mass GTPases of the Rho subfamily. Ral, a Ras subfamily GTPase, binds the C3 exoenzymes from Clostridium botulinum and C. limosum with high affinity without being a substrate for ADP ribosylation. In the complex, the ADP-ribosyltransferase activity of C3 is blocked, while binding of NAD and NAD-glycohydrolase activity remain. Here we report the crystal structure of C3 from C. botulinum in a complex with GDP-bound RalA at 1.8 A resolution. C3 binds RalA with a helix-loop-helix motif that is adjacent to the active site. A quaternary complex with NAD suggests a mode for ADP-ribosyltransferase inhibition. Interaction of C3 with RalA occurs at a unique interface formed by the switch-II region, helix alpha3 and the P loop of the GTPase. C3-binding stabilizes the GDP-bound conformation of RalA and blocks nucleotide release. Our data indicate that C. botulinum exoenzyme C3 is a single-domain toxin with bifunctional properties targeting Rho GTPases by ADP ribosylation and Ral by a guanine nucleotide dissociation inhibitor-like effect, which blocks nucleotide exchange.

Auf dem Weg zu neuen Hemmstoffen: Die Bindung des Zn2+‐Cyclen‐Komplexes an das menschliche Ras‐Protein stabilisiert eine Proteinkonformation mit schwacher Affinität für Effektoren, was den Komplex zu einer Leitsubstanz für Inhibierungsstudien der Ras‐Effektor‐Wechselwirkung macht. Das Bild zeigt die NMR‐Struktur von Ras⋅Mg2+⋅GppNHp im Komplex mit Zn2+‐Cyclen.

Chemometric models for on-line process monitoring have become well established in pharmaceutical bioprocesses. The main drawback is the required calibration effort and the inflexibility regarding system or process changes. So, a recalibration is necessary whenever the process or the setup changes even slightly. With a large and diverse Raman dataset, however, it was possible to generate generic partial least squares regression models to reliably predict the concentrations of important metabolic compounds, such as glucose-, lactate-, and glutamine-indifferent CHO cell cultivations. The data for calibration were collected from various cell cultures from different sites in different companies using different Raman spectrophotometers. In testing, the developed “generic” models were capable of predicting the concentrations of said compounds from a dilution series in FMX-8 mod medium, as well as from an independent CHO cell culture. These spectra were taken with a completely different setup and with different Raman spectrometers, demonstrating the model flexibility. The prediction errors for the tests were mostly in an acceptable range (<10% relative error). This demonstrates that, under the right circumstances and by choosing the calibration data carefully, it is possible to create generic and reliable chemometric models that are transferrable from one process to another without recalibration.

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