ResBoost: characterizing and predicting catalytic residues in enzymes

Abstract Background Identifying the catalytic residues in enzymes can aid in understanding the molecular basis of an enzyme's function and has significant implications for designing new drugs, identifying genetic disorders, and engineering proteins with novel functions. Since experimentally determining catalytic sites is expensive, better computational methods for identifying catalytic residues are needed. Results We propose ResBoost, a new computational method to learn characteristics of catalytic residues. The method effectively selects and combines rules of thumb into a simple, easily interpretable logical expression that can be used for prediction. We formally define the rules of thumb that are often used to narrow the list of candidate residues, including residue evolutionary conservation, 3D clustering, solvent accessibility, and hydrophilicity. ResBoost builds on two methods from machine learning, the AdaBoost algorithm and Alternating Decision Trees, and provides precise control over the inherent trade-off between sensitivity and specificity. We evaluated ResBoost using cross-validation on a dataset of 100 enzymes from the hand-curated Catalytic Site Atlas (CSA). Conclusion ResBoost achieved 85% sensitivity for a 9.8% false positive rate and 73% sensitivity for a 5.7% false positive rate. ResBoost reduces the number of false positives by up to 56% compared to the use of evolutionary conservation scoring alone. We also illustrate the ability of ResBoost to identify recently validated catalytic residues not listed in the CSA

Twinned or not twinned, that is the question: crystallization and preliminary crystallographic analysis of the 2F1(3)F1 module pair of human fibronectin.

Human fibronectin (Fn) is a large multidomain protein found in the extracellular matrix and plasma. It is involved in many cellular processes, including cell adhesion and migration during embryogenesis and wound healing. The ability to bind Fn is a characteristic that has been demonstrated for a number of pathogens. For Staphylococcus aureus and Streptococcus pyogenes in particular, Fn-binding bacterial proteins (FnBPs) have been shown to mediate not only bacterial adhesion to host cells but also the uptake of bacteria by the cells. FnBPs interact with the amino-terminal region of Fn, where five type I ((1-5)F1) Fn modules are located. Although the structures of two F1 module pairs have been determined by NMR, no X-ray structures have been reported. To explore the conformational interactions between modules and the binding properties of FnBPs, the (2)F1(3)F1 module pair was crystallized using the vapour-diffusion method at 298 K. 12 X-ray diffraction data sets have been collected: six on an in-house rotating anode (three native, one Pt derivative and two peptide-bound) and six at synchrotron-radiation sources (two native and four derivative). Following analysis of these data, some of which have very high multiplicity (up to 50), probable space-group assignments were made (P42(1)2, P4(1)2(1)2 or P4(3)2(1)2) and the possibly twinned nature of the crystals was investigated using six different tests. The results presented here suggest that the crystals are not twinned

Parameters affecting the X-ray dose absorbed by macromolecular crystals.

The lifetime of a macromolecular crystal in an X-ray beam is assumed to be limited by the absorbed dose. This dose, expressed in Gray (Gy = J kg(-1)), is a function of a number of parameters: the absorption coefficients of the constituent atoms of the crystal, the number of molecules per asymmetric unit, the beam energy, flux, size and profile, the crystal size, and the total irradiation time. The effects of these variables on the predicted absorbed dose, calculated using the program RADDOSE, are discussed and are illustrated with reference to the irradiation of a selenomethionine protein crystal of unknown structure. The results of RADDOSE can and will in the future be used to inform the data collection procedure as it sets a theoretical upper limit on the total exposure time at a certain X-ray source. However, as illustrated with an example for which the experimental data are compared with prediction, the actual lifetime of a crystal could become shorter in those cases where specific damage breaks down crucial crystal contacts

Practical radiation damage-induced phasing

International audienceAlthough crystallographers typically seek to mitigate radiation damage in macromolecular crystals, in some cases, radiation damage to specific atoms can be used to determine phases de novo. This process is called radiation damage-induced phasing or "RIP." Here, we provide a general overview of the method and a practical set of data collection and processing strategies for phasing macromolecular structures using RIP