PONDEROSA-C/S: client–server based software package for automated protein 3D structure determination

Abstract

Peak-picking Of Noe Data Enabled by Restriction Of Shift Assignments-Client Server (PONDEROSA-C/S) builds on the original PONDEROSA software (Lee et al. in Bioinformatics 27:1727–1728. doi:10.1093/bioinformatics/btr200, 2011) and includes improved features for structure calculation and refinement. PONDEROSA-C/S consists of three programs: Ponderosa Server, Ponderosa Client, and Ponderosa Analyzer. PONDEROSA-C/S takes as input the protein sequence, a list of assigned chemical shifts, and nuclear Overhauser data sets (13C- and/or 15N-NOESY). The output is a set of assigned NOEs and 3D structural models for the protein. Ponderosa Analyzer supports the visualization, validation, and refinement of the results from Ponderosa Server. These tools enable semi-automated NMR-based structure determination of proteins in a rapid and robust fashion. We present examples showing the use of PONDEROSA-C/S in solving structures of four proteins: two that enable comparison with the original PONDEROSA package, and two from the Critical Assessment of automated Structure Determination by NMR (Rosato et al. in Nat Methods 6:625–626. doi:10.1038/nmeth0909-625, 2009) competition. The software package can be downloaded freely in binary format from http://pine.nmrfam.wisc.edu/download_packages.html. Registered users of the National Magnetic Resonance Facility at Madison can submit jobs to the PONDEROSA-C/S server at http://ponderosa.nmrfam.wisc.edu, where instructions, tutorials, and instructions can be found. Structures are normally returned within 1–2 days.Electronic supplementary materialThe online version of this article (doi:10.1007/s10858-014-9855-x) contains supplementary material, which is available to authorized users.

APSY-NMR for protein backbone assignment in high-throughput structural biology

“…In conclusion, considering the aforementioned unique assets, the use of APSY-NMR experiments in combination with a suitable automated assignment routine, as exemplified here with UNIO-MATCH-2014, is a valid alternative to the many previously proposed approaches for automated polypeptide backbone NMR assignment in proteins (e.g., Atreya et al 2000; Bartels et al 1997; Crippen et al 2010; Fredriksson et al 2012; Lee et al 2014; Lemak et al 2008; Lescop and Brutscher 2009; Moseley et al 2001; Schmidt and Güntert 2012; 2013; Schmucki et al 2009; Staykova et al 2008; Tikole et al 2012; Zawadzka-Kazimierczuk et al 2012; Zimmermann et al 1997). The Figure 3 illustrates that within the range covered by the 30 proteins of Table 1, the result of polypeptide backbone assignments based on the present protocol of using APSY-NMR and UNIO-MATCH-2014 does not depend critically on the protein size.…”

Probabilistic validation of protein NMR chemical shift assignments

“…Alternatively, ARECA accepts input files generated by PONDEROSA-C/S (Lee et al 2014), which performs peak picking on the NOESY spectra and generates a single compact file containing assignments and peak lists.…”

MolProbity for the masses–of data

“…Ideally, an NMR structural biologist would diagnose these local errors in a structure, and examine the corresponding restraints and primary data to correct misassignments or misplaced peaks in the spectra during several rounds of refinement. Development of improved “semi-automated” software tools, such as NMRFAM-SPARKY (Lee et al 2015) and Ponderosa-C/S (Lee et al 2014), for working with the restraints, assignments, and data can help with this task. Also, there are experimental causes of errors.…”