TEMPy documentation

TEMPy is an object-oriented Python library designed to help the user in the analysis of structures of macromolecular assemblies, especially in the context of 3D electron microscopy density maps. It is designed with a set of functionalities that assess the goodness-of-fit between a given atomic model and a density map or between two maps using a variety of different scoring functions.It can also generate various ensembles of alternative fits, which has been shown to be useful in assessing a model fit and find other models with good density fit. TEMPy also includes a genetic algorithm based multi-component fitting method, gamma-TEMPy.

TEMPy also enables integration of data from cross-linking coupled to mass-spectrometry. Methods to calculate solvent accessible distances between crosslinked residues and evaluate models based on the agreement with expected distance distribution, are currently implemented.

TEMPy makes use of open source python libraries including NumPy, SciPy and Biopython. TEMPy is flexible, allowing users to build their own functions for specific purposes.

For the use of plotting TEMPy uses matplotlib.


TEMPy2 now available: here. You can find tutorial files there

This software is made available under GPL V3, together with some additional documentation.


If you use TEMPy, please cite:

Cragnolini T, Sahota H, Joseph AP, Sweeney A, Malhotra S, Vasishtan D, Topf M (2021a) TEMPy2: A Python library with improved 3D electron microscopy density-fitting and validation workflows. Acta Crystallogr Sect D Struct Biol 77:41–47. https://doi.org/10.1107/S2059798320014928.

Other references:

  1. Cragnolini et al (2021b) Automated Modeling and Validation of Protein Complexes in Cryo-EM Maps. Methods Mol Biol 2215:189–223.
  2. Sinnott et al (2020) Combining Information from Crosslinks and Monolinks in the Modeling of Protein Structures. Structure 28:1061-1070.e3.
  3. Joseph et al (2017) Improved metrics for comparing structures of macromolecular assemblies determined by 3D electron-microscopy. J Struct Biol 99(1): 12-26
  4. Joseph et al (2016) Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment. Methods. 1;100:42-9
  5. Farabella et al (2015) TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits. J. Appl. Cryst. 48, 1314-1323
  6. Vasishtan and Topf (2011) Scoring functions for cryoEM density fitting. J Struct Biol 174:333-343.
  7. Pandurangan AP, Vasishtan D, Alber F, Topf M. (2015) γ-TEMPy: Simultaneous Fitting of Components in 3D-EM Maps of Their Asssembly Using a Genetic Algorithm. Structure. 23(12), 2365-2376.
  8. Bullock JMA, Schwab J, Thalassinos K, Topf M. (2016). The importance of non-accessible crosslinks and solvent accessible surface distance in modelling proteins with restraints from crosslinking mass spectrometry. MCP. 5(7):2491-500.

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