From https://gitlab.com/KomBioMol/gromologist#preparing-rest2-topologies

Gromologist

Gromologist is a package designed to facilitate handling, editing and manipulating GROMACS topology files (.top and .itp), as well as compatible structures (.pdb and .gro).

• Gromologist  
  • Installation
  • How to cite
  • Usage    
    • Basic features      
      • Reading and writing files
      • File inspection, checks and printing
      • Producing lightweight files
      • Dealing with unspecified 'define' keywords in topologies
    • Editing topologies      
      • Adding mutations to proteins
      • Adding bonds within or between molecules
      • Adding disulfide bonds and coordination bonds with transition metals
      • Adding and removing atoms while maintaining ordered numbering
      • Adding alchemical B-states
      • Removing or swapping alchemical states
      • Duplicating and reassigning types
      • Adding NBFIX terms
      • Explicitly listing parameters in topology & finding missing parameters
      • Preparing REST2 topologies
    • Dihedral optimization
    • Editing structures      
      • Adding atoms along a vector specified by other atoms, and deleting them
      • Interpolating between two pre-aligned structures
      • Filling beta-values with custom data (for visualization)
      • Creating new PDB as a subset of existing one
      • Renumbering atoms or residues in a structure
      • Adding chain, CONECT or element information
      • Converting a 3-point water model to a 4-point one
    • Selection language syntax
    • Access to Gromacs utilities

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Installation

The latest "official" release can be obtained directly through pip by typing pip install gromologist.

To get the latest development version, first locally clone the git repo (git clone https://gitlab.com/KomBioMol/gromologist.git), then install the package into Python by typing pip install . in the main Gromologist directory. If you're using Anaconda, the same will work with /path/to/anaconda/bin/pip.

Note that Gromologist has no explicit dependencies, although a few specific functionalities will require basic scientific libraries such as numpy or sklearn.