text: Title: [ENH] Include a featurization function for protein sequences
  Body: # Brief Description
  
  I would like to propose a function that featurizes protein sequences according to the following baseline featurizations:
  
  - MW
  - pKa
  - T-features
  - One-hot encoding
  
  This proposed function would accept a column of strings, find the appropriate strings to featurize, and then return a featurization matrix (akin to how morgans are computed).
  
  # Example API
  
  ```python
  # Return a protein sequence featurization matrix using the “longest” sequence as the reference sequence.
  import janitor.biology
  df.sequence_features(sequence_column=‘prot_seq’, featurization_type=‘t’, sequence_length=“longest”) 
  
  # Featurize using MW, but only take most common sequence.
  ## By using “most_common_only”, any sequence not equal to the most common length is discarded.
  df.sequence_features(sequence_column=‘prot_seq’, featurization_type=‘mw’, sequence_length=‘most_common_only’)
  
  ## By using “most_common_max”, any sequence greater than the most common length is discarded, while those less than the most common length are right-padded with the * symbol
  df.sequence_features(sequence_column=“prot_seq”, featurization_type=“pka”, sequence_length=“most_common_max”)
  ```