Is it common practice to transform variables before training a mixture model? For example if a variable looks to be log-normal distributed, is there any harm in log-tranforming it before feeding it into a Gaussian Mixture Model? What about other transformations?

And for those of you who work with mixture models, how common is it to do things like this?

Sorry if this is a basic question, no one around me works with this stuff and I wanted to hear from people with experience.