Is it possible to use a pretrained scikit learn model to make predictions on a dataset with different features (than those used during training)
Technically, the only constraint would be the number of features that has to be the same than during the training phase (in most scikit learn models).
Will it perform well ?
I would say it really depends on the type of model/approach you are using and what is behind:

Note that these new features are very similar to the ones used in training

Generally speaking it will probably not perform well unless the training features and the new features are related in a way that is acceptable by your model.