Method for improving the secretion of a polypeptide of interest by a eukaryotic host cell, which method comprises modifying the value of a set of relevant protein features in the amino acid backbone of the polypeptide to fall within an optimal range or to become more close to an optimal value for one or more protein features in the eukaryotic host, wherein protein features are properties that can be computationally derived from the protein amino acid sequence and DNA sequence, the method comprising the steps of: (i) determining an optimal range and an optimal value for one or more protein features in the eukaryotic host, wherein an optimal range or an optimal value of protein features for a eukaryotic host are determined by: I. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; II. computing protein features for all proteins in the dataset S; III. determining an optimal value (F_opt) for each feature for the eukaryote host by fitting a probability distribution for each protein feature computed from secreted proteins S+ such that the distribution of the feature values is well described by the chosen probability distribution; IV. determining an optimal range of each feature for the eukaryote host; and (ii) determining a set of relevant protein features in the eukaryotic host, which features will improve the secretion of the polypeptide by the eukaryotic host if one or more of these relevant features is modified in the amino acid backbone of the polypeptide, wherein a relevant set of features is determined by: a. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; b. computing protein features for all proteins in the dataset S; c. using a statistical classification method to select a subset of protein features (Fs) that gives the best performance of a statistical classifier to distinguish between secreted proteins S+ and non-secreted proteins S- in the dataset S, according to a suitably defined classifier performance criterion; and (iii) modifying the value of the relevant protein features to fall within the optimal range or more close to the optimal value as determined in (i), wherein (i) and (ii) may be performed in any order. (i) determining an optimal range and an optimal value for one or more protein features in the eukaryotic host, wherein an optimal range or an optimal value of protein features for a eukaryotic host are determined by: I. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; II. computing protein features for all proteins in the dataset S; III. determining an optimal value (F_opt) for each feature for the eukaryote host by fitting a probability distribution for each protein feature computed from secreted proteins S+ such that the distribution of the feature values is well described by the chosen probability distribution; IV. determining an optimal range of each feature for the eukaryote host; and I. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; II. computing protein features for all proteins in the dataset S; III. determining an optimal value (F_opt) for each feature for the eukaryote host by fitting a probability distribution for each protein feature computed from secreted proteins S+ such that the distribution of the feature values is well described by the chosen probability distribution; IV. determining an optimal range of each feature for the eukaryote host; and (ii) determining a set of relevant protein features in the eukaryotic host, which features will improve the secretion of the polypeptide by the eukaryotic host if one or more of these relevant features is modified in the amino acid backbone of the polypeptide, wherein a relevant set of features is determined by: a. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; b. computing protein features for all proteins in the dataset S; c. using a statistical classification method to select a subset of protein features (Fs) that gives the best performance of a statistical classifier to distinguish between secreted proteins S+ and non-secreted proteins S- in the dataset S, according to a suitably defined classifier performance criterion; and a. collecting or creating a dataset S, which contains the secretion levels of a suitable amount of proteins in a certain eukaryotic host and the amino acid and DNA sequences of these proteins; b. computing protein features for all proteins in the dataset S; c. using a statistical classification method to select a subset of protein features (Fs) that gives the best performance of a statistical classifier to distinguish between secreted proteins S+ and non-secreted proteins S- in the dataset S, according to a suitably defined classifier performance criterion; and (iii) modifying the value of the relevant protein features to fall within the optimal range or more close to the optimal value as determined in (i), wherein (i) and (ii) may be performed in any order.