The invention discloses a recommendation method and device for recommending mutable sites from
small sample experiment data, and the method comprises the following steps: obtaining the
small sample experiment data, including sequences and data of wild enzymes and mutants, and obtaining an optimal
mutant sequence according to the
data type of the mutants; predicting according to the optimal
mutant sequence to obtain a
mutant structure; predicting according to the mutant structure to obtain a substrate
binding pocket; predicting a
single mutation site based on a
protein structure model, and selecting a residue with a distance from the center of a substrate
binding pocket smaller than a threshold value 1 as a recommended
single mutation site; selecting sites in
small sample experimental data, mutating each site in
a site set into 19 other amino acids, combining every two other amino acids to construct a
double mutation set, predicting a
mutation result, and obtaining recommended
double mutation sites according to a sorting result; selecting sites in small sample experiment data, obtaining coordinates of the sites in a variant structure for clustering analysis, and selecting one site from each cluster to be combined with other clusters to construct multiple mutations; predicting
mutation results of multiple mutations, and obtaining recommended multiple
mutation sites according to a sorting result; the method is effectively operated under the condition of small sample data; through the strong generalization ability of the large
language model, the
structure and function information in the biomolecules can be captured, so that the sequence of the
enzyme is effectively coded for more accurate
inference.