MACHINE LEARNING FOR DESIGNING ANTIBODIES AND NANOBODIES IN-SILICO

A computer-implemented method for generating a set of candidate variant amino acid sequences of an antibody, a nanobody, or a fragment thereof, having binding ability to a target protein, may comprise: (a) obtaining a set of seed amino acid sequences; and (b) processing the set of seed amino acid sequences using a first trained machine learning algorithm to generate the set of candidate amino acid sequences, wherein the first trained machine learning algorithm is trained with first training data comprising a set of training amino acid sequences for the target protein, wherein the first trained machine learning algorithm is further trained through a transfer learning method using a second trained machine learning algorithm, wherein the second trained machine learning algorithm is trained with second training data comprising a set of training amino acid sequences for a second target protein, wherein the second target protein is different from the target protein.