Fig. 1: In silico evolution platform for solenoid protein generation.
From: Designing novel solenoid proteins with in silico evolution
A The input repeat sequence of length L is repeated N times to make the full NxL sequence, whose structure is then predictedWi with AF2. The resulting design is scored with a cost function that combines AF2 pLDDT, as well as a solenoid-type probability score. The sequence pool is updated using a genetic algorithm. This continues until a set threshold for the cost function is met, and the output protein structure is taken forward. The sequence is redesigned using ProteinMPNN for successful backbones obtained through the in silico evolution platform. B Outcomes of different solenoid category and repeat lengths for solenoids generated with the in silico evolution platform. C Example of trajectory for β-solenoid from an initial random sequence to final solenoid design. Generation 0 is the initial random starting sequence. The cost function value of the best candidate (red) is shown for each generation. The mean fitness (black), pLDDT (blue) and solenoid score (green) for each generation is shown. 1 standard deviation around the mean is shown by the shaded regions. Top candidate structures colored by pLDDT score (blue: 90–100, cyan: 70–90, yellow: 50–70, orange 0–50) are shown for generations 0, 1, 3, and 5.
