Table 2:

Recent advances in structure prediction and computational protein design

Category	Method	Result	Ref
Structure Prediction	AlphaFold	Highly accurate results predicting protein structure from amino acid sequence	[124]
	AlphaFold-2	Updated version of AlphaFold that has solved the protein folding problem	[125]
	RosettaFold	Similar protein structure prediction as AlphaFold	[126]
	ProteinMPNN	Protein backbone sequence design using deep learning	[127]
	trRosetta	De novo protein structure prediction using deep neural networks	[128]
	RaptorX	Web based server for protein structure prediction from amino acid sequence	[129]
	ProGen	Language models can predict protein function from sequence families	[130]
	AminoBERT	Structure prediction using a language model	[131]
	Pfam	Annotating protein function from amino acid sequence with a deep learning model	[17]
		Prediction of protein fitness from evolutionary data	[132]
Protein Design	Deep learning-based design of zinc finger nucleases for specific DNA binding regions		[133]
	Design of IL-2 mimetic protein with reduced toxicity		[134]
	Development of a capsid protein using deep learning		[135]
	De novo design of a chimeric antigen receptor, small molecule regulated, kill switch		[136]
	Computational design of membrane permeable proteins		[137]
	Protein design of axel-rotator-like components		[138]
	Design of proteins binding to specific targets from aa sequence alone		[31]
	Development of nanocage structural proteins		[139]
	Computational design of large multicomponent proteins		[140]
	Rational design of donut-shaped proteins		[141]
	Design of IgG antibodies using multi-state design simulations		[142]
	Design of helical membrane proteins		[143]
	De novo design of a β barrel protein		[144]