PFRMAT SS 
TARGET T0077 
AUTHOR 4219-2752-2186 
METHOD An optimized nearest neighbour method (ONNM) has been used 
METHOD to predict the protein secondary structure. In ONNM, the  
METHOD parameters used in  standard nearest neighbour method has  
METHOD been optimized (Raghava, 1995, PhD Thesis). ONNM uses 
METHOD neural network method for predicting secondary structure of 
METHOD amino acids which shows the low probability of correct  
METHOD prediction by nearest neighbour method.  
REMARK Secondary structure was predicted using single sequence 
MODEL 1 
M C 0.96 
A C 0.83 
P C 0.79 
V C 0.51 
K C 0.42 
S C 0.51 
Q H 0.57 
E H 0.56 
S H 0.66 
I H 0.64 
N H 0.75 
Q H 0.75 
K H 0.53 
L H 0.59 
A H 0.65 
L E 0.64 
V E 0.73 
I E 0.67 
K E 0.42 
S C 0.69 
G C 0.80 
K C 0.60 
Y E 0.54 
T E 0.48 
L E 0.67 
G E 0.58 
Y E 0.48 
K C 0.58 
S C 0.59 
T C 0.51 
V H 0.57 
K H 0.66 
S H 0.63 
L H 0.78 
R H 0.59 
Q C 0.56 
G C 0.58 
K C 0.65 
S C 0.48 
K C 0.53 
L E 0.54 
I E 0.66 
I E 0.83 
I E 0.77 
A C 0.47 
A C 0.50 
N C 0.67 
T C 0.71 
P C 0.47 
V C 0.50 
L C 0.49 
R H 0.52 
K H 0.58 
S H 0.49 
E H 0.69 
L H 0.69 
E H 0.71 
Y H 0.79 
Y H 0.82 
A H 0.73 
M H 0.70 
L H 0.81 
S H 0.58 
K H 0.48 
T C 0.50 
K E 0.45 
V E 0.69 
Y E 0.77 
Y E 0.79 
F E 0.76 
Q C 0.50 
G C 0.80 
G C 0.85 
N C 0.74 
N C 0.74 
E C 0.46 
L C 0.48 
G C 0.54 
T H 0.49 
A H 0.53 
V H 0.51 
G H 0.44 
K C 0.38 
L E 0.49 
F E 0.53 
R E 0.71 
V E 0.57 
G E 0.46 
V E 0.52 
V E 0.68 
S E 0.51 
I E 0.52 
L E 0.49 
E C 0.44 
A C 0.52 
G C 0.71 
D C 0.71 
S C 0.69 
D C 0.49 
I C 0.60 
L C 0.57 
T E 0.47 
T E 0.55 
L C 0.67 
A C 0.96 
END 
