2.2.3 Evolutionary
Analysis
1. The sequence of Fab (PDB ID:1cu4) was used to generate
relative conservation scores for each amino acid position
using the Bayesian method implemented in the ConSurf
server [25].
2. The sequence homologues of Fab were identified after three
iterations of CS-BLAST algorithm against UNIREF90
database.
3. The selected sequence homologues with an E-value <0.0001
were then aligned using MAFFT [26].
4. The resulting Multiple Sequence Alignment (500 sequences
with !35% similarity) was used to calculate the conservation
scores, which ranged from 1 (variable) to 9 (highly conserved).
The Fab residues were color-coded based on conservation
scores obtained.
2.2.4 Correlation
Analysis
1. Correlations between all the residues in the six systems were
analyzed for the entire 100-ns MD trajectory (25,000 frames)
using the normalized covariance to characterize the correlation
in motion of protein residues [27], ranging from À1 to 1.
2. If two residues move in the same (opposite) direction in most
the frames, the motion is considered as (anti-)correlated, and
the correlation value is close to À1 or 1. If the correlation value
between two residues is close to zero, they are generally uncorrelated. The correlation evaluation was performed by using
CARMA [28] (see Notes 4–6, Fig. 2).
2.2.5 Weighted Network,
Community Analysis,
Optimal/Suboptimal Paths
in Fab/Peptide Systems
1. A network is defined as a set of nodes with connecting edges.
The nodes in this work represent the amino acid residues and
the essential bound water molecules. An edge between two
nodes was defined if any heavy atoms from the two residues/
water molecules are within 4.5 A ˚ of each other in over 75% of
the analyzed frames (see Note 7, Fig. 3).
2. Neighboring residues in sequence are not considered to be in
contact because they will form numerous trivial suboptimal
paths in the weighted network.
3. The dynamical networks were constructed based on the 100-ns
trajectories.
4. To study the water effect on the network, the crystallized water
molecules on the antibody-antigen interface were kept from
the system.
5. The communities within a network were defined as the
sub-structures of the network in which the nodes are more
heavily interconnected to each other than to other nodes.
The community was identified by the Girvan-Newman algorithm [29]. For simplicity and clarity, communities with
The Allosteric Effect in Antibody-Antigen Recognition
179
Analysis
1. The sequence of Fab (PDB ID:1cu4) was used to generate
relative conservation scores for each amino acid position
using the Bayesian method implemented in the ConSurf
server [25].
2. The sequence homologues of Fab were identified after three
iterations of CS-BLAST algorithm against UNIREF90
database.
3. The selected sequence homologues with an E-value <0.0001
were then aligned using MAFFT [26].
4. The resulting Multiple Sequence Alignment (500 sequences
with !35% similarity) was used to calculate the conservation
scores, which ranged from 1 (variable) to 9 (highly conserved).
The Fab residues were color-coded based on conservation
scores obtained.
2.2.4 Correlation
Analysis
1. Correlations between all the residues in the six systems were
analyzed for the entire 100-ns MD trajectory (25,000 frames)
using the normalized covariance to characterize the correlation
in motion of protein residues [27], ranging from À1 to 1.
2. If two residues move in the same (opposite) direction in most
the frames, the motion is considered as (anti-)correlated, and
the correlation value is close to À1 or 1. If the correlation value
between two residues is close to zero, they are generally uncorrelated. The correlation evaluation was performed by using
CARMA [28] (see Notes 4–6, Fig. 2).
2.2.5 Weighted Network,
Community Analysis,
Optimal/Suboptimal Paths
in Fab/Peptide Systems
1. A network is defined as a set of nodes with connecting edges.
The nodes in this work represent the amino acid residues and
the essential bound water molecules. An edge between two
nodes was defined if any heavy atoms from the two residues/
water molecules are within 4.5 A ˚ of each other in over 75% of
the analyzed frames (see Note 7, Fig. 3).
2. Neighboring residues in sequence are not considered to be in
contact because they will form numerous trivial suboptimal
paths in the weighted network.
3. The dynamical networks were constructed based on the 100-ns
trajectories.
4. To study the water effect on the network, the crystallized water
molecules on the antibody-antigen interface were kept from
the system.
5. The communities within a network were defined as the
sub-structures of the network in which the nodes are more
heavily interconnected to each other than to other nodes.
The community was identified by the Girvan-Newman algorithm [29]. For simplicity and clarity, communities with
The Allosteric Effect in Antibody-Antigen Recognition
179