BioJava can also do calculation of Accessible Surface Areas (ASA) through an implementation of the rolling ball algorithm of Shrake and Rupley [Shrake 1973].

This code will do the ASA calculation and output the values per residue and the total:

AtomCache cache = new AtomCache();

cache.setUseMmCif(true);

StructureIO.setAtomCache(cache);

Structure structure = StructureIO.getStructure("1smt");

AsaCalculator asaCalc = new AsaCalculator(structure,

AsaCalculator.DEFAULT_PROBE_SIZE,

1000, 1, false);

GroupAsa[] groupAsas = asaCalc.getGroupAsas();

double tot = 0;

for (GroupAsa groupAsa: groupAsas) {

System.out.printf("%1s\t%5s\t%3s\t%6.2f\n",

groupAsa.getGroup().getChainId(),

groupAsa.getGroup().getResidueNumber(),

groupAsa.getGroup().getPDBName(),

groupAsa.getAsaU());

tot+=groupAsa.getAsaU();

}

System.out.printf("Total area: %9.2f\n",tot);

See [DemoAsa](https://github.com/biojava/biojava/blob/master/biojava3-structure/src/main/java/demo/DemoAsa.java) for a fully working demo.

[Shrake 1973]: http://www.sciencedirect.com/science/article/pii/0022283673900119

See [DemoCrystalInterfaces](https://github.com/biojava/biojava/blob/master/biojava3-structure/src/main/java/demo/DemoCrystalInterfaces.java) for a fully working demo of the example above.

One can also cluster the interfaces based on their similarity. The similarity is measured through contact overlap: number of common contacts over average number of contact in both chains. The clustering can be done as following:

List<StructureInterfaceCluster> clusters = interfaces.getClusters();

for (StructureInterfaceCluster cluster:clusters) {

System.out.print("Cluster "+cluster.getId()+" members: ");

for (StructureInterface member:cluster.getMembers()) {

System.out.print(member.getId()+" ");

}

System.out.println();

}