SERVER FOR COMPUTING/PREDICTING DEPTH, CAVITY SIZES, LIGAND BNDING SITES AND pKa


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Utility of DEPTH

  1. Describe residue burial [ref]
  2. Protein Binding Site Predictinon
  3. Protein mutagenesis stability prediction [ref]
  4. Hydrogen Exchange rate prediction [ref]
  5. Protein-Protein Interface Hot Spot Prediction [ref]
  6. Protein Residue Conservation Prediction [ref]
  7. Protein cavity (number and size) computation
  8. Predicting the pKa values of ionizable residues
DEPTH Algorithm
  1. Solvating Protein Molecule
  2. Removal of non-bulk solvents
  3. Sampling Solvent Configurations


Utility of DEPTH

Depth measures the closest distance of a residue/atom to bulk solvent.

Accessible surface area is a parameter that is widely used in analyses of protein structure and stability. However accessible surface area does not distinguish between atoms just below the protein surface and those in the core of the protein. In order to differentiate between such buried residues, we describe a computational procedure for calculating the depth of a residue from the protein surface. A detailed description of the computation of depth can be found here.

Residue depth correlates significantly better than accessibility with effects of mutations on protein stability and on protein-protein interactions. The deepest residues in the native state invariably undergo hydrogen exchange through global unfolding of the protein and are often significantly protected in the corresponding molten globule states. Depth is often a more useful descriptor of residue burial than accessibility. This is probably related to the fact that the protein interior and surrounding solvent differ significantly in polarity and packing density. Hence the strengths of van der Waals and electrostatic interactions between residues in a protein may be expected to depend on the distance of the residue(s) from the protein surface. The depth algorithm has been extended to develop a procedure for accurate calculation of cavity volumes in proteins. These calculations, along with existing thermodynamic data on stabilities of cavity containing mutants, have recently been used to obtain an estimate of the strength of the hydrophobic driving force in protein folding. In genral, Depth

  • provides wider dynamic range for residue burial (as compared to accessible surface area)
  • correlates well with protein stability
  • correlates well with amide proton hydrogen exchange rates
  • predicts protein-protein interaction hot spots
  • helps explain evolutionary variability in protein sequences
  • Molecular Dynamics Simulation Trajectory Analysis
  • Phi Value Prediction
  • Protein 3D Structure Model Assessment
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DEPTH Algorithm

STEP 1: Solvating Protein Molecule

The protein molecule of interest is placed at the center of a pre-equilibrated box of solvent (water). Full atomic water model SPC216 (generated using GROMACS genbox with spc216.gro structural file) is used here.
Water molecules that clash with atoms of the protein, i.e., are within 2.6 Å of protein atoms, are removed from the box.
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STEP 2: Removal of non-bulk solvents

Other than the clashing water molecules, non-bulk waters are also removed from the box.
Non-bulk waters are those that are trapped in cavities (Figure 1) and isolated from the bulk solvent.
Isolated water are detected by inspecting the number of water molecules in its immediate neighborhood.
If there are less that 2 (default value) water molecules within a spherical volume of radius 4.2 Å (default value), the water is considered non-bulk, and removed from the solvent box (Figure 2). The 'solvent neighborhood radius' and the 'minimum number of neighborhood waters' mentioned above are both user-tunable parameters. The removal of a non-bulk water could render some of its immediate neighboring water also as non-bulk waters. For this reason, the removal of bulk waters is iterated till no more water is removed from the solvent box.
Figure 1   Figure 2
 
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STEP 3: Sampling Solvent Configurations

The bulk water surrounding a protein is freely diffusing. To mimic this dynamics of bulk water, the protein is solvated repeatedly, each time in a different orientation. New orientations are generated by rotating the protein by a random angle about an axis passing through its center of mass, and translating it along the X-axis to a random distance < 2.8 Å (the average distance between neighboring water molecule in the box). Each solvation of the protein is considered to represent a snapshot of the dynamics of bulk-water. With sufficient number of solvations, water molecules can explore all regions accessible to bulk solvent, hence mimicking bulk-water dynamics (Figure 3).
At each solvation iteration, the value of atom/residue depth is computed as the distance between the atom/residue to the closest molecule of bulk water. Depth is finally reported as the average depth over all solvation iterations. The user can specify the 'number of solvation cycles '(default = 25).

Figure 3: Mimicking solvent dynamics by repeated solvation
Protein molecules from each solvation are superposed to show only
water movement (first hydration layer above protein surface)
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