Protein-interface analysis

Calculate interface contributions and compare local mutations. Use a prepared multi-chain PoseStack and a score function from the same parameter database.

Define partners from metadata

Build partner masks from the author chain labels in pdb_info:

chain_labels = pose_stack.pdb_info.chain_labels
partner_a = torch.as_tensor(chain_labels == "A", device=pose_stack.device)
partner_b = torch.as_tensor(chain_labels == "B", device=pose_stack.device)

Masks have shape [n_poses, max_n_blocks]. Check the selected chain labels and block counts; file residue numbers need not match block indices.

Score the interface

The convenience reduction sums both stored orientations between the masks:

from tmol.ops import calculate_block_pair_ddg

interface_by_term = calculate_block_pair_ddg(
    pose_stack,
    partner_a,
    partner_b,
    sfxn=score_function,
    sum_terms=False,
    minimize=False,
    pack=False,
)

The result sums weighted interactions between the two masks. For residue-pair analysis, render a block-pair scorer and add matrix[i, j] + matrix[j, i]; one orientation alone can miss an interaction.

Batch explicit mutations

Construct one pose per requested site/state, then restrict task choices monotonically:

scan_batch = PoseStackBuilder.from_poses([pose_stack] * n_requests, device)
task = PackerTask(scan_batch, PackerPalette())

mutation_mask = torch.zeros_like(scan_batch.block_type_ind, dtype=torch.bool)
mutation_mask[mutant_pose_indices, target_block_indices] = True

task.restrict_to_repacking(~mutation_mask)
task.restrict_absent_name3s({"ALA"}, mutation_mask)
task.disable_packing_by_block_mask(~local_shells)

Add the appropriate conformer samplers and call pack_rotamers() once on the batch. Include an independently repacked WT control for each site, use the same declared shell for its WT/mutant pair, verify all non-target identities, and record stochastic outcomes rather than presenting a single pack as converged.

For one target block per pose, pass an integer index tensor to calculate_block_pair_ddg() together with the partner mask. That indexed route avoids a dense target-mask reduction.

Interpret the result

Report the exact computational experiment: score function and weights, input and preparation, partner masks, packing shell, allowed identities, samplers, device, number of outcomes, minimization settings, and comparison rule. Compare each mutant with its independently repacked WT control.

Examples and reference

Interface example · Analysis API · Packing