diff --git a/fusedrug/data/protein/structure/flexible_align_chains_structure.py b/fusedrug/data/protein/structure/flexible_align_chains_structure.py
index dd33b4a2..032d551a 100644
--- a/fusedrug/data/protein/structure/flexible_align_chains_structure.py
+++ b/fusedrug/data/protein/structure/flexible_align_chains_structure.py
@@ -1,5 +1,5 @@
 from jsonargparse import CLI
-from typing import List, Union, Dict, Tuple
+from typing import List, Union, Dict, Tuple, Optional
 from Bio import Align
 from tiny_openfold.utils.superimposition import superimpose
 
@@ -19,7 +19,8 @@ def flexible_align_chains_structure(
     apply_rigid_transformation_to_dynamic_chain_ids: Union[List[Tuple], str],
     static_ordered_chains: Union[List[Tuple], str],
     output_pdb_filename_extentionless: str,
-    minimal_matching_sequence_level_chunk: int = 8,
+    minimal_matching_sequence_level_chunk: Optional[int] = 8,
+    backbone_only_based: bool = False,
     ###chain_id_type:str = "author_assigned",
 ) -> None:
     """
@@ -117,9 +118,15 @@ def flexible_align_chains_structure(
         static_matching["atom14_gt_exists"].astype(bool),
     )
     # orig_atom_pos_shape = dynamic_matching["atom14_gt_positions"].shape
+    use_for_static = static_matching["atom14_gt_positions"]
+    use_for_dynamic = dynamic_matching["atom14_gt_positions"]
+    if backbone_only_based:
+        use_for_static = use_for_static[:, :4, ...]
+        use_for_dynamic = use_for_dynamic[:, :4, ...]
+
     _, rmsd, rot_matrix, trans_matrix = superimpose(
-        static_matching["atom14_gt_positions"].reshape(-1, 3),
-        dynamic_matching["atom14_gt_positions"].reshape(-1, 3),
+        use_for_static.reshape(-1, 3),
+        use_for_dynamic.reshape(-1, 3),
         combined_mask.reshape(-1),
         verbose=True,
     )
@@ -199,7 +206,9 @@ def _apply_indices(x: Dict, indices: np.ndarray) -> Tuple[str, np.ndarray]:
 
 
 def get_alignment_indices(
-    target: str, query: str, minimal_matching_sequence_level_chunk: int
+    target: str,
+    query: str,
+    minimal_matching_sequence_level_chunk: Optional[int],
 ) -> Tuple[np.ndarray, np.ndarray]:
     aligner = Align.PairwiseAligner()
 
@@ -214,7 +223,9 @@ def get_alignment_indices(
     query_indices = []
 
     for (target_start, target_end), (query_start, query_end) in zip(*alignment.aligned):
-        if target_end - target_start >= minimal_matching_sequence_level_chunk:
+        if (minimal_matching_sequence_level_chunk is None) or (
+            target_end - target_start >= minimal_matching_sequence_level_chunk
+        ):
             target_indices.extend(list(range(target_start, target_end)))
             query_indices.extend(list(range(query_start, query_end)))