BoltzGen / model /boltzgen /data /sample /cluster.py
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from typing import Dict, List
import numpy as np
from numpy.random import Generator
from boltzgen.data import const
from boltzgen.data.data import ChainInfo, InterfaceInfo, Record
from boltzgen.data.sample.sampler import Sample, Sampler
def get_chain_cluster(chain: ChainInfo, record: Record) -> str: # noqa: ARG001
"""Get the cluster id for a chain.
Parameters
----------
chain : ChainInfo
The chain id to get the cluster id for.
record : Record
The record the interface is part of.
Returns
-------
str
The cluster id of the chain.
"""
return chain.cluster_id
def get_interface_cluster(interface: InterfaceInfo, record: Record) -> str:
"""Get the cluster id for an interface.
Parameters
----------
interface : InterfaceInfo
The interface to get the cluster id for.
record : Record
The record the interface is part of.
Returns
-------
str
The cluster id of the interface.
"""
chain1 = record.chains[interface.chain_1]
chain2 = record.chains[interface.chain_2]
cluster_1 = str(chain1.cluster_id)
cluster_2 = str(chain2.cluster_id)
cluster_id = (cluster_1, cluster_2)
cluster_id = tuple(sorted(cluster_id))
return cluster_id
def get_chain_weight(
chain: ChainInfo,
record: Record, # noqa: ARG001
clusters: Dict[str, int],
beta_chain: float,
alpha_prot: float,
alpha_nucl: float,
alpha_ligand: float,
) -> float:
"""Get the weight of a chain.
Parameters
----------
chain : ChainInfo
The chain to get the weight for.
record : Record
The record the chain is part of.
clusters : Dict[str, int]
The cluster sizes.
beta_chain : float
The beta value for chains.
alpha_prot : float
The alpha value for proteins.
alpha_nucl : float
The alpha value for nucleic acids.
alpha_ligand : float
The alpha value for ligands.
Returns
-------
float
The weight of the chain.
"""
prot_id = const.chain_type_ids["PROTEIN"]
rna_id = const.chain_type_ids["RNA"]
dna_id = const.chain_type_ids["DNA"]
ligand_id = const.chain_type_ids["NONPOLYMER"]
weight = beta_chain / clusters[chain.cluster_id]
if chain.mol_type == prot_id:
weight *= alpha_prot
elif chain.mol_type in [rna_id, dna_id]:
weight *= alpha_nucl
elif chain.mol_type == ligand_id:
weight *= alpha_ligand
return weight
def get_interface_weight(
interface: InterfaceInfo,
record: Record,
clusters: Dict[str, int],
beta_interface: float,
alpha_prot: float,
alpha_nucl: float,
alpha_ligand: float,
) -> float:
"""Get the weight of an interface.
Parameters
----------
interface : InterfaceInfo
The interface to get the weight for.
record : Record
The record the interface is part of.
clusters : Dict[str, int]
The cluster sizes.
beta_interface : float
The beta value for interfaces.
alpha_prot : float
The alpha value for proteins.
alpha_nucl : float
The alpha value for nucleic acids.
alpha_ligand : float
The alpha value for ligands.
Returns
-------
float
The weight of the interface.
"""
prot_id = const.chain_type_ids["PROTEIN"]
rna_id = const.chain_type_ids["RNA"]
dna_id = const.chain_type_ids["DNA"]
ligand_id = const.chain_type_ids["NONPOLYMER"]
chain1 = record.chains[interface.chain_1]
chain2 = record.chains[interface.chain_2]
n_prot = (chain1.mol_type) == prot_id
n_nuc = chain1.mol_type in [rna_id, dna_id]
n_ligand = chain1.mol_type == ligand_id
n_prot += chain2.mol_type == prot_id
n_nuc += chain2.mol_type in [rna_id, dna_id]
n_ligand += chain2.mol_type == ligand_id
weight = beta_interface / clusters[get_interface_cluster(interface, record)]
weight *= alpha_prot * n_prot + alpha_nucl * n_nuc + alpha_ligand * n_ligand
return weight
class ClusterSampler(Sampler):
"""The weighted sampling approach, as described in AF3.
Each chain / interface is given a weight according
to the following formula, and sampled accordingly:
w = b / n_clust *(a_prot * n_prot + a_nuc * n_nuc
+ a_ligand * n_ligand)
"""
def __init__(
self,
alpha_prot: float = 3.0,
alpha_nucl: float = 3.0,
alpha_ligand: float = 1.0,
beta_chain: float = 0.5,
beta_interface: float = 1.0,
) -> None:
"""Initialize the sampler.
Parameters
----------
alpha_prot : float, optional
The alpha value for proteins.
alpha_nucl : float, optional
The alpha value for nucleic acids.
alpha_ligand : float, optional
The alpha value for ligands.
beta_chain : float, optional
The beta value for chains.
beta_interface : float, optional
The beta value for interfaces.
"""
self.alpha_prot = alpha_prot
self.alpha_nucl = alpha_nucl
self.alpha_ligand = alpha_ligand
self.beta_chain = beta_chain
self.beta_interface = beta_interface
def sample(self, records: List[Record]) -> list[Sample]:
"""Sample a structure from the dataset infinitely.
Parameters
----------
records : List[Record]
The records to sample from.
Returns
-------
List[Sample]
The samples.
"""
# Compute chain cluster sizes
chain_clusters: Dict[str, int] = {}
for record in records:
for chain in record.chains:
if not chain.valid:
continue
cluster_id = get_chain_cluster(chain, record)
if cluster_id not in chain_clusters:
chain_clusters[cluster_id] = 0
chain_clusters[cluster_id] += 1
# Compute interface clusters sizes
interface_clusters: Dict[str, int] = {}
for record in records:
for interface in record.interfaces:
if not interface.valid:
continue
cluster_id = get_interface_cluster(interface, record)
if cluster_id not in interface_clusters:
interface_clusters[cluster_id] = 0
interface_clusters[cluster_id] += 1
# Compute weights
chain_samples, chain_weights = [], []
int_samples, int_weights = [], []
for record in records:
for chain_id, chain in enumerate(record.chains):
if not chain.valid:
continue
weight = get_chain_weight(
chain,
record,
chain_clusters,
self.beta_chain,
self.alpha_prot,
self.alpha_nucl,
self.alpha_ligand,
)
chain_samples.append((record.id, chain_id))
chain_weights.append(weight)
for int_id, interface in enumerate(record.interfaces):
if not interface.valid:
continue
weight = get_interface_weight(
interface,
record,
interface_clusters,
self.beta_interface,
self.alpha_prot,
self.alpha_nucl,
self.alpha_ligand,
)
int_samples.append((record.id, int_id))
int_weights.append(weight)
# Normalize weights
weights_sum = np.sum(chain_weights) + np.sum(int_weights)
chain_weights = np.array(chain_weights) / weights_sum
int_weights = np.array(int_weights) / weights_sum
# Create samples
chain_samples = [
Sample(record_id=s[0], chain_id=s[1], weight=w)
for s, w in zip(chain_samples, chain_weights)
]
int_samples = [
Sample(record_id=s[0], interface_id=s[1], weight=w)
for s, w in zip(int_samples, int_weights)
]
samples = chain_samples + int_samples
return samples