Trait LMPNNFeatures

pub trait LMPNNFeatures {
    // Required methods
    fn encode_amino_acids(&self, device: &Device) -> Result<Tensor>;
    fn featurize(&self, device: &Device) -> Result<ProteinFeatures>;
    fn get_res_index(&self) -> Vec<u32>;
    fn to_numeric_backbone_atoms(&self, device: &Device) -> Result<Tensor>;
    fn to_numeric_atom37(&self, device: &Device) -> Result<Tensor>;
    fn to_numeric_ligand_atoms(
        &self,
        device: &Device,
    ) -> Result<(Tensor, Tensor, Tensor)>;
    fn to_pdb(&self);
}

Convert the AtomCollection into a struct that can be passed to a model.

Required Methods

fn encode_amino_acids(&self, device: &Device) -> Result<Tensor>

fn featurize(&self, device: &Device) -> Result<ProteinFeatures>

fn get_res_index(&self) -> Vec<u32>

fn to_numeric_backbone_atoms(&self, device: &Device) -> Result<Tensor>

fn to_numeric_atom37(&self, device: &Device) -> Result<Tensor>

fn to_numeric_ligand_atoms( &self, device: &Device, ) -> Result<(Tensor, Tensor, Tensor)>

fn to_pdb(&self)

Implementations on Foreign Types

impl LMPNNFeatures for AtomCollection

Methods for Convering an AtomCollection into a LigandMPNN-ready datasets

fn encode_amino_acids(&self, device: &Device) -> Result<Tensor>

Return a 2D tensor of [1, seqlength]

fn to_numeric_backbone_atoms(&self, device: &Device) -> Result<Tensor>

create numeric Tensor of shape [1, , 4, 3] where the 4 is N/CA/C/O

fn to_numeric_atom37(&self, device: &Device) -> Result<Tensor>

create numeric Tensor of shape [, 37, 3]

fn featurize(&self, device: &Device) -> Result<ProteinFeatures>

fn to_numeric_ligand_atoms( &self, device: &Device, ) -> Result<(Tensor, Tensor, Tensor)>

fn to_pdb(&self)

fn get_res_index(&self) -> Vec<u32>

Implementors