#![allow(dead_code)]
use scirs2_core::ndarray::Array2;
use std::collections::{HashMap, HashSet};
pub struct MolecularDesignOptimizer {
target_properties: TargetProperties,
fragment_library: FragmentLibrary,
scoring_function: ScoringFunction,
constraints: DesignConstraints,
strategy: OptimizationStrategy,
}
#[derive(Debug, Clone)]
pub struct TargetProperties {
pub molecular_weight: Option<(f64, f64)>, pub logp: Option<(f64, f64)>,
pub logs: Option<(f64, f64)>,
pub hbd: Option<(usize, usize)>,
pub hba: Option<(usize, usize)>,
pub rotatable_bonds: Option<(usize, usize)>,
pub tpsa: Option<(f64, f64)>,
pub custom_descriptors: HashMap<String, (f64, f64)>,
}
#[derive(Debug, Clone)]
pub struct FragmentLibrary {
pub fragments: Vec<MolecularFragment>,
pub connection_rules: ConnectionRules,
pub fragment_scores: HashMap<usize, f64>,
pub privileged_scaffolds: Vec<usize>,
}
#[derive(Debug, Clone)]
pub struct MolecularFragment {
pub id: usize,
pub smiles: String,
pub attachment_points: Vec<AttachmentPoint>,
pub properties: FragmentProperties,
pub pharmacophores: Vec<PharmacophoreFeature>,
}
#[derive(Debug, Clone)]
pub struct AttachmentPoint {
pub atom_idx: usize,
pub bond_types: Vec<BondType>,
pub direction: Vec3D,
}
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum BondType {
Single,
Double,
Triple,
Aromatic,
}
#[derive(Debug, Clone)]
pub struct Vec3D {
pub x: f64,
pub y: f64,
pub z: f64,
}
#[derive(Debug, Clone)]
pub struct FragmentProperties {
pub mw_contribution: f64,
pub logp_contribution: f64,
pub hbd_count: usize,
pub hba_count: usize,
pub rotatable_count: usize,
pub tpsa_contribution: f64,
}
#[derive(Debug, Clone)]
pub struct PharmacophoreFeature {
pub feature_type: PharmacophoreType,
pub position: Vec3D,
pub tolerance: f64,
}
#[derive(Debug, Clone)]
pub enum PharmacophoreType {
HBondDonor,
HBondAcceptor,
Hydrophobic,
Aromatic,
PositiveCharge,
NegativeCharge,
MetalCoordination,
}
#[derive(Debug, Clone)]
pub struct ConnectionRules {
pub compatible_pairs: HashMap<(usize, usize), f64>,
pub forbidden_connections: HashSet<(usize, usize)>,
pub reaction_templates: Vec<ReactionTemplate>,
}
#[derive(Debug, Clone)]
pub struct ReactionTemplate {
pub name: String,
pub reactants: Vec<FunctionalGroup>,
pub product_pattern: String,
pub feasibility: f64,
}
#[derive(Debug, Clone)]
pub struct FunctionalGroup {
pub smarts: String,
pub count: usize,
}
#[derive(Debug, Clone)]
pub enum ScoringFunction {
Additive { weights: HashMap<String, f64> },
MLBased { model_path: String },
DockingBased { receptor: ProteinStructure },
MultiObjective { objectives: Vec<ObjectiveFunction> },
PharmacophoreMatching { reference: PharmacophoreModel },
}
#[derive(Debug, Clone)]
pub struct ProteinStructure {
pub pdb_id: String,
pub active_site: Vec<usize>,
pub grid_box: GridBox,
}
#[derive(Debug, Clone)]
pub struct GridBox {
pub center: Vec3D,
pub dimensions: Vec3D,
pub spacing: f64,
}
#[derive(Debug, Clone)]
pub struct PharmacophoreModel {
pub features: Vec<PharmacophoreFeature>,
pub distance_constraints: Vec<DistanceConstraint>,
pub angle_constraints: Vec<AngleConstraint>,
}
#[derive(Debug, Clone)]
pub struct DistanceConstraint {
pub feature1: usize,
pub feature2: usize,
pub min_distance: f64,
pub max_distance: f64,
}
#[derive(Debug, Clone)]
pub struct AngleConstraint {
pub feature1: usize,
pub feature2: usize,
pub feature3: usize,
pub min_angle: f64,
pub max_angle: f64,
}
#[derive(Debug, Clone)]
pub enum ObjectiveFunction {
BindingAffinity { weight: f64 },
SyntheticAccessibility { weight: f64 },
ADMET {
property: ADMETProperty,
weight: f64,
},
Novelty {
reference_set: Vec<String>,
weight: f64,
},
Diversity { weight: f64 },
}
#[derive(Debug, Clone)]
pub enum ADMETProperty {
Absorption,
Distribution,
Metabolism,
Excretion,
Toxicity,
Solubility,
Permeability,
Stability,
}
#[derive(Debug, Clone)]
pub struct DesignConstraints {
pub max_mw: f64,
pub lipinski: bool,
pub veber: bool,
pub pains_filter: bool,
pub max_sa_score: f64,
pub min_qed: f64,
pub smarts_filters: Vec<String>,
}
#[derive(Debug, Clone)]
pub enum OptimizationStrategy {
FragmentGrowing { core: MolecularFragment },
FragmentLinking { fragments: Vec<MolecularFragment> },
FragmentHopping { scaffold: MolecularFragment },
DeNovo,
LeadOptimization { lead: String },
}
impl MolecularDesignOptimizer {
pub fn new(target_properties: TargetProperties, fragment_library: FragmentLibrary) -> Self {
Self {
target_properties,
fragment_library,
scoring_function: ScoringFunction::Additive {
weights: Self::default_weights(),
},
constraints: DesignConstraints::default(),
strategy: OptimizationStrategy::DeNovo,
}
}
fn default_weights() -> HashMap<String, f64> {
let mut weights = HashMap::new();
weights.insert("mw_penalty".to_string(), -0.1);
weights.insert("logp_penalty".to_string(), -0.2);
weights.insert("hbd_penalty".to_string(), -0.1);
weights.insert("hba_penalty".to_string(), -0.1);
weights.insert("rotatable_penalty".to_string(), -0.05);
weights.insert("tpsa_penalty".to_string(), -0.1);
weights.insert("fragment_score".to_string(), 1.0);
weights
}
pub fn with_scoring(mut self, scoring: ScoringFunction) -> Self {
self.scoring_function = scoring;
self
}
pub fn with_constraints(mut self, constraints: DesignConstraints) -> Self {
self.constraints = constraints;
self
}
pub fn with_strategy(mut self, strategy: OptimizationStrategy) -> Self {
self.strategy = strategy;
self
}
pub fn build_qubo(&self) -> Result<(Array2<f64>, HashMap<String, usize>), String> {
match &self.strategy {
OptimizationStrategy::FragmentGrowing { core } => {
self.build_fragment_growing_qubo(core)
}
OptimizationStrategy::DeNovo => self.build_de_novo_qubo(),
_ => Err("Strategy not yet implemented".to_string()),
}
}
fn build_fragment_growing_qubo(
&self,
core: &MolecularFragment,
) -> Result<(Array2<f64>, HashMap<String, usize>), String> {
let positions = core.attachment_points.len();
let fragments = self.fragment_library.fragments.len();
let n_vars = positions * fragments;
let mut qubo = Array2::zeros((n_vars, n_vars));
let mut var_map = HashMap::new();
for p in 0..positions {
for f in 0..fragments {
let var_name = format!("x_{f}_{p}");
var_map.insert(var_name, p * fragments + f);
}
}
self.add_fragment_scores(&mut qubo, &var_map, core)?;
self.add_property_constraints(&mut qubo, &var_map, core)?;
self.add_connection_compatibility(&mut qubo, &var_map, core)?;
self.add_uniqueness_constraints(&mut qubo, &var_map, positions, fragments)?;
Ok((qubo, var_map))
}
fn build_de_novo_qubo(&self) -> Result<(Array2<f64>, HashMap<String, usize>), String> {
let max_positions = 10; let fragments = self.fragment_library.fragments.len();
let position_vars = max_positions * fragments;
let connection_vars = max_positions * (max_positions - 1) / 2;
let n_vars = position_vars + connection_vars;
let mut qubo = Array2::zeros((n_vars, n_vars));
let mut var_map = HashMap::new();
for i in 0..max_positions {
for f in 0..fragments {
let var_name = format!("x_{f}_{i}");
var_map.insert(var_name, i * fragments + f);
}
}
let mut var_idx = position_vars;
for i in 0..max_positions {
for j in i + 1..max_positions {
let var_name = format!("y_{i}_{j}");
var_map.insert(var_name, var_idx);
var_idx += 1;
}
}
self.add_de_novo_objective(&mut qubo, &var_map, max_positions)?;
self.add_connectivity_constraints(&mut qubo, &var_map, max_positions)?;
self.add_global_property_constraints(&mut qubo, &var_map, max_positions)?;
Ok((qubo, var_map))
}
fn add_fragment_scores(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
core: &MolecularFragment,
) -> Result<(), String> {
let positions = core.attachment_points.len();
for p in 0..positions {
for f in 0..self.fragment_library.fragments.len() {
let var_name = format!("x_{f}_{p}");
if let Some(&var_idx) = var_map.get(&var_name) {
let score = self
.fragment_library
.fragment_scores
.get(&f)
.unwrap_or(&0.0);
let compatibility = self.compute_attachment_compatibility(
&core.attachment_points[p],
&self.fragment_library.fragments[f],
);
qubo[[var_idx, var_idx]] -= score * compatibility;
}
}
}
Ok(())
}
fn compute_attachment_compatibility(
&self,
attachment: &AttachmentPoint,
fragment: &MolecularFragment,
) -> f64 {
let compatible = fragment.attachment_points.iter().any(|frag_attach| {
attachment
.bond_types
.iter()
.any(|bt| frag_attach.bond_types.contains(bt))
});
if compatible {
1.0
} else {
0.0
}
}
fn add_property_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
core: &MolecularFragment,
) -> Result<(), String> {
let penalty = 100.0;
if let Some((min_mw, max_mw)) = self.target_properties.molecular_weight {
let core_mw = core.properties.mw_contribution;
for f in 0..self.fragment_library.fragments.len() {
let frag_mw = self.fragment_library.fragments[f]
.properties
.mw_contribution;
let total_mw = core_mw + frag_mw;
if total_mw < min_mw || total_mw > max_mw {
for p in 0..core.attachment_points.len() {
let var_name = format!("x_{f}_{p}");
if let Some(&var_idx) = var_map.get(&var_name) {
qubo[[var_idx, var_idx]] += penalty;
}
}
}
}
}
self.add_logp_constraints(qubo, var_map, core, penalty)?;
self.add_hbond_constraints(qubo, var_map, core, penalty)?;
Ok(())
}
fn add_logp_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
core: &MolecularFragment,
penalty: f64,
) -> Result<(), String> {
if let Some((min_logp, max_logp)) = self.target_properties.logp {
let core_logp = core.properties.logp_contribution;
for f in 0..self.fragment_library.fragments.len() {
let frag_logp = self.fragment_library.fragments[f]
.properties
.logp_contribution;
let total_logp = core_logp + frag_logp;
if total_logp < min_logp || total_logp > max_logp {
for p in 0..core.attachment_points.len() {
let var_name = format!("x_{f}_{p}");
if let Some(&var_idx) = var_map.get(&var_name) {
qubo[[var_idx, var_idx]] += penalty * 0.5;
}
}
}
}
}
Ok(())
}
fn add_hbond_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
core: &MolecularFragment,
penalty: f64,
) -> Result<(), String> {
if let Some((min_hbd, max_hbd)) = self.target_properties.hbd {
let core_hbd = core.properties.hbd_count;
for f in 0..self.fragment_library.fragments.len() {
let frag_hbd = self.fragment_library.fragments[f].properties.hbd_count;
let total_hbd = core_hbd + frag_hbd;
if total_hbd < min_hbd || total_hbd > max_hbd {
for p in 0..core.attachment_points.len() {
let var_name = format!("x_{f}_{p}");
if let Some(&var_idx) = var_map.get(&var_name) {
qubo[[var_idx, var_idx]] += penalty * 0.3;
}
}
}
}
}
Ok(())
}
fn add_connection_compatibility(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
core: &MolecularFragment,
) -> Result<(), String> {
let positions = core.attachment_points.len();
for p1 in 0..positions {
for p2 in p1 + 1..positions {
for f1 in 0..self.fragment_library.fragments.len() {
for f2 in 0..self.fragment_library.fragments.len() {
let var1 = format!("x_{f1}_{p1}");
let var2 = format!("x_{f2}_{p2}");
if let (Some(&idx1), Some(&idx2)) = (var_map.get(&var1), var_map.get(&var2))
{
if self
.fragment_library
.connection_rules
.forbidden_connections
.contains(&(f1, f2))
{
qubo[[idx1, idx2]] += 1000.0;
} else if let Some(&score) = self
.fragment_library
.connection_rules
.compatible_pairs
.get(&(f1, f2))
{
qubo[[idx1, idx2]] -= score;
}
}
}
}
}
}
Ok(())
}
fn add_uniqueness_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
positions: usize,
fragments: usize,
) -> Result<(), String> {
let penalty = 100.0;
for p in 0..positions {
for f1 in 0..fragments {
for f2 in f1 + 1..fragments {
let var1 = format!("x_{f1}_{p}");
let var2 = format!("x_{f2}_{p}");
if let (Some(&idx1), Some(&idx2)) = (var_map.get(&var1), var_map.get(&var2)) {
qubo[[idx1, idx2]] += penalty;
}
}
}
}
Ok(())
}
fn add_de_novo_objective(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
max_positions: usize,
) -> Result<(), String> {
for i in 0..max_positions {
for f in 0..self.fragment_library.fragments.len() {
let var_name = format!("x_{f}_{i}");
if let Some(&var_idx) = var_map.get(&var_name) {
let score = self
.fragment_library
.fragment_scores
.get(&f)
.unwrap_or(&0.0);
qubo[[var_idx, var_idx]] -= score;
if self.fragment_library.privileged_scaffolds.contains(&f) {
qubo[[var_idx, var_idx]] -= 2.0;
}
}
}
}
for i in 0..max_positions {
for j in i + 1..max_positions {
let conn_var = format!("y_{i}_{j}");
if let Some(&conn_idx) = var_map.get(&conn_var) {
qubo[[conn_idx, conn_idx]] += 0.1;
}
}
}
Ok(())
}
fn add_connectivity_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
max_positions: usize,
) -> Result<(), String> {
let penalty = 100.0;
for i in 0..max_positions {
for f in 0..self.fragment_library.fragments.len() {
let frag_var = format!("x_{f}_{i}");
if let Some(&frag_idx) = var_map.get(&frag_var) {
let mut _has_connection = false;
for j in 0..max_positions {
if i != j {
let conn_var = if i < j {
format!("y_{i}_{j}")
} else {
format!("y_{j}_{i}")
};
if let Some(&conn_idx) = var_map.get(&conn_var) {
qubo[[frag_idx, frag_idx]] += penalty;
qubo[[frag_idx, conn_idx]] -= penalty;
_has_connection = true;
}
}
}
}
}
}
self.add_connection_compatibility_de_novo(qubo, var_map, max_positions)?;
Ok(())
}
fn add_connection_compatibility_de_novo(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
max_positions: usize,
) -> Result<(), String> {
for i in 0..max_positions {
for j in i + 1..max_positions {
let conn_var = format!("y_{i}_{j}");
if let Some(&conn_idx) = var_map.get(&conn_var) {
for f1 in 0..self.fragment_library.fragments.len() {
for f2 in 0..self.fragment_library.fragments.len() {
let var1 = format!("x_{f1}_{i}");
let var2 = format!("x_{f2}_{j}");
if let (Some(&idx1), Some(&idx2)) =
(var_map.get(&var1), var_map.get(&var2))
{
if self
.fragment_library
.connection_rules
.forbidden_connections
.contains(&(f1, f2))
{
qubo[[conn_idx, idx1]] += 50.0;
qubo[[conn_idx, idx2]] += 50.0;
}
}
}
}
}
}
}
Ok(())
}
fn add_global_property_constraints(
&self,
qubo: &mut Array2<f64>,
var_map: &HashMap<String, usize>,
max_positions: usize,
) -> Result<(), String> {
let penalty = 10.0;
if let Some((_min_mw, max_mw)) = self.target_properties.molecular_weight {
for i in 0..max_positions {
for f in 0..self.fragment_library.fragments.len() {
let var_name = format!("x_{f}_{i}");
if let Some(&var_idx) = var_map.get(&var_name) {
let mw = self.fragment_library.fragments[f]
.properties
.mw_contribution;
if mw > max_mw {
qubo[[var_idx, var_idx]] += penalty * 10.0;
}
let mw_penalty = if mw > max_mw / max_positions as f64 {
(mw - max_mw / max_positions as f64) * penalty
} else {
0.0
};
qubo[[var_idx, var_idx]] += mw_penalty;
}
}
}
}
Ok(())
}
pub fn decode_solution(
&self,
solution: &HashMap<String, bool>,
) -> Result<DesignedMolecule, String> {
match &self.strategy {
OptimizationStrategy::FragmentGrowing { core } => {
self.decode_fragment_growing(solution, core)
}
OptimizationStrategy::DeNovo => self.decode_de_novo(solution),
_ => Err("Decoding not implemented for this strategy".to_string()),
}
}
fn decode_fragment_growing(
&self,
solution: &HashMap<String, bool>,
core: &MolecularFragment,
) -> Result<DesignedMolecule, String> {
let mut fragments = vec![core.clone()];
let mut connections = Vec::new();
for (var_name, &value) in solution {
if value && var_name.starts_with("x_") {
let parts: Vec<&str> = var_name[2..].split('_').collect();
if parts.len() == 2 {
let frag_idx: usize = parts[0].parse().unwrap_or(0);
let pos_idx: usize = parts[1].parse().unwrap_or(0);
if frag_idx < self.fragment_library.fragments.len() {
fragments.push(self.fragment_library.fragments[frag_idx].clone());
connections.push(Connection {
from_fragment: 0,
from_attachment: pos_idx,
to_fragment: fragments.len() - 1,
to_attachment: 0,
bond_type: BondType::Single,
});
}
}
}
}
let properties = self.calculate_properties(&fragments);
let score = self.calculate_score(&fragments, &connections);
Ok(DesignedMolecule {
fragments,
connections,
properties,
score,
smiles: None, })
}
fn decode_de_novo(&self, solution: &HashMap<String, bool>) -> Result<DesignedMolecule, String> {
let mut fragment_positions: HashMap<usize, usize> = HashMap::new();
let mut connections = Vec::new();
for (var_name, &value) in solution {
if value && var_name.starts_with("x_") {
let parts: Vec<&str> = var_name[2..].split('_').collect();
if parts.len() == 2 {
let frag_idx: usize = parts[0].parse().unwrap_or(0);
let pos_idx: usize = parts[1].parse().unwrap_or(0);
fragment_positions.insert(pos_idx, frag_idx);
}
}
}
for (var_name, &value) in solution {
if value && var_name.starts_with("y_") {
let parts: Vec<&str> = var_name[2..].split('_').collect();
if parts.len() == 2 {
let pos1: usize = parts[0].parse().unwrap_or(0);
let pos2: usize = parts[1].parse().unwrap_or(0);
if fragment_positions.contains_key(&pos1)
&& fragment_positions.contains_key(&pos2)
{
connections.push(Connection {
from_fragment: pos1,
from_attachment: 0,
to_fragment: pos2,
to_attachment: 0,
bond_type: BondType::Single,
});
}
}
}
}
let fragments: Vec<_> = fragment_positions
.iter()
.map(|(_, &frag_idx)| self.fragment_library.fragments[frag_idx].clone())
.collect();
Ok(DesignedMolecule {
fragments,
connections,
properties: MolecularProperties::default(),
score: 0.0,
smiles: None,
})
}
fn calculate_properties(&self, fragments: &[MolecularFragment]) -> MolecularProperties {
let mut props = MolecularProperties::default();
for fragment in fragments {
props.molecular_weight += fragment.properties.mw_contribution;
props.logp += fragment.properties.logp_contribution;
props.hbd += fragment.properties.hbd_count;
props.hba += fragment.properties.hba_count;
props.rotatable_bonds += fragment.properties.rotatable_count;
props.tpsa += fragment.properties.tpsa_contribution;
}
props
}
fn calculate_score(&self, fragments: &[MolecularFragment], _connections: &[Connection]) -> f64 {
match &self.scoring_function {
ScoringFunction::Additive { weights } => {
let mut score = 0.0;
let props = self.calculate_properties(fragments);
if let Some((min, max)) = self.target_properties.molecular_weight {
if props.molecular_weight < min || props.molecular_weight > max {
score += weights.get("mw_penalty").unwrap_or(&0.0)
* (props.molecular_weight - f64::midpoint(min, max)).abs();
}
}
for fragment in fragments {
if let Some(&frag_score) =
self.fragment_library.fragment_scores.get(&fragment.id)
{
score += weights.get("fragment_score").unwrap_or(&1.0) * frag_score;
}
}
score
}
_ => 0.0,
}
}
}
impl Default for DesignConstraints {
fn default() -> Self {
Self {
max_mw: 500.0,
lipinski: true,
veber: true,
pains_filter: true,
max_sa_score: 6.0,
min_qed: 0.3,
smarts_filters: Vec::new(),
}
}
}
#[derive(Debug, Clone)]
pub struct Connection {
pub from_fragment: usize,
pub from_attachment: usize,
pub to_fragment: usize,
pub to_attachment: usize,
pub bond_type: BondType,
}
#[derive(Debug, Clone)]
pub struct DesignedMolecule {
pub fragments: Vec<MolecularFragment>,
pub connections: Vec<Connection>,
pub properties: MolecularProperties,
pub score: f64,
pub smiles: Option<String>,
}
#[derive(Debug, Clone, Default)]
pub struct MolecularProperties {
pub molecular_weight: f64,
pub logp: f64,
pub logs: f64,
pub hbd: usize,
pub hba: usize,
pub rotatable_bonds: usize,
pub tpsa: f64,
pub sa_score: f64,
pub qed_score: f64,
}
pub struct LeadOptimizer {
lead_compound: String,
objectives: Vec<OptimizationObjective>,
modifications: AllowedModifications,
admet_predictor: ADMETPredictor,
}
#[derive(Debug, Clone)]
pub enum OptimizationObjective {
Potency { target_ic50: f64 },
Selectivity { off_targets: Vec<String> },
ADMET { properties: Vec<ADMETProperty> },
ReduceMW { target_mw: f64 },
Solubility { target_logs: f64 },
}
#[derive(Debug, Clone)]
pub struct AllowedModifications {
pub bioisosteres: HashMap<String, Vec<String>>,
pub r_groups: Vec<RGroupModification>,
pub scaffold_hopping: bool,
pub max_similarity: f64,
}
#[derive(Debug, Clone)]
pub struct RGroupModification {
pub position: String,
pub substituents: Vec<String>,
pub preferred_properties: HashMap<String, f64>,
}
#[derive(Debug, Clone)]
pub struct ADMETPredictor {
pub models: HashMap<ADMETProperty, PredictionModel>,
pub experimental_data: HashMap<String, ADMETProfile>,
}
#[derive(Debug, Clone)]
pub struct PredictionModel {
pub model_type: ModelType,
pub parameters: Vec<f64>,
pub accuracy: f64,
}
#[derive(Debug, Clone)]
pub enum ModelType {
RandomForest,
NeuralNetwork,
SVM,
PhysicsBased,
}
#[derive(Debug, Clone)]
pub struct ADMETProfile {
pub absorption: AbsorptionProfile,
pub distribution: DistributionProfile,
pub metabolism: MetabolismProfile,
pub excretion: ExcretionProfile,
pub toxicity: ToxicityProfile,
}
#[derive(Debug, Clone)]
pub struct AbsorptionProfile {
pub caco2_permeability: f64,
pub pgp_substrate: bool,
pub pgp_inhibitor: bool,
pub oral_bioavailability: f64,
}
#[derive(Debug, Clone)]
pub struct DistributionProfile {
pub plasma_protein_binding: f64,
pub vd: f64, pub bbb_penetration: bool,
pub tissue_distribution: HashMap<String, f64>,
}
#[derive(Debug, Clone)]
pub struct MetabolismProfile {
pub cyp_substrate: HashMap<String, bool>,
pub cyp_inhibitor: HashMap<String, bool>,
pub metabolic_stability: f64,
pub major_metabolites: Vec<String>,
}
#[derive(Debug, Clone)]
pub struct ExcretionProfile {
pub renal_clearance: f64,
pub hepatic_clearance: f64,
pub half_life: f64,
}
#[derive(Debug, Clone)]
pub struct ToxicityProfile {
pub ld50: f64,
pub mutagenicity: bool,
pub hepatotoxicity: bool,
pub cardiotoxicity: bool,
pub herg_inhibition: f64,
}
pub struct VirtualScreeningEngine {
library: CompoundLibrary,
protocol: ScreeningProtocol,
hit_criteria: HitSelectionCriteria,
}
#[derive(Debug, Clone)]
pub struct CompoundLibrary {
pub source: LibrarySource,
pub size: usize,
pub diversity: DiversityMetrics,
pub filters: Vec<LibraryFilter>,
}
#[derive(Debug, Clone)]
pub enum LibrarySource {
Commercial { vendor: String },
FDAApproved,
NaturalProducts,
Fragments,
Virtual { rules: Vec<EnumerationRule> },
}
#[derive(Debug, Clone)]
pub struct DiversityMetrics {
pub scaffold_diversity: f64,
pub property_coverage: f64,
pub pharmacophore_coverage: f64,
}
#[derive(Debug, Clone)]
pub enum LibraryFilter {
MolecularWeight { min: f64, max: f64 },
Lipinski,
PAINS,
SMARTS { pattern: String, exclude: bool },
}
#[derive(Debug, Clone)]
pub struct EnumerationRule {
pub scaffold: String,
pub variation_points: Vec<VariationPoint>,
pub strategy: EnumerationStrategy,
}
#[derive(Debug, Clone)]
pub struct VariationPoint {
pub position: String,
pub building_blocks: Vec<String>,
}
#[derive(Debug, Clone)]
pub enum EnumerationStrategy {
Exhaustive,
RandomSampling { size: usize },
Focused { criteria: Vec<String> },
}
#[derive(Debug, Clone)]
pub enum ScreeningProtocol {
StructureBased {
receptor: ProteinStructure,
docking_program: DockingProgram,
scoring_function: String,
},
LigandBased {
reference_ligands: Vec<String>,
similarity_metric: SimilarityMetric,
threshold: f64,
},
PharmacaophoreBased {
pharmacophore: PharmacophoreModel,
tolerance: f64,
},
MachineLearning {
model: String,
features: Vec<String>,
},
}
#[derive(Debug, Clone)]
pub enum DockingProgram {
AutoDock,
Glide,
FlexX,
GOLD,
Vina,
}
#[derive(Debug, Clone)]
pub enum SimilarityMetric {
Tanimoto,
Dice,
Cosine,
Euclidean,
}
#[derive(Debug, Clone)]
pub struct HitSelectionCriteria {
pub score_threshold: f64,
pub top_n: Option<usize>,
pub diversity_selection: bool,
pub manual_inspection: bool,
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_molecular_design() {
let target = TargetProperties {
molecular_weight: Some((300.0, 500.0)),
logp: Some((2.0, 5.0)),
logs: None,
hbd: Some((0, 5)),
hba: Some((0, 10)),
rotatable_bonds: Some((0, 10)),
tpsa: Some((40.0, 140.0)),
custom_descriptors: HashMap::new(),
};
let mut fragments = Vec::new();
for i in 0..5 {
fragments.push(MolecularFragment {
id: i,
smiles: format!("C{}O", "C".repeat(i)),
attachment_points: vec![AttachmentPoint {
atom_idx: 0,
bond_types: vec![BondType::Single],
direction: Vec3D {
x: 1.0,
y: 0.0,
z: 0.0,
},
}],
properties: FragmentProperties {
mw_contribution: (i as f64).mul_add(14.0, 50.0),
logp_contribution: (i as f64).mul_add(0.5, 0.5),
hbd_count: 1,
hba_count: 1,
rotatable_count: i,
tpsa_contribution: 20.0,
},
pharmacophores: vec![],
});
}
let library = FragmentLibrary {
fragments,
connection_rules: ConnectionRules {
compatible_pairs: HashMap::new(),
forbidden_connections: HashSet::new(),
reaction_templates: vec![],
},
fragment_scores: HashMap::new(),
privileged_scaffolds: vec![],
};
let optimizer = MolecularDesignOptimizer::new(target, library);
let mut result = optimizer.build_qubo();
assert!(result.is_ok());
}
#[test]
fn test_fragment_growing() {
let core = MolecularFragment {
id: 999,
smiles: "c1ccccc1".to_string(),
attachment_points: vec![
AttachmentPoint {
atom_idx: 0,
bond_types: vec![BondType::Single, BondType::Aromatic],
direction: Vec3D {
x: 1.0,
y: 0.0,
z: 0.0,
},
},
AttachmentPoint {
atom_idx: 3,
bond_types: vec![BondType::Single, BondType::Aromatic],
direction: Vec3D {
x: -1.0,
y: 0.0,
z: 0.0,
},
},
],
properties: FragmentProperties {
mw_contribution: 78.0,
logp_contribution: 2.0,
hbd_count: 0,
hba_count: 0,
rotatable_count: 0,
tpsa_contribution: 0.0,
},
pharmacophores: vec![PharmacophoreFeature {
feature_type: PharmacophoreType::Aromatic,
position: Vec3D {
x: 0.0,
y: 0.0,
z: 0.0,
},
tolerance: 1.0,
}],
};
let target = TargetProperties {
molecular_weight: Some((200.0, 400.0)),
logp: Some((1.0, 4.0)),
logs: None,
hbd: Some((0, 3)),
hba: Some((0, 6)),
rotatable_bonds: None,
tpsa: None,
custom_descriptors: HashMap::new(),
};
let library = FragmentLibrary {
fragments: vec![MolecularFragment {
id: 0,
smiles: "CCO".to_string(),
attachment_points: vec![AttachmentPoint {
atom_idx: 0,
bond_types: vec![BondType::Single],
direction: Vec3D {
x: 1.0,
y: 0.0,
z: 0.0,
},
}],
properties: FragmentProperties {
mw_contribution: 45.0,
logp_contribution: 0.2,
hbd_count: 1,
hba_count: 1,
rotatable_count: 1,
tpsa_contribution: 20.0,
},
pharmacophores: vec![],
}],
connection_rules: ConnectionRules {
compatible_pairs: HashMap::new(),
forbidden_connections: HashSet::new(),
reaction_templates: vec![],
},
fragment_scores: {
let mut scores = HashMap::new();
scores.insert(0, 1.0);
scores
},
privileged_scaffolds: vec![],
};
let optimizer = MolecularDesignOptimizer::new(target, library)
.with_strategy(OptimizationStrategy::FragmentGrowing { core });
let mut result = optimizer.build_qubo();
assert!(result.is_ok());
let (_qubo, var_map) = result.expect("QUBO building should succeed after is_ok check");
assert!(!var_map.is_empty());
}
}