💍 The Bio-Active Hormone Lab: Peptide Drug Discovery 🧬¶

Objective: Learn how to model real-world therapeutic macrocycles like Oxytocin and Cyclosporine A using physics-based generation.

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🌟 What is a Macrocycle?¶

In drug discovery, a macrocycle is a molecule containing a large ring (usually 12 or more atoms). Unlike linear peptides which are floppy and easily destroyed by the body, macrocycles are pre-organized into specific shapes. This makes them:

1. Potent: They fit into their target protein like a perfect key.
2. Stable: Their circular structure protects them from being chopped up by enzymes.

In this lab, we use synth-pdb to find the "Native" physical conformation of these therapeutic giants.

In [ ]:

# @title Setup & Installation { display-mode: "form" }
import os
import sys
from pathlib import Path

try:
    current_path = Path(".").resolve()
    repo_root = current_path.parent.parent
    if (repo_root / "synth_pdb").exists():
        if str(repo_root) not in sys.path:
            sys.path.insert(0, str(repo_root))
            print(f"📌 Added local library to path: {repo_root}")
except Exception:
    pass

if 'google.colab' in str(get_ipython()):
    if not os.path.exists("installed.marker"):
        print("Running on Google Colab. Installing dependencies...")
        get_ipython().run_line_magic('pip', 'install synth-pdb py3Dmol biotite numpy matplotlib')

        with open("installed.marker", "w") as f:
            f.write("done")

        print("🔄 Installation complete. KERNEL RESTARTING AUTOMATICALLY...")
        os.kill(os.getpid(), 9)
    else:
        print("✅ Dependencies Ready.")
else:
    import synth_pdb
    print(f"✅ Running locally. Using synth-pdb version: {synth_pdb.__version__}")

# @title Setup & Installation { display-mode: "form" } import os import sys from pathlib import Path try: current_path = Path(".").resolve() repo_root = current_path.parent.parent if (repo_root / "synth_pdb").exists(): if str(repo_root) not in sys.path: sys.path.insert(0, str(repo_root)) print(f"📌 Added local library to path: {repo_root}") except Exception: pass if 'google.colab' in str(get_ipython()): if not os.path.exists("installed.marker"): print("Running on Google Colab. Installing dependencies...") get_ipython().run_line_magic('pip', 'install synth-pdb py3Dmol biotite numpy matplotlib') with open("installed.marker", "w") as f: f.write("done") print("🔄 Installation complete. KERNEL RESTARTING AUTOMATICALLY...") os.kill(os.getpid(), 9) else: print("✅ Dependencies Ready.") else: import synth_pdb print(f"✅ Running locally. Using synth-pdb version: {synth_pdb.__version__}")

In [ ]:

import py3Dmol

from synth_pdb.batch_generator import BatchedGenerator
from synth_pdb.generator import generate_pdb_content

print("Molecular Pharmacopoeia: ONLINE 🧪")

import py3Dmol from synth_pdb.batch_generator import BatchedGenerator from synth_pdb.generator import generate_pdb_content print("Molecular Pharmacopoeia: ONLINE 🧪")

1. Case Study: Oxytocin (The Disulfide Loop)¶

Oxytocin is a 9-residue peptide hormone. It is held in its active shape by a disulfide bridge between its first and sixth residues (Cys1 and Cys6).

The Challenge: To close a disulfide loop, the two Sulfur atoms must come within ~2.0Å of each other. In a random linear chain, this is nearly impossible. We use physics-based minimization to "pull" the ring shut.

In [ ]:

# Sequence: CYS-TYR-ILE-GLN-ASN-CYS-PRO-LEU-GLY
oxytocin_seq = "CYS-TYR-ILE-GLN-ASN-CYS-PRO-LEU-GLY"

print("💍 Synthesizing Oxytocin with Disulfide Closure...")

# We generate the structure and enable minimization to resolve the loop
oxy_pdb = generate_pdb_content(
    sequence_str=oxytocin_seq,
    minimize_energy=True,
    cap_termini=True
)

print("✅ Synthesis Complete.")

# Sequence: CYS-TYR-ILE-GLN-ASN-CYS-PRO-LEU-GLY oxytocin_seq = "CYS-TYR-ILE-GLN-ASN-CYS-PRO-LEU-GLY" print("💍 Synthesizing Oxytocin with Disulfide Closure...") # We generate the structure and enable minimization to resolve the loop oxy_pdb = generate_pdb_content( sequence_str=oxytocin_seq, minimize_energy=True, cap_termini=True ) print("✅ Synthesis Complete.")

In [ ]:

view = py3Dmol.view(width=800, height=500)
view.setBackgroundColor('#fdfdfd')
view.addModel(oxy_pdb, 'pdb')

# 1. Style the main backbone with ribbons
view.setStyle({'model': -1}, {'cartoon': {'color': '#a29bfe', 'opacity': 0.9}})

# 2. STYLE THE BRIDGE: Show Cys side chains as thick sticks
# Use addStyle to layer the Cys representation without breaking connectivity.
view.addStyle({'resn': 'CYS'}, {'stick': {'radius': 0.2, 'color': '#fdcb6e'}})

# 3. Highlight the Sulfur atoms as spheres for prominence
view.addStyle({'resn': 'CYS', 'atom': 'SG'}, {'sphere': {'radius': 0.4, 'color': '#fdcb6e'}})
view.addLabel("Disulfide Bridge", {'backgroundColor': '#e17055', 'fontColor': 'white'}, {'resn': 'CYS', 'atom': 'SG'})

view.zoomTo()
view.center()
view.show()

print("Educational Insight: Note how 'Cys1' and 'Cys6' residues are forced into proximity to satisfy the disulfide geometry.")

view = py3Dmol.view(width=800, height=500) view.setBackgroundColor('#fdfdfd') view.addModel(oxy_pdb, 'pdb') # 1. Style the main backbone with ribbons view.setStyle({'model': -1}, {'cartoon': {'color': '#a29bfe', 'opacity': 0.9}}) # 2. STYLE THE BRIDGE: Show Cys side chains as thick sticks # Use addStyle to layer the Cys representation without breaking connectivity. view.addStyle({'resn': 'CYS'}, {'stick': {'radius': 0.2, 'color': '#fdcb6e'}}) # 3. Highlight the Sulfur atoms as spheres for prominence view.addStyle({'resn': 'CYS', 'atom': 'SG'}, {'sphere': {'radius': 0.4, 'color': '#fdcb6e'}}) view.addLabel("Disulfide Bridge", {'backgroundColor': '#e17055', 'fontColor': 'white'}, {'resn': 'CYS', 'atom': 'SG'}) view.zoomTo() view.center() view.show() print("Educational Insight: Note how 'Cys1' and 'Cys6' residues are forced into proximity to satisfy the disulfide geometry.")

2. Case Study: Cyclosporine A (D-Amino Acid Macrocycle)¶

Cyclosporine A is a powerhouse drug used to prevent organ transplant rejection. It is an 11-mer cyclic peptide that features multiple D-amino acids.

The Challenge: Head-to-tail cyclization requires the first residue to bond with the last residue. D-amino acids (mirror images of normal L-amino acids) are used to prevent the cycle from being broken down by the body.

In [ ]:

# We use a representative 11-mer with D-Alanine to show the cyclic capability
cyclosporine_proxy = "ALA-VAL-LEU-ILE-D-ALA-GLY-MET-PHE-PRO-LEU-VAL"

print("💍 Cyclizing 11-mer with D-amino acid integration...")

cyc_pdb = generate_pdb_content(
    sequence_str=cyclosporine_proxy,
    cyclic=True,       # Enable head-to-tail closure
    minimize_energy=True,
    cap_termini=False
)

print("✅ Cyclic Macrocycle Generated.")

# We use a representative 11-mer with D-Alanine to show the cyclic capability cyclosporine_proxy = "ALA-VAL-LEU-ILE-D-ALA-GLY-MET-PHE-PRO-LEU-VAL" print("💍 Cyclizing 11-mer with D-amino acid integration...") cyc_pdb = generate_pdb_content( sequence_str=cyclosporine_proxy, cyclic=True, # Enable head-to-tail closure minimize_energy=True, cap_termini=False ) print("✅ Cyclic Macrocycle Generated.")

In [ ]:

import py3Dmol

view = py3Dmol.view(width=800, height=500)
view.setBackgroundColor('#fdfdfd')
view.addModel(cyc_pdb, 'pdb')

# Style the Cyclic Backbone with high-contrast colors
view.setStyle({'model': -1}, {'cartoon': {'color': '#00b894', 'opacity': 0.8}})
view.setStyle({'model': -1}, {'stick': {'radius': 0.2, 'color': '#55efc4'}})

# Highlight the D-Alanine residue in Intense Red
view.setStyle({'resn': 'D-ALA'}, {'stick': {'radius': 0.5, 'color': '#d63031'}})
view.addLabel("D-Alanine Hinge", {'backgroundColor': '#d63031', 'fontColor': 'white'}, {'resn': 'D-ALA'})

view.zoomTo()
view.center()
view.show()

print("Educational Insight: The D-Alanine (red) provides a 'hinge' that helps stabilize the circular backbone.")

import py3Dmol view = py3Dmol.view(width=800, height=500) view.setBackgroundColor('#fdfdfd') view.addModel(cyc_pdb, 'pdb') # Style the Cyclic Backbone with high-contrast colors view.setStyle({'model': -1}, {'cartoon': {'color': '#00b894', 'opacity': 0.8}}) view.setStyle({'model': -1}, {'stick': {'radius': 0.2, 'color': '#55efc4'}}) # Highlight the D-Alanine residue in Intense Red view.setStyle({'resn': 'D-ALA'}, {'stick': {'radius': 0.5, 'color': '#d63031'}}) view.addLabel("D-Alanine Hinge", {'backgroundColor': '#d63031', 'fontColor': 'white'}, {'resn': 'D-ALA'}) view.zoomTo() view.center() view.show() print("Educational Insight: The D-Alanine (red) provides a 'hinge' that helps stabilize the circular backbone.")

3. Finding the "Native" State (The Low-Energy Ensemble)¶

Macrocycles are highly constrained, but they can still "breathe". In drug discovery, we want the structure that is the most stable (lowest energy). We use Batched Generation to sample many possibilities and find the global minimum.

In [ ]:

n_peptides = 20
print(f"🔥 Sampling {n_peptides} possible conformations for our therapeutic lead...")

generator = BatchedGenerator(oxytocin_seq, n_batch=n_peptides, full_atom=True)
batch = generator.generate_batch(drift=10.0)

print("✅ Ensemble Generated.")
print("Educational Note: In a real lab, you would run MD simulations on these samples to find the one with the best binding affinity.")

n_peptides = 20 print(f"🔥 Sampling {n_peptides} possible conformations for our therapeutic lead...") generator = BatchedGenerator(oxytocin_seq, n_batch=n_peptides, full_atom=True) batch = generator.generate_batch(drift=10.0) print("✅ Ensemble Generated.") print("Educational Note: In a real lab, you would run MD simulations on these samples to find the one with the best binding affinity.")

In [ ]:

import py3Dmol

view = py3Dmol.view(width=800, height=450)
view.setBackgroundColor('#fdfdfd')

# Qualitative palette for the ensemble
colors = ['#6c5ce7', '#e17055', '#00b894', '#0984e3', '#fdcb6e']

for i in range(min(5, n_peptides)):
    view.addModel(batch.to_pdb(i), 'pdb')
    # Use thin "sticks" for an ultra-premium look across the ensemble
    view.setStyle({'model': i}, {'stick': {'radius': 0.15, 'color': colors[i % len(colors)], 'opacity': 0.8}})
    # Use addStyle for the spheres so they don't erase the side-chain sticks
    view.addStyle({'model': i, 'atom': 'SG'}, {'sphere': {'radius': 0.4, 'color': '#fab1a0'}})

view.zoomTo()
view.center()
view.show()

import py3Dmol view = py3Dmol.view(width=800, height=450) view.setBackgroundColor('#fdfdfd') # Qualitative palette for the ensemble colors = ['#6c5ce7', '#e17055', '#00b894', '#0984e3', '#fdcb6e'] for i in range(min(5, n_peptides)): view.addModel(batch.to_pdb(i), 'pdb') # Use thin "sticks" for an ultra-premium look across the ensemble view.setStyle({'model': i}, {'stick': {'radius': 0.15, 'color': colors[i % len(colors)], 'opacity': 0.8}}) # Use addStyle for the spheres so they don't erase the side-chain sticks view.addStyle({'model': i, 'atom': 'SG'}, {'sphere': {'radius': 0.4, 'color': '#fab1a0'}}) view.zoomTo() view.center() view.show()

🏆 Experiment for the User¶

Try replacing PRO in the macrocycle with D-PRO and see if the ring closure becomes easier or harder. 🧪

The molecules are yours to discover. 🧪💍🧬