Path A - Module 54: Final Project: From Sequence to Analysis

Welcome to the end of your odyssey, Master. You have spent 49 modules learning the pieces of the puzzle. Now, you will put them all together to complete a professional project: The Design of an Amyloid-Beta Intercalator.

Your Final Mission

You are given a target (the Amyloid-Beta fibril) and a candidate sequence (KLVFF). You must transform this information into a fully characterized, simulation-ready complex.

Step 1: Target Preparation

Load the fibril, audit it, and repair it. Make sure it is physically sound.

import molsysmt as msm

# 1. Load and Audit
fibril = msm.convert('pdb:2BEG', to_form='molsysmt.MolSys')
msm.build.add_missing_heavy_atoms(fibril)
msm.build.add_missing_hydrogens(fibril)
print("Target prepared and repaired.")

Step 2: Therapeutic Synthesis

Synthesize the KLVFF peptide with appropriate cappings and initial conformation.

# 2. Build the peptide
peptide = msm.build.build_peptide('KLVFF', n_terminal='ACE', c_terminal='NME', 
                                   configuration='beta-strand')
msm.build.add_missing_hydrogens(peptide)
print("Therapeutic peptide synthesized.")

Step 3: Systems Assembly & Solvation

Join both systems and put them in a realistic environment.

# 3. Merge and Solvate
complex = msm.merge([fibril, peptide])
final_complex = msm.build.solvate(complex, box_shape='cubic', clearance='1.0 nm', 
                            ionic_strength='150 mM')
print(f"Complex assembled and solvated with {msm.get(final_complex, element='system', n_atoms=True)} atoms.")

Step 4: Physics Relaxation

Relax the system to ensure there are no clashes.

# 4. Energy Minimization
msm.molecular_mechanics.potential_energy_minimization(final_complex)
print("Energy relaxation completed.")

Step 5: Binding Characterization

Prove that your design works by measuring the interaction.

# 5. Buried Area and H-Bonds
buried = msm.physchem.get_area_buried(final_complex, selection='molecule_type=="peptide"', 
                                      selection_2='molecule_type=="protein"')

hbonds = msm.hbonds.get_hbonds(final_complex, selection='molecule_type=="peptide"', 
                               selection_2='molecule_type=="protein"')

print(f"FINAL REPORT:")
print(f" - Lost Surface Area (Buried): {buried}")
print(f" - Number of Stabilizing H-Bonds: {len(hbonds)}")

Final Words

You have completed the Path of the Alzheimer’s Architect. You have the skills to model, design, and simulate complex molecular systems using the most powerful framework in Computational Biology.

The MolSysMT Mastery is yours.