Preparing Cyclic Peptides and Aligning them to a Reference Structure

Tutorial Created with Software Release: 2026-2

Topics: Biologics Drug Discovery, Peptide Design

Products Used: BioLuminate

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Tutorial Content

1. Introduction
2. Creating Projects and Importing Structures
3. Preparing Cyclic Peptides
4. Aligning Cyclic Peptides to a Reference Conformation
5. Conclusion and References
6. Glossary of Terms

1. Introduction

Cyclic peptides are a versatile class of molecules in modern drug discovery, filling the gap between small molecule drugs and larger biologics. Unlike proteins, cyclic peptides are relatively small, structurally constrained, and lack complex folding behavior. Protein preparation workflows often impose assumptions about protonation, hydrogen bonding, and flexibility that are not appropriate for these systems. In contrast, small-molecule preparation methods more accurately capture their chemical features by enumerating protonation states, stereochemistry, and optimized geometries. This directly impacts downstream modeling, as treating cyclic peptides as ligand-like entities leads to more reliable docking poses, scoring, and binding affinity predictions.

Many downstream computational methods require a target-bound pose for the ligand. In the absence of experimental information, you can obtain a pose using docking tools like Glide or MacroDock. When a validated structure for a closely related ligand is available (either for a macrocycle from the same series or a linear peptide in a cyclizable conformation), using ligand alignment can provide a better starting point, especially for methods like free energy perturbation (FEP). However, with their many rotatable bonds and cyclization-induced strain, macrocycles pose a challenge to ligand alignment approaches designed for small molecules. It is important to note that traditional rigid-body alignment via the Superposition panel is generally insufficient , since two macrocycle conformations can differ substantially. Alignment with Glide-MCS requires adequate sampling of the macrocyclic ring, and some rings are difficult to sample. This can limit the quality of the resulting alignment.

This tutorial uses the PCSK9 inhibitor peptides reported in this publication. In this tutorial, you will learn how to configure LigPrep settings appropriate for cyclic peptides, and understand the best practices that ensure reliable prepared structures for subsequent modeling tasks such as docking, conformational sampling, and FEP+ calculations. Finally, you will align several of the cyclic peptides from the series to an experimental reference structure.

2. Creating Projects and Importing Structures

3. Preparing Cyclic Peptides

When preparing cyclic peptides for modeling applications such as docking or FEP+, we recommend using the LigPrep panel over the Protein Preparation Workflow panel as cyclic peptides are better treated as discrete organic molecules for the following reasons:

• Protein Preparation Workflow relies on the Chemical Component Dictionary (CCD) and standard residue templates, which may fail to correctly assign bond orders, formal charges, or atom types for the non-standard amino acids, sidechain bridges, and non-natural linkers commonly found in cyclic peptides.
• For protonation state assignments, LigPrep uses Epik, which predicts pKa based on substructure rules trained on small-molecule data, a method far more appropriate for isolated peptides than PROPKA used in Protein Preparation Workflow which is parameterized for standard amino acids.
• Unlike the Protein Preparation Workflow, LigPrep can enumerate stereoisomers.
• LigPrep allows unrestrained minimization of cyclic peptides as ligand-like entities. In contrast, the Protein Preparation Workflow applies restrained minimization, which is suitable for refining experimental crystal structures but not for computationally built cyclic peptides which may have significant strain.

Optional: Assigning residue names to prepared cyclic peptides

Cyclic peptides often need their residues correctly identified and named before they can be used in downstream modeling (FEP+). This can be achieved through Protein Preparation Workflow which works well for most cyclic peptides composed of standard or well-characterized non-standard amino acids. In practice, it’s good to always double-check the resulting residue names, bond orders, and formal charges against the expected sequence before proceeding.

To assign residue names to the prepared cyclic peptides, you may follow these steps:

• Load the prepared structure(s) into the Protein Preparation Workflow panel.
• Make sure Preprocess is toggled-on.
• Click More Options under Preprocess.
• Uncheck all other options except Assign bond orders: Reassign all (CCD).
• Toggle-off Optimize H-bond Assignments and Minimize and Delete Waters
• Give a suitable Job name and run the job.

The following interactive tutorial guides you how to prepare a cyclic peptide using the LigPrep panel.

4. Aligning Cyclic Peptides to a Reference Conformation

In this section, you will align the cyclic peptide you prepared in the previous section to the bioactive conformation of a closely related peptide for which an experimental target-bound structure is available.

The structure resulting from LigPrep is a low-energy conformation, but it is very likely not the one your ligand would adopt when binding to the target. Docking software like Glide or MacroDock can be helpful to identify bound poses, especially when no reference experimental structure is available. However, if a validated structure of a closely related ligand is available, aligning the ligands to this structure has several advantages: First, using alignment can lower computational costs because it does not require extensive conformational sampling. The second advantage is that good ligand alignment can lower the error for subsequent FEP+ calculations, by making sure that the initial positions of non-perturbed atoms align as closely as possible.

Unfortunately, most flexible ligand alignment algorithms developed for small molecules struggle with aligning macrocycles, as the strain induced by deforming the cyclic backbone needs to be carefully balanced with the RMSD during alignment. For this purpose, the ligand alignment panel provides an explicit option for aligning macrocycles.

The following interactive tutorial guides you through aligning the ligand you prepared in the previous section and a few additional ligands from the same series to an experimental reference structure for a very similar macrocycle ligand.

Customizing the alignment

When you enable the macrocycle option for the ligand alignment panel, the backend used for the job switches to the tug_align.py script from the Schrödinger suite. If you find that results from using tug_align with the default parameters are not satisfactory for your system, you can try calling tug_align.py from the command line with the following options:

• Use the -receptor_structure flag to only accept aligned poses if they have no clashes with the target receptor. This can be helpful when working with deeper, more rigid pockets.
• The script tries to automatically determine the shared substructure to use for alignment, but if you want to place the focus on a particular part of the ligand, you can provide a SMARTS pattern defining the common core. This option can be particularly helpful when aligning macrocycles to a linear peptide
• If alignment fails for too many ligands, you can relax the strain and/or RMSD criteria by adjusting -convergence_strain or -convergence_rmsd.
• You can use -freeze_torsion to lock particular torsions in place and optimize the alignment “around them”.

See the documentation page for the tug_align.py utility for more details and usage examples.

5. Conclusion and References

In this tutorial, you learned how to configure LigPrep settings appropriate for cyclic peptides, and understand the best practices that ensure reliable prepared structures for subsequent modeling tasks such as docking, conformational sampling, and FEP+ calculations. You also learned how to align several of the cyclic peptides from the series to an experimental reference structure.

6. Glossary of Terms

Entries - a simplified view of the Project Table that allows you to perform basic operations such as selection and inclusion

Included - the entry is represented in the Workspace, the circle in the In column is blue

Project Table - displays the contents of a project and is also an interface for performing operations on selected entries, viewing properties, and organizing structures and data

Recent actions - This is a list of your recent actions, which you can use to reopen a panel, displayed below the Browse row. (Right-click to delete.)

Scratch Project - a temporary project in which work is not saved, closing a scratch project removes all current work and begins a new scratch project

Selected - (1) the atoms are chosen in the Workspace. These atoms are referred to as "the selection" or "the atom selection". Workspace operations are performed on the selected atoms. (2) The entry is chosen in the Entries table (and Project Table) and the row for the entry is highlighted. Project operations are performed on all selected entries

Working Directory - the location where files are saved

Workspace - the 3D display area in the center of the main window, where molecular structures are displayed