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title tags authors affiliations date bibliography
Cocktail Shaker: An open source drug expansion and enumeration library for peptides
Python
Cheminformatics
RDKit
Peptides
name orcid affiliation
Suliman Sharif
0000-0002-1342-9258
1
name index
None
1
23 November 2019
paper.bib

Introduction

Without expensive software, the rapid creation and design of peptide ligand libraries has been a challenge for many drug discovery scientists. Currently, protein- and peptide-based therapeutics constitute 10% of the pharmaceutical market and will make up a larger proportion of the market in the future [@Craig:2013-1; @Bruno:2013-2]. With the demand for designing new peptide therapeutics on the rise, new high throughput peptide-specific informatic tools are needed. Currently, two platforms for this purpose exist: Molecular Operating Environment (MOE) [@Reynolds:2010-3] and Rapid Peptides Generator (RPG) [@Maillet:2020-4] but both have drawbacks. MOE works efficiently for creating peptide molecule 3D chemical files in one particular format (mol2), but at the high cost for a licence. RPG, although free of charge, does not account for non-natural amino acids and production of multiple chemical files. In this study, I present the first open source python package, Cocktail Shaker, developed for exploring, expanding, and synthesizing chemical peptide data.

Methodology and Implementation

Cocktail Shaker operates within the RDKit platform [@Landrum:2019-5] and is designed for the chemically-oriented computational research community. RDKit utilizes C++-based functions for speed and rapid creation of molecule objects. The toolkit offers a variety of utilities that includes: parsing and producing ready-to-use scientific files designed for any chemical software, employing click chemistry methods for ease of exchange compounds, chemical data writing, and chemical representation enumeration employed for machine learning.

Cocktail Shaker consists of three major class objects available to the user: PeptideMolecule, CocktailShaker, and FileWriter.

Using string manipulation PeptideMolecule can build SMILES strings with allocated slots defined by the user. The user can then enter the produced SMILES into the CocktailShaker object with a library of ligands represented by smiles and optional arguments of whether to include generation of stereoisomers and/or natural amino acids. Cocktail Shaker will generate all combinations of the library and allocate them to a slot within the peptide. This process of string manipulation is presented in Figure 1.

Full string manipulation diagram of how Cocktail Shaker works with a ligand library of just bromine and iodine. 1D representations are labeled above with their 2D depictions displayed below.

Cocktail Shaker also allows for File Writing of the molecules into a wide array of chemical formats (found in the documentation). Cocktail Shaker uses RDKit to convert from 1D to 2D and the CIR Resolver built from webchem to convert 1D SMILES to 3D. At the request of the user, the data is saved into one large data file or separated using the keyword fragmentation. This additional API allows the user the flexibility to write a variety of files to implement in their respective chemical software.

Conclusion

Using Cocktail Shaker, individual research groups and companies can quickly construct private compound collections and progressively improve public libraries with increased variations of chemical compound data.

Cocktail Shaker with its first version release provides a basis for drug expansion and enumeration. For future releases Cocktail Shaker will be expanding into specifying shapes of compounds and, recently partnered with MolPort, vendor information on any compound generated. It was presented at the RDKit UGM conference at the University of Hamburg to the cheminformatics community with positive feedback with its second version 1.0.1. With incorporated feedback it will now be released with version 1.1.8. With more contributions Cocktail Shaker will be an exciting tool for drug library creation and drug discovery for scientists and engineers alike.

Acknowledgements

We acknowledge contributions from Ryland Forsythe as an academic consultation, Marvin Corro for quality assurance, Rose Gierth for technical documentation, and Elena Chow for her work on the graphics.

References