Comprehensive computational design of ordered peptide macrocycles

By P. Hosseinzadeh, G. Bhardwaj, Vikram Khipple Mulligan, M. Shortridge, Timothy W. Craven, Fátima Pardo-Avila, Stephen A. Rettie, David E. Kim, Daniel‐Adriano Silva, Yehia M. Ibrahim and 5 more. 2017

183 citations recorded by the source corpus.

Macrocycles by design Macrocyclic peptides have diverse properties, including antibiotic and anticancer activities. This makes them good therapeutic leads, but screening libraries only cover a fraction of the sequence space available to peptides comprising D and L amino acids. Hosseinzadeh et al. achieved near-complete coverage in sampling the sequence space for 7- to 10-residue cyclic peptides and identified more than 200 designs predicted to fold into stable structures. Of 12 structures determined, nine were close to the computational models. They also sampled and designed 11- to 14-residue macrocycles, but without complete coverage. The designed macrocycles provide a path forward for engineering new therapeutics. Science, this issue p. 1461 Heterochiral peptide macrocycles have been designed de novo with high accuracy. Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with l-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of l- and d-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.

Subfields: Molecular Biology

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Citations in the corpus

Recent advances in de novo protein design: Principles, methods, and applications (2021, methodology): “Kinematic closure methods in Rosetta (76, 78) can be used to enumerate backbones of cyclic peptides with seven to ten residues nearly exhaustively (79).”
Better together: Elements of successful scientific software development in a distributed collaborative community (2020, methodology): “In 2015, Rosetta@home was ported to the Android operating system to run on volunteers’ cell phones and mobile devices during recharge periods, when the CPU is typically underutilized[50], to perform biomolecular structure prediction tasks.”
Designing Peptides on a Quantum Computer (2019, background): “The latter class of algorithms, which include Rosetta’s AbinitoRelax ( 46 – 49 ) and simple_cycpep_predict applications ( 16 , 17 ) , sample tens of thousands to millions of alternative backbone conformations given a fixed sequence, relaxing and computing energies of each conformation sampled.”
Reconfigurable asymmetric protein assemblies through implicit negative design (2021, unknown): “The interface residues of the docked hetero-dimer complexes were optimized using Rosetta combinatorial sequence ( 37 – 40 ) design using “ ref2015, ” “ beta_nov16, ” or “ beta_genpot ” as score functions ( 41 ).”
Essentials of de novo protein design: Methods and applications (2018, methodology): “40 Instead of characterizing the energy landscape, other strategies also evaluate the compatibility between sequence and tertiary structure.”