Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design

Author:

Jain Ajay N.ORCID,Brueckner Alexander C.ORCID,Jorge ChristineORCID,Cleves Ann E.ORCID,Khandelwal Purnima,Cortes Janet CaceresORCID,Mueller LucianoORCID

Abstract

AbstractSystematic optimization of large macrocyclic peptide ligands is a serious challenge. Here, we describe an approach for lead-optimization using the PD-1/PD-L1 system as a retrospective example of moving from initial lead compound to clinical candidate. We show how conformational restraints can be derived by exploiting NMR data to identify low-energy solution ensembles of a lead compound. Such restraints can be used to focus conformational search for analogs in order to accurately predict bound ligand poses through molecular docking and thereby estimate ligand strain and protein-ligand intermolecular binding energy. We also describe an analogous ligand-based approach that employs molecular similarity optimization to predict bound poses. Both approaches are shown to be effective for prioritizing lead-compound analogs. Surprisingly, relatively small ligand modifications, which may have minimal effects on predicted bound pose or intermolecular interactions, often lead to large changes in estimated strain that have dominating effects on overall binding energy estimates. Effective macrocyclic conformational search is crucial, whether in the context of NMR-based restraints, X-ray ligand refinement, partial torsional restraint for docking/ligand-similarity calculations or agnostic search for nominal global minima. Lead optimization for peptidic macrocycles can be made more productive using a multi-disciplinary approach that combines biophysical data with practical and efficient computational methods.

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

Reference39 articles.

1. Goto Y, Suga H (2021) The RaPID platform for the discovery of pseudo-natural macrocyclic peptides. Acc Chem Res 54(18):3604–3617

2. Miller MM, Mapelli C, Allen MP, Bowsher MS, Boy KM, Gillis EP, Langley DR, Mull E, Poirier MA, Sanghvi N, Sun LQ, Tenney DT, Yeung KS, Zhu J, Reid PC, Scola PM (2016) Macrocyclic inhibitors of the PD-1/PD-L1 and CD80 (B7-1)/PD-L1 protein/protein interactions. US Patent 9:308

3. Jiao L, Dong Q, Zhai W, Zhao W, Shi P, Wu Y, Zhou X, Gao Y (2022) A PD-L1 and VEGFR2 dual targeted peptide and its combination with irradiation for cancer immunotherapy. Pharmacol Res 182(106):343

4. Labute P (2010) LowModeMD: Implicit low-mode velocity filtering applied to conformational search of macrocycles and protein loops. J Chem Info Model 50(5):792–800

5. Chen IJ, Foloppe N (2013) Tackling the conformational sampling of larger flexible compounds and macrocycles in pharmacology and drug discovery. Bioorg Med Chem 21(24):7898–7920

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