Conformation of the Macrocyclic Drug Lorlatinib in Polar and Nonpolar Environments: A MD Simulation and NMR Study

Cheng, Peng; Atilaw, Yoseph; Wang, Jinan; Xu, Zhijian; Poongavanam, Vasanthanathan; Shi, Jiye; Kihlberg, Jan; Zhu, Weiliang; Erdélyi, Máté

doi:10.1021/acsomega.9b03797

“…This observation is consistent with current literature describing similar behavior for a broad range of peptidic and non-peptidic macrocycles. 38 , 43 , 57 …”

Section: Discussionmentioning

confidence: 99%

“… 96 Based on results from NMR, X-ray crystallography, and computational sampling, these studies report an increase of intramolecular hydrogen bonds and a decrease of the polar surface area for macrocyclic systems in an apolar environment compared to water. 51 , 57 …”

Section: Discussionmentioning

confidence: 99%

Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments

Kamenik

¹

,

Kraml

²

,

Hofer

³

et al. 2020

J. Chem. Inf. Model.

View full text Add to dashboard Cite

The relation of surface polarity and conformational preferences is decisive for cell permeability and thus bioavailability of macrocyclic drugs. Here, we employ grid inhomogeneous solvation theory (GIST) to calculate solvation free energies for a series of six macrocycles in water and chloroform as a measure of passive membrane permeability. We perform accelerated molecular dynamics simulations to capture a diverse structural ensemble in water and chloroform, allowing for a direct profiling of solvent-dependent conformational preferences. Subsequent GIST calculations facilitate a quantitative measure of solvent preference in the form of a transfer free energy, calculated from the ensemble-averaged solvation free energies in water and chloroform. Hence, the proposed method considers how the conformational diversity of macrocycles in polar and apolar solvents translates into transfer free energies. Following this strategy, we find a striking correlation of 0.92 between experimentally determined cell permeabilities and calculated transfer free energies. For the studied model systems, we find that the transfer free energy exceeds the purely water-based solvation free energies as a reliable estimate of cell permeability and that conformational sampling is imperative for a physically meaningful model. We thus recommend this purely physics-based approach as a computational tool to assess cell permeabilities of macrocyclic drug candidates.

show abstract

“…from a structure refinement that uses (experimental) restraints. Motivated by the poor, < 0.5 mg/mL, aqueous solubility of the studied peptides, NOE build-up rates and scalar coupling constants were obtained by recording spectra for DMSO-d 6 solutions, similar to previous investigations of systems barely soluble in water, 65,68,69,72 at a 900 MHz NMR spectrometer, as described in detail by Danelius et al 40 We used two different sets of data as theoretical input ensembles for the NAMFIS algorithm: (i) one generated from an MSM constructed using unbiased MD simulations, or (ii) one computed using restraint-free Monte Carlo conformational search, as described earlier. 40 The latter theoretical input ensemble was built by combination of the output conformers from two independent conformational searches using the OPLS-2005 and the AMBER* force fields, respectively, as implemented in the software Macromodel v9.1.…”

Section: Methodsmentioning

confidence: 99%

“…NAMFIS analysis. To identify the conformational families adopted in solution, we used the NMR Analysis of Molecular Flexibility In Solution (NAMFIS) algorythm, 41 which has previously been successfully applied to describe the solution ensembles of linear peptides 65 as well as of peptide, [66][67][68] natural product 69,70 and drug 71,72 macrocycles. It identifies solution conformers and their molar fraction by deconvoluting time-averaged NMR spectroscopic data using a computationally generated ensemble as an additional input.…”

Section: Methodsmentioning

confidence: 99%

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Ge¹,

Zhang²,

Erdélyi³

et al. 2020

Preprint

1

0

View full text Add to dashboard Cite

<div><div><div><p>Understanding mechanisms of protein folding and binding is crucial to designing their molecular function. Molecular dynamics (MD) simulations and Markov State Model (MSM) approaches provide a powerful way to understand complex conformational change that occurs over long timescales. Consideration of such dynamics are important for the design of therapeutic peptidomimetic ligands, whose affinity and binding mechanism are dictated by a combination of folding and binding. To examine the role of preorganization in peptide binding to protein targets, we performed massively parallel explicit-solvent MD simulations of cyclic β-hairpin ligands designed to disrupt the MDM2-p53 interaction. MSM analysis of over 3 ms of aggregate trajectory data enabled us to build a detailed mechanistic model of coupled folding and binding of four cyclic peptides which we compare to experimental binding affinities and rates. The results show a striking relationship between the relative preorganization of each ligand in solution and its affinity for MDM2. Specifically, changes in peptide conformational populations predicted by the MSMs suggest that entropy loss upon binding is the main factor influencing affinity. The MSMs also enable detailed examination of non-native interactions which lead to misfolded states, and comparison of structural ensembles with experimental NMR measurements. In contrast to an MSM study of p53 TAD binding to MDM2, MSMs of cyclic β-hairpin binding show a conformational selection mechanism. Finally, we make progress towards predicting accurate off-rates of cyclic peptides using multiensemble Markov models (MEMMs) constructed from unbiased and biased simulated trajectories.</p></div></div></div>

show abstract

“…NAMFIS analysis. To identify the conformational families adopted in solution, we used the NMR Analysis of Molecular Flexibility In Solution (NAMFIS) algorithm, 41 which has previously been successfully applied to describe the solution ensembles of linear peptides 66 as well as of peptide, [67][68][69] natural product 70,71 and drug 72,73 macrocycles. It identifies solution conformers and their molar fraction by deconvoluting time-averaged NMR spectroscopic data using a computationally generated ensemble as an additional input.…”

Section: Methodsmentioning

confidence: 99%

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Ge

¹

,

Zhang²,

Erdélyi³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

<div><div><div><p>Understanding mechanisms of protein folding and binding is crucial to designing their molecular function. Molecular dynamics (MD) simulations and Markov State Model (MSM) approaches provide a powerful way to understand complex conformational change that occurs over long timescales. Consideration of such dynamics are important for the design of therapeutic peptidomimetic ligands, whose affinity and binding mechanism are dictated by a combination of folding and binding. To examine the role of preorganization in peptide binding to protein targets, we performed massively parallel explicit-solvent MD simulations of cyclic β-hairpin ligands designed to disrupt the MDM2-p53 interaction. MSM analysis of over 3 ms of aggregate trajectory data enabled us to build a detailed mechanistic model of coupled folding and binding of four cyclic peptides which we compare to experimental binding affinities and rates. The results show a striking relationship between the relative preorganization of each ligand in solution and its affinity for MDM2. Specifically, changes in peptide conformational populations predicted by the MSMs suggest that entropy loss upon binding is the main factor influencing affinity. The MSMs also enable detailed examination of non-native interactions which lead to misfolded states, and comparison of structural ensembles with experimental NMR measurements. In contrast to an MSM study of p53 TAD binding to MDM2, MSMs of cyclic β-hairpin binding show a conformational selection mechanism. Finally, we make progress towards predicting accurate off-rates of cyclic peptides using multiensemble Markov models (MEMMs) constructed from unbiased and biased simulated trajectories.</p></div></div></div>

show abstract

Conformation of the Macrocyclic Drug Lorlatinib in Polar and Nonpolar Environments: A MD Simulation and NMR Study

Cited by 19 publications

References 58 publications

Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments

Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Contact Info

Product

Resources

About