A General Picture of Cucurbit[8]uril Host-Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamical feature of host-guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has intermediate portal size and cavity volume. It can exploit almost all host-guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of 7 commonly abused and structurally diverse drugs to the CB8 host was performed and a general dynamical binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted to improve the intra-molecular conformational preference and thus the description of inter-molecular host-guest interactions. The interaction pattern and binding thermodynamics show significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host-guest binding.

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Synthesis and Guest-Binding Properties of pH/Reduction Dual-Responsive Cyclophane Dimer

Molecules ◽

10.3390/molecules26113097 ◽

2021 ◽

Vol 26 (11) ◽

pp. 3097

Author(s):

Osamu Hayashida ◽

Yudai Tanaka ◽

Takaaki Miyazaki

Keyword(s):

Electrostatic Interaction ◽

Disulfide Bonds ◽

Water Soluble ◽

Guest Molecules ◽

Binding Behavior ◽

Dual Responsive ◽

Guest Binding ◽

Basic Solutions ◽

Ph Conditions ◽

Almost All

A water-soluble cyclophane dimer having two disulfide groups as a reduction-responsive cleavable bond as well as several acidic and basic functional groups as a pH-responsive ionizable group 1 was successfully synthesized. It was found that 1 showed pH-dependent guest-binding behavior. That is, 1 strongly bound an anionic guest, 6-p-toluidinonaphthalene-2-sulfonate (TNS) with binding constant (K/M−1) for 1:1 host-guest complexes of 9.6 × 104 M−1 at pH 3.8, which was larger than those at pH 7.4 and 10.7 (6.0 × 104 and 2.4 × 104 M−1, respectively), indicating a favorable electrostatic interaction between anionic guest and net cationic 1. What is more, release of the entrapped guest molecules by 1 was easily controlled by pH stimulus. Large favorable enthalpies (ΔH) for formation of host-guest complexes were obtained under the pH conditions employed, suggesting that electrostatic interaction between anionic TNS and 1 was the most important driving force for host-guest complexation. Such contributions of ΔH for formation of host-guest complexes decreased along with increased pH values from acidic to basic solutions. Upon addition of dithiothreitol (DTT) as a reducing reagent to an aqueous PBS buffer (pH 7.4) containing 1 and TNS, the fluorescence intensity originating from the bound guest molecules decreased gradually. A treatment of 1 with DTT gave 2, having less guest-binding affinity by the cleavage of disulfide bonds of 1. Consequently, almost all entrapped guest molecules by 1 were released from the host. Moreover, such reduction-responsive cleavage of 1 and release of bound guest molecules was performed more rapidly in aqueous buffer at pH 10.7.

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Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields

Journal of Chemical Information and Modeling ◽

10.1021/acs.jcim.0c01217 ◽

2020 ◽

Author(s):

Zhe Huai ◽

Zhaoxi Shen ◽

Zhaoxi Sun

Keyword(s):

Free Energy ◽

Force Fields ◽

Free Energy Calculations ◽

Urinary Protein ◽

Interaction Patterns ◽

Major Urinary Protein ◽

Energy Calculations ◽

Binding Thermodynamics ◽

Amber Force Fields

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Assessment of AMBER Force Fields for Simulations of ssDNA

Journal of Chemical Theory and Computation ◽

10.1021/acs.jctc.0c00931 ◽

2021 ◽

Vol 17 (2) ◽

pp. 1208-1217

Author(s):

Thomas J. Oweida ◽

Ho Shin Kim ◽

Johnny M. Donald ◽

Abhishek Singh ◽

Yaroslava G. Yingling

Keyword(s):

Force Fields ◽

Amber Force Fields

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RNA Stability Under Different Combinations of Amber Force Fields and Solvation Models

Journal of Biomolecular Structure and Dynamics ◽

10.1080/07391102.2010.10507372 ◽

2010 ◽

Vol 28 (3) ◽

pp. 431-441 ◽

Cited By ~ 40

Author(s):

Zhou Gong ◽

Yunjie Zhao ◽

Yi Xiao

Keyword(s):

Force Fields ◽

Rna Stability ◽

Solvation Models ◽

Amber Force Fields

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Faculty Opinions recommendation of Assessment of AMBER Force Fields for Simulations of ssDNA.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.739351368.793582444 ◽

2021 ◽

Author(s):

Alex MacKerell

Keyword(s):

Force Fields ◽

Amber Force Fields

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Thermodynamics of Helix formation in small peptides of varying lengthin vacuo, implicit solvent and explicit solvent: Comparison between AMBER force fields

Journal of Theoretical and Computational Chemistry ◽

10.1142/s0219633619500159 ◽

2019 ◽

Vol 18 (03) ◽

pp. 1950015

Author(s):

Zhaoxi Sun ◽

Xiaohui Wang

Keyword(s):

Amino Acids ◽

Free Energy ◽

Hydrogen Bonds ◽

Force Fields ◽

Implicit Solvent ◽

Conformational Ensemble ◽

Helix Formation ◽

Solvent Models ◽

Explicit Solvent ◽

Amber Force Fields

Helix formation is of great significance in protein folding. The helix-forming tendencies of amino acids are accumulated along the sequence to determine the helix-forming tendency of peptides. Computer simulation can be used to model this process in atomic details and give structural insights. In the current work, we employ equilibrate-state free energy simulation to systematically study the folding/unfolding thermodynamics of a series of mutated peptides. Two AMBER force fields including AMBER99SB and AMBER14SB are compared. The new 14SB force field uses refitted torsion parameters compared with 99SB and they share the same atomic charge scheme. We find that in vacuo the helix formation is mutation dependent, which reflects the different helix propensities of different amino acids. In general, there are helix formers, helix indifferent groups and helix breakers. The helical structure becomes more favored when the length of the sequence becomes longer, which arises from the formation of additional backbone hydrogen bonds in the lengthened sequence. Therefore, the helix indifferent groups and helix breakers will become helix formers in long sequences. Also, protonation-dependent helix formation is observed for ionizable groups. In 14SB, the helical structures are more stable than in 99SB and differences can be observed in their grouping schemes, especially in the helix indifferent group. In solvents, all mutations are helix indifferent due to protein–solvent interactions. The decrease in the number of backbone hydrogen bonds is the same with the increase in the number of protein–water hydrogen bonds. The 14SB in explicit solvent is able to capture the free energy minima in the helical state while 14SB in implicit solvent, 99SB in explicit solvent and 99SB in implicit solvent cannot. The helix propensities calculated under 14SB agree with the corresponding experimental values, while the 99SB results obviously deviate from the references. Hence, implicit solvent models are unable to correctly describe the thermodynamics even for the simple helix formation in isolated peptides. Well-developed force fields and explicit solvents are needed to correctly describe the protein dynamics. Aside from the free energy, differences in conformational ensemble under different force fields in different solvent models are observed. The numbers of hydrogen bonds formed under different force fields agree and they are mostly determined by the solvent model.

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