Achieving Strong Positive Cooperativity through Activating Weak Non‐Covalent Interactions

Ma, Yan‐Long; Ke, Hua Zhu; Valkonen, Arto; Rissanen, Kari; Jiang, Wei

doi:10.1002/ange.201711077

Cited by 29 publications

(13 citation statements)

References 50 publications

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“…During the last six years, we reported a series of naphthol‐ based macrocyclic receptors which have been used in molecular recognition, molecular sensing, molecular machine, cooperative self‐assembly and supramolecular hydrogel . We recently synthesized a tetralactam macrocycle with 2,3‐dibutoxylnaphthalene .…”

Section: Background and Originality Contentmentioning

confidence: 99%

Selective Recognition of Phenazine by 2,6‐Dibutoxylnaphthalene‐Based Tetralactam Macrocycle

Wang

Valkonen

et al. 2019

Chin. J. Chem.

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Summary of main observation and conclusion A 2,6‐dibutoxylnaphthalene‐based tetralactam macrocycle was designed and synthesized. This macrocycle shows highly selective recognition to phenazine – a well‐known secondary metabolite in bacteria and an emerging disinfection byproduct in drinking water. In contrast, the macrocycle shows no binding to the structurally similar dibenzo‐1,4‐dioxin. It was revealed that hydrogen bonding, π‐π and σ‐π interactions are the major driving forces between phenazine and the new tetralactam macrocycle. A perfect complementarity in electrostatic potential surfaces may explain the high selectivity. In addition, the macrocycle shows fluorescent response to phenazine, demonstrating its potential in fluorescent detection of phenazine.

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Section: Background and Originality Contentmentioning

confidence: 99%

Selective Recognition of Phenazine by 2,6‐Dibutoxylnaphthalene‐Based Tetralactam Macrocycle

Wang

Valkonen

et al. 2019

Chin. J. Chem.

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“…Cooperativity occurs when a binding event can either increase or decrease the strength of subsequent binding events [60]. In the presence of ions, electrostatic attractions can also lead to cooperativity [61]. Indeed, experiments must verify 1:1 binding (as was done here) otherwise computation would need to consider other possibilities.…”

Section: We Avoid Multimeric Systems Which Introduce Additional Complmentioning

confidence: 98%

SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations

Amezcua

Khoury

Mobley

2021

J Comput Aided Mol Des

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“…Cooperativity occurs when a binding event can either increase or decrease the strength of subsequent binding events [56]. In the presence of ions, electrostatic attractions can also lead to cooperativity [57]. Indeed, experiments must verify 1:1 binding (as was done here) otherwise computation would need to consider other possibilities.…”

Section: Here We Avoid Multimeric Systems Which Introduce Additionalmentioning

confidence: 98%

SAMPL7 Host-Guest Challenge Overview: Assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations

Amezcua¹,

Khoury²,

Mobley

2020

Preprint

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The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges have thus frequently included a component focusing on host-guest binding, which removes some of these challenges while still focusing on molecular recognition. Here, we report on the results of the SAMPL7 blind prediction challenge for host-guest affinity prediction. In this study, we focused on three different host-guest categories -- a familiar deep cavity cavitand series which has been featured in several prior challenges (where we examine binding of a series of guests to two hosts), a new series of cyclodextrin derivatives which are monofunctionalized around the rim to add amino acid-like functionality (where we examine binding of a two guests to a series of hosts), and binding of a series of guests to a new acyclic TrimerTrip host which is related to previous cucurbituril hosts. Many predictions used methods based on molecular simulations, and overall success was mixed, though several methods stood out. As in SAMPL6, we find that one strategy for achieving reasonable accuracy here was to make empirical corrections to binding predictions based on previous data for host categories which have been studied well before, though this can be of limited value when new systems are included. Additionally, we found that methods using the AMOEBA polarizable force field had considerable success for the two host categories in which they participated. The new TrimerTrip system was also found to introduce some sampling problems, because multiple conformations may be relevant to binding and interconvert only slowly. Overall, results in this challenge tentatively suggest that further investigation of polarizable force fields for these challenges may be warranted.

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Achieving Strong Positive Cooperativity through Activating Weak Non‐Covalent Interactions

Cited by 29 publications

References 50 publications

Selective Recognition of Phenazine by 2,6‐Dibutoxylnaphthalene‐Based Tetralactam Macrocycle

Selective Recognition of Phenazine by 2,6‐Dibutoxylnaphthalene‐Based Tetralactam Macrocycle

SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations

SAMPL7 Host-Guest Challenge Overview: Assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations

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