Matched Molecular Pair Analysis in drug discovery

Dossetter, Alexander G.; Griffen, Ed; Leach, Andrew G.

doi:10.1016/j.drudis.2013.03.003

Cited by 124 publications

(104 citation statements)

References 35 publications

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“…4-6 Therefore, researchers are beginning to adopt a consistent definition of activity cliffs that looks at similarity in terms of matched molecular pairs (MMP), and extracting activity data from publicly available repositories. 7-9 …”

Section: Introductionmentioning

confidence: 99%

Structure-Based Predictions of Activity Cliffs

Husby

Bottegoni

Kufareva

et al. 2015

J. Chem. Inf. Model.

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In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods.

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Section: Introductionmentioning

confidence: 99%

Structure-Based Predictions of Activity Cliffs

Husby

Bottegoni

Kufareva

et al. 2015

J. Chem. Inf. Model.

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“…In this paper we discuss the use of matched molecular pair (MMP) methods [14] for investigating enantioseparation data. MMP techniques find local chemical changes in similar compounds and look for trends where the same type of chemical change is associated with a consistent change in activity.…”

Section: Introductionmentioning

confidence: 99%

Mining Chromatographic Enantioseparation Data Using Matched Molecular Pair Analysis

et al. 2016

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Abstract:We apply matched molecular pair (MMP) analysis to data from ChirBase, which contains literature reports of chromatographic enantioseparations. For the 19 chiral stationary phases we examined, we were able to identify 289 sets of pairs where there is a statistically significant and consistent difference in enantioseparation due to a small chemical change. In many cases these changes highlight enantioselectivity differences between pairs or small families of closely related molecules that have for many years been used to probe the mechanisms of chromatographic chiral recognition; for example, the comparison of N-H vs. N-Me analytes to determine the criticality of an N-H hydrogen bond in chiral molecular recognition. In other cases, statistically significant MMPs surfaced by the analysis are less familiar or somewhat puzzling, sparking a need to generate and test hypotheses to more fully understand. Consequently, mining of appropriate datasets using MMP analysis provides an important new approach for studying and understanding the process of chromatographic enantioseparation.

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“…The hydrophobic characteristics of most functional groups are predictable as evidenced by the satisfactory correlation of calculated log Ps with measured values. However, molecular matched pair studies [32][33][34][35] have shown that a number of substituents can have the opposite effect on hydrophobicity compared to that which is predicted (Table 2). Notably, the hydrophobic groups F [36] and Me [37] can under certain circumstances improve solubility, whereas polar groups such as CN, SO 2 Me and CO 2 H can reduce solubility.…”

Section: Reducing Hydrophobicitymentioning

confidence: 90%

Novel tactics for designing water-soluble molecules in drug discovery

Walker

2014

Expert Opinion on Drug Discovery

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From a strategic point of view, improving the solubility of a compound should be straightforward because it can be accomplished by simply reducing hydrophobicity or crystalline stability. However, the structural elements and physical properties which control solubility also influence potency, pharmacokinetics and toxicity. Furthermore, there are practical aspects such as the quantity and quality of solubility-related data, which hamper the development of structure-solubility relationships. Given that poor aqueous solubility remains a primary issue in drug discovery, there is a continuous need for novel methods to overcome it.

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Matched Molecular Pair Analysis in drug discovery

Cited by 124 publications

References 35 publications

Structure-Based Predictions of Activity Cliffs

Structure-Based Predictions of Activity Cliffs

Mining Chromatographic Enantioseparation Data Using Matched Molecular Pair Analysis

Novel tactics for designing water-soluble molecules in drug discovery

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