Divergent Modes of Enzyme Inhibition in a Homologous Structure−Activity Series

Ferreira, Rafaela Salgado; Bryant, Clifford; Ang, Kenny Kean‐Hooi; McKerrow, James H.; Shoichet, Brian K.; Renslo, Adam R.

doi:10.1021/jm9009229

Cited by 81 publications

(74 citation statements)

References 24 publications

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“…The inhibition of cruzain enzymatic activity by all compounds was measured using a competition based assay with the substrate Z-PheArg-aminomethylcoumarin (Z-FR-AMC) [41]. All compounds were screened at 50 µM, and only compounds having an inhibition value of >70% were chosen to determine IC 50 values.…”

Section: Cruzain Inhibition Activitymentioning

confidence: 99%

Synthesis and structure–activity relationship study of a new series of antiparasitic aryloxyl thiosemicarbazones inhibiting Trypanosoma cruzi cruzain

Espíndola

Cardoso

Filho

et al. 2015

European Journal of Medicinal Chemistry

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The discovery of new antiparasitic compounds against Trypanosoma cruzi, the etiological agent of Chagas disease, is necessary. Novel aryloxy/aryl thiosemicarbazone-based conformationally constrained analogs of thiosemicarbazones (1) and (2) were developed as potential inhibitors of the T. cruzi protease cruzain, using a rigidification strategy of the iminic bond of (1) and (2). A structure-activity relationship analysis was performed in substituents attached in both aryl and aryloxy rings. This study indicated that apolar substituents or halogen atom substitution at the aryl position improved cruzain inhibition and antiparasitic activity in comparison to unsubstituted thiosemicarbazone. Two of these compounds displayed potent inhibitory antiparasitic activity by inhibiting cruzain and consequently were able to reduce the parasite burden in infected cells and cause parasite cell death through necrosis. In conclusion, we demonstrated that conformational restriction is a valuable strategy in the development of antiparasitic thiosemicarbazones.

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Section: Cruzain Inhibition Activitymentioning

confidence: 99%

Synthesis and structure–activity relationship study of a new series of antiparasitic aryloxyl thiosemicarbazones inhibiting Trypanosoma cruzi cruzain

Espíndola

Cardoso

Filho

et al. 2015

European Journal of Medicinal Chemistry

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show abstract

“…2,4 Although high hit rates may be useful for diagnosing NSI, our collective HTS data have shown that hit rates can differ substantially even within the same enzyme class, in a manner that is not due to NSI. The challenge to predict enzyme susceptibility to nonspecific inhibition is illustrated by the diverse inhibitory profiles among caspase family members (-1, -3, -6, -7, and -8) in our first case study.…”

Section: Nonspecific Inhibition Is Enzyme Isoform and Protein Construmentioning

confidence: 89%

“…2 Over the past decade, significant progress has been made, mostly by the academic research team of Shoichet, to clarify the mechanisms of nonspecific inhibition. Much of this work proved that promiscuous inhibitors physically interact with protein targets but do so by forming colloidal aggregates at micromolar compound concentration in an aqueous environment.…”

Section: Introductionmentioning

confidence: 99%

Case Studies of Minimizing Nonspecific Inhibitors in HTS Campaigns That Use Assay-Ready Plates

Liu¹,

Beresini²,

Johnson³

et al. 2012

SLAS Discovery

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Identifying chemical lead matter by high-throughput screening (HTS) has been a common practice in early stage drug discovery. Evolution of small-molecule library composition to include more drug-like molecules with desirable physical chemical properties combined with improving assay technologies has vastly enhanced the capability of HTS. However, HTS campaigns can still be plagued by false positives arising from nonspecific inhibitors. The generation of assay-ready plates has permitted an incremental advancement to the speed and efficiency of HTS but has the potential to enhance the occurrence of nonspecific inhibitors. A subtle change in the order of reagent addition to the assay-ready plates can greatly alleviate falsepositive inhibition. Our case studies with six different kinase and protease targets reveal that this type of inhibition affects targets regardless of enzyme class and is unpredictable based on protein construct or inhibitor chemical scaffold. These case studies support a model where a diversity set of compounds should be tested first for hit rates as a function of order of addition, carrier protein, and relevant mechanistic studies prior to launch of the HTS campaign.

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“…For cell-based assays, membrane permeability might also influence experimental data. Additional accounts of problems with experimental data have appeared in the recent literature [183,184].…”

Section: Biological Datamentioning

confidence: 99%

The Challenge of Affinity Prediction: Scoring Functions for Structure‐Based Virtual Screening

Sotriffer¹,

Matter²

2011

Methods and Principles in Medicinal Chemistry

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The purpose of virtual screening is to provide hits with novel chemical structure as a starting point for lead optimization after careful assessment of their optimization potential [1].Structure-based virtual screening works on the premise of shape and interaction complementarity of the ligand with its putative target binding site, for which experimental 3D structures or validated homology models are available. Using docking algorithms combined in various ways with other filters (e.g., drug-likeness, physiochemical properties, binding site constraints, pharmacophore models, and molecular similarity), compounds are selected that have a high likelihood to interact with the target. To this end, the first step is to generate a proposed binding conformation (pose) using validated docking engines. These poses need to be sorted to identify the conformation that is closest to an experimental binding pose. Subsequently, the free energy of binding (DG ) for a particular conformation of a single compound interacting with the protein has to be estimated to rank the ligands and select those with the highest chance for biological activity. Approaches providing such estimates of affinity are, thus, of utmost importance in virtual screening. Normally, this pose ranking and affinity estimation is carried out with the help of scoring functions. Scoring functions are approximate mathematical models for predicting the strength of the noncovalent interaction between two binding partners. Such functions also guide the conformational and orientational search of the ligand in the binding cavity during the docking process.This chapter focuses on different aspects of scoring functions for affinity prediction and pose ranking. First, we will outline the physicochemical background of current scoring approaches. As different scoring functions were recently reviewed [2-4] and their performance was extensively compared [5-8], we will provide only a brief overview of the different scoring function classes and focus on unique features and applications. Hence, we outline novel strategies and computational tools with an impact on improving the success rate in scoring protein-ligand interactions.

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Divergent Modes of Enzyme Inhibition in a Homologous Structure−Activity Series

Cited by 81 publications

References 24 publications

Synthesis and structure–activity relationship study of a new series of antiparasitic aryloxyl thiosemicarbazones inhibiting Trypanosoma cruzi cruzain

Synthesis and structure–activity relationship study of a new series of antiparasitic aryloxyl thiosemicarbazones inhibiting Trypanosoma cruzi cruzain

Case Studies of Minimizing Nonspecific Inhibitors in HTS Campaigns That Use Assay-Ready Plates

The Challenge of Affinity Prediction: Scoring Functions for Structure‐Based Virtual Screening

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