Experimental Confirmation of New Drug–Target Interactions Predicted by Drug Profile Matching

Végner, László; Peragovics, Ágnes; Tombor, László; Jelinek, Balázs; Czobor, Pál; Bender, Andreas; Simon, Zoltán Boldizsár; Málnási‐Csizmadia, András

doi:10.1021/jm400813y

Cited by 14 publications

(10 citation statements)

References 91 publications

(138 reference statements)

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“…The original work of Biospectra by Fliri et al in 2005 is the first large-scale screening between 1045 drugs and 92 proteins. This works identified important molecular mechanisms of drug clinical effects and has been the foundation of many following research on drug side-effects 21222324 . The broad-scale in vitro pharmacology profiling by Novartis research analyzed drug promiscuity against 220 targets (including 73 unintended targets) 20 .…”

Section: Introductionmentioning

confidence: 99%

Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach

Liu

Altman

2015

J. Chem. Inf. Model.

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The molecular mechanism of many drug side-effects is unknown and difficult to predict. Previous methods for explaining side effects have focused on known drug targets and their pathways. However, low affinity binding to proteins that are not usually considered drug targets may also drive side-effects. In order to assess these alternative targets, we used the 3D structures of 563 essential human proteins systematically to predict binding to 216 drugs. We first benchmarked our affinity predictions with available experimental data. We then combined singular value decomposition and canonical component analysis (SVD-CCA) to predict side-effects based on these novel target profiles. Our method predicts side-effects with good accuracy (average AUC: 0.82 for side effects present in < 50% of drug labels). We also noted that side-effect frequency is the most important feature for prediction, and can confound efforts at elucidating mechanism; our method allows us to remove the contribution of frequency and isolate novel biological signals. In particular, our analysis produces 2768 triplet associations between 50 essential proteins, 99 drugs and 77 side-effects. Although experimental validation is difficult because many of our essential proteins do not have validated assays, we nevertheless attempted to validate a subset of these associations using experimental assay data. Our focus on essential proteins allows us to find potential associations that would likely be missed if we used recognized drug targets. Our associations provide novel insights about the molecular mechanisms of drug side-effects, and highlight the need for expanded experimental efforts to investigate drug binding to proteins more broadly.

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Section: Introductionmentioning

confidence: 99%

Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach

Liu

Altman

2015

J. Chem. Inf. Model.

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“…It is clear that the man-made compounds are significantly more likely to be in this box and that they represent a more dangerous class of compounds than the naturally occurring compounds despite some structural similarities. [79] Many of the predictions were verified by experimental testing. [76] A variation on this approach is that certain authors have studied the data available for compounds that have been tested in many assays to identify what physical or other molecular properties tend to correspond to compounds that bind in lots of these assays as compared to those that only bind to one or few.…”

Section: Computational Approachesmentioning

confidence: 87%

“…This approach has recently been exemplified by predicting the likelihood that a set of known drugs might bind to angiotensinconverting enzyme, cyclooxygenase (1 and 2) or the dopamine receptor (D1 or D2). [79] Many of the predictions were verified by experimental testing. However, the uncertainty in the prediction combined with the issue of translating any binding into biological effects make the interpretation of such studies troublesome.…”

Section: Computational Approachesmentioning

confidence: 87%

Predicting the activity and toxicity of new psychoactive substances: a pharmaceutical industry perspective

Leach

2013

Drug Testing and Analysis

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Predicting the effect that new compounds might have when administered to human beings is a common desire shared by researchers in the pharmaceutical industry and those interested in psychoactive compounds (illicit or otherwise). The experience of the pharmaceutical industry is that making such predictions at a usefully accurate level is not only difficult but that even when billions of dollars are spent to ensure that only compounds likely to have a desired effect without unacceptable side-effects are dosed to humans in clinical trials, they fail in more than 90% of cases. A range of experimental and computational techniques is used and they are placed in their context in this paper. The particular roles played by computational techniques and their limitations are highlighted; these techniques are used primarily to reduce the number of experiments that must be performed but cannot replace those experiments.

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“…A DPM teljesítményének vizsgálatára három hatáskategóriát választottak ki: az angiotenzinkonvertá-lóenzim-inhibitort, a ciklooxigenáz-inhibitort és a dopaminreceptor-agonistákat; a predikciókat irodalmi elemzéssel, valamint kísérleti úton igazolták. A kutatók úgy ítélik meg, hogy a DPM hatékony megközelítési mód-szer új gyógyszer-célfehérje párok felfedezéséhez [30].…”

Section: áBraunclassified

A hagyományos kínai fitoterápia értelmezése és beillesztése a nyugati típusú orvoslásba az emberi genom ismeretének birtokában

Blázovics

2018

Orvosi Hetilap

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The terminology of traditional Chinese medicine (TCM) is hardly interpretable in the context of human genome, therefore the human genome program attracted attention towards the Western practice of medicine in China. In the last two decades, several important steps could be observed in China in relation to the approach of traditional Chinese and Western medicine. The Chinese government supports the realization of information databases for research in order to clarify the molecular biology level to detect associations between gene expression signal transduction pathways and protein-protein interactions, and the effects of bioactive components of Chinese drugs and their effectiveness. The values of TCM are becoming more and more important for Western medicine as well, because molecular biological therapies did not redeem themselves, e.g., in tumor therapy. Orv Hetil. 2018; 159(18): 696-702.

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Experimental Confirmation of New Drug–Target Interactions Predicted by Drug Profile Matching

Cited by 14 publications

References 91 publications

Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach

Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach

Predicting the activity and toxicity of new psychoactive substances: a pharmaceutical industry perspective

A hagyományos kínai fitoterápia értelmezése és beillesztése a nyugati típusú orvoslásba az emberi genom ismeretének birtokában

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