Dataset Information

Lidocaine Ineffectiveness Suggests New Psychopharmacology Drug Target.

ABSTRACT:

Objectives

The mechanism of many neuropsychiatric disorders remains unknown, but the ineffectiveness of the sodium channel blocker lidocaine has been suggested to be a biomarker for Attention Deficit Hyperactivity Disorder (ADHD) and a severe form of Premenstrual Syndrome (PMS) that is considered psychiatric. We conducted single-arm double-blind clinical trials to test whether lidocaine ineffectiveness can be used as a biomarker to identify people with these conditions and provide a clue as to the molecular mechanism and potential psychopharmacological intervention.

Experimental design

We developed a noninvasive taste test for lidocaine ineffectiveness, validated by comparing lidocaine injections to pain testing in 12 subjects, and assessed it in individuals with ADHD and PMS.

Principal observations

Lidocaine ineffectiveness had a strong association in women with ADHD + PMS in a sample of 53 subjects and controls (p < 0.001).

Conclusions

These results suggest the possibility of the biological understanding of the combination of ADHD and PMS that is characteristic of the psychiatric disorder Premenstrual Dysphoric Disorder (PMDD). These results and comparison to family pedigrees of a neuromuscular channelopathy with overlapping symptoms suggest the possibility that the clinical phenotype in PMDD is produced by sensory overstimulation, and amenable to molecular understanding and treatment.

SUBMITTER: Mintz M

PROVIDER: S-EPMC9235314 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Lidocaine Ineffectiveness Suggests New Psychopharmacology Drug Target.

Mintz Mark M Badner Victor V Feldman Lynn K LK Mintz Pnina P Saraghi Mana M Diaz Jonathan J Mezhebovsky Irina I Axelrod Irene I Gleeson Joseph J Liu Chang C Smith Cathy C Chow Helen H Zurakowski David D Segal Michael M MM

Psychopharmacology bulletin 20220601 3

<h4>Objectives</h4>The mechanism of many neuropsychiatric disorders remains unknown, but the ineffectiveness of the sodium channel blocker lidocaine has been suggested to be a biomarker for Attention Deficit Hyperactivity Disorder (ADHD) and a severe form of Premenstrual Syndrome (PMS) that is considered psychiatric. We conducted single-arm double-blind clinical trials to test whether lidocaine ineffectiveness can be used as a biomarker to identify people with these conditions and provide a clue ...[more]

PMID: 35815177

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Project description:BackgroundIdentification of novel drug-target interactions (DTIs) is important for drug discovery. Experimental determination of such DTIs is costly and time consuming, hence it necessitates the development of efficient computational methods for the accurate prediction of potential DTIs. To-date, many computational methods have been proposed for this purpose, but they suffer the drawback of a high rate of false positive predictions.ResultsHere, we developed a novel computational DTI prediction method, DASPfind. DASPfind uses simple paths of particular lengths inferred from a graph that describes DTIs, similarities between drugs, and similarities between the protein targets of drugs. We show that on average, over the four gold standard DTI datasets, DASPfind significantly outperforms other existing methods when the single top-ranked predictions are considered, resulting in 46.17 % of these predictions being correct, and it achieves 49.22 % correct single top ranked predictions when the set of all DTIs for a single drug is tested. Furthermore, we demonstrate that our method is best suited for predicting DTIs in cases of drugs with no known targets or with few known targets. We also show the practical use of DASPfind by generating novel predictions for the Ion Channel dataset and validating them manually.ConclusionsDASPfind is a computational method for finding reliable new interactions between drugs and proteins. We show over six different DTI datasets that DASPfind outperforms other state-of-the-art methods when the single top-ranked predictions are considered, or when a drug with no known targets or with few known targets is considered. We illustrate the usefulness and practicality of DASPfind by predicting novel DTIs for the Ion Channel dataset. The validated predictions suggest that DASPfind can be used as an efficient method to identify correct DTIs, thus reducing the cost of necessary experimental verifications in the process of drug discovery. DASPfind can be accessed online at: http://www.cbrc.kaust.edu.sa/daspfind.Graphical abstractThe conceptual workflow for predicting drug-target interactions using DASPfind.

Dataset Information

Lidocaine Ineffectiveness Suggests New Psychopharmacology Drug Target.

Objectives

Experimental design

Principal observations

Conclusions

Publications

Lidocaine Ineffectiveness Suggests New Psychopharmacology Drug Target.

Similar Datasets

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