ReviewACS chemical neuroscience2024
Empirical Analysis of Drug Targets for Nervous System Disorders.
Review in ACS chemical neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- A Benchmark Set of Bioactive Molecules for Diversity Analysis of Compound Libraries and Combinatorial Chemical Spaces.Journal of chemical information and modeling · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The discovery and development of drugs to treat diseases of the nervous system remains challenging. There is a higher attrition rate in the clinical stage for nervous system experimental drugs compared to other disease areas. In the preclinical stage, additional challenges arise from the considerable effort required to find molecules that penetrate the blood-brain barrier (BBB) coupled with the poor predictive value of many preclinical models of nervous system diseases. In the era of target-based drug discovery, the critical first step of drug discovery projects is the selection of a therapeutic target which is largely driven by its presumed pathogenic involvement. For nervous system diseases, however, the feasibility of identifying potent molecules within the stringent range of molecular properties necessary for BBB penetration should represent another important factor in target selection. To address the latter, the present review analyzes the distribution of human protein targets of FDA-approved drugs for nervous system disorders and compares it with drugs for other disease areas. We observed a substantial difference in the distribution of therapeutic targets across the two clusters. We expanded on this finding by analyzing the physicochemical properties of nervous and non-nervous system drugs in each target class by using the central nervous system multiparameter optimization (CNS MPO) algorithm. These data may serve as useful guidance in making more informed decisions when selecting therapeutic targets for nervous system disorders.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.