{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mueller LG"],"funding":["National Institute of Neurological Disorders and Stroke","NIA NIH HHS","NIMH NIH HHS","NINDS NIH HHS","National Institute of Mental Health","National Institute on Aging"],"pagination":["394-399"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10988710"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(3)"],"pubmed_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."],"journal":["ACS chemical neuroscience"],"pubmed_title":["Empirical Analysis of Drug Targets for Nervous System Disorders."],"pmcid":["PMC10988710"],"funding_grant_id":["R33 NS119659","R01AG068130","P30 MH075673","R01 AG068130","R01AG059799","R33NS119659","UH3 NS115718","R01 AG059799","UH3NS115718","P30MH075673","T32 AG058527","UG3 NS115718"],"pubmed_authors":["Tsukamoto T","Slusher BS","Mueller LG"],"additional_accession":[]},"is_claimable":false,"name":"Empirical Analysis of Drug Targets for Nervous System Disorders.","description":"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.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Feb","modification":"2025-04-04T02:43:25.697Z","creation":"2025-04-04T02:43:25.697Z"},"accession":"S-EPMC10988710","cross_references":{"pubmed":["38237559"],"doi":["10.1021/acschemneuro.3c00676"]}}