New therapeutic approaches to identifying molecules for opioid abuse treatment
New therapeutic approaches to identifying molecules for opioid abuse treatment
批准号:
10385998
负责人:
SEAN EKINS
金额:
$25.62万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-15 至 2024-04-14
关键词:
AcuteAdverse effectsAgonistAnxietyBiological AssayBusinessesCessation of lifeCollaborationsCouplingData SetDatabasesDecision TreesDiseaseDoseDrug AddictionDrug abuseEnsureExpert SystemsFeedbackHTR2A geneHallucinogensHeadIbogaineIn VitroIntellectual PropertyLeadLearningLinkLysergic Acid DiethylamideMachine LearningMedicalMental disordersMetabolicMethadoneModelingNamesNatural ProductsNetwork-basedNeuronal PlasticityOpiate AddictionOpioidOverdosePathway interactionsPharmaceutical ChemistryPharmaceutical PreparationsPharmacologic SubstancePhaseProductionPropertyRandomized Clinical TrialsReportingResearchSeedsSerotoninSolubilitySourceSpecificitySupervisionTestingTherapeuticToxic effectUnited StatesValidationWorkaddictionalgorithm traininganalogbasechronic paincompliance behaviorcost effectivedeep learning modelecstasyexperienceimprovedimproved functioningin vivoinnovationinterestlead optimizationmachine learning modelnovelnovel therapeutic interventionnovel therapeuticsopen sourceopioid abuseopioid epidemicopioid mortalityopioid use disorderreceptorrecurrent neural networkresearch and developmentresponsescale upserotonin receptorsmall molecule librariessupervised learningsupport vector machinesynthetic opioid
中文摘要
项目摘要
合作制药公司是一家专注于开发治疗疑难杂症的小企业,
疾病持续过度依赖阿片类药物治疗慢性疼痛,尽管它们改善功能的能力很差,
导致近年来阿片类药物过量死亡和成瘾的严重和令人震惊的流行。
尽管存在压倒性的成瘾危机,但几乎没有治疗方法存在,并且疗效低下。因此,一个关键的未满足的需求
是阿片类药物滥用障碍的有效和安全的治疗方法。最近的研究表明迷幻药
还能够减少药物依赖,包括阿片类药物滥用,
极其罕见这种药物滥用的停止与神经突发生的诱导有关,
神经可塑性迷幻药的标志虽然迷幻体验和神经可塑性诱导
似乎是相互联系的,已经提出了几种类似的迷幻药,诱导神经可塑性和药物-
回避,而似乎缺乏迷幻的经验。虽然数量很少,但这些类似物具有
被命名为“精神致活素”,并且是用于治疗阿片类药物滥用的有希望的候选者。德-
迷幻体验和神经可塑性诱导的耦合与受体特异性有关,
精神质体原对5 HT 2A是特异性的。在这里,我们建议使用生成机器学习的组合,
模型与我们的监督机器模型的丰富经验,以产生新的类似迷幻药
其将具有改善的5-HT 2A特异性、ADME性质,并且易于合成以快速扩增5-HT 2A,
一系列已知的精神致活素,显著增加阿片类药物滥用的潜在治疗选择
治疗
英文摘要
Project Summary
Collaborations Pharmaceuticals Inc. is a small business focused on developing treatments for difficult to treat
diseases. The ongoing overreliance on opioids for chronic pain despite their poor ability to improve function has
contributed to a significant and alarming epidemic of opioid overdose deaths and addictions in recent years.
Despite the overwhelming addiction crisis, few therapies exist, and with low efficacy. Thus, a critical unmet need
is an effective and safe treatment for opioid abuse disorders. Recent research has suggested that psychedelics
are also capable of reducing drug-dependence, including opioid abuse, and that serious adverse effects are
extremely rare. This drug abuse cessation is linked to the induction of neuritogenesis and increased
neuroplasticity, a hallmark of psychedelics. While the psychedelic experience and neuroplasticity induction
appear interlinked, several analogs of psychedelics have been proposed which induce neuroplasticity and drug-
avoidance while seemingly lacking the psychedelic experience. Although few in number, these analogs have
been named “psychoplastogens” and are promising candidates for treatment of opioid drug abuse. The de-
coupling of the psychedelic experience and neuroplasticity induction is linked to receptor specificity as
psychoplastogens are specific to 5HT2A. Here, we propose to use a combination of generative machine learning
models with our extensive experience of supervised machine models to generate new analogs of psychedelics
that will have improved 5-HT2A specificity, ADME properties, and are easily synthesizable to rapidly expand the
pool of known psychoplastogens, significantly increasing potential therapeutic options for opioid abuse
treatment.
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