Algorithm for drug discovery

描述（由申请人提供）：我们对吸毒行为背后的神经机制的理解已经取得了重大进展，但是在开发药物治疗干预方面还没有实现类似的进展，特别是在精神运动兴奋剂滥用方面。药物滥用的治疗干预是迫切需要的。本申请的目的是描述我们认为是一种发现药物精神药理学特性的新方法，并将其应用于新型治疗药物的研究。我们的方法使用自动化程序来分析开放领域的勘探行为。我们正在开发的算法，被称为模式阵列，能够在一次会话中筛选大量潜在的行为端点（bbb10万），并识别出最能表征特定药物的行为模式。这些模式的组合可以作为已知和新型精神活性化合物的高度特异性精神药理学“指纹”。本提案的目的是探索模式阵列的能力，以表征精神活性药物的高度特异性。该提案必须平衡筛选多种药物的发展需要与对单一滥用药物类别进行集中系统检查的愿望。考虑到这一点，我们将通过调查几种滥用药物的行为“特征”来开发适当的方法和工作数据库，然后将我们的注意力转向可卡因疗法。这项建议的目标将在两个具体目标中实现。具体目标1将使用来自不同类别的药物和具有不同作用机制的一类药物创建一个精神药理学概况数据库。具体目标2将确定算法推导的潜在可卡因疗法的“模式轮廓”。此外，这一目的将调查当拮抗剂与可卡因联合使用时的“模式轮廓”。将研究处于临床试验中的可卡因疗法以及D3拮抗剂和苯佐托品类似物等新型疗法。这些实验的结果将服务于两个目标。首先，它将细化算法中的数学和编程要求，并测试模式阵列中的优缺点。二是建立数据挖掘的核心数据库，为筛选具有潜在临床疗效的新型化合物提供模板。

DESCRIPTION (provided by applicant): Significant advances in our understanding of the neural mechanisms that underlie drug-taking behavior have been made, however similar advances in developing pharmacotherapeutic interventions have yet to be realized, especially in psychomotor stimulant abuse. Medications for treatment intervention in drug abuse are sorely needed. The purpose of this application is to describe what we believe to be a novel approach to discovering the psychopharmacological properties of a drug and to apply it to the study of novel therapeutic agents. Our approach uses an automated procedure for analyzing exploratory behavior in the open field. The algorithm we are developing, termed Pattern Arrays, is capable of screening a very large number of potential behavioral endpoints (>100,000) within a single session and identifying those patterns of behavior that best characterize the particular drug. A constellation of such patterns could serve as a highly specific psychopharmacological 'fingerprint' for known and novel psychoactive compounds. The objective of this proposal is to explore the capacity of the Pattern Array to characterize psychoactive drugs with a high degree of specificity. The proposal necessarily balances a developmental need to screen a diverse set of drugs with the desire to conduct a focused systematic examination of a single abused drug class. With this in mind, we will develop appropriate methodologies and a working database by investigating the behavioral 'signatures' of several abused drug classes, and then turn our attention to cocaine therapeutics. The objectives of this proposal will be realized in two specific aims. Specific Aim 1 will create a database of psychopharmacological profiles using drugs from different classes and drugs within a class that have different mechanisms of action. Specific Aim 2 will determine the algorithmically derived 'pattern profile' of potential cocaine therapeutics. In addition this aim will investigate the 'pattern profile' when the antagonist is given in combination with cocaine. Cocaine therapeutics that are in clinical trials as well as novel therapeutics such as D3 antagonists and benzotropine analogues will be investigated. The results of these experiments will serve two goals. First, it will refine the mathematical and programming requirements in the algorithm and test strengths and weakness in the Pattern Array. Second, it will establish a core database for data mining and provide a template for use in screening novel compounds with potential clinical efficacy.