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Abstract：
Antimicrobial resistance (AMR) is one of the most serious global public health threats as it compromises the successful treatment of deadly infectious diseases like tuberculosis. New therapeutics are constantly needed but it takes a long time and is expensive to explore new biochemical space. One way to address this issue is to repurpose the validated targets and identify novel chemotypes that can simultaneously bind to multiple binding pockets of these targets as a new lead generation strategy. This study reports such a strategy, dynamic hybrid pharmacophore model (DHPM), which represents the combined interaction features of different binding pockets contrary to the conventional approaches, where pharmacophore models are generated from single binding sites. We have considered Mtb-DapB, a validated mycobacterial drug target, as our model system to explore the effectiveness of DHPMs to screen novel unexplored compounds. Mtb-DapB has a cofactor binding site (CBS) and an adjacent substrate binding site (SBS). Four different model systems of Mtb-DapB were designed where, either NADPH/NADH occupies CBS in presence/absence of an inhibitor 2, 6-PDC in the adjacent SBS. Two more model systems were designed, where 2, 6-PDC was linked to NADPH and NADH to form hybrid molecules. The six model systems were subjected to 200 ns molecular dynamics simulations and trajectories were analyzed to identify stable ligand-receptor interaction features. Based on these interactions, conventional pharmacophore models (CPM) were generated from the individual binding sites while DHPMs were created from hybrid-molecules occupying both binding sites. A huge library of 1,563,764 publicly available molecules were screened by CPMs and DHPMs. The screened hits obtained from both types of models were compared based on their Hashed binary molecular fingerprints and 4-point pharmacophore fingerprints using Tanimoto, Cosine, Dice and Tversky similarity matrices. Molecules screened by DHPM exhibited significant structural diversity, better binding strength and drug like properties as compared to the compounds screened by CPMs indicating the efficiency of DHPM to explore new chemical space for anti-TB drug discovery. The idea of DHPM can be applied for a wide range of mycobacterial or other pathogen targets to venture into unexplored chemical space.
摘要：
抗菌素耐药性（AMR）是最严重的全球公共卫生威胁之一，因为它损害了结核病等致命传染病的成功治疗。不断需要新的治疗方法，但探索新的生化空间需要很长时间，而且成本很高。解决此问题的一种方法是重新利用已验证的靶标，并鉴定可以同时结合这些靶标的多个结合口袋的新型化学型，作为新的前导生成策略。这项研究报告了这样一个策略，动态混合药效团模型(DHPM)，这代表了与传统方法相反的不同结合袋的组合相互作用特征，其中药效基团模型是从单个结合位点产生的。我们考虑过Mtb-DapB,经过验证的分枝杆菌药物靶标，作为我们的模型系统，探索DHPM筛选新的未开发化合物的有效性。Mtb-DapB具有辅因子结合位点(CBS)和相邻的底物结合位点(SBS)。设计了四种不同的Mtb-DapB模型系统，在相邻SBS中存在/不存在抑制剂2,6-PDC的情况下,NADPH/NADH占据CBS。设计了两个模型系统，其中2,6-PDC与NADPH和NADH连接以形成杂合分子。对六个模型系统进行了200ns的分子动力学模拟，并分析了轨迹以识别稳定的配体-受体相互作用特征。基于这些互动,常规药效基团模型(CPM)由单个结合位点产生,而DHPM由占据两个结合位点的杂合分子产生.通过CPM和DHPM筛选了1,563,764个公开可用分子的巨大文库。根据他们的Hashed二元分子指纹和使用Tanimoto的4点药效基团指纹进行比较，余弦,Dice和Tversky相似度矩阵。DHPM筛选的分子表现出显著的结构多样性，与通过CPM筛选的化合物相比,更好的结合强度和药物样性质表明DHPM探索用于抗TB药物发现的新化学空间的效率。DHPM的想法可以应用于广泛的分枝杆菌或其他病原体靶标，以进入未开发的化学空间。
