The generation of conformers has been a long-standing interest to structural chemists and biologists alike. A subset of proteins known as intrinsically disordered proteins (IDPs) fail to exhibit a fixed structure and, therefore, must also be studied in this light of conformer generation. Unlike in the small molecule setting, ground truth data are sparse in the IDP setting, undermining many existing conformer generation methods that rely on such data for training. Boltzmann generators, trained solely on the energy function, serve as an alternative but display a mode collapse that similarly preclude their direct application to IDPs. We investigate the potential of training an RL Boltzmann generator against a closely related "Gibbs score," and demonstrate that conformer coverage does not track well with such training. This suggests that the inadequacy of solely training against the energy is independent of the modeling modality
翻译:结构化学家和生物学家都长期关注如何产生符合要求者,结构化学家和生物学家都长期关注如何产生符合要求者。被称为内在无序蛋白质(IDPs)的一组蛋白质未能展现出固定结构,因此也必须从符合要求者的生成角度来研究。与小分子环境不同,在国内流离失所者环境中,地面真相数据很少,破坏了许多依靠这种数据进行培训的现有符合要求者生成方法。完全通过能源功能培训的Boltzmann发电机作为一种替代方法,但显示一种模式崩溃,同样排除了它们直接应用于国内流离失所者。我们调查了针对一个密切相关的“Gibbs分”培训RL Boltzmann发电机的可能性,并证明符合要求的覆盖面与这种培训不相符。这表明,仅进行能源培训的不足与模型模式无关。