Mapping atoms across chemical reactions is important for substructure searches, automatic extraction of reaction rules, identification of metabolic pathways, and more. Unfortunately, the existing mapping algorithms can deal adequately only with relatively simple reactions but not those in which expert chemists would benefit from computer’s help. Here we report how a combination of algorithmics and expert chemical knowledge significantly improves the performance of atom mapping, allowing the machine to deal with even the most mechanistically complex chemical and biochemical transformations. The key feature of our approach is the use of few but judiciously chosen reaction templates that are used to generate plausible “intermediate” atom assignments which then guide a graph-theoretical algorithm towards the chemically correct isomorphic mappings. The algorithm performs significantly better than the available state-of-the-art reaction mappers, suggesting its uses in database curation, mechanism assignments, and – above all – machine extraction of reaction rules underlying modern synthesis-planning programs.

We prove that recent results of Baumgartner and Willis on contraction groups of automorphisms of metrizable totally disconnected locally compact groups (Israel J. Math. 142 (2004), 221-248) remain true for nonmetrizable groups.Let G be a (Hausdorff) topological group and τ an automorphism of G. The subgroupis called the contraction subgroup of τ . Recent work of Baumgartner and Willis [1] demonstrates the significance of the contractions subgroups in the theory of totally disconnected locally compact groups, by linking these subgroups with the theory of tidy subgroups and scales of automorphisms [1, Section 3]. This link is established under the extra assumption that the group be metrizable. It is the purpose of this note to prove that the results of Baumgartner and Willis remain true, without any modifications, for any totally disconnected locally compact group.A careful scrutiny of the proofs in [1] reveals that it is enough to prove that Theorem 3.8 of [1] remains true for not necessarily metrizable groups. With this accomplished, the proofs of the remaining results in [1, Section 3] do not require any changes.

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Depression, a devastating psychiatric disorder, is a leading cause of disability worldwide. Current antidepressants address specific symptoms of the disease, but there is vast room for improvement . In this respect, new compounds that act beyond classical antidepressants to target signal transduction pathways governing synaptic plasticity and cellular resilience are highly warranted. The extracellular signal-regulated kinase (ERK) pathway is implicated in mood regulation, but its pleiotropic functions and lack of target specificity prohibit optimal drug development. Here, we identified the transcription factor ELK-1, an ERK downstream partner , as a specific signaling module in the pathophysiology and treatment of depression that can be targeted independently of ERK. ELK1 mRNA was upregulated in postmortem hippocampal tissues from depressed suicides; in blood samples from depressed individuals, failure to reduce ELK1 expression was associated with resistance to treatment. In mice, hippocampal ELK-1 overexpression per se produced depressive behaviors; conversely, the selective inhibition of ELK-1 activation prevented depression-like molecular, plasticity and behavioral states induced by stress. Our work stresses the importance of target selectivity for a successful approach for signal-transduction-based antidepressants, singles out ELK-1 as a depression-relevant transducer downstream of ERK and brings proof-of-concept evidence for the druggability of ELK-1.