Summary Aberrant expression ratio of Cl − transporters, NKCC1 and KCC2, is implicated in several brain conditions. NKCC1 inhibition by the FDA-approved diuretic drug, bumetanide, rescues core symptoms in rodent models and/or clinical trials with patients. However, bumetanide has a strong diuretic effect due to inhibition of the kidney Cl − transporter NKCC2, creating critical drug compliance issues and health concerns. Here, we report the discovery of a new chemical class of selective NKCC1 inhibitors and the lead drug candidate ARN23746. ARN23746 restores the physiological intracellular Cl − in murine Down syndrome neuronal cultures, has excellent solubility and metabolic stability, and displays no issues with off-target activity in vitro . ARN23746 recovers core symptoms in mouse models of Down syndrome and autism, with no diuretic effect, nor overt toxicity upon chronic treatment in adulthood. ARN23746 is ready for advanced preclinical/manufacturing studies toward the first sustainable therapeutics for the neurological conditions characterized by impaired Cl − homeostasis.

The detection and characterization of binding pockets and allosteric communication in proteins is crucial for studying biological regulation and performing drug design. Nowadays, ever-longer molecular dynamics (MD) simulations are routinely used to investigate the spatiotemporal evolution of proteins. Yet, there is no computational tool that can automatically detect all the pockets and potential allosteric communication networks along these extended MD simulations. Here, we use a novel and fully automated algorithm that examines pocket formation, dynamics, and allosteric communication embedded in microsecond-long MD simulations of three pharmaceutically relevant proteins, namely, PNP, A2A, and Abl kinase. This dynamic analysis uses pocket crosstalk, defined as the temporal exchange of atoms between adjacent pockets, along the MD trajectories as a fingerprint of hidden allosteric communication networks. Importantly, this study indicates that dynamic pocket crosstalk analysis provides new mechanistic understandings on allosteric communication networks, enriching the available experimental data. Thus, our results suggest the prospective use of this unprecedented dynamic analysis to characterize transient binding pockets for structure-based drug design.

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Plinabulin is a novel tubulin-binding agent that is currently in phase 3 clinical trials for cancer treatment and prevention of chemotherapy-induced neutropenia. Plinabulin binds within a distinct tubulin pocket, which differentiates it from other tubulin binders. Aimed at disclosing structural and energetic details of plinabulin binding to tubulin, we combine X-ray crystallography and computational modeling. We compare the plinabulin residence time with that of colchicine and combretastatin-A4. Our study helps understand potential mechanisms underlying differential effects of this family of anti-tubulin drugs.

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