Integrative structural and functional analysis of human malic enzyme 3: A potential therapeutic target for pancreatic cancer.

Malic enzymes (ME1, ME2, and ME3) are involved in cellular energy regulation, redox homeostasis, and biosynthetic processes, through the production of pyruvate and reducing agent NAD(P)H. Recent studies have implicated the third and least well-characterized isoform, mitochondrial NADP+-dependent malic enzyme 3 (ME3), as a therapeutic target for pancreatic cancers. Here, we utilized an integrated structure approach to determine the structures of ME3 in various ligand-binding states at near-atomic resolutions. ME3 is captured in the open form existing as a stable tetramer and its dynamic Domain C is critical for activity. Catalytic assay results reveal that ME3 is a non-allosteric enzyme and does not require modulators for activity while structural analysis suggests that the inner stability of ME3 Domain A relative to ME2 disables allostery in ME3. With structural information available for all three malic enzymes, the foundation has been laid to understand the structural and biochemical differences of these enzymes and could aid in the development of specific malic enzyme small molecule drugs.

A phenotypic high-content, high-throughput screen identifies inhibitors of NLRP3 inflammasome activation.

Inhibition of the NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome has recently emerged as a promising therapeutic target for several inflammatory diseases. After priming and activation by inflammation triggers, NLRP3 forms a complex with apoptosis-associated speck-like protein containing a CARD domain (ASC) followed by formation of the active inflammasome. Identification of inhibitors of NLRP3 activation requires a well-validated primary high-throughput assay followed by the deployment of a screening cascade of assays enabling studies of structure-activity relationship, compound selectivity and efficacy in disease models. We optimized a NLRP3-dependent fluorescent tagged ASC speck formation assay in murine immortalized bone marrow-derived macrophages and utilized it to screen a compound library of 81,000 small molecules. Our high-content screening assay yielded robust assay metrics and identified a number of inhibitors of NLRP3-dependent ASC speck formation, including compounds targeting HSP90, JAK and IKK-ß. Additional assays to investigate inflammasome priming or activation, NLRP3 downstream effectors such as caspase-1, IL-1ß and pyroptosis form the basis of a screening cascade to identify NLRP3 inflammasome inhibitors in drug discovery programs.

Discovery of 1,5-disubstituted pyridones: a new class of positive allosteric modulators of the metabotropic glutamate 2 receptor.

A series of 1,5-disubstituted pyridones was identified as positive allosteric modulators (PAMs) of the metabotropic glutamate receptor 2 (mGluR2) via high throughput screening (HTS). Subsequent SAR exploration led to the identification of several compounds with improved in vitro activity. Lead compound 8 was further profiled and found to attenuate the increase in PCP induced locomotor activity in mice.

Conformational sampling with stochastic proximity embedding and self-organizing superimposition: establishing reasonable parameters for their practical use.

Stochastic proximity embedding (SPE) and self-organizing superimposition (SOS) are two recently introduced methods for conformational sampling that have shown great promise in several application domains. Our previous validation studies aimed at exploring the limits of these methods and have involved rather exhaustive conformational searches producing a large number of conformations. However, from a practical point of view, such searches have become the exception rather than the norm. The increasing popularity of virtual screening has created a need for 3D conformational search methods that produce meaningful answers in a relatively short period of time and work effectively on a large scale. In this work, we examine the performance of these algorithms and the effects of different parameter settings at varying levels of sampling. Our goal is to identify search protocols that can produce a diverse set of chemically sensible conformations and have a reasonable probability of sampling biologically active space within a small number of trials. Our results suggest that both SPE and SOS are extremely competitive in this regard and produce very satisfactory results with as few as 500 conformations per molecule. The results improve even further when the raw conformations are minimized with a molecular mechanics force field to remove minor imperfections and any residual strain. These findings provide additional evidence that these methods are suitable for many everyday modeling tasks, both high- and low-throughput.