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Gram-negative bacteria are notoriously more resistant to antibiotics than Gram-positive bacteria, primarily due to the presence of the outer membrane and a plethora of active efflux pumps. However, the potency of antibiotics also varies dramatically between different Gram-negative pathogens, suggesting major mechanistic differences in how antibiotics penetrate permeability barriers.

Dynamic in vitro antibacterial studies provide valuable insight on effective dosing strategies prior to translating to in vivo models. Frequent sampling is required to monitor the pharmacodynamics (PD) of these studies, leading to significant work when quantifying the bacterial load of the samples. Spreading a bacterial suspension on agar to allow colony counting is a proven process for measuring very low levels of growth, but commercial automation equipment to handle agar plating and colony counting at scale is not readily available. We describe a process to greatly decrease the hands-on time required for PD assays by utilizing general-purpose liquid handling robots to plate bacteria and a custom-made plate imager to automate colony counting. The platform developed handles the biological assay from beginning to end as well as sample tracking at each step of the process. The process relies heavily on custom automation scheduling software to enable dynamic process decisions and coordinate data flow throughout. Using the described platform, we can efficiently quantify100 PD samples per day while maintaining the necessary dynamic range of the assay. Alleviating the main bottleneck in the dynamic antibacterial studies has allowed us to accelerate the rate of experiments to provide antibacterial dosing data within shorter timelines.

Background Plaque Reduction Neutralization Test (PRNT) is the standard assay used for measuring neutralizing antibody responses to Herpes simplex virus type-2 (HSV-2). The PRNT is a cumbersome, time-consuming and laborious assay. The development of a faster, high throughput microneutralization assay (MNA) for HSV-2 viruses carried out in a 96-well format will allow for rapid testing of large numbers of samples for drug and vaccine development. Methods We describe the generation of a MNA that utilizes a pair of anti-HSV human monoclonal antibodies (mAbs) for virus detection in HSV-2 infected Vero cells. Antibodies were generated by B-cell cloning from PBMC’s isolated from HSV-1 negative/HSV-2 positive donors. We describe the selection and characterization of the antibodies used for virus detection by ELISA with purified, recombinant anti-HSV glycoproteins, antibody binding in infected cells, and Western Blot. We determine the anti-HSV-2 neutralizing titers of immune sera from mice by MNA and PRNT and compare these results by linear regression analysis. Results We show that neutralization titers for HSV-2, determined by the 96-well MNA correlate with titers determined by a PRNT completed in 24-well plates in both the absence (R2 = 0.8250) and presence (R2 = 0.7075) of complement. Conclusions We have successfully developed an MNA that can be used in place of the burdensome PRNT to determine anti-HSV-2 neutralizing activity in serum. This MNA has much greater throughput than the PRNT, allowing many more samples to be processed in a shorter time saving ∼90 % of the time required by the laboratory scientist to complete the task as compared to the traditional PRNT.

Antiretroviral therapy is able to effectively control but not eradicate HIV infection, which can persist, leading to the need for lifelong therapy. The existence of latently HIV-infected cells is a major barrier to the eradication of chronic HIV infection. Histone deacetylase inhibitors (HDACis), small molecules licensed for oncology indications, have shown the ability to produce HIV transcripts in vitro and in vivo. The pharmacologic parameters that drive optimal HIV latency reversal in vivo are unknown and could be influenced by such factors as the HDACi binding kinetics, concentration of compound, and duration of exposure. This study evaluates how these parameters affect HIV latency reversal for a series of novel HDACis that differ in their enzymatic on and off rates. Varying cellular exposure, using automated washout methods of HDACi in a Jurkat cell model of HIV latency, led to the investigation of the relationship between pharmacokinetic (PK) properties, target engagement (TE), and pharmacodynamic (PD) responses. Using an automated robotic platform enabled miniaturization of a suspension cell-based washout assay that required multiple manipulations over the 48 h duration of the assay. Quantification of histone acetylation (TE) revealed that HDACis showed early peaks and differences in the durability of response between different investigated HDACis. By expanding the sample times, the shift between TE and PD, as measured by green fluorescent protein, could be fully characterized. The comprehensive data set generated by automating the assays described here was used to establish a PK/PD model for HDACi-induced HIV latency reversal.

Agonist shift assays feature cross-titrations of allosteric modulators and orthosteric ligands. Information generated in agonist shift assays can include a modulator's effect on the orthosteric agonist's potency (alpha) and efficacy (beta), as well as direct agonist activity of the allosteric ligand (tauB) and the intrinsic binding affinity of the modulator to the unoccupied receptor (KB). Because of the heavy resource demand and complex data handling, these allosteric parameters are determined infrequently during the course of a drug discovery program and on a relatively small subset of compounds. Automation of agonist shift assays enables this data-rich analysis to evaluate a larger number of compounds, offering the potential to differentiate compound classes earlier and prospectively prioritize based on desired molecular pharmacology. A high-throughput calcium-imaging agonist shift assay was pursued to determine the allosteric parameters of over 1000 positive allosteric modulator (PAM) molecules for the human muscarinic acetylcholine receptor 1 (M1). Control compounds were run repeatedly to demonstrate internal consistency. Comparisons between potency measurements and the allosteric parameter results demonstrate that these different types of measurements do not necessarily correlate, highlighting the importance of fully characterizing and understanding the allosteric properties of leads.

High-throughput screening (HTS) is a widespread method in early drug discovery for identifying promising chemical matter that modulates a target or phenotype of interest. Because HTS campaigns involve screening millions of compounds, it is often desirable to initiate screening with a subset of the full collection. Subsequently, virtual screening methods prioritize likely active compounds in the remaining collection in an iterative process. With this approach, orthogonal virtual screening methods are often applied, necessitating the prioritization of hits from different approaches. Here, we introduce a novel method of fusing these prioritizations and benchmark it prospectively on 17 screening campaigns using virtual screening methods in three descriptor spaces. We found that the fusion approach retrieves 15% to 65% more active chemical series than any single machine-learning method and that appropriately weighting contributions of similarity and machine-learning scoring techniques can increase enrichment by 1% to 19%. We also use fusion scoring to evaluate the tradeoff between screening more chemical matter initially in lieu of replicate samples to prevent false-positives and find that the former option leads to the retrieval of more active chemical series. These results represent guidelines that can increase the rate of identification of promising active compounds in future iterative screens.

In the triage of hits from a high-throughput screening campaign or during the optimization of a lead compound, it is relatively routine to test compounds at multiple concentrations to determine potency and maximal effect. Additional follow-up experiments, such as agonist shift, can be quite valuable in ascertaining compound mechanism of action (MOA). However, these experiments require cross-titration of a test compound with the activating ligand of the receptor requiring 100-200 data points, severely limiting the number tested in MOA assays in a screening triage. We describe a process to enhance the throughput of such cross-titration experiments through the integration of Hewlett Packard's D300 digital dispenser onto one of our robotics platforms to enable on-the-fly cross-titration of compounds in a 1536-well plate format. The process handles all the compound management and data tracking, as well as the biological assay. The process relies heavily on in-house-built software and hardware, and uses our proprietary control software for the platform. Using this system, we were able to automate the cross-titration of compounds for both positive and negative allosteric modulators of two different G protein-coupled receptors (GPCRs) using two distinct assay detection formats, IP1 and Ca

Agonist shift assays feature cross-titrations of allosteric modulators and orthosteric ligands. Information generated in agonist shift assays can include a modulator's effect on the orthosteric agonist's potency (alpha) and efficacy (beta), as well as direct agonist activity of the allosteric ligand (tauB) and the intrinsic binding affinity of the modulator to the unoccupied receptor (KB). Because of the heavy resource demand and complex data handling, these allosteric parameters are determined infrequently during the course of a drug discovery program and on a relatively small subset of compounds. Automation of agonist shift assays enables this data-rich analysis to evaluate a larger number of compounds, offering the potential to differentiate compound classes earlier and prospectively prioritize based on desired molecular pharmacology. A high-throughput calcium-imaging agonist shift assay was pursued to determine the allosteric parameters of over 1000 positive allosteric modulator (PAM) molecules for the human muscarinic acetylcholine receptor 1 (M

N-methyl-d-aspartate receptors (NMDARs) mediate glutamatergic signaling that is critical to cognitive processes in the central nervous system, and NMDAR hypofunction is thought to contribute to cognitive impairment observed in both schizophrenia and Alzheimer’s disease. One approach to enhance the function of NMDAR is to increase the concentration of an NMDAR coagonist, such as glycine or d-serine, in the synaptic cleft. Inhibition of alanine–serine–cysteine transporter-1 (Asc-1), the primary transporter of d-serine, is attractive because the transporter is localized to neurons in brain regions critical to cognitive function, including the hippocampus and cortical layers III and IV, and is colocalized with d-serine and NMDARs. To identify novel Asc-1 inhibitors, two different screening approaches were performed with whole-cell amino acid uptake in heterologous cells stably expressing human Asc-1: (1) a high-throughput screen (HTS) of 3 M compounds measuring 35S l-cysteine uptake into cells attached to scintillation proximity assay beads in a 1536 well format and (2) an iterative focused screen (IFS) of a 45 000 compound diversity set using a 3H d-serine uptake assay with a liquid scintillation plate reader in a 384 well format. Critically important for both screening approaches was the implementation of counter screens to remove nonspecific inhibitors of radioactive amino acid uptake. Furthermore, a 15 000 compound expansion step incorporating both on- and off-target data into chemical and biological fingerprint-based models for selection of additional hits enabled the identification of novel Asc-1-selective chemical matter from the IFS that was not identified in the full-collection HTS.