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The characterization of drug-target interactions is a key component of drug discovery, testing, and development. Affinity chromatography is one approach that can be used for this type of analysis. For instance, this may be done by using an immobilized target as a stationary phase and a drug as the applied solute. This review will discuss the various ways in which affinity chromatographic methods have been used to examine drug-target interactions, with an emphasis on high-performance methods. The general principles of this approach and factors to consider in its use for drug-target interaction analysis will first be examined. Methods based on zonal elution or frontal analysis for binding and competition studies will then be discussed. Various techniques for kinetic studies will next be considered, along with approaches that employ secondary binding agents and hybrid techniques. In each case, the general principles and theory of an approach will be given along with examples of its use in drug-target interaction studies. Advantages or limitations of each approach will be provided as well. This information should make it possible in the future to extend these techniques to other drug-target systems of interest in biomedical research and drug testing or development. 

The analysis of biomolecular interactions is important in characterizing and understanding many fundamental processes that occur in the body and biological systems. A variety of methods are available for studying the extent and rate of binding of these interactions. Some of these techniques are homogeneous methods, with all interacting components being present in the solution-phase, while others are heterogeneous, such as involving both solution-phase and solid-phase components. LC and HPLC have often been used to study biomolecular processes. Although these chromatographic methods make use of both a liquid phase (i.e., the mobile phase and applied samples) and a solid phase (the stationary phase and support), they can be used to study solution-phase interactions. This review examines several strategies that have been developed and employed to use LC and HPLC for this purpose. These strategies include the Hummel-Dreyer method, solution-phase frontal analysis, and the use of physical entrapment for a soluble component of a biomolecular interaction. Other strategies that are discussed are those in which the stationary phase of the column is used as a secondary component or capture agent when studying a solution-phase interaction, as occurs in normal-role affinity chromatography and ultrafast affinity extraction. The general principles for each of these strategies will be considered, along with their advantages, potential limitations, and applications. 

Abstract Phase‐sensitive integrated photonic devices are highly susceptible to minor manufacturing deviations, resulting in significant performance inconsistencies. This variability has limited the scalability and widespread adoption of these devices. Here, a major advancement is achieved through continuous‐wave (CW) visible light (405 and 520 nm) trimming of plasma‐enhanced chemical vapor deposition (PECVD) silicon‐rich nitride (SRN) waveguides. The demonstrated method achieves precise, bidirectional refractive index tuning with a single laser source in CMOS‐compatible SRN samples with refractive indices of 2.4 and 2.9 (measured at 1550 nm). By utilizing a cost‐effective setup for real‐time resonance tracking in micro‐ring resonators, the resonant wavelength shifts as fine as 10 pm are attained. Additionally, a record red shift of 49.1 nm and a substantial blue shift of 10.6 nm are demonstrated, corresponding to refractive index changes of approximately 0.11 and −2 × 10⁻². The blue and red shifts are both conclusively attributed to thermal annealing. These results highlight SRN's exceptional capability for permanent optical tuning, establishing a foundation for stable, precisely controlled performance in phase‐sensitive integrated photonic devices. 

Background: DJ-1 is a protein whose mutation causes rare heritable forms of Parkinson’s disease (PD) and is of interest as a target for treating PD and other disorders. This work used high performance affinity microcolumns to screen and examine the binding of small molecules to DJ-1, as could be used to develop new therapeutics or to study the role of DJ-1 in PD. Non-covalent entrapment was used to place microgram quantities of DJ-1 in an unmodified form within microcolumns, which were then used in multiple studies to analyze binding by model compounds and possible drug candidates to DJ-1. Results: Several factors were examined in optimizing the entrapment method, including the addition of a reducing agent to maintain a reduced active site cysteine residue in DJ-1, the concentration of DJ-1 employed, and the entrapment times. Isatin was used as a known binding agent (dissociation constant, ~2.0 µM) and probe for DJ-1 activity. This compound gave good retention on 2.0 cm × 2.1 mm inner diameter DJ-1 microcolumns made under the final entrapment conditions, with a typical retention factor of 14 and elution in ~8 min at 0.50 mL/min. These DJ-1 microcolumns were used to evaluate the binding of small molecules that were selected in silico to bind or not to bind DJ-1. A compound predicted to have good binding with DJ-1 gave a retention factor of 122, an elution time of ~15 min at 0.50 mL/min, and an estimated dissociation constant for this protein of 0.5 µM. Significance: These chromatographic tools can be used in future work to screen additional possible binding agents for DJ-1 or adapted for examining drug candidates for other proteins. This work represents the first time protein entrapment has been deployed with DJ-1, and it is the first experimental confirmation of binding to DJ-1 by a small lead compound selected in silico. 

The analysis of interactions between biological agents or with surrounding chemicals is important in many areas of modern biochemical, biomedical, and environmental research. Microscale platforms based on affinity chromatography have been shown to be a powerful set of tools for these studies. This approach makes use of an immobilized binding agent as a stationary phase in a microscale platform for either direct examination of the interactions of this agent with an applied target solute or as a secondary capture agent to probe a solution‐phase interaction. This review will examine the various platforms and strategies that have been used in microscale affinity chromatography, or µAC, to characterize and study biointeractions. The general principles of µAC and schemes based on this approach will be examined, along with applications of this technique. Examples of approaches that will be considered will include zonal and frontal analysis methods, as well as a variety of schemes by which µAC can be employed in kinetic studies. In each case, the theory and principles of these methods will be provided along with examples of their use in biointeraction studies. 

Information Retrieval (IR) plays a pivotal role indiverse Software Engineering (SE) tasks, e.g., bug localization and triaging, bug report routing, code retrieval, requirements analysis, etc. SE tasks operate on diverse types of documents including code, text, stack-traces, and structured, semi-structured and unstructured meta-data that often contain specialized vocabularies. As the performance of any IR-based tool critically depends on the underlying document types, and given the diversity of SE corpora, it is essential to understand which models work best for which types of SE documents and tasks.We empirically investigate the interaction between IR models and document types for two representative SE tasks (bug localization and relevant project search), carefully chosen as they require a diverse set of SE artifacts (mixtures of code and text),and confirm that the models’ performance varies significantly with mix of document types. Leveraging this insight, we propose a generalized framework, SRCH, to automatically select the most favorable IR model(s) for a given SE task. We evaluate SRCH w.r.t. these two tasks and confirm its effectiveness. Our preliminary user study shows that SRCH’s intelligent adaption of the IR model(s) to the task at hand not only improves precision and recall for SE tasks but may also improve users’ satisfaction.