Biomolecules: sample and data quality in interaction analysis

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00:00:00 Sample and data quality in interaction analysis - two sides of the same coin
00:01:46 Poll Questions
00:01:46 Sample and data quality in interaction analysis - two sides of the same coin
00:02:57 Poll Answers
00:02:57 Sample and data quality in interaction analysis - two sides of the same coin
00:03:11 Frequently asked questions and trends in interaction analysis.
00:04:30 Frequently asked questions and trends in interaction analysis.
00:05:20 Reliable characterization of a binding interaction requires high data quality at good level of method understanding
00:05:51 ITC –gold standard in interaction analysis.
00:07:07 Ease of use without compromising performance in a broad range of affinities. MicroCal™ PEAQ ITC
00:07:56 Inadequate maintenance and experimental setup one of the main causes of poor data quality. Make a sanity check of the raw ITC data
00:09:21 Fully integrated wash module ensures adequate maintenance
00:09:46 Quality of experiment design facilitated by Design of Experiment software.MicroCal PEAQ-ITC
00:10:25 High-resolution data on interaction profiles delivers multiple insights on samples’ behavior.
00:11:41 Reliable characterization of a binding interaction requires high sample quality.
00:12:15 Basic characterization of protein state and stability in solution is warranted for high quality of results
00:13:45 Multiple biophysical methods used for characterization of sample quality
00:14:13 Untitled
00:15:03 Untitled
00:15:31 Scientific network shares best practices and advocates for sample quality control
00:16:22 Reliable characterization of a binding interaction requires high sample quality.
00:16:30 Error in sample concentration and lack of understanding of sample state in solution affect quality of interaction analysis
00:17:36 N<1. Amount of protein competent for ligand binding can be directly established by ITC
00:18:24 N<1. Do not leave it entirely to mathematics! Characterize protein state in solution.
00:19:06 ITC flags for a complex mechanism of interaction for a series of ligands.
00:19:54 Assessing protein oligomerization state with benchtop instruments.
00:21:03 Assessing protein oligomerization state with benchtop instruments.
00:23:01 Latest development in DLS technology opens up for broader application in sample QC.
00:23:46 Case study examples
00:23:51 Case study 1. Early Drug Discovery.Project setbacks could have been avoided with early on control of sample quality.
00:24:07 Biosensor assay development prematuarly deemed unsuccessful
00:25:14 Major issues with protein quality uncovered with DLS and ITC clarifying lack of specific binding in biosensor assay.
00:25:28 Case study 2.DLS and ESI-MS help to identify and resolve issues with irreproducible assay results and bring protein kinase X project back on track.
00:25:47 Throubleshooting irreproducible data from biochemical and biophysical assays run with protein kinase X.
00:26:47 Protein stability profile established and optimized with DLS.
00:28:58 Controlling quality of ligands is as important.
00:30:05 Case study 3. Solubility issues with LMW ligands and positive controls impact quality of the binding data.
00:30:21 Strickingly different affinity of two isomeric ligands of protein X.
00:32:32 Incorrect concentration of LMW compound impacts quality of the binding data
00:32:43 Errors in ligand concentration will impact the enthalpy data.
00:33:28 Case study 5.Value of sample quality assurance in a large scale Structural Biology project
00:33:51 Introduction
00:35:09 Project setback. Incomplete data from thermal shift binding assays, DSF.
00:35:43 Due diligence of the quality of constructs and protein batches used in the project..
00:37:29 Profiling protein stability and homogeneity in solution.
00:38:57 Optimization of PARPs homogeneity with DLS and DSC
00:40:19 Enabling X-ray structure determination along the way.
00:41:02 Project setbacks waived and milestones reached through sample quality controls and stability optimization with DLS, DSC and ITC.
00:41:30 Untitled
00:41:44 SUMMARY
00:44:32 Join us for the 3rd European MicroCal – Bioscience meeting
00:45:27 Thank you for attending

Dynamic interactions involving biomolecules drive and regulate all biological processes, making interaction analysis a key area of academic and industrial research and development. A variety of biophysical techniques are used in this field, including Nuclear Magnetic Resonance (NMR), Isothermal Titration Calorimetry (ITC), biosensors (such as SPR and BLI) and fluorescence-based assays. 

Over the years, clear trends in interaction analysis have driven towards increased ease of use of the advanced techniques, despite the increasing complexity of biomolecules and binding modes being studied.
While methodologies and technologies in interaction analysis continue to evolve, one fundamental prerequisite to the success remains constant: good control over the quality of interacting species, their complexes, and conditions for the binding process. Overlooking this requirement could result in poor performance of a biophysical technique, misleading and irreproducible results and lack of convergence with orthogonal and complementary data generated in a project.

This presentation will give examples which highlight the need for ensuring sample quality and observing good experimental practices for the generation of meaningful and reliable binding data. Case study examples will be given to illustrate the impact of early in-solution profiling of the stability and homogeneity of biomolecules and ligands with: 

•    Dynamic Light Scattering (DLS)
•    Differential Scanning Calorimetry (DSC)
•    Multi-Detection Size Exclusion Chromatography (SEC) and
•    Taylor Dispersion Analysis (TDA) on the success of research projects in Drug Discovery.