| 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.