Validated ligand binding sites in CCK receptors. Next step: Computer aided design of novel CCK ligands

Computer-aided drug design becomes an important part of G-protein coupled receptors (GPCR) drug discovery process that is applied for improving the efficiency of derivation and optimization of novel ligands. It represents the combination of methods that-use-structural information of a receptor binding site of known ligands to design new ligands. In this report, we give a brief description of ligand binding sites in cholecystokinin and gastrin receptors (CK1R and CCK2R) which were delineated using experimental and computational methods, and then, we show how the validated ligand binding sites can be used to design and improve novel ligands. The translation of the knowledge of ligand-binding sites of different GPCRs to computer-aided design of novel ligands is summarized.

A Sensitivity Approach for Eliminating Clashes from Computer Aided Design Model Assemblies

Clashes occur when components in an assembly unintentionally violate others. If clashes are not identified and designed out before manufacture, product function will be reduced or substantial cost will be incurred in rework. This paper introduces a novel approach for eliminating clashes by identifying which parameters defining the part features in a computer aided design (CAD) assembly need to change and by how much. Sensitivities are calculated for each parameter defining the part and the assembly as the change in clash volume due to a change in each parameter value. These sensitivities give an indication of important parameters and are used to predict the optimum combination of changes in each parameter to eliminate the clash. Consideration is given to the fact that it is sometimes preferable to modify some components in an assembly rather than others and that some components in an assembly cannot be modified as the designer does not have control over their shape. Successful elimination of clashes has been demonstrated in a number of example assemblies.

Time Efficient Assessment and Feedback Methods for Large Computer-Aided-Design Cohorts

Timely and individualized feedback on coursework is desirable from a student perspective as it facilitates formative development and encourages reflective learning practice. Faculty however are faced with a significant and potentially time consuming challenge when teaching larger cohorts if they are to provide feedback which is timely, individualized and detailed. Additionally, for subjects which assess non-traditional submissions, such as Computer-Aided-Design (CAD), the methods for assessment and feedback tend not to be so well developed or optimized. Issues can also arise over the consistency of the feedback provided. Evaluations of Computer-Assisted feedback in other disciplines (Denton et al, 2008), (Croft et al, 2001) have shown students prefer this method of feedback to traditional “red pen” marking and also that such methods can be more time efficient for faculty.
Herein, approaches are described which make use of technology and additional software tools to speed up, simplify and automate assessment and the provision of feedback for large cohorts of first and second year engineering students studying modules where CAD files are submitted electronically. A range of automated methods are described and compared with more “manual” approaches. Specifically one method uses an application programming interface (API) to interrogate SolidWorks models and extract information into an Excel spreadsheet, which is then used to automatically send feedback emails. Another method describes the use of audio recordings made during model interrogation which reduces the amount of time while increasing the level of detail provided as feedback.
Limitations found with these methods and problems encountered are discussed along with a quantified assessment of time saving efficiencies made.

Designing computer architecture research workloads

MinneSPEC proposes reduced input sets that microprocessor designers can use to model representative short-running workloads. A four-step methodology verifies the program behavior similarity of these input sets to reference sets.