Iterative binding refinement

THEDA employs a two-phase approach constructive binding and iterative binding refinement. The former phase[8] vertically divides the task into three subtasks and solve them separately. It uses cost functions to predict the impact caused by one subtask on the other. The later phase[9] refines the data path by globally evaluating and improving each individual binding decision. 

The library was tested using a known competition assay (142), and binding activities for the 30 pools were acquired. While the pool complexity was low, as was therefore the possibility of false positives/artifacts, the extreme similarity of all the library components with known calcium channel blockers (compare the monomers in Fig. 7.19 leading to nifedipine. Mi = A, M2 = K, M3 = T, with all the others) meant a constant level of activity was to be expected for all pools. For such a small focused library, parallel synthesis would probably have been more suitable to acquire a refined SAR, but we will see how iterative deconvolution succeeded anyway in both identifying active individuals and showing significant activity differences for different pools. The screening results are reported in Table 7.1. Five pools showed activity > 1 xM, 12 pools had an activity between 100 nM and 1 xM, and 11 pools were active between 10 and 100 nM. Two pools showed an activity around 7-8 nM They both contained methyl acetoacetate (M2, K) as well as 2-fluorobenzaldehyde (M3, P) and 2-nitroben-zaldehyde (M3, T), respectively. 

In this chapter, we will present the processor synthesis part of THEDA. The general design consideration is described in Section 2. The target architecture is described in Section 3. Scheduling is described in Section 4. Constructive and iterative refined approaches to the data path binding problem are described in Section 5. Finally, we conclude with a summary. 

The objective of data path refinement is to improve the data path produced by the constructive binding phase. It iteratively rips up and relocates a cluster of... 

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