The discipline of retrosynthetic analysis is now just over 40 years old. From the earliest day, attempts were made to incorporate this approach into computer programs to test the extent in which chemical perception and synthetic thinking could be formalized. Despite pioneering research efforts, computer‐aided synthetic analysis failed to achieve widespread routine use by chemists, which can be attributed in part to the difficulty of building the required high‐quality retrosynthetic transform databases required for credible analyses. However, with the advent over the past 25 years of large comprehensive reaction databases, work on successfully automating the construction of reliable and comprehensive reaction rule databases is promising to revitalize research in this field. This review compares and contrasts the diverse approaches taken by selected programs in both the design and implementation of molecule feature perception and reaction rule representation, and we review the concepts of synthetic strategy selection, representation, and execution. In particular, we discuss the current work on automating the construction of reliable and comprehensive synthetic rule sets from available reaction databases in newer programs such as ARChem. We argue that the progress achieved in this aspect paves the way to a deeper exploration of computer approaches to applying strategy and control in the synthesis problem. © 2011 John Wiley & Sons, Ltd. This article is categorized under: Computer and Information Science > Chemoinformatics

Conformation constraints and molecular flexibility strongly affect the bioactivity of flexible molecules. The present study offers a new conceptual framework, as well as a practical quantitative procedure, for discussing and quantifying these effects. The theory is formulated in terms of weighted overlaps between the volume in conformation space occupied by the flexible ligand and the pre-prescribed conformational requirements imposed by the host molecule (“region of bioactivity”). From this theory a quantitative structure activity relationship (QSAR) type descriptor, which quantifies the effect of conformation constraints on bioactivity, was derived and the resulting model was shown to be in excellent correlation with the observed activity of the molecules. Three characteristic scenarios for the relationship between flexibility and bioactivity are outlined and demonstrated in realistic systems:  conformationally constrained alanine hexapeptides, a series of substance P analogues, and a set of conformationally constrained Arg−Gly−Asp containing peptides.

No abstract

We present three complementary approaches for score-tuning that improve docking performance in pose prediction, virtual screening and binding affinity assessment. The methodology utilizes experimental data to customize the scoring function for the system of interest considering the specific docking scenario. The tuning approach, which has been implemented as an automated utility in eHiTS, is introduced as a solution to one of the conundrums of the molecular docking paradigm, namely, the lack of a universally well performing scoring function. The accuracy of scoring functions has been shown to be generally system-dependent, and particularly lacking for binding energy and bio-activity predictions. In the proposed approach, pose and energy predictions are enhanced by adjusting the relative weights of the eHiTS energy terms to improve score-RMSD or score-affinity correlations. In a virtual screening context ligand-based similarity is used to rescale the docking score such that better enrichment factors are achieved. We discuss the algorithmic details of the methods, and demonstrate the effects of score tuning on a variety of targets, including CDK2, BACE1 and neuraminidase, as well as on the popular benchmarks--the Directory of Useful Decoys and the PDBBind database.

No abstract