feature Should medicinal chemists do molecular modelling?

In this article we discuss the pros and cons of medicinal chemists undertaking three-dimensional (3D) computer-aided Q2 drug design (CADD) activities for themselves, from the viewpoint of both medicinal chemists and computational chemists. We describe how best this can be implemented, the potential benefits that can be obtained and the pitfalls that are often encountered. It is not common practice for a computational chemist or molecular modeller to leave his or her workstation, don a white coat and perform organic chemistry experiments in a medicinal chemistry lab. Indeed many people would consider this to be rather reckless behaviour. Conversely there has always been a school of thought that medicinal chemists should carry out, to a greater or lesser extent, some elements of computer-aided drug design (CADD) for themselves, but is this suggestion just as reckless? In this article we discuss the reasoning behind this approach, how it could be implemented and the potential advantages and pitfalls that can accompany this endeavour. Medicinal chemists use computer programs on a daily basis during the course of their work, for example to generate experiments in an electronic laboratory notebook, perform database searches, retrieve biological test results, calculate physicochemical properties and generate plots to examine structure-activity relationships. When chemical structures are involved, they are usually considered in two dimensions. For the purposes of this article, the definition of CADD will not cover such activities, but rather focus on computational approaches using three-dimensional (3D) molecular structures, such as conformational analysis, molecular overlays, pharmacophore modelling and searching, ligand-protein docking, among others. A comprehensive review of CADDrelated software and resources has recently been publishe

Phylogenomics and the rise of the angiosperms.

Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins5-7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes8. This 15-fold increase in genus-level sampling relative to comparable nuclear studies9 provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade