The Role of Semaphorin 4D in Bone Remodeling and Cancer Metastasis

Semaphorin 4D (Sema4D; CD100) is a transmembrane homodimer 150-kDa glycoprotein member of the Semaphorin family. Semaphorins were first identified as chemorepellants that guide neural axon growth. Sema4D also possesses immune regulatory activity. Recent data suggest other Sema4D functions: inactivation of platelets, stimulation of angiogenesis, and regulation of bone formation. Sema4D is a coupling factor expressed on osteoclasts that inhibits osteoblast differentiation. Blocking Sema4D may, therefore, be anabolic for bone. Sema4D and its receptor Plexin-B1 are commonly dysregulated in cancers, suggesting roles in cancer progression, invasion, tumor angiogenesis, and skeletal metastasis. This review focuses on Sema4D in bone and cancer biology and the molecular pathways involved, particularly Sema4D-Plexin-B1 signaling crosstalk between cancer cells and the bone marrow microenvironment-pertinent areas since a humanized Sema4D-neutralizing antibody is now in early phase clinical trials in cancers and neurological disorders

Multistep Reaction Based De Novo Drug Design: Generating Synthetically Feasible Design Ideas

We describe a “multistep reaction driven” evolutionary algorithm approach to de novo molecular design. Structures generated by the approach include a proposed synthesis path intended to aid the chemist in assessing the synthetic feasibility of the ideas that are generated. The methodology is independent of how the design ideas are scored, allowing multicriteria drug design to address multiple issues including activity at one or more pharmacological targets, selectivity, physical and ADME properties, and off target liabilities; the methods are compatible with common computer-aided drug discovery “scoring” methodologies such as 2D- and 3D-ligand similarity, docking, desirability functions based on physiochemical properties, and/or predictions from 2D/3D QSAR or machine learning models and combinations thereof to be used to guide design. We have performed experiments to assess the extent to which known drug space can be covered by our approach. Using a library of 88 generic reactions and a database of ∼20 000 reactants, we find that our methods can identify “close” analogs for ∼50% of the known small molecule drugs with molecular weight less than 300. To assess the quality of the in silico generated synthetic pathways, synthesis chemists were asked to rate the viability of synthesis pathways: both “real” and in silico generated. In silico reaction schemes generated by our methods were rated as very plausible with scores similar to known literature synthesis schemes