Drug combinations may exhibit synergistic or antagonistic effects. Rational design of synergistic drug combinations remains a challenge despite active experimental and computational efforts. Because drugs manifest their action via their targets, the effects of drug combinations should depend on the interaction of their targets in a network manner. We therefore modeled the effects of drug combinations along with their targets interacting in a network, trying to elucidate the relationships between the network topology involving drug targets and drug combination effects. We used three-node enzymatic networks with various topologies and parameters to study two-drug combinations. These networks can be simplifications of more complex networks involving drug targets, or closely connected target networks themselves. We found that the effects of most of the combinations were not sensitive to parameter variation, indicating that drug combinational effects largely depend on network topology. We then identified and analyzed consistent synergistic or antagonistic drug combination motifs. Synergistic motifs encompass a diverse range of patterns, including both serial and parallel combinations, while antagonistic combinations are relatively less common and homogenous, mostly composed of a positive feedback loop and a downstream link. Overall our study indicated that designing novel synergistic drug combinations based on network topology could be promising, and the motifs we identified could be a useful catalog for rational drug combination design in enzymatic systems.

Adult stem cells play an important role in maintaining tissue homeostasis. Although these cells are found in many tissues, the presence of stem cells in the human minor salivary glands is not well explored. Using the explant culture method, we isolated a population of cells with self-renewal and differentiation capacities harboring that reside in the human minor salivary glands, called human minor salivary gland mesenchymal stem cells (hMSGMSCs). These cells show embryonic stem cell and mesenchymal stem cell phenotypes. Our results demonstrate that hMSGMSCs have the potential to undergo mesodermal, ectodermal and endodermal differentiation in conditioned culture systems in vitro. Furthermore, in vivo transplantation of hMSGMSCs into SCID mice after partial hepatectomy shows that hMSGMSCs are able to survive and engraft, characterized by the survival of labeled cells and the expression of the hepatocyte markers AFP and KRT18. These data demonstrate the existence of hMSGMSCs and suggest their potential in cell therapy and regenerative medicine.

In this Perspective, we focus on new, systems-centric views of structure-based drug design (SBDD) that we believe will impact future drug discovery research and development. We will first discuss new ways to identify drug targets based on systems intervention analysis, and then we will introduce emerging SBDD methods driven by advancements in systems biology.

Binding kinetics is closely related to the efficacy of drugs. Several aspects of binding kinetics, such as long residence or frequent dissociation, have been proposed to affect drug properties such as efficacy, selectivity, and multi-target potency. However, a comprehensive and balanced study of binding kinetics in various scenarios is still needed. We performed a comprehensive computational analysis of the role of drug binding kinetics in various situations such as enzyme inhibition, receptor binding, multi-target drug targeting, signal transduction pathways, and metabolic networks. Molecular studies of enzyme inhibition, receptor binding, and multi-target drugs have shown that at constant binding affinity, fast associating drugs show better enzyme inhibitory effects, earlier and higher receptor occupancy peaks, and better multi-target performances, while slow dissociating drugs show prolonged receptor occupancy, as suggested by others. Different situations exemplify slightly different kinetic-efficacy relationships, and each must be considered separately. At the systems level, binding kinetics can not only change the overall effect of drugs, but can also affect signaling dynamics. For example, in the tumor necrosis factor α-induced nuclear factor-κB pathway, inhibitor addition can delay the onset of oscillations and decrease their frequencies, with these changes varying with the binding kinetics of the inhibitor. The effects of drug binding kinetics also depend on network topology and where the target is located in the network. For successful drug discovery, both molecular binding kinetics and systems level requirements need to be considered.