Cyanovirin-N (CV-N) is an antiviral lectin with potent activity against enveloped viruses, including HIV. The mechanism of action involves high affinity binding to mannose-rich glycans that decorate the surface of enveloped viruses. In the case of HIV, antiviral activity of CV-N is postulated to require multivalent interactions with envelope protein gp120, achieved through a pseudo-repeat of sequence that adopts two near-identical glycan-binding sites, and possibly involves a 3D-domain-swapped dimeric form of CV-N. Here, we present a covalent dimer of CV-N that increases the number of active glycan-binding sites, and we characterize its ability to recognize four glycans in solution. A CV-N variant was designed in which two native repeats were separated by the “nested” covalent insertion of two additional repeats of CV-N, resulting in four possible glycan-binding sites. The resulting Nested CV-N folds into a wild-type-like structure as assessed by circular dichroism and NMR spectroscopy, and displays high thermal stability with a T_m of 59 °C, identical to WT. All four glycan-binding domains encompassed by the sequence are functional as demonstrated by isothermal titration calorimetry, which revealed two sets of binding events to dimannose with dissociation constants K_d of 25 μM and 900 μM, assigned to domains B and B’ and domains A and A’ respectively. Nested CV-N displays a slight increase in activity when compared to WT CV-N in both an anti-HIV cellular assay and a fusion assay. This construct conserves the original binding specifityies of domain A and B, thus indicating correct fold of the two CV-N repeats. Thus, rational design can be used to increase multivalency in antiviral lectins in a controlled manner.

Myxoma virus (MYXV) is Leporipoxvirus that possesses a specific rabbit‐restricted host tropism but exhibits a much broader cellular host range in cultured cells. MYXV is able to efficiently block all aspects of the type I interferon (IFN)‐induced antiviral state in rabbit cells, partially in human cells and very poorly in mouse cells. The mechanism(s) of this species‐specific inhibition of type I IFN‐induced antiviral state is not well understood. Here we demonstrate that MYXV encoded protein M029, a truncated relative of the vaccinia virus (VACV) E3 double‐stranded RNA (dsRNA) binding protein that inhibits protein kinase R (PKR), can also antagonize the type I IFN‐induced antiviral state in a highly species‐specific manner. In cells pre‐treated with type I IFN prior to infection, MYXV exploits M029 to overcome the induced antiviral state completely in rabbit cells, partially in human cells, but not at all in mouse cells. However, in cells pre‐infected with MYXV, IFN‐induced signaling is fully inhibited even in the absence of M029 in cells from all three species, suggesting that other MYXV protein(s) apart from M029 block IFN signaling in a speciesindependent manner. We also show that the antiviral state induced in rabbit, human or mouse cells by type I IFN can inhibit M029‐knockout MYXV even when PKR is genetically knocked‐out, suggesting that M029 targets other host proteins for this antiviral state inhibition. Thus, the MYXV dsRNA binding protein M029 not only antagonizes PKR from multiple species but also blocks the type I IFN antiviral state independently of PKR in a highly species‐specific fashion.

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic Model 2, it can fit clinical data to a greater precision. However, we found that Model 2 can forecast future PSA levels more accurately. These findings suggest that including more realistic mechanisms of androgen dynamics in a two population model may help androgen resistance timing prediction.

Background:
Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor.

Results:
We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise.

Conclusions:
The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling.