Modeling the Potential of Treg-Based Therapies for Transplant Rejection: Effect of Dose, Timing, and Accumulation Site

Introduction: The adoptive transfer of regulatory T cells (Tregs) has emerged as a method to promote graft tolerance. Clinical trials have demonstrated the safety of adoptive transfer and are now assessing their therapeutic efficacy. Strategies that generate large numbers of antigen specific Tregs are even more efficacious. However, the combinations of factors that influence the outcome of adoptive transfer are too numerous to be tested experimentally. Here, mathematical modeling is used to predict the most impactful treatment scenarios. Methods: We adapted our mathematical model of murine heart transplant rejection to simulate Treg adoptive transfer and to correlate therapeutic efficacy with Treg dose and timing, frequency of administration, and distribution of injected cells. Results: The model predicts that Tregs directly accumulating to the graft are more protective than Tregs localizing to draining lymph nodes. Inhibiting antigen-presenting cell maturation and effector functions at the graft site was more effective at modulating rejection than inhibition of T cell activation in lymphoid tissues. These complex dynamics define non-intuitive relationships between graft survival and timing and frequency of adoptive transfer. Conclusion: This work provides the framework for better understanding the impact of Treg adoptive transfer and will guide experimental design to improve interventions.

DYNAMICAL MODEL OF IN-HOST HIV INFECTION: WITH DRUG THERAPY AND MULTI VIRAL STRAINS

In this paper, a mathematical model for the effect of drug therapy on the in-host dynamics of HIV is considered and analyzed. As the process of reverse transcription is highly error prone, it causes mutation of virus which results in the emergence of drug resistant virus. This is also accounted in the model and corresponding model with both drug resistant and drug sensitive viral strains is studied. We found that, if reproductive ratios for both the strains are less than one, the virus population goes to extinction. If the reproductive ratio of either strain is greater than one and the reproductive ratio of drug resistant virus is smaller than that of drug sensitive virus then both the virus strains persist and infection is not cleared. However if reproductive ratio of drug resistant virus is greater than that of drug sensitive virus then the drug resistant virus out-competes the drug sensitive virus and only drug resistant virus survives. Hence the ratio of two reproduction ratios works as invading capacity threshold value for drug resistant strain. We also noted that by increasing the effective efficacy of the drug, virus may be cleared. Numerical simulations are performed to support and elaborate the analytical findings.

Optimal control of HIV-virus dynamics

In this paper we consider a mathematical model of HIV-virus dynamics and propose an efficient control strategy to keep the number of HIV virons under a pre-specified level and to reduce the total amount of medications that patients receive. The model considered is a nonlinear third-order model. The third-order model describes dynamics of three most dominant variables: number of healthy white blood cells (T-cells), number of infected T-cells, and number of virus particles. There are two control variables in this model corresponding to two categories of antiviral drugs: reverse transcriptase inhibitors (RTI) and protease inhibitors (PI). The proposed strategy is based on linearization of the nonlinear model at the equilibrium point (steady state). The corresponding controller has two components: the first one that keeps the system state variables at the desired equilibrium (set-point controller) and the second-one that reduces in an optimal way deviations of the system state variables from their desired equilibrium values. The second controller is based on minimization of the square of the error between the actual and desired (equilibrium) values for the linearized system (linear-quadratic optimal controller). The obtained control strategy recommends to HIV researchers and experimentalists that the constant dosages of drugs have to be administrated at all times (set point controller, open-loop controller) and that the variable dosages of drugs have to be administrated on a daily basis (closed-loop controller, feedback controller).

How can (-)-epigallocatechin gallate from green tea prevent HIV-1 infection? Mechanistic insights from computational modeling and the implication for rational design of anti-HIV-1 entry inhibitors

Possible inhibitors preventing human immunodeficiency virus type 1 (HIV-1) entry into the cells are recognized as hopeful next-generation anti-HIV-1 drugs. It is highly desirable to develop a potent inhibitor blocking binding of glycoprotein CD4 of the cell with glycoprotein gp120 of HIV-1, because the gp120-CD4 binding is the initial step of HIV-1 entry into the cells. It has been recently reported that (-)-epigallocatechin gallate (EGCG) from green tea is an inhibitor blocking gp120-CD4 binding. But the inhibitory mechanism remains unknown. For understanding the inhibitory mechanism, extensive molecular docking, molecular dynamics simulations, and binding free-energy calculations have been performed in this study to predict the most favorable structures of CD4-EGCG, gp120-CD4, and gp120-CD4-EGCG binding complexes in water. The results reveal that EGCG binds with CD4 in such a way that the calculated binding affinity of gp120 with the CD4-EGCG complex is negligible. So, the favorable binding of EGCG with CD4 can effectively block gp120-CD4 binding. The calculated CD4-EGCG binding affinity (DeltaG(bind) = -5.5 kcal/mol, K(d) = 94 microM) is in excellent agreement with available experimental data suggesting IC(50) approximately 100 microM for EGCG-blocking CD4-gp120 binding. These results and insights provide a rational basis for future design of novel, more potent inhibitors to block gp120-CD4 binding.