Prediction of the binding free energies of new TIBO-like HIV-1 reverse transcriptase inhibitors using a combination of PROFEC, PB/SA, CMC/MD, and free energy calculations

We have ranked 13 different TIBO derivatives with respect to their relative free energies of binding using two approximate computational methods: adap tive chemical Monte Carlo/ molecular dynamics (CMC/MD) and Poisson-Boltzman n/solvent accessibility (PB/SA) calculations. Eight of these derivatives ha ve experimentally determined binding affinities. The remaining new derivati ves were constructed based on contour maps around R86183 (8Cl-TIBO), genera ted with the program PROFEC (pictorial representation of free energy change s). The rank order among the derivatives with known binding affinity was in good agreement with experimental results for both methods, with average er rors in the binding free energies of 1.0 kcal/mol for CMC/MD and 1.3 kcal/m ol for the PB/SA method. With both methods, we found that one of the new de rivatives was predicted to bind 1-2 kcal/mol better than R86183, which is t he hitherto most tightly binding derivative. This result was subsequently s upported by the most rigorous free energy computational methods: free energ y perturbation (FEP) and thermodynamic integration (TI). The strategy we ha ve used here should be generally useful in structure-based drug optimizatio n. An initial ligand is derivatized based on PROFEC suggestions, and the de rivatives are ranked with CMC/MD and PB/SA to identify promising compounds. Since these two methods rely on different sets of approximations, they ser ve as a good complement to each other. Predictions of the improved affinity can be reinforced with FEP or TI and the best compounds synthesized and te sted. Such a computational strategy would allow many different derivatives to be tested in a reasonable time, focusing synthetic efforts on the most p romising modifications.