Free Energy Calculation Methodologies In Drug Resistance Mechanism Analyses And Implications For Genetic Diseases Treatment

It is well known that chemical drugs play vital role in the treatments of various diseases. However, the continuous use of some drugs may eventually lead to the decrease or even loss of efficacy, namely drug resistance. The main reason for drug resistance may be attributed to the mutations of drug targets, which usually leads to the decreased binding affinities of some drugs. Due to the continuous occurrence of drug resistance, it becomes an inevitable question on how to elucidate the mechanisms of drug resistance for the purpose of anti-resistant drug design. Although the X-ray crystal diffraction and NMR techniques can provide the 3-D structure of a drug-target complex, it is difficult or even impossible to crystallize all the mutated structures when facing up a large number of drug resistant mutants. With the rapid development of theoretical approaches and computational power, molecular simulations have become indispensable tools for the studies of drug resistance mechanisms. Here, by using various free energy calculation methodologies, we revealed the drug resistance mechanisms for two kinase systems and proposed a chemical strategy for the treatment of genetic diseases caused by “gain of function” or “loss of function” mutations in some drug targets.There are currently numerous free energy calculation approaches with various accuracies and also system-dependence, and therefore it is quite necessary to evaluate the performance of those approaches. Here, we firstly evaluated the performance of the currently widely used two-end-state free energy calculation approach, MM/PB(GB)SA, and proposed some suggestions to improve the prediction accuracy when using this approach. Afterward, we proposed a computational strategy by combining conventional molecular docking and MM/PB(GB)SA rescoring. The results show that, in most cases, the MM/GBSA rescoring can enhance the prediction accuracy of molecular docking.By using the proposed computational strategy, we investigated the drug resistance mechanisms for two systems: crizotinib-ALK(three mutants) and crizotinib-ROS1(one mutant). To the ALK system, the two-end-state calculations show that the mutations L1152 R and G1202 R have substantial effects on the conformational entropy of the ligand binding. And all the three mutations(L1152R, G1202 R, and S1206Y) can weaken the hydrogen bonding interactions between crizotinib and the wild-type ALK, thereafter leading to drug resistance. Besides, we have also investigated and compared the unbinding pathways between the wild-type and three mutated crizotinib-ALK systems by using enhanced sampling simulations(ABF). The results illustrates that both G1202 R and S1206 Y mutations can hinder the binding of crizotinib to the binding channel outside of the ALK binding pocket, and thereby cause drug resistance on their binding/unbinding process. As for the system of ROS1, we have characterized the 2-D free energy surface of the crizotinib binding/unbinding process by using advanced free energy calculation approaches(funnel based metadynamics and absolute binding free energy calculation based on umbrella sampling). We found that the enlarged P-loop region of the G2032 R mutant resulted in the remarkable decrease of the residence time of crizotinib(characterized by the flatted free energy surface), and therefore induced seriously drug resistance.Finally, we analyzed the effects of the genetic diseases associated mutations on drugs binding and proposed a chemical strategy for the treatment of genetic diseases. The principle of the strategy is that inherited diseases arising from gain-of-function(GOF) or loss-of-function(LOF) mutations of certain genes can be ameliorated by the antagonists and/or agonists of the target genes. However, a premise for this chemical therapeutic strategy is that the GOF/LOF mutations in drug targets have negligible influence on drug-target binding. Hence, we evaluated the genetic diseases associated mutations on drugs binding using the molecular docking and MM/GBSA rescoring strategy. The result shows that, in most cases, there is negligible effect of the disease-associated mutations on the drugs binding. And at the same time, we note that there are currently 20~50% investigated drugs having been clinically tested or used in the treatment of the associated genetic diseases, supporting the chemical strategy for combating genetic diseases.