Abstract
Oncogenic mutations in the kinase domain of the B-Raf protein have long been associated with cancers involving the MAPK pathway (RAF-MEK-ERK). One constitutive ERK activating mutation in B-Raf, the V600E (valine to glutamate) replacement occurring adjacent to a site of threonine phosphorylation (T599) occurs in many types of cancer, and in a large percentage of certain cancers, such as melanoma. Because natural ATP binding activity and the V600E mutation are both known to alter the physical behavior of the activation loop in the B-Raf ATP binding domain, this system is especially amenable to comparative analyses of all-atom molecular dynamics simulations modeling the various genetic and drug class variants. Here, we employ machine learning enabled identification of functionally conserved protein dynamics to compare how the binding interactions of four B-Raf inhibitors differently impact the functional loop dynamics controlling ATP activation of B-Raf in the MAPK pathway. We demonstrate that drug development targeting B-Raf has progressively moved towards ATP competitive inhibitors that demonstrate less tendency to mimic the functionally conserved dynamic shifts associated with ATP binding in this domain. We argue that a functional dynamic mimicry of ATP by first generation B-Raf inhibitors increases the side effect of hyperactivation (i.e. inducing MAPK activation in non-tumorous cells in the absence of secondary mutation). Within the context of the binding interaction of each inhibitor, we compare the functional dynamic impacts of V600E and other sensitizing and drug resistance causing mutations in the activation and P-loops, confirming sites of low mutational tolerance in these two functional regions. Lastly, we investigate V600E sensitivity of B-Raf loop dynamics in an evolutionary context, demonstrating that while it has an ancient origin with primitive eukaryotes, the functional sensitivity to V600E was also secondarily increased during early jawed vertebrate evolution.
Author Summary Our lab has recently developed a combined simulation-based and machine learning method and user-friendly software for identifying dynamic motions in proteins that are preserved over evolutionary time scales (i.e. are functionally conserved). Our method also can assess how genetic or chemical variation affects these functionally conserved motions. Here, we utilize this approach to computationally demonstrate how one of the most common mutations that arise in tumors, the V600E B-Raf protein mutation, disrupts the functioning of protein loop dynamics responsible for normal regulation of the oncogenic B-Raf protein and its growth signaling pathway. We demonstrate that cancer recurrence in the absence of new mutations may be caused by drug interactions impacting these dynamics. We propose that mimicry of the functional dynamics of natural chemical activators (i.e. agonists) by many cancer targeting drugs may be a potent causal factor in recurrence of cancer in the absence of secondary mutation. By combining comparative modeling of molecular dynamics and analyses of molecular evolution, we also demonstrate that the unusual sensitivity of B-Raf protein regulatory loop dynamics to this mutation has an ancient evolutionary origin.
Competing Interest Statement
The authors have declared no competing interest.
List of abbreviations
- FDM
- functional dynamic mimicry
- MD
- molecular dynamic (simulation)
- GPU
- graphic processor unit
- PDB
- Protein Data Bank
- NCBI
- National Center for Biotechnology Information
- BRAF
- B-Raf gene sequence
- B-Raf
- protein product of BRAF gene
- ATP
- adenosine triphosphate
- DNA
- deoxyribonucleic acid
- MAPK
- mitogen-activated protein kinase
- BRAFi
- B-Raf inhibitor
- V600E
- valine to glutamic acid mutation and position 600
- CR1 CR2 CR3
- conserved region 1, 2, or 3
- KD
- kinase domain
- P-loop
- ATP stabilizing loop
- KL divergence
- Kullback-Leibler divergence
- dFLUX
- change in atom fluctuation or rmsf
- rmsf
- root mean square fluctuation
- CC
- canonical correlation
- DROIDS
- software acronym for ‘detecting outlier impacts in dynamic simulation’, our software package for comparative protein dynamics simulation
- maxDemon
- software acronym for ‘Maxwell’s demon’, our machine learning application for DROIDS