Roman V. Agafonov

Using ancient protein kinases to unravel a modern cancer drug’s mechanism

Evolution of dynamics affects function The drug Gleevac inhibits Abl kinases and is used to treat multiple cancers. The closely related Src kinases also play a role in cancer but are not inhibited effectively by Gleevac. Nevertheless, Gleevac-bound structures of Src and Abl are nearly identical. Based on this structural information and protein sequence data, Wilson et al. reconstructed the common ancestor of Src and Abl. Mutations that affected conformational dynamics caused Gleevac affinity to be gained on the evolutionary trajectory toward Abl and lost on the trajectory toward Src. Science, this issue p. 882 Characterization of ancestors of the kinases Src and Abl reveals why they respond differently to the cancer drug Gleevec. Macromolecular function is rooted in energy landscapes, where sequence determines not a single structure but an ensemble of conformations. Hence, evolution modifies a protein’s function by altering its energy landscape. Here, we recreate the evolutionary pathway between two modern human oncogenes, Src and Abl, by reconstructing their common ancestors. Our evolutionary reconstruction combined with x-ray structures of the common ancestor and pre–steady-state kinetics reveals a detailed atomistic mechanism for selectivity of the successful cancer drug Gleevec. Gleevec affinity is gained during the evolutionary trajectory toward Abl and lost toward Src, primarily by shifting an induced-fit equilibrium that is also disrupted in the clinical T315I resistance mutation. This work reveals the mechanism of Gleevec specificity while offering insights into how energy landscapes evolve.

Energetic dissection of Gleevec's selectivity toward human tyrosine kinases

Protein kinases are obvious drug targets against cancer, owing to their central role in cellular regulation. Since the discovery of Gleevec, a potent and specific inhibitor of Abl kinase, as a highly successful cancer therapeutic, the ability of this drug to distinguish between Abl and other tyrosine kinases such as Src has been intensely investigated but without much success. Using NMR and fast kinetics, we establish a new model that solves this longstanding question of how the two tyrosine kinases adopt almost identical structures when bound to Gleevec but have vastly different affinities. We show that, in contrast to all other proposed models, the origin of Abls high affinity lies predominantly in a conformational change after binding. An energy landscape providing tight affinity via an induced fit and binding plasticity via a conformational-selection mechanism is likely to be general for many inhibitors.

The energy landscape of adenylate kinase during catalysis

Kinases perform phosphoryl-transfer reactions in milliseconds; without enzymes, these reactions would take about 8,000 years under physiological conditions. Despite extensive studies, a comprehensive understanding of kinase energy landscapes, including both chemical and conformational steps, is lacking. Here we scrutinize the microscopic steps in the catalytic cycle of adenylate kinase, through a combination of NMR measurements during catalysis, pre-steady-state kinetics, molecular-dynamics simulations and crystallography of active complexes. We find that the Mg2+ cofactor activates two distinct molecular events: phosphoryl transfer (>105-fold) and lid opening (103-fold). In contrast, mutation of an essential active site arginine decelerates phosphoryl transfer 103-fold without substantially affecting lid opening. Our results highlight the importance of the entire energy landscape in catalysis and suggest that adenylate kinases have evolved to activate key processes simultaneously by precise placement of a single, charged and very abundant cofactor in a preorganized active site.

Evolutionary drivers of thermoadaptation in enzyme catalysis

With early life likely to have existed in a hot environment, enzymes had to cope with an inherent drop in catalytic speed caused by lowered temperature. Here we characterize the molecular mechanisms underlying thermoadaptation of enzyme catalysis in adenylate kinase using ancestral sequence reconstruction spanning 3 billion years of evolution. We show that evolution solved the enzyme’s key kinetic obstacle—how to maintain catalytic speed on a cooler Earth—by exploiting transition-state heat capacity. Tracing the evolution of enzyme activity and stability from the hot-start toward modern hyperthermophilic, mesophilic, and psychrophilic organisms illustrates active pressure versus passive drift in evolution on a molecular level, refutes the debated activity/stability trade-off, and suggests that the catalytic speed of adenylate kinase is an evolutionary driver for organismal fitness.

Conformational Selection in a Protein-Protein Interaction Revealed by Dynamic Pathway Analysis

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here, we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using nuclear magnetic resonance (NMR) spectroscopy, stopped-flow kinetics, and isothermal titration calorimetry, we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding.

A minor conformation of a lanthanide tag on adenylate kinase characterized by paramagnetic relaxation dispersion NMR spectroscopy

NMR relaxation dispersion techniques provide a powerful method to study protein dynamics by characterizing lowly populated conformations that are in dynamic exchange with the major state. Paramagnetic NMR is a versatile tool for investigating the structures and dynamics of proteins. These two techniques were combined here to measure accurate and precise pseudocontact shifts of a lowly populated conformation. This method delivers valuable long-range structural restraints for higher energy conformations of macromolecules in solution. Another advantage of combining pseudocontact shifts with relaxation dispersion is the increase in the amplitude of dispersion profiles. Lowly populated states are often involved in functional processes, such as enzyme catalysis, signaling, and protein/protein interactions. The presented results also unveil a critical problem with the lanthanide tag used to generate paramagnetic relaxation dispersion effects in proteins, namely that the motions of the tag can interfere severely with the observation of protein dynamics. The two-point attached CLaNP-5 lanthanide tag was linked to adenylate kinase. From the paramagnetic relaxation dispersion only motion of the tag is observed. The data can be described accurately by a two-state model in which the protein-attached tag undergoes a 23° tilting motion on a timescale of milliseconds. The work demonstrates the large potential of paramagnetic relaxation dispersion and the challenge to improve current tags to minimize relaxation dispersion from tag movements.

Evolution and intelligent design in drug development

Sophisticated protein kinase networks, empowering complexity in higher organisms, are also drivers of devastating diseases such as cancer. Accordingly, these enzymes have become major drug targets of the twenty-first century. However, the holy grail of designing specific kinase inhibitors aimed at specific cancers has not been found. Can new approaches in cancer drug design help win the battle with this multi-faced and quickly evolving enemy? In this perspective we discuss new strategies and ideas that were born out of a recent breakthrough in understanding the molecular basis underlying the clinical success of the cancer drug Gleevec. An “old” method, stopped-flow kinetics, combined with old enzymes, the ancestors dating back up to about billion years, provides an unexpected outlook for future intelligent design of drugs.

Dynamics of human protein kinase Aurora A linked to drug selectivity

Protein kinases are major drug targets, but the development of highly-selective inhibitors has been challenging due to the similarity of their active sites. The observation of distinct structural states of the fully-conserved Asp-Phe-Gly (DFG) loop has put the concept of conformational selection for the DFG-state at the center of kinase drug discovery. Recently, it was shown that Gleevec selectivity for the Tyr-kinase Abl was instead rooted in conformational changes after drug binding. Here, we investigate whether protein dynamics after binding is a more general paradigm for drug selectivity by characterizing the binding of several approved drugs to the Ser/Thr-kinase Aurora A. Using a combination of biophysical techniques, we propose a universal drug-binding mechanism, that rationalizes selectivity, affinity and long on-target residence time for kinase inhibitors. These new concepts, where protein dynamics in the drug-bound state plays the crucial role, can be applied to inhibitor design of targets outside the kinome.

Dynamics of human protein kinases linked to drug selectivity

Protein kinases are major drug targets, but the development of highly-selective inhibitors has been challenging due to the similarity of their active sites. The observation of distinct structural states of the fully-conserved Asp-Phe-Gly (DFG) loop has put the concept of conformational selection for the DFG-state at the center of kinase drug discovery. Recently, it was shown that Gleevec selectivity for the Tyr-kinases Abl was instead rooted in conformational changes after drug binding. Here, we investigate whether protein dynamics after binding is a more general paradigm for drug selectivity by characterizing the binding of several approved drugs to the Ser/Thr-kinase Aurora A. Using a combination of biophysical techniques, we propose a universal drug-binding mechanism, that rationalizes selectivity, affinity and long on-target residence time for kinase inhibitors. These new concepts, where protein dynamics in the drug-bound state plays the crucial role, can be applied to inhibitor design of targets outside the kinome. eLife digest The Ser/Thr kinase Aurora A is an important target for the development of new anticancer therapies. A longstanding question is how to specifically and effectively inhibit only this kinase in a background of over 550 protein kinases with very similar structures. To this end, understanding the inhibition mechanism of Aurora A by different drugs is essential. Here, we characterize the kinetic mechanism of three distinct kinase drugs, Gleevec (Imatinib), Danusertib (PHA739358) and AT9283 (Pyrazol-4-yl Urea) for Aurora A. We show that inhibitor affinities do not rely exclusively on the recognition of a specific conformation of the Asp-Phe-Gly loop of the kinase. Our quantitative kinetics data put forward an opposing mechanism in which a slow conformational change after drug binding (i.e., induced-fit step) dictates drug affinity.

Drug targets evolve, and so should the methods

ABSTRACT Design of specific kinase inhibitors is an appealing approach for developing new anticancer treatments. However, only a few success stories have been reported to date. Here we demonstrate how the combination of old-fashioned and new biophysical tools together with recent advances in genomics and molecular evolution can aid in overcoming existing limitations.