Doeke Romke Hekstra
Department of Molecular and Cellular Biology, Harvard University
Structural biology has dramatically changed our understanding of the molecular processes underlying life. But, we still do not understand how and why molecular machines work the way they do in terms of their motions, energetics, and excited states. The central aim of my current research is to understand the mechanical basis of protein function, that is, the collective motions and the forces that guide these motions, enabling the conformational and energetic changes required for functional transitions. In addition, my long-term interest is in understanding how these mechanical properties originate in the evolutionary process, and how they, in turn, guide future evolution.
In combination with conventional biophysical techniques, I intend to address these aims using an experimental method for which I provided proof of concept in my postdoctoral work. The method, “EF-X”, combines the use of strong electric field (EF) pulses with time-resolved X-ray crystallography to exert precise, controlled patterns of force (piconewtons) on proteins and to read out the resulting motions in fine detail across the protein.
Mechanical models of proteins based on experiments. A first step along the way is to develop an experimental strategy for separating protein motions into discrete modes. This will require technical developments, for example expanding the accessible range of time scales by EF-X, and a series of systematic measurements on protein crystals on different time scales, along perpendicular directions, the use of charge mutants, etc. To make the measurements quantitative, we will also develop calibration methods, using linear electric field effects in spectroscopy and/or electron paramagnetic resonance.
This work will also have a substantial theoretical component, as it is, in my view, an open challenge to develop quantitative mechanical models of proteins that are sufficiently succint that they can be compared to, and ideally refined iteratively by, experiment.
Relating physics to function. A second step is to learn how best to identify those mechanical properties of proteins that concern the reaction coordinate, that is, to determine which motions are important. Using a few well-studied enzymes, I want to determine the merits of a forward approach (from physical model to predicted functional motions), a reverse approach (seeing which motions are disrupted by functional mutants), and a comparative approach (seeing which motions are evolutionarily conserved).
Applications. I am interested in applying these methods to a number of basic questions. First, how are natural, evolved proteins different from (more) random sequences of amino acids, even those that adopt a ‘native fold’? Do their properties depend on their evolutionary history? Can we test this dependence by laboratory ‘forward evolution’? Do the mechanical properties of proteins restrict their future evolution? Human-designed enzymes are still many orders of magnitude less efficient than natural enzymes, but the causes of this (partial) failure are subject to debate. Quite conceivably, the low-energy states of “rational enzymes” are well designed, but not the conformational fluctuations around these states. Are the mechanical properties of these designed proteins different? Does subsequent evolution make them more natural-like?
With this research program, I hope to arrive at a description of functional proteins that captures the interplay of evolutionary and physical causality: why and how proteins work.
D.R. Hekstra, K.I. White, M.A. Socolich, R. Henning, V. Šrajer and R. Ranganathan, Electric field-stimulated protein mechanics, Nature, 540: 400-405, 2016.
M.A. Stiffler, D.R. Hekstra and R. Ranganathan, "Evolvability as a Function of Purifying Selection in TEM-1 β-lactamase", Cell, 160 (5): 882-892, 2015.
D.R. Hekstra, S. Cocco, R. Monasson and S. Leibler, "Trend and fluctuations: Analysis and design of population dynamics measurements in replicate ecosystems", Physical Review E, 88: 062714, 2013.
D.R. Hekstra and S. Leibler, “Contingency and Statistical Laws in Replicate Microbial Closed Ecosystems”, Cell, 149 (5): 1164-1173, 2012.
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