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The Problem: Evolution produces systems that display remarkable structural and functional properties that can rival or exceed the performance of man-made systems. For example, protein molecules fold spontaneously into precise, well-ordered structures and can carry out specific binding, catalysis of difficult chemical reactions, and allosteric regulation. At a larger spatial scale, networks of proteins assemble to form metabolic and signaling systems that show efficient and selective processing of material and information. These performance characteristics can coexist with robustness to random perturbation and the capacity to adapt to new functional states as conditions of selection vary in the environment. The goal of our laboratory is to understand the design principles that underlie structure, function, and adaptation in biological systems. For maximal experimental and theoretical power, we focus at the atomic to cellular scale. The Strategy: Our approach is to break the problem down into three essential tasks: (1) to define the pattern of constraints that specify biological systems, (2) to determine the underlying physics, and (3) to understand the generative process that produces these (and not other) architectures. In other words, we wish to understand what nature has built, how it works, and why it is built the way it is. Answers to these core questions lie at the essence of understanding and engineering biological systems, and more fundamentally, to explain how they are even possible through the random, algorithmic process that we call evolution.
The Problem: Evolution produces systems that display remarkable structural and functional properties that can rival or exceed the performance of man-made systems. For example, protein molecules fold spontaneously into precise, well-ordered structures and can carry out specific binding, catalysis of difficult chemical reactions, and allosteric regulation. At a larger spatial scale, networks of proteins assemble to form metabolic and signaling systems that show efficient and selective processing of material and information. These performance characteristics can coexist with robustness to random perturbation and the capacity to adapt to new functional states as conditions of selection vary in the environment. The goal of our laboratory is to understand the design principles that underlie structure, function, and adaptation in biological systems. For maximal experimental and theoretical power, we focus at the atomic to cellular scale. The Strategy: Our approach is to break the problem down into three essential tasks: (1) to define the pattern of constraints that specify biological systems, (2) to determine the underlying physics, and (3) to understand the generative process that produces these (and not other) architectures. In other words, we wish to understand what nature has built, how it works, and why it is built the way it is. Answers to these core questions lie at the essence of understanding and engineering biological systems, and more fundamentally, to explain how they are even possible through the random, algorithmic process that we call evolution.
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Zenodo (CERN European Organization for Nuclear Research) (2024)
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Eugene Klyshko, Justin Sung-Ho Kim,Lauren McGough,Victoria Valeeva,Ethan Lee,Rama Ranganathan,Sarah Rauscher
bioRxiv : the preprint server for biologyno. 1 (2024): 3244-3244
Emre Sevgen,Joshua Moller, Adrian Lange, John Parker, Sean Quigley, Jeff Mayer, Poonam Srivastava,Sitaram Gayatri, David Hosfield,Maria Korshunova,Micha Livne,Michelle Gill,
biorxiv(2023)
biorxiv(2022)
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