Name
Abstract | ||
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Proteins are the fundamental building blocks of all biological systems. To perform their function, proteins generally undergo self-motions that result in changes in their three- dimensional shape. In order to understand the function of a protein and thus to be able to infer how to therapeutically regulate its function, it is necessary to have detailed knowledge of the feasible self-motions of the protein. Such knowledge cannot be obtained by existing experimental methods. In this paper, we present preliminary evidence that accurate and computationally efficient simulation of the self-motions of a protein may be achieved by partitioning the simulation based on the type of self-motions. In support of this view, we present a method and accompanying simulation results that the large- scale motions of a protein can be simulated based entirely on kinematic considerations. The proposed method leverages insights from kinematics and operational space control from robotics. We believe the proposed method to be a first step towards a general, accurate, and efficient method for the simulation of protein motion. I. INTRODUCTION Proteins perform the majority of cellular functions in all living organisms. They do so by binding to other pro- teins or molecules—or by breaking such a binding. For two molecules to bind to each other, they have to exhibit geometric and physicochemical complementarity at the in- teraction surface. To achieve this level of complementarity, most proteins change their shape during the binding process. Establishing and breaking bindings among proteins and other biomolecules is responsible for almost all cellular functions, including metabolism, transport of nutrients, synthesis of proteins, signaling, and gene regulation. Our research is concerned with the internal motions performed by proteins and their bindings with other biomolecules. Fig. 1 shows an example of a protein that undergoes self-motions to perform its function. Because protein motion is so fundamental to many cellular processes, an accurate understanding of protein motion would bring about tremendous scientific advances: It would facilitate the design of drugs to cure or treat many diseases, it would shed light onto some of the cellular processes that remain poorly understood, and it would provide insights into the mechanisms that underlie diseases such as Alzheimer's, Mad Cow disease, and Creutzfeldt-Jakob disease. Experimental techniques available today cannot observe the motion of proteins directly—they are only able to mea- sure secondary phenomena that arise as a consequence of the |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CDC.2007.4434801 | New Orleans, LA |
Keywords | Field | DocType |
biology computing,proteins,biological systems,computationally efficient simulation,kinematic consideration,large-scale motions,mechanistic view,protein motion | Kinematics,Computer science,Theoretical computer science,Artificial intelligence,Mechanism (philosophy),Robotics,Operational space control | Conference |
ISSN | ISBN | Citations |
0191-2216 E-ISBN : 978-1-4244-1498-7 | 978-1-4244-1498-7 | 0 |
PageRank | References | Authors |
0.34 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Filip Jagodzinski | 1 | 71 | 14.83 |
| Oliver Brock | 2 | 38 | 1.86 |