dorsal/arxiv
View SchemaStatistical Geometry of Packing Defects of Lattice Chain Polymer from Enumeration and Sequential Monte Carlo Method
| Authors | Jie Liang, Jinfeng Zhang, Rong Chen |
|---|---|
| Categories | |
| ArXiv ID | physics/0203015 |
| URL | https://arxiv.org/abs/physics/0203015 |
| DOI | 10.1063/1.1493772 |
Abstract
Voids exist in proteins as packing defects and are often associated with protein functions. We study the statistical geometry of voids in two-dimensional lattice chain polymers. We define voids as topological features and develop a simple algorithm for their detection. For short chains, void geometry is examined by enumerating all conformations. For long chains, the space of void geometry is explored using sequential Monte Carlo importance sampling and resampling techniques. We characterize the relationship of geometric properties of voids with chain length, including probability of void formation, expected number of voids, void size, and wall size of voids. We formalize the concept of packing density for lattice polymers, and further study the relationship between packing density and compactness, two parameters frequently used to describe protein packing. We find that both fully extended and maximally compact polymers have the highest packing density, but polymers with intermediate compactness have low packing density. To study the conformational entropic effects of void formation, we characterize the conformation reduction factor of void formation and found that there are strong end-effect. Voids are more likely to form at the chain end. The critical exponent of end-effect is twice as large as that of self-contacting loop formation when existence of voids is not required. We also briefly discuss the sequential Monte Carlo sampling and resampling techniques used in this study.
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"abstract": "Voids exist in proteins as packing defects and are often associated with\nprotein functions. We study the statistical geometry of voids in\ntwo-dimensional lattice chain polymers. We define voids as topological features\nand develop a simple algorithm for their detection. For short chains, void\ngeometry is examined by enumerating all conformations. For long chains, the\nspace of void geometry is explored using sequential Monte Carlo importance\nsampling and resampling techniques. We characterize the relationship of\ngeometric properties of voids with chain length, including probability of void\nformation, expected number of voids, void size, and wall size of voids. We\nformalize the concept of packing density for lattice polymers, and further\nstudy the relationship between packing density and compactness, two parameters\nfrequently used to describe protein packing. We find that both fully extended\nand maximally compact polymers have the highest packing density, but polymers\nwith intermediate compactness have low packing density. To study the\nconformational entropic effects of void formation, we characterize the\nconformation reduction factor of void formation and found that there are strong\nend-effect. Voids are more likely to form at the chain end. The critical\nexponent of end-effect is twice as large as that of self-contacting loop\nformation when existence of voids is not required. We also briefly discuss the\nsequential Monte Carlo sampling and resampling techniques used in this study.",
"arxiv_id": "physics/0203015",
"authors": [
"Jie Liang",
"Jinfeng Zhang",
"Rong Chen"
],
"categories": [
"physics.bio-ph",
"cond-mat.stat-mech",
"physics.chem-ph",
"q-bio"
],
"doi": "10.1063/1.1493772",
"title": "Statistical Geometry of Packing Defects of Lattice Chain Polymer from Enumeration and Sequential Monte Carlo Method",
"url": "https://arxiv.org/abs/physics/0203015"
},
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