Constraint-Based Hydrophobic Core Construction for Protein Structure Prediction in the Face-Centered-Cubic Lattice

نویسنده

  • Sebastian Will
چکیده

We present an algorithm for exact protein structure prediction in the FCC-HP-model. This model is a lattice protein model on the face-centered-cubic lattice that models the main force of protein folding, namely the hydrophobic force. The structure prediction for this model can be based on the construction of hydrophobic cores. The main focus of the paper is on an algorithm for constructing maximally and submaximally compact hydrophobic cores of a given size. This algorithm treats core construction as a constraint satisfaction problem (CSP), and the paper describes its constraint model. The algorithm employs symmetry excluding constraint-based search and relies heavily on good upper bounds on the number of contacts. Here, we use and strengthen upper bounds presented earlier. The resulting structure prediction algorithm (including previous work) handles sequences of sizes in the range of real proteins fast, i.e. we predict a first structure often within a few minutes. The algorithm is the first exact one for the FCC, besides full enumeration which is impracticable for chain lengths greater than about 15. We tested the algorithm successfully up to sequence length of 160, which is far beyond the capabilities even of previous heuristic approaches.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hybrid Local Search for Simplified Protein Structure Prediction

Protein structure prediction based on Hydrophobic-Polar energy model essentially becomes searching for a conformation having a compact hydrophobic core at the center. The hydrophobic core minimizes the interaction energy between the amino acids of the given protein. Local search algorithms can quickly find very good conformations by moving repeatedly from the current solution to its “best” neig...

متن کامل

Protein Structure Prediction with Large Neighborhood Constraint Programming Search

Protein structure predictions is regarded as a highly challenging problem both for the biology and for the computational communities. Many approaches have been developed in the recent years, moving to increasingly complex lattice models or even off-lattice models. This paper presents a Large Neighborhood Search (LNS) to find the native state for the Hydrophobic-Polar (HP) model on the Face Cent...

متن کامل

Neighborhood Selection in Constraint-Based Local Search for Protein Structure Prediction

Protein structure prediction (PSP) is a very challenging constraint optimization problem. Constraint-based local search approaches have obtained promising results in solving constraint models for PSP. However, the neighborhood exploration policies adopted in these approaches either remain exhaustive or are based on random decisions. In this paper, we propose heuristics to intelligently explore ...

متن کامل

Protein Structure Prediction on the Face Centered Cubic Lattice by Local Search

Ab initio protein structure prediction is an important problem for which several algorithms have been developed. Algorithms differ by how they represent 3D protein conformations (on-lattice, off-lattice, coarse-grain or fine-grain model), by the energy model they consider, and whether they are heuristic or exact algorithms. This paper presents a local search algorithm to find the native state f...

متن کامل

Two constraint-based tools for protein folding

Introduction. A protein is a list of linked units called aminoacids. There are 20 different kinds of aminoacids and the typical length of a protein is less than 500 units. The Protein Structure Prediction Problem (PSP) is the problem of predicting the 3D native conformation of a protein, when its aminoacid sequence is known. The process for reaching this state is called the protein folding. It ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

دوره   شماره 

صفحات  -

تاریخ انتشار 2002