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Scoring Function based on Neighbourhood Preference Statistics

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NEPRE--CodePackage

LiuLab | Article | Code Package

Introduction

Nepre is a scoring function for calculating the protein's potential energy. And it will help to predict the 3D structure of a protein. Nepre is designed to be efficient, flexible and protable with two algorithms included:

  • Calculate the potential energy using fixed cutoff (Nepre-F).
  • Calculate the potential energy using the cutoff defined by the radius of amino acid (Nepre-R).

Nepre-F

Users can use the distance cutoff between 4 angstrom and 10 angstrom to calculate the potential energy (distance cutoff=6A is recommended).

Nepre-R

High-resolution protein structures are used to get statistical result of radius distributions and fitted by gaussian function. Then Nepre will calculate the potential energy according to the mean value of radius of each amino acid type.

Installation

The Nepre is implemented with Python 2.7, and the installation is straightforward. It can be downloaded and executed if numpy modules are installed in the python environment.

The required package is numpy.

The usage for Nepre-F and Nepre-R can be found in the corresponding folders (Cutoff & Radius).

CopyRight

Nepre is created by LiuLab of Beijing Computation Science Research Center(CSRC).

Status

Nepre is built completely on python2.7. The support to Python 3.x will be added soon.

Contact Us

Email: [email protected]
Address: Building 9, East Zone, ZPark II, No.10 East Xibeiwang Road, Haidian District, Beijing 100193, China.

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