APoc: large-scale identification of similar protein pockets
نویسندگان
چکیده
MOTIVATION Most proteins interact with small-molecule ligands such as metabolites or drug compounds. Over the past several decades, many of these interactions have been captured in high-resolution atomic structures. From a geometric point of view, most interaction sites for grasping these small-molecule ligands, as revealed in these structures, form concave shapes, or 'pockets', on the protein's surface. An efficient method for comparing these pockets could greatly assist the classification of ligand-binding sites, prediction of protein molecular function and design of novel drug compounds. RESULTS We introduce a computational method, APoc (Alignment of Pockets), for the large-scale, sequence order-independent, structural comparison of protein pockets. A scoring function, the Pocket Similarity Score (PS-score), is derived to measure the level of similarity between pockets. Statistical models are used to estimate the significance of the PS-score based on millions of comparisons of randomly related pockets. APoc is a general robust method that may be applied to pockets identified by various approaches, such as ligand-binding sites as observed in experimental complex structures, or predicted pockets identified by a pocket-detection method. Finally, we curate large benchmark datasets to evaluate the performance of APoc and present interesting examples to demonstrate the usefulness of the method. We also demonstrate that APoc has better performance than the geometric hashing-based method SiteEngine. AVAILABILITY AND IMPLEMENTATION The APoc software package including the source code is freely available at http://cssb.biology.gatech.edu/APoc.
منابع مشابه
Effects of the difference in similarity measures on the comparison of ligand-binding pockets using a reduced vector representation of pockets
Comprehensive analysis and comparison of protein ligand-binding pockets are important to predict the ligands which bind to parts of putative ligand binding pockets. Because of the recent increase of protein structure information, such analysis demands a fast and efficient method for comparing ligand binding pockets. Previously we proposed a fast alignment-free method based on a simple represent...
متن کاملComprehensive identification of "druggable" protein ligand binding sites.
We have developed a new computational algorithm for de novo identification of protein-ligand binding pockets and performed a large-scale validation of the algorithm on two systematically collected datasets from all crystallographic structures in the Protein Data Bank (PDB). This algorithm, called DrugSite, takes a three-dimensional protein structure as input and returns the location, volume and...
متن کاملPocketome via comprehensive identification and classification of ligand binding envelopes.
We developed a new computational algorithm for the accurate identification of ligand binding envelopes rather than surface binding sites. We performed a large scale classification of the identified envelopes according to their shape and physicochemical properties. The predicting algorithm, called PocketFinder, uses a transformation of the Lennard-Jones potential calculated from a three-dimensio...
متن کاملApolipoprotein C-III isoforms: kinetics and relative implication in lipid metabolism.
Apolipoprotein C-III (apoC-III) production rate (PR) is strongly correlated with plasma triglyceride (TG) levels. ApoC-III exists in three different isoforms, according to the sialylation degree of the protein. We investigated the kinetics and respective role of each apoC-III isoform in modulating intravascular lipid/lipoprotein metabolism. ApoC-III kinetics were measured in a sample of 18 heal...
متن کاملHuman apoC-IV: isolation, characterization, and immunochemical quantification in plasma and plasma lipoproteins.
Apolipoprotein C-IV (apoC-IV), the newest member of the low-molecular-weight apoC group, has been characterized in blood plasma of rabbits, in which it is a major proline-rich apoC component (Zhang, L-H., L. Kotite, and R. J. Havel. 1996. Identification, characterization, cloning, and expression of apoC-IV, a novel sialoglycoprotein of rabbit plasma lipoproteins. J. Biol. Chem. 271: 1776-1783)....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Bioinformatics
دوره 29 5 شماره
صفحات -
تاریخ انتشار 2013