Life Sciences Commons^™

Characterizing The Behavior Of Mutated Proteins With Emcap: The Energy Minimization Curve Analysis Pipeline, Matthew Lee, Bodi Van Roy, Filip Jagodzinski

WWU Honors College Senior Projects

Studies of protein mutants in wet laboratory experiments are expensive and time consuming. Computational experiments that simulate the motions of protein with amino acid substitutions can complement wet lab experiments for studying the effects of mutations. In this work we present a computational pipeline that performs exhaustive single-point amino acid substitutions in silico. We perform energy minimization as part of molecular dynamics (MD) of our generated mutant proteins, and the wild type, and log the energy potentials for each step of the simulations. We motivate several metrics that rely on the energy minimization curves of the wild type and mutant, …

Detecting And Accounting For Multiple Sources Of Positional Variance In Peak List Registration Analysis And Spin System Grouping, Andrey Smelter, Eric C. Rouchka, Hunter N. B. Moseley

Molecular and Cellular Biochemistry Faculty Publications

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of …

Clustering And Classification Of Multi-Domain Proteins, Neethu Shah

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Rapid development of next-generation sequencing technology has led to an unprecedented growth in protein sequence data repositories over the last decade. Majority of these proteins lack structural and functional characterization. This necessitates design and development of fast, efficient, and sensitive computational tools and algorithms that can classify these proteins into functionally coherent groups.

Domains are fundamental units of protein structure and function. Multi-domain proteins are extremely complex as opposed to proteins that have single or no domains. They exhibit network-like complex evolutionary events such as domain shuffling, domain loss, and domain gain. These events therefore, cannot be represented in the …

Beta Atomic Contacts: Identifying Critical Specific Contacts In Protein Binding Interfaces, Qian Lu, Chee Keong Kwoh, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the …

Secondary Structure, A Missing Component Of Sequence- Based Minimotif Definitions, David P. Sargeant, Michael R. Gryk, Mark W. Maciejewsk, Vishal Thapar, Vamsi Kundeti, Sanguthevar Rajasekaran, Pedro Romero, Keith Dunker, Shun-Cheng Li, Tomonori Kaneko, Martin Schiller

Life Sciences Faculty Research

Minimotifs are short contiguous segments of proteins that have a known biological function. The hundreds of thousands of minimotifs discovered thus far are an important part of the theoretical understanding of the specificity of protein-protein interactions, posttranslational modifications, and signal transduction that occur in cells. However, a longstanding problem is that the different abstractions of the sequence definitions do not accurately capture the specificity, despite decades of effort by many labs. We present evidence that structure is an essential component of minimotif specificity, yet is not used in minimotif definitions. Our analysis of several known minimotifs as case studies, analysis …

Achieving High Accuracy Prediction Of Minimotifs, Tian Mi, Sanguthevar Rajasekaran, Jerlin Camilus Merlin, Michael R. Gryk, Martin Schiller

Life Sciences Faculty Research

The low complexity of minimotif patterns results in a high false-positive prediction rate, hampering protein function prediction. A multi-filter algorithm, trained and tested on a linear regression model, support vector machine model, and neural network model, using a large dataset of verified minimotifs, vastly improves minimotif prediction accuracy while generating few false positives. An optimal threshold for the best accuracy reaches an overall accuracy above 90%, while a stringent threshold for the best specificity generates less than 1% false positives or even no false positives and still produces more than 90% true positives for the linear regression and neural network …

Minimotif Miner 3.0: Database Expansion And Significantly Improved Reduction Of False-Positive Predictions From Consensus Sequences., Tian Mi, Jerlin Camilus Merlin, Sandeep Deverasetty, Michael R. Gryk, Travis J. Bill, Andrew W. Brooks, Logan Lee, Viraj Rathnayake, Christian A. Ross, David P. Sargeant, Christy L. Strong, Paula Watts, Sanguthevar Rajasekaran, Martin Schiller

Life Sciences Faculty Research

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins …

A Comparison Of The Functional Modules Identified From Time Course And Static Ppi Network Data, Xiwei Tang, Jianxin Wang, Binbin Liu, Min Li, Gang Chen, Yi Pan

Computer Science Faculty Publications

Background: Cellular systems are highly dynamic and responsive to cues from the environment. Cellular function and response patterns to external stimuli are regulated by biological networks. A protein-protein interaction (PPI) network with static connectivity is dynamic in the sense that the nodes implement so-called functional activities that evolve in time. The shift from static to dynamic network analysis is essential for further understanding of molecular systems.

Results: In this paper, Time Course Protein Interaction Networks (TC- PINs) are reconstructed by incorporating time series gene expression into PPI networks. Then, a clustering algorithm is used to create functional modules from three …

Identifying Protein Complexes From Interaction Networks Based On Clique Percolation And Distance Restriction, Jianxin Wang, Binbin Liu, Min Li, Yi Pan

Computer Science Faculty Publications

Background: Identification of protein complexes in large interaction networks is crucial to understand principles of cellular organization and predict protein functions, which is one of the most important issues in the post-genomic era. Each protein might be subordinate multiple protein complexes in the real protein-protein interaction networks.Identifying overlapping protein complexes from protein-protein interaction networks is a considerable research topic.

Result: As an effective algorithm in identifying overlapping module structures, clique percolation method (CPM) has a wide range of application in social networks and biological networks. However, the recognition accuracy of algorithm CPM is lowly. Furthermore, algorithm CPM is unfit to …

Recent Advances In Clustering Methods For Protein Interaction Networks, Jianxin Wang, Min Li, Youping Deng, Yi Pan

Computer Science Faculty Publications

The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and …

A Novel Approach To Phylogenetic Tree Construction Using Stochastic Optimization And Clustering, Ling Qin, Yixin Chen, Yi Pan, Ling Chen

Computer Science Faculty Publications

Background: The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational biology.

Results: A new phylogenetic tree construction method from a given set of objects (proteins, species, etc.) is presented. As an extension of ant colony optimization, this method proposes an adaptive phylogenetic clustering algorithm based on a digraph to find a tree structure that defines the ancestral relationships among the given objects.

Conclusion: Our phylogenetic tree construction method is tested to compare its results with that of the genetic algorithm (GA). Experimental results show that …