A Computational Framework for Predicting the Motions of a Protein System From a Robot Kinematics Viewpoint

2013 ◽  
Author(s):  
Keisuke Arikawa
Keyword(s):  
Robot Manipulator ◽  
Structural Data ◽  
Protein Molecule ◽  
Data Bank ◽  
Computational Time ◽  
Robot Kinematics ◽  
Efficient Computation ◽  
Elastic Network Model ◽  
Computational Framework ◽  
Structural Compliance

There is an analogy between the kinematic structures of proteins and robotic mechanisms. On the basis of this analogy, we have so far developed some methods for predicting the internal motions of proteins from their three-dimensional structural data in protein data bank (PDB). However, these methods are basically applicable to a single protein molecule. In this study, we extended these methods to apply them to systems that consist of multiple molecules including proteins (protein systems), and developed a computational framework for predicting the motions of the molecules. The model used in this method is a type of elastic network model. In particular, proteins are modeled as a robot manipulator constrained by the springs (the dihedral angles on the main chains correspond to the joint angles). The interactions between molecules are also modeled as springs. The basic concept for predicting the motions is based on the analysis of structural compliance. By applying statically balanced forces to the model in various directions, we extracted those motions with larger structural compliance. To reduce the computational time, we formulated the method with the prospect of efficient computation including parallel computation. In addition, we developed a preparatory computer program implementing the proposed algorithms, and analyzed some protein systems. The results showed that the proposed computational framework can efficiently analyze large protein systems.

Analyzing Motion Properties of Proteins Affected by Localized Structures From a Robot Kinematics Perspective

2015 ◽  
Author(s):  
Keisuke Arikawa
Keyword(s):  
Protein Data Bank ◽  
Complex Shape ◽  
Structural Data ◽  
Data Bank ◽  
Robot Kinematics ◽  
Motion Prediction ◽  
Serial Manipulators ◽  
Localized Structures ◽  
Motion Modes ◽  
Structural Compliance

On the basis of robot kinematics, we have thus far developed a method for predicting the motion of proteins from their 3D structural data given in the Protein Data Bank (PDB data). In this method, proteins are modeled as serial manipulators constrained by springs and the structural compliance properties of the models are evaluated. We focus on localized instead of whole structures of proteins. Employing the same model used in our method of motion prediction, the motion properties of the localized structures and the relation between the motion properties of localized and whole structures are analyzed. First, we present a method for graphically expressing the deformation of objects with a complex shape, such as proteins, by approximating the shape as a rectangular prism with a mesh on its surface. We then formulate a method for comparing the motion properties of localized structures cleaved from the whole structure and those remaining in it by expressing the motion of the latter using the decomposed motion modes of the former according to the structural compliance. Finally, we show a method for evaluating the effect of a localized structure on the motion properties of proteins by applying forces to localized structures. In the formulations, we demonstrate applications as illustrative examples using the PDB data of a real protein.

Structural Compliance Analysis and Internal Motion Properties of Proteins From a Robot Kinematics Perspective: Formulation of Basic Equations

2016 ◽  
Vol 8 (2) ◽  
Author(s):  
Keisuke Arikawa
Keyword(s):  
Kinematic Model ◽  
Structural Data ◽  
Forced Response ◽  
Internal Motion ◽  
Robot Kinematics ◽  
Dihedral Angles ◽  
Protein Model ◽  
Applied Forces ◽  
Basic Equations ◽  
Structural Compliance

From a perspective of robot kinematics, we develop a method for predicting internal motion properties and understanding the functions of proteins from their three-dimensional (3D) structural data (protein data bank (PDB) data). The key ideas are based on the structural compliance analysis of proteins. In this paper, we mainly discuss the basic equations for the analysis. First, a kinematic model of a protein is introduced. Proteins are simply modeled as serial manipulators constrained by linear springs, where the dihedral angles on the main chains correspond to the joint angles of manipulators. Then, the kinematic equations of the protein model are derived. In particular, the forced response or the deformation caused by the forces in static equilibrium forms the basis for the structural compliance analysis. In the formulations, the protein models are regarded as manipulators that control the positions in the model or the distances between them, by the dihedral angles on the main chains. Next, the structural compliance of the protein model is defined, and a method for extracting the information about the internal motion properties from the structural compliance is shown. In general, the structural compliance refers to the relationship between the applied forces and the deformation of the parts surrounded by the application points. We define it in a more general form by separating the parts whose deformations are evaluated from those where forces are applied. When decomposing motion according to the magnitude of the structural compliance, we can infer that the lower compliance motion will easily occur. Finally, we show two application examples using PDB data of lactoferrin and hemoglobin. Despite using an approximate protein model, the predicted internal motion properties agree with the measured ones.

Extension of the Kinematics-Based Method for Predicting the Motion of Proteins

2014 ◽  
Author(s):  
Keisuke Arikawa
Keyword(s):  
Computational Cost ◽  
Three Dimensional ◽  
Structural Data ◽  
Data Bank ◽  
Serial Manipulators ◽  
Protein Model ◽  
The Matrix ◽  
Basic Equations ◽  
Definition Of ◽  
Structural Compliance

On the basis of an analogy between the kinematic structures of proteins and robotic mechanisms, we have so far developed methods for predicting the internal motion of proteins from three-dimensional structural data in the protein data bank (PDB). With these methods, we model proteins as serial manipulators constrained by springs, and calculate the structural compliance of the protein model. In this study, toward more practical purposes, we reformulate and extend the existing methods by broadening the definition of structural compliance and reducing the number of variables for expressing the conformation of the model. The broadening is performed by separating the parts whose deformations are evaluated from those where forces are applied. This separation allows the calculation of the effective forces causing deformation in other specified parts. We also reduce the number of conformation variables from the consideration based on the algebraic structure of the basic equations. The size of the matrix whose inverse must be calculated is thus minimized, and the computational cost is reduced. We verify the effectiveness of these extensions by analyzing the PDB data of some proteins.

scholarly journals Fundamental resource trade-offs for encoded distributed optimization

2020 ◽  
Author(s):  
A Salman Avestimehr ◽  
Seyed Mohammadreza Mousavi Kalan ◽  
Mahdi Soltanolkotabi
Keyword(s):  
Computational Time ◽  
Massive Data ◽  
Data Sets ◽  
Massive Data Sets ◽  
Computational Framework ◽  
Data Set ◽  
Trade Offs ◽  
Major Bottleneck ◽  
Computing Environments ◽  
Analyze Data

Abstract Dealing with the shear size and complexity of today’s massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments is that some of the worker nodes may run slow. These nodes a.k.a. stragglers can significantly slow down computation as the slowest node may dictate the overall computational time. A recent computational framework, called encoded optimization, creates redundancy in the data to mitigate the effect of stragglers. In this paper, we develop novel mathematical understanding for this framework demonstrating its effectiveness in much broader settings than was previously understood. We also analyze the convergence behavior of iterative encoded optimization algorithms, allowing us to characterize fundamental trade-offs between convergence rate, size of data set, accuracy, computational load (or data redundancy) and straggler toleration in this framework.

scholarly journals Dimer Interface Organization is a Main Determinant of Intermonomeric Interactions and Correlates with Evolutionary Relationships of Retroviral and Retroviral-Like Ddi1 and Ddi2 Proteases

2020 ◽  
Vol 21 (4) ◽  
pp. 1352 ◽  
Author(s):  
János András Mótyán ◽  
Márió Miczi ◽  
József Tőzsér
Keyword(s):  
Structural Characteristics ◽  
Limited Proteolysis ◽  
Structural Data ◽  
Data Bank ◽  
Life Cycles ◽  
Evolutionary Relationships ◽  
Multiple Sequence ◽  
Dimer Interface ◽  
Viral Proteases ◽  
Eukaryotic Organisms

The life cycles of retroviruses rely on the limited proteolysis catalyzed by the viral protease. Numerous eukaryotic organisms also express endogenously such proteases, which originate from retrotransposons or retroviruses, including DNA damage-inducible 1 and 2 (Ddi1 and Ddi2, respectively) proteins. In this study, we performed a comparative analysis based on the structural data currently available in Protein Data Bank (PDB) and Structural summaries of PDB entries (PDBsum) databases, with a special emphasis on the regions involved in dimerization of retroviral and retroviral-like Ddi proteases. In addition to Ddi1 and Ddi2, at least one member of all seven genera of the Retroviridae family was included in this comparison. We found that the studied retroviral and non-viral proteases show differences in the mode of dimerization and density of intermonomeric contacts, and distribution of the structural characteristics is in agreement with their evolutionary relationships. Multiple sequence and structure alignments revealed that the interactions between the subunits depend mainly on the overall organization of the dimer interface. We think that better understanding of the general and specific features of proteases may support the characterization of retroviral-like proteases.

Advanced CFD Simulations of free-surface flows around modern sailing yachts using a newly developed openFOAM solver

2016 ◽  
Author(s):  
Janek Meyer ◽  
Hannes Renzsch ◽  
Kai Graf ◽  
Thomas Slawig
Keyword(s):  
Free Surface ◽  
Large Scale ◽  
Breaking Waves ◽  
Free Surface Flows ◽  
Body Motion ◽  
Computational Time ◽  
Efficient Computation ◽  
Surface Flows ◽  
Scale Free ◽  
Wide Range

While plain vanilla OpenFOAM has strong capabilities with regards to quite a few typical CFD-tasks, some problems actually require additional bespoke solvers and numerics for efficient computation of high-quality results. One of the fields requiring these additions is the computation of large-scale free-surface flows as found e.g. in naval architecture. This holds especially for the flow around typical modern yacht hulls, often planing, sometimes with surface-piercing appendages. Particular challenges include, but are not limited to, breaking waves, sharpness of interface, numerical ventilation (aka streaking) and a wide range of flow phenomenon scales. A new OF-based application including newly implemented discretization schemes, gradient computation and rigid body motion computation is described. In the following the new code will be validated against published experimental data; the effect on accuracy, computational time and solver stability will be shown by comparison to standard OF-solvers (interFoam / interDyMFoam) and Star CCM+. The code’s capabilities to simulate complex “real-world” flows are shown on a well-known racing yacht design.

scholarly journals A New Approach to the Solution of Robot Kinematics Based on Relative Transformation Matrices

2016 ◽  
Vol 5 (3) ◽  
pp. 213
Author(s):  
Mohammad Reza Elhami ◽  
Iman Dashti
Keyword(s):  
Robot Manipulator ◽  
Robot Kinematics ◽  
Coordinate Frame ◽  
End Effector ◽  
New Approach ◽  
Transformation Matrices ◽  
The World ◽  
Convenient Approach ◽  
Position And Orientation ◽  
Relative Transformation

In analyzing robot manipulator kinematics, we need to describe relative movement of adjacent linkages or joints in order to obtain the pose of end effector (both position and orientation) in reference coordinate frame. Denavit-Hartenberg established a method based on a 4×4 homogenous matrix so called “A” matrix. This method used by most of the authors for kinematics and dynamic analysis of the robot manipulators. Although it has many advantages, however, finding the elements of this matrix and link/joint’s parameters is sometimes complicated and confusing. By considering these difficulties, the authors proposed a new approach called ‘convenient approach’ that is developed based on “Relative Transformations Principle”. It provides a very simple and convenient way for the solution of robot kinematics compared to the conventional D-H representation. In order to clarify this point, the kinematics of the world known Stanford manipulator has been solved through D-H representation as well as convenient approach and the results are compared.

MRPC (Missing Regions in Polypeptide Chains): a knowledgebase

2019 ◽  
Vol 52 (6) ◽  
pp. 1422-1426
Author(s):  
Rajendran Santhosh ◽  
Namrata Bankoti ◽  
Adgonda Malgonnavar Padmashri ◽  
Daliah Michael ◽  
Jeyaraman Jeyakanthan ◽  
...  
Keyword(s):  
Protein Structures ◽  
Three Dimensional ◽  
Protein Molecule ◽  
Data Bank ◽  
Protein Crystal ◽  
Dimensional Structure ◽  
Protein Structure Analysis ◽  
Three Dimensional Structure ◽  
X Ray Crystallography ◽  
Polypeptide Chains

Missing regions in protein crystal structures are those regions that cannot be resolved, mainly owing to poor electron density (if the three-dimensional structure was solved using X-ray crystallography). These missing regions are known to have high B factors and could represent loops with a possibility of being part of an active site of the protein molecule. Thus, they are likely to provide valuable information and play a crucial role in the design of inhibitors and drugs and in protein structure analysis. In view of this, an online database, Missing Regions in Polypeptide Chains (MRPC), has been developed which provides information about the missing regions in protein structures available in the Protein Data Bank. In addition, the new database has an option for users to obtain the above data for non-homologous protein structures (25 and 90%). A user-friendly graphical interface with various options has been incorporated, with a provision to view the three-dimensional structure of the protein along with the missing regions using JSmol. The MRPC database is updated regularly (currently once every three months) and can be accessed freely at the URL http://cluster.physics.iisc.ac.in/mrpc.

scholarly journals BLASTing away preconceptions in crystallization trials

2019 ◽  
Vol 75 (3) ◽  
pp. 184-192 ◽  
Author(s):  
Gabriel Jan Abrahams ◽  
Janet Newman
Keyword(s):  
Protein Data Bank ◽  
Sequence Similarity ◽  
Three Dimensional ◽  
Protein Sequences ◽  
Protein Molecule ◽  
Data Bank ◽  
Dimensional Structure ◽  
Critical Step ◽  
Quantitative Verification ◽  
Better Than

Crystallization is in many cases a critical step for solving the three-dimensional structure of a protein molecule. Determining which set of chemicals to use in the initial screen is typically agnostic of the protein under investigation; however, crystallization efficiency could potentially be improved if this were not the case. Previous work has assumed that sequence similarity may provide useful information about appropriate crystallization cocktails; however, the authors are not aware of any quantitative verification of this assumption. This research investigates whether, given current information, one can detect any correlation between sequence similarity and crystallization cocktails. BLAST was used to quantitate the similarity between protein sequences in the Protein Data Bank, and this was compared with three estimations of the chemical similarities of the respective crystallization cocktails. No correlation was detected between proteins of similar (but not identical) sequence and their crystallization cocktails, suggesting that methods of determining screens based on this assumption are unlikely to result in screens that are better than those currently in use.

WAP(version 2.0): an updated computing and visualization server for water molecules

2008 ◽  
Vol 41 (5) ◽  
pp. 952-954 ◽  
Author(s):  
S. Praveen ◽  
J. Ramesh ◽  
P. Sivasankari ◽  
G. Sowmiya ◽  
K. Sekar
Keyword(s):  
Three Dimensional ◽  
Protein Molecule ◽  
Data Bank ◽  
Internet Technology ◽  
Water Molecules ◽  
Molecular Graphics ◽  
Hydration Shells ◽  
Macromolecular Protein ◽  
Version 2.0 ◽  
Nucleic Acid Structures

By exploiting the fast-growing Internet technology, the interactive computing serverWater Analysis Package(WAP, version 2.0) has been updated with more flexible options to better understand the role of the water O atoms present in three-dimensional macromolecular (protein or nucleic acid) structures. The updated robust server facilitates the computation and visualization of water molecules from various hydration shells, interfacial water molecules and those water molecules that stabilize various secondary structural elements. It is also possible to detect the interactions of water molecules with various parts (polar atoms, nonpolar atoms, main-chain and side-chain atoms) of the protein molecule. Furthermore, a molecular graphics visualization program is interfaced to display the nature of the interactions of the water molecules. The Protein Data Bank archive interfaced with the server is updated every week; hence users get to analyse the latest structures. The computing server can be obtained from http://dicsoft2.physics.iisc.ernet.in/wap/.

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