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Author: Ashini Bolia
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 153
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Book Description
Molecular docking serves as an important tool in modeling protein-ligand interactions. Most of the docking approaches treat the protein receptor as rigid and move the ligand in the binding pocket through an energy minimization, which is an incorrect approach as proteins are flexible and undergo conformational changes upon ligand binding. However, modeling receptor backbone flexibility in docking is challenging and computationally expensive due to the large conformational space that needs to be sampled. A novel flexible docking approach called BP-Dock (Backbone Perturbation docking) was developed to overcome this challenge. BP-Dock integrates both backbone and side chain conformational changes of a protein through a multi-scale approach. In BP-Dock, the residues along a protein chain are perturbed mimicking the binding induced event, with a small Brownian kick, one at a time. The fluctuation response profile of the chain upon these perturbations is computed by Perturbation Response Scanning (PRS) to generate multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, this approach was applied to a large and diverse dataset of unbound structures as receptors. Furthermore, the protein-peptide docking of PICK1-PDZ proteins was investigated. This study elucidates the determinants of PICK1-PDZ binding that plays crucial roles in numerous neurodegenerative disorders. BP-Dock approach was also extended to the challenging problem of protein-glycan docking and applied to analyze the energetics of glycan recognition in Cyanovirin-N (CVN), a cyanobacterial lectin that inhibits HIV by binding to its highly glycosylated envelope protein gp120. This study provide the energetic contribution of the individual residues lining the binding pocket of CVN and explore the effect of structural flexibility in the hinge region of CVN on glycan binding, which are also verified experimentally. Overall, these successful applications of BP-Dock highlight the importance of modeling backbone flexibility in docking that can have important implications in defining the binding properties of protein-ligand interactions.Finally, an induced fit docking approach called Adaptive BP-Dock is presented that allows both protein and ligand conformational sampling during the docking. Adaptive BP-Dock can provide a faster and efficient docking approach for the virtual screening of novel targets for rational drug design and aid our understanding of protein-ligand interactions.
Author: Ashini Bolia
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 153
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Book Description
Molecular docking serves as an important tool in modeling protein-ligand interactions. Most of the docking approaches treat the protein receptor as rigid and move the ligand in the binding pocket through an energy minimization, which is an incorrect approach as proteins are flexible and undergo conformational changes upon ligand binding. However, modeling receptor backbone flexibility in docking is challenging and computationally expensive due to the large conformational space that needs to be sampled. A novel flexible docking approach called BP-Dock (Backbone Perturbation docking) was developed to overcome this challenge. BP-Dock integrates both backbone and side chain conformational changes of a protein through a multi-scale approach. In BP-Dock, the residues along a protein chain are perturbed mimicking the binding induced event, with a small Brownian kick, one at a time. The fluctuation response profile of the chain upon these perturbations is computed by Perturbation Response Scanning (PRS) to generate multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, this approach was applied to a large and diverse dataset of unbound structures as receptors. Furthermore, the protein-peptide docking of PICK1-PDZ proteins was investigated. This study elucidates the determinants of PICK1-PDZ binding that plays crucial roles in numerous neurodegenerative disorders. BP-Dock approach was also extended to the challenging problem of protein-glycan docking and applied to analyze the energetics of glycan recognition in Cyanovirin-N (CVN), a cyanobacterial lectin that inhibits HIV by binding to its highly glycosylated envelope protein gp120. This study provide the energetic contribution of the individual residues lining the binding pocket of CVN and explore the effect of structural flexibility in the hinge region of CVN on glycan binding, which are also verified experimentally. Overall, these successful applications of BP-Dock highlight the importance of modeling backbone flexibility in docking that can have important implications in defining the binding properties of protein-ligand interactions.Finally, an induced fit docking approach called Adaptive BP-Dock is presented that allows both protein and ligand conformational sampling during the docking. Adaptive BP-Dock can provide a faster and efficient docking approach for the virtual screening of novel targets for rational drug design and aid our understanding of protein-ligand interactions.
Author: Andrzej Kolinski
Publisher: Springer Science & Business Media
ISBN: 144196889X
Category : Science
Languages : en
Pages : 360
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Book Description
The book gives a comprehensive review of the most advanced multiscale methods for protein structure prediction, computational studies of protein dynamics, folding mechanisms and macromolecular interactions. It approaches span a wide range of the levels of coarse-grained representations, various sampling techniques and variety of applications to biomedical and biophysical problems. This book is intended to be used as a reference book for those who are just beginning their adventure with biomacromolecular modeling but also as a valuable source of detailed information for those who are already experts in the field of biomacromolecular modeling and in related areas of computational biology or biophysics.
Author: Benjamin Robert Jagger
Publisher:
ISBN:
Category :
Languages : en
Pages : 129
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Book Description
A detailed understanding of the interaction between a drug candidate molecule and its target is essential for the development, optimization, and efficacy prediction of a drug. Kinetic parameters such as the association rate and residence time of a molecule have been shown to better correlate with in vivo efficacy than more commonly used thermodynamic parameters. Efficient and accurate computational predictions of these quantities are therefore of great interest for their potential to inform and improve the development of novel pharmaceuticals. In this dissertation, I present the development and application of a multiscale molecular simulation approach which combines molecular dynamics and Brownian dynamics simulations with the theory of milestoning to efficiently calculate protein-ligand binding and unbinding rates. I begin with an overview of many of the existing multiscale simulation approaches for studying drug-protein binding. Then I present the methodology we have developed, Simulation Enabled Estimation of Kinetic Rates (SEEKR), and demonstrate its effectiveness for predicting the association and dissociation rates of the inhibitor, benzamidine, to the trypsin protein; a common model system. I then present the effectiveness of our multiscale milestoning approach for rank-ordering a series of chemically diverse ligands to the model system [beta]-cyclodextrin. This study includes a direct comparison of both efficiency and accuracy to long timescale molecular dynamics simulations and also outlines best practices for the use of our approach and the assessment of sampling convergence. Finally, I present the implementation of a new milestoning algorithm, Markovian Milestoning with Voronoi Tesselations, in our multiscale methodology to significantly decrease the simulation cost of kinetics calculations, improve the assessment of sampling convergence, and provide a framework for the future development of additional capabilities with the SEEKR method. This study also includes the development and deployment of our toolkit along with documentation and tutorials to facilitate its use and continued improvement by the scientific community.
Author: Andrzej Kolinski
Publisher: Springer
ISBN: 9781441968883
Category : Science
Languages : en
Pages : 355
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Book Description
The book gives a comprehensive review of the most advanced multiscale methods for protein structure prediction, computational studies of protein dynamics, folding mechanisms and macromolecular interactions. It approaches span a wide range of the levels of coarse-grained representations, various sampling techniques and variety of applications to biomedical and biophysical problems. This book is intended to be used as a reference book for those who are just beginning their adventure with biomacromolecular modeling but also as a valuable source of detailed information for those who are already experts in the field of biomacromolecular modeling and in related areas of computational biology or biophysics.
Author: Holger Gohlke
Publisher: John Wiley & Sons
ISBN: 3527329668
Category : Medical
Languages : en
Pages : 361
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Book Description
Innovative and forward-looking, this volume focuses on recent achievements in this rapidly progressing field and looks at future potential for development. The first part provides a basic understanding of the factors governing protein-ligand interactions, followed by a comparison of key experimental methods (calorimetry, surface plasmon resonance, NMR) used in generating interaction data. The second half of the book is devoted to insilico methods of modeling and predicting molecular recognition and binding, ranging from first principles-based to approximate ones. Here, as elsewhere in the book, emphasis is placed on novel approaches and recent improvements to established methods. The final part looks at unresolved challenges, and the strategies to address them. With the content relevant for all drug classes and therapeutic fields, this is an inspiring and often-consulted guide to the complexity of protein-ligand interaction modeling and analysis for both novices and experts.
Author:
Publisher: Academic Press
ISBN: 0128211350
Category : Science
Languages : en
Pages : 552
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Book Description
Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more. Includes comprehensive coverage on molecular biology Presents ample use of tables, diagrams, schemata and color figures to enhance the reader's ability to rapidly grasp the information provided Contains contributions from renowned experts in the field
Author: Dushyanthan Puvanendrampillai
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Krishnanand N. Kaipa
Publisher: Springer
ISBN: 3319515950
Category : Technology & Engineering
Languages : en
Pages : 265
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Book Description
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.
Author: Bartlomiej Tywoniuk
Publisher:
ISBN:
Category :
Languages : en
Pages : 170
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Book Description
Author: Benjamin Michael Samudio
Publisher:
ISBN: 9781369201079
Category :
Languages : en
Pages :
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Book Description
Proteins are fascinating biomolecular "machines" that enable the chemistry of life to occur. They underlie such diverse processes as energy transduction and immunity. Science continuous to unravel how these proteins work and many exciting questions remain to be answered. A paramount goal in the study of proteins is the understanding of how protein structure and dynamics facilitate chemistry. Proteins undergo conformational changes which make certain chemistry more probable. Elucidating these conformational changes is a major challenge to which both experimental and computational methods are applied. Computational methods can complement experimental ones by modeling protein conformational changes at an atomic level of detail. In addition, more elaborate computational methods can model chemical changes and reactions. This provides a link between structure and chemistry which is central to descriptions of protein function. This dissertation describes my research involving proteins which has been carried out at two institutions, the University of California in Davis (UC Davis) and the Novartis Institutes for Biomedical Research (NIBR), and correspondingly is divided into two parts. Part I: Unidirectional Proton Translocation Involving Glu-242 of Cytochrome c Oxidase (UC Davis) Cytochrome c oxidase (CcO) is the fourth protein complex in the electron transport chain (ETC) of mitochondria and some bacteria. This protein is embedded within the proton impermeable inner membrane of mitochondria and outer membrane in bacteria. CcO functions to: 1) reduce dioxygen to water and 2) move protons in a scalar manner from a lower concentration of protons in the mitochondrial matrix to a higher concentration of protons in the intermembrane space in a process known as proton pumping. Proton pumping establishes an electrochemical gradient across the inner membrane which is essential to aerobic life. CcO is remarkable because it is able to pump protons against the electrochemical gradient via a thermodynamically unfavorable but unidirectional and productive trajectory. CcO is unique as of this writing, in that it is designated as a "true" proton pump meaning that the protons which are pumped through CcO are not also substrates in the redox reactions which occur within this enzyme. Though a wealth of knowledge has been generated regarding CcO, much uncertainty remains about the microscopic details of the proton pumping process. Experimental methods have produced a detailed framework describing many aspects of CcO structure and function, however, probing this enzyme at the molecular level can be difficult. To this end, computational molecular modeling offers a complement to experimental efforts. The methods that are a part of computational molecular modeling can provide keen insight into biophysical processes. There are many different methods and ways to apply them, however, and it is not always straightforward how to best develop and deploy a model for a particular system. CcO presents an especially challenging system since the process of proton translocation involves levels of detail spanning electronic structure dynamics to large protein conformational changes. Computational methods must therefore be systematically tested and validated in order to increase confidence that their results are meaningful for investigations of CcO. In the current work, several computational models of CcO are compared. These models differ from one another in the level of detail describing a key region of the proton pumping pathway within CcO. This region contains a highly conserved residue, Glu-242 (bovine heart mitochondria numbering), which has been shown to be pivotal in relaying protons across the proton pumping pathway. The results of this work indicate that there are differences regarding the energetics and dynamics of Glu-242 side chain isomerization depending on the level of detail used in the model. These differences lead to differing descriptions of proton translocation as it involves Glu-242 and underscores the need to thoroughly examine the application of computational models. In Chapter 1, the major structures and functioning of CcO is outlined. The analogy that underlies this chapter is of CcO functioning similar to a macroscopic pump in moving protons from one side of the membrane to the other. The CcO reaction cycle is akin to the repetitive motions of a piston as it operates to pump material. In Chapter 2, the proton pump pathway through CcO is characterized. The focus then collects on a region of this pathway which is instrumental in the process of proton pumping named the "motif" region. Finally a four-state model is used to describe the participation in proton pumping of Glu-242 or its physiochemical analogue at this region. In Chapter 3, proton leaks and proton leak prevention are described. Proton leaks are thought to occur in some structural variants of CcO. In these cases, the unidirectional and productive movement of protons through CcO is compromised as indicated by abnormal proton pumping stoichiometry. Kinetic gating is a conceptual framework whereby the prevention of these leaks may be rationalized. This chapter ends with the description of a criterion that must be met in order to prevent protons from leaking. Chapter 4 introduces common methods used in molecular modeling. Finally, in Chapter 5 computational molecular models involving the motif region are compared. These models employ varying levels of detail. This offers a test of how increasing levels of model detail effects the conclusions which might be drawn regarding proton pumping. A proposal for how unidirectional proton translocation may occur in CcO is offered based on the results of the molecular models at the higher level of detail. In conclusion, these models are used to speculate on how proton leaks occur in structural variants of CcO and how unidirectional proton translocation may occur in CcO enzymes which lack Glu-242 or its equivalent. Part II: Ensemble Surrogate AutoShim: Probing Sensitivity to Parameter Modification (NIBR) Ensemble Surrogate AutoShim (ESA) is a powerful and versatile virtual docking and screening method which has proven to be useful in drug discovery and design. ESA is powerful in that it transforms general all-purpose scoring functions into target-tailored scoring functions using a combined 2D and 3D-QSAR based approach that involves virtual docking. These target-tailored scoring functions are then trained to reproduce bioactivity data against a given target resulting in a knowledge-based model that is used in virtual screening. Held-out test set validations of ESA models show that they routinely outperforms exclusively all-purpose scoring function based approaches. Chapter 1 outlines the ESA method in general. The versatility of the ESA method stems from the fact that various ligand preparation, docking and scoring, and pose filtering and refinement schemes may be implemented within the ESA framework. For example, the ESA method is open to the inclusion of any conventional all-purpose scoring function and docking program within its framework. This versatility offers flexibility in the implementation of the ESA method and invites an exploration of the parameters underlying this method. In Chapter 2, a systematic evaluation of ESA parameter modification is undertaken and quantified through statistical analysis. The results of this work indicate that several parameters significantly influence the quality of ESA models. Based on these results, a protocol is proposed which produces the most predictive ESA models on average of any parameter configuration and protocol studied so far on the data set evaluated.
