Towards Fully Automated High Performance Computing Drug Discovery PDF Download

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Languages : en
Pages : 56

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Author: Alexander Heifetz
Publisher: Springer Nature
ISBN: 1071634496
Category : Science
Languages : en
Pages : 430

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Book Description
This volume explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. The first section collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. The second section delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step and readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, High Performance Computing for Drug Discovery and Biomedicine allows a diverse audience, including computer scientists, computational and medicinal chemists, biologists, clinicians, pharmacologists and drug designers, to navigate the complex landscape of what is currently possible and to understand the challenges and future directions of HPC-based technologies.

Author: D. C. Young
Publisher: John Wiley & Sons
ISBN: 9780470451847
Category : Science
Languages : en
Pages : 344

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Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Author: Silvano Coletti
Publisher: Springer Nature
ISBN: 3031306910
Category : Technology & Engineering
Languages : en
Pages : 96

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This book highlights the different aspects of the research project “E4C Horizon 2020 European Project” aimed at fighting the coronavirus by combining the best supercomputing resources and artificial intelligence with state-of-the-art experimental facilities up through clinical validation. Coronavirus disease has become an important public issue across the globe since December 2019. There is an urgent need to develop potent anti-COVID-19 agents for the prevention of the outbreak and stop viral infections. To this aim, a public–private consortium composed by European and national infrastructures, center of excellence, universities, and a pharmaceutical company started the E4C Horizon 2020 European Project: Its core idea was to use the EXaSCale smArt pLatform Against paThogEns (EXSCALATE) supercomputing platform for a process known as “drug repurposing”, namely to identify the most promising safe in man drugs for immediate treatment of the already infected population and then novel pan-coronavirus inhibitors to address future emergencies. This ambitious goal exploited a “chemical library” of 500 billion molecules, thanks to a processing capacity of more than 3 million molecules per second, made available by the computing power of the EXSCALATE platform.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 3

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We proposed to determine the underpinnings of a high-throughput computational infrastructure that would support future efforts in therapeutics against biothreat pathogens. Existing modeling capabilities focus on pathogen detection, but extending such capabilities to high-throughput molecular docking would lead to a proactive method to guide the development of therapeutics. This project will focus on determining the feasibility of extending current databases to accommodate molecular docking. We will also examine the feasibility of massive parallelization of docking algorithms and the utility of docking libraries. Transferring this new technique to a high-performance computing (HPC) platform at LLNL would result in a unique capability not available elsewhere in government or industry. We have accomplished the proposed work defined in this LDRD FS study. (1) We successfully defined the feasibility of using three different small-molecule databases for high-throughput docking, the NCI diversity set, ZINC and the ACD. (2) We analyzed the accuracy and parallelization capabilities of six separate docking programs: DOCK, AutoDock, FlexX, Glide, and eHiTS. Each program is completely amenable to parallel execution. The fastest code was eHiTS, and Glide was the most accurate. (3) Customizing large libraries was cumbersome without the proper software, making the databases a bit difficult to tailor. The ZINC database has some prefiltered versions. (4) Scripts were created for quality and job control functions. Further development is needed for analysis and visualization needs. The successful conclusion of this project enables LLNL to have a high-throughput computational docking capability where we have evaluated the codes to specific docking problems and utilized LLNL's HPC for significant gains in performance. We have established a CRADA with an industrial partner (funded by the National Institutes of Health) that will fully utilize this technology for biodefense therapeutic design and development.

Author: Claudio N. Cavasotto
Publisher: CRC Press
ISBN: 1482217856
Category : Medical
Languages : en
Pages : 558

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Book Description
In Silico Drug Discovery and Design: Theory, Methods, Challenges, and Applications provides a comprehensive, unified, and in-depth overview of the current methodological strategies in computer-aided drug discovery and design. Its main aims are to introduce the theoretical framework and algorithms, discuss the range of validity, strengths and limita

Author: Nathan Brown
Publisher: Royal Society of Chemistry
ISBN: 1839160543
Category : Computers
Languages : en
Pages : 425

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Book Description
Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.

Author: Prof Mohammed
Publisher: Biocuration Labs
ISBN: 1517184851
Category : Medical
Languages : en
Pages : 36

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This book has originated from Practical class on Genomics & Proteomics that are offered to students of Computational Biology, Bangalore University of Bangalore. The idea to write a book on Computational Biology was born during the preparations of these practical where I realized that it is extremely difficult to achieve an overview of the area of Drug Discovery and to follow the progress of this field. This is the first book in 2015 and was written in English .Computational Biology is a major topic in modern medical, Life science and pharmacological research and is of central importance in the computational biology science. Accordingly, The enormous increase in data on Drug Designing has led me to leave out the practical on Computational Biology and. This topic has since evolved into a huge research area of its own that could not be considered adequately within this book. My knowledge of Drug Designing practical has exploded in the past 5 years, Bioinformatics could be treated here with the same thoroughness. It is the aim of the present book to describe the Bioinformatics practical approach for life science students.

Author: Jean-Paul Renaud
Publisher: John Wiley & Sons
ISBN: 1118900502
Category : Medical
Languages : en
Pages : 1367

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With the most comprehensive and up-to-date overview of structure-based drug discovery covering both experimental and computational approaches, Structural Biology in Drug Discovery: Methods, Techniques, and Practices describes principles, methods, applications, and emerging paradigms of structural biology as a tool for more efficient drug development. Coverage includes successful examples, academic and industry insights, novel concepts, and advances in a rapidly evolving field. The combined chapters, by authors writing from the frontlines of structural biology and drug discovery, give readers a valuable reference and resource that: Presents the benefits, limitations, and potentiality of major techniques in the field such as X-ray crystallography, NMR, neutron crystallography, cryo-EM, mass spectrometry and other biophysical techniques, and computational structural biology Includes detailed chapters on druggability, allostery, complementary use of thermodynamic and kinetic information, and powerful approaches such as structural chemogenomics and fragment-based drug design Emphasizes the need for the in-depth biophysical characterization of protein targets as well as of therapeutic proteins, and for a thorough quality assessment of experimental structures Illustrates advances in the field of established therapeutic targets like kinases, serine proteinases, GPCRs, and epigenetic proteins, and of more challenging ones like protein-protein interactions and intrinsically disordered proteins

Author: Mohini Gore
Publisher: Springer Nature
ISBN: 1071634410
Category : Medical
Languages : en
Pages : 357

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Book Description
This second edition provides new and updated methods and techniques for identification of drug target, binding sites prediction, high- throughput virtual screening, lead discovery and optimization, conformational sampling, prediction of pharmacokinetic properties using computer-based methodologies. Chapters also focus on the application of the latest artificial intelligence technologies for computer aided drug discovery. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Drug Discovery and Design, Second Edition aims to effectively utilize computational methodologies in discovery and design of novel drugs.