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Virtual Screening in Drug Discovery by Juan Alvarez,Brian Shoichet Pdf
Virtual screening can reduce costs and increase hit rates for lead discovery by eliminating the need for robotics, reagent acquisition or production, and compound storage facilities. The increased robustness of computational algorithms and scoring functions, the availability of affordable computational power, and the potential for timely structural
Virtual Screening for Chemists by Ishika Saha,Patrick G. Harran Pdf
Virtual Screening for Chemists focuses the discussion on principles underlying the most widely used methods for virtual screening today. References for more technical details have been provided where relevant. The authors have paid special attention to highlighting resources that are readily accessible to the academic community and hope these will facilitate your research aims. Demonstrative workflows have been included at the end of the e-book to allow you to familiarize yourself with the general steps involved in a virtual library screening pipeline. Familiarity with basic python and command line interface may be helpful in these examples, but scripts and execution instructions have been provided to guide you through the entire workflow. The input datasets used in the demonstrative examples are derived from the authors’ in-house virtual library, but the exercises may be adapted to other datasets of the reader’s choice.
Chemoinformatics Approaches to Virtual Screening by Alexandre Varnek,Alex Tropsha Pdf
Chemoinformatics is broadly a scientific discipline encompassing the design, creation, organization, management, retrieval, analysis, dissemination, visualization and use of chemical information. It is distinct from other computational molecular modeling approaches in that it uses unique representations of chemical structures in the form of multiple chemical descriptors; has its own metrics for defining similarity and diversity of chemical compound libraries; and applies a wide array of statistical, data mining and machine learning techniques to very large collections of chemical compounds in order to establish robust relationships between chemical structure and its physical or biological properties. Chemoinformatics addresses a broad range of problems in chemistry and biology; however, the most commonly known applications of chemoinformatics approaches have been arguably in the area of drug discovery where chemoinformatics tools have played a central role in the analysis and interpretation of structure-property data collected by the means of modern high throughput screening. Early stages in modern drug discovery often involved screening small molecules for their effects on a selected protein target or a model of a biological pathway. In the past fifteen years, innovative technologies that enable rapid synthesis and high throughput screening of large libraries of compounds have been adopted in almost all major pharmaceutical and biotech companies. As a result, there has been a huge increase in the number of compounds available on a routine basis to quickly screen for novel drug candidates against new targets/pathways. In contrast, such technologies have rarely become available to the academic research community, thus limiting its ability to conduct large scale chemical genetics or chemical genomics research. However, the landscape of publicly available experimental data collection methods for chemoinformatics has changed dramatically in very recent years. The term "virtual screening" is commonly associated with methodologies that rely on the explicit knowledge of three-dimensional structure of the target protein to identify potential bioactive compounds. Traditional docking protocols and scoring functions rely on explicitly defined three dimensional coordinates and standard definitions of atom types of both receptors and ligands. Albeit reasonably accurate in many cases, conventional structure based virtual screening approaches are relatively computationally inefficient, which has precluded them from screening really large compound collections. Significant progress has been achieved over many years of research in developing many structure based virtual screening approaches. This book is the first monograph that summarizes innovative applications of efficient chemoinformatics approaches towards the goal of screening large chemical libraries. The focus on virtual screening expands chemoinformatics beyond its traditional boundaries as a synthetic and data-analytical area of research towards its recognition as a predictive and decision support scientific discipline. The approaches discussed by the contributors to the monograph rely on chemoinformatics concepts such as: -representation of molecules using multiple descriptors of chemical structures -advanced chemical similarity calculations in multidimensional descriptor spaces -the use of advanced machine learning and data mining approaches for building quantitative and predictive structure activity models -the use of chemoinformatics methodologies for the analysis of drug-likeness and property prediction -the emerging trend on combining chemoinformatics and bioinformatics concepts in structure based drug discovery The chapters of the book are organized in a logical flow that a typical chemoinformatics project would follow - from structure representation and comparison to data analysis and model building to applications of structure-property relationship models for hit identification and chemical library design. It opens with the overview of modern methods of compounds library design, followed by a chapter devoted to molecular similarity analysis. Four sections describe virtual screening based on the using of molecular fragments, 2D pharmacophores and 3D pharmacophores. Application of fuzzy pharmacophores for libraries design is the subject of the next chapter followed by a chapter dealing with QSAR studies based on local molecular parameters. Probabilistic approaches based on 2D descriptors in assessment of biological activities are also described with an overview of the modern methods and software for ADME prediction. The book ends with a chapter describing the new approach of coding the receptor binding sites and their respective ligands in multidimensional chemical descriptor space that affords an interesting and efficient alternative to traditional docking and screening techniques. Ligand-based approaches, which are in the focus of this work, are more computationally efficient compared to structure-based virtual screening and there are very few books related to modern developments in this field. The focus on extending the experiences accumulated in traditional areas of chemoinformatics research such as Quantitative Structure Activity Relationships (QSAR) or chemical similarity searching towards virtual screening make the theme of this monograph essential reading for researchers in the area of computer-aided drug discovery. However, due to its generic data-analytical focus there will be a growing application of chemoinformatics approaches in multiple areas of chemical and biological research such as synthesis planning, nanotechnology, proteomics, physical and analytical chemistry and chemical genomics.
Drug discovery is all about finding small molecules that interact in a desired way with larger molecules, namely proteins and other macromolecules in the human body. If the three-dimensional structures of both the small and large molecule are known, their interaction can be tested by computer simulation with a reasonable degree of accuracy. Alternatively, if active ligands are already available, molecular similarity searches can be used to find new molecules. This virtual screening can even be applied to compounds that have yet to be synthesized, as opposed to "real" screening that requires cost- and labor-intensive laboratory testing with previously synthesized drug compounds. Unique in its focus on the end user, this is a real "how to" book that does not presuppose prior experience in virtual screening or a background in computational chemistry. It is both a desktop reference and practical guide to virtual screening applications in drug discovery, offering a comprehensive and up-to-date overview. Clearly divided into four major sections, the first provides a detailed description of the methods required for and applied in virtual screening, while the second discusses the most important challenges in order to improve the impact and success of this technique. The third and fourth, practical parts contain practical guidelines and several case studies covering the most important scenarios for new drug discovery, accompanied by general guidelines for the entire workflow of virtual screening studies. Throughout the text, medicinal chemists from academia, as well as from large and small pharmaceutical companies report on their experience and pass on priceless practical advice on how to make best use of these powerful methods.
Natural Compounds as Drugs, Volume I by Frank Petersen,René Amstutz Pdf
In a real tour de force of pharmacological literature, this edited volume’s chapters highlight the biodiversity-driven approaches which are now of eminent importance in natural products research. It addresses the question why natural products display such complex chemical information, what makes them unique, as they often are, and what their characteristics are. Practical questions such as supply of natural substances and production optimization strategies are also covered.
Virtual Screening: An Alternative or Complement to High Throughput Screening? by Gerhard Klebe Pdf
In the next couple of years the human genome will be fully sequenced. This will provide us with the sequence and overall function of all human genes as well as the complete genome for many micro-organisms. Subsequently it is hoped, by means of powerful bioinformatic tools, to determine the gene variants that contribute to various multifactorial diseases and genes that exist in certain infectious agents but not humans. As a consequence, this will allow us to define the most appropriate levels for drug intervention. It can be expected that the number of potential drug targets will increase, possibly by a factor of 10 or more. Nevertheless, sequencing the human genome or, for that matter, the genome of other species will only be the starting point for the understanding of their biological function. Structural genomics is a likely follow-up, combined with new techniques to validate the therapeutic relevance of such newly discovered targets. Accordingly, it can be expected that in the near future we will witness a substantial increase in novel putative targets for drugs. To address these new targets effectively, we require new approaches and innovative tools. At present, two alternative, yet complementary, techniques are employed: experimental high-throughput screening (HTS) of large compound libraries, increasingly provided by combinatorial chemistry, and computational methods for virtual screening and de novo design. As kind of status report on the maturity of virtual screening as a technique in drug design, the first workshop on new approaches in drug design and discovery was held in March 1999, at Schloß Rauischholzhausen, near Marburg in Germany. More than 80 scientists gathered and discussed their experience with the different techniques. The speakers were invited to summarize their contributions together with their impressions on the present applicability of their approach. Several of the speakers followed this request which is summarized in this publication.
Computer Applications in Drug Discovery and Development by Puratchikody, A.,Prabu, S. Lakshmana,Umamaheswari, A. Pdf
With more restrictions upon animal experimentations, pharmaceutical industries are currently focusing on a new generation of experiments and technologies that are considerably more efficient and less controversial. The integration of computational and experimental strategies has led to the identification and development of promising compounds. Computer Applications in Drug Discovery and Development is a pivotal reference source that provides innovative research on the application of computers for discovering and designing new drugs in modern molecular biology and medicinal chemistry. While highlighting topics such as chemical structure databases and dataset utilization, this publication delves into the current panorama of drug discovery, where high drug failure rates are a major concern and properly designed virtual screening strategies can be a time-saving, cost-effective, and productive alternative. This book is ideally designed for chemical engineers, pharmacists, molecular biologists, students, researchers, and academicians seeking current research on the unexplored avenues and future perspectives of drug design.
Virtual Screening for Bioactive Molecules by Hans-Joachim Böhm,Gisbert Schneider Pdf
Recent progress in high-throughput screening, combinatorial chemistry and molecular biology has radically changed the approach to drug discovery in the pharmaceutical industry. New challenges in synthesis result in new analytical methods. At present, typically 100,000 to one million molecules have to be tested within a short period and, therefore, highly effective screening methods are necessary for today's researchers - preparing and characterizing one compound after another belongs to the past. Intelligent, computer-based search agents are needed and "virtual screening" provides solutions to many problems. Such screening comprises innovative computational techniques designed to turn raw data into valuable chemical information and to assist in extracting the relevant molecular features. This handbook is unique in bringing together the various efforts in the field of virtual screening to provide the necessary methodological framework for more effective research. Leading experts give a thorough introduction to the state of the art along with a critical assessment of both successful applications and drawbacks. The information collated here will be indispensable for experienced scientists, as well as novices, working in medicinal chemistry and related disciplines.
Virtual Screening and Drug Docking, Volume 59 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Can docking scoring functions guarantee success in virtual screening?, No dance, no partner! A tale of flexibility in docking and virtual screening, Handling Imbalance Data in Virtual Screening, Rational computational approaches to predict novel drug candidates against leishmaniasis, Virtual screening against Mtb DNA gyrase: Applications and success stories, Using Filters in Virtual Screening: A Brief Guide to Minimize Errors and Maximize Efficiency, and more. Additional chapters in the new release include Machine Learning and Deep Learning Strategies for Virtual Screening, Applications of the Virtual Screening to find the novel HIV-1 therapeutic agents, and Large-scale screening of small molecules with docking strategies and its impact on drug discovery. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Annual Reports on Medicinal Chemistry series Updated release includes the latest information on Virtual Screening and Drug Docking
Computational Drug Discovery and Design by Mohini Gore,Umesh B. Jagtap Pdf
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.
Applied Chemoinformatics by Thomas Engel,Johann Gasteiger Pdf
Edited by world-famous pioneers in chemoinformatics, this is a clearly structured and applications-oriented approach to the topic, providing up-to-date and focused information on the wide range of applications in this exciting field. The authors explain methods and software tools, such that the reader will not only learn the basics but also how to use the different software packages available. Experts describe applications in such different fields as structure-spectra correlations, virtual screening, prediction of active sites, library design, the prediction of the properties of chemicals, the development of new cosmetics products, quality control in food, the design of new materials with improved properties, toxicity modeling, assessment of the risk of chemicals, and the control of chemical processes. The book is aimed at advanced students as well as lectures but also at scientists that want to learn how chemoinformatics could assist them in solving their daily scientific tasks. Together with the corresponding textbook Chemoinformatics - Basic Concepts and Methods (ISBN 9783527331093) on the fundamentals of chemoinformatics readers will have a comprehensive overview of the field.
Computation in BioInformatics by S. Balamurugan,Anand T. Krishnan,Dinesh Goyal,Balakumar Chandrasekaran,Boomi Pandi Pdf
COMPUTATION IN BIOINFORMATICS Bioinformatics is a platform between the biology and information technology and this book provides readers with an understanding of the use of bioinformatics tools in new drug design. The discovery of new solutions to pandemics is facilitated through the use of promising bioinformatics techniques and integrated approaches. This book covers a broad spectrum of the bioinformatics field, starting with the basic principles, concepts, and application areas. Also covered is the role of bioinformatics in drug design and discovery, including aspects of molecular modeling. Some of the chapters provide detailed information on bioinformatics related topics, such as silicon design, protein modeling, DNA microarray analysis, DNA-RNA barcoding, and gene sequencing, all of which are currently needed in the industry. Also included are specialized topics, such as bioinformatics in cancer detection, genomics, and proteomics. Moreover, a few chapters explain highly advanced topics, like machine learning and covalent approaches to drug design and discovery, all of which are significant in pharma and biotech research and development. Audience Researchers and engineers in computation biology, information technology, bioinformatics, drug design, biotechnology, pharmaceutical sciences.
High-Performance Modelling and Simulation for Big Data Applications by Joanna Kołodziej,Horacio González-Vélez Pdf
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
Biophysical and Computational Tools in Drug Discovery by Anil Kumar Saxena Pdf
This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.
