Nuclear receptors (NR) are ligand-induced activated transcription factors that are involved in numerous biological processes. Since the 1990's when the first structures were determined by means of X ray diffraction, the number of NR structures has increased considerably. Moreover several "omics" projects (genomics, pharmcogenomics and proteomics) have opened up great opportunities for the discovery of new targets, the characterization of abnormal protein patterns, the selection of "tailored" drugs and the evaluation of drug efficacy even with a lack of structural data. Furthermore, structure-based drug design, computational methods for in silico screening and nanobiotechnology- based tools are simplifying this time-consuming and money-intensive research of lead compounds and, possibly, new drugs. Biological interactions such as those that occur between a protein and ligand are concerted events where flexible molecules interact. Thus understanding flexibility of large molecules or biological complexes is of primary importance to help define the right model to approximate the reality for drug discovery, virtual screening, food safety analysis, etc. NRs are known as flexible targets, with many structural similarities, in particular for their Ligand Binding Domain: these similarities could be assumed to share behavioural qualities that belong to this class of compounds. Thus to supply a possible, complete and exhaustive answer to questions about the behaviour of NRs, their interactions with new potential drugs, endocrine disruptors such as animal and human food toxins, food additives or industry residuals, it is mandatory to approach the problem from a different point of view: a molecular modelling approach, steered synthesis, and in vitro and in vivo tests, etc. The aim of this book is to provide a state of the art review on investigations into Nuclear Receptors.

Nuclear receptors are ligand activated transcription factors that control numerous biological functions. Consequently, altering activity of these receptors is proposed, and indeed documented, to affect many physiological and pathological conditions in experimental animals and humans. Thus, nuclear receptors have become a major target in the effort to treat numerous diseases. This book will shed light on and emphasize intricate processes involved in designing as well as discovering physiological and pharmacological modulators of these important proteins. World-renowned scientists will share with the reader their professional expertise and extensive experience acquired through decades working with nuclear receptors. Chapters address the various means and consequences of modulating nuclear receptor activity will be presented and discussed. These modulators cover a wide span of moieties ranging from synthetic chemicals to natural products. In addition, the classification of these chemicals ranges from pan agonists to selective agonists and inverse agonists to antagonists. They also include proteolytic means to obliterate the receptor in the event that modulating its activity through canonical pharmacological agents becomes less effective and/or less desirable due to anticipated or experienced toxicities. Modulation of receptor activity may also take place in the absence of a ligand or through manipulating the structure of the receptor itself by controlling posttranslational events.

There are numerous excellent reviews on fragment-based drug discovery (FBDD), but there are to date no hand-holding guides or protocols with which one can embark on this orthogonal approach to complement traditional high throughput screening methodologies. This Methods in Enzymology volume offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens. The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD. Also elaborated by experienced researchers in FBDD are sample preparations of fragments, proteins, and GPCR as well as examples of how to generate leads from hits. Offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD

Molecular Modeling of Proteins, Second Edition provides a theoretical background of various methods available and enables non-specialists to apply methods to their problems by including updated chapters and new material not covered in the first edition. This detailed volume opens by featuring classical and advanced simulation methods as well as methods to set-up complex systems such as lipid membranes and membrane proteins and continues with chapters devoted to the simulation and analysis of conformational changes of proteins, computational methods for protein structure prediction, usage of experimental data in combination with computational techniques, as well as protein-ligand interactions, which are relevant in the drug design process. Written for the highly successful Methods in Molecular Biology series, chapters include thorough introductions, step-by-step instructions and notes on troubleshooting and avoiding common pitfalls. Update-to-date and authoritative, Molecular Modeling of Proteins, Second Edition aims to aid researchers in the physical, chemical and biosciences interested in utilizing this powerful technology.

This is a comprehensive introduction to Landau-Lifshitz equations and Landau-Lifshitz-Maxwell equations, beginning with the work by Yulin Zhou and Boling Guo in the early 1980s and including most of the work done by this Chinese group led by Zhou and Guo since. The book focuses on aspects such as the existence of weak solutions in multi dimensions, existence and uniqueness of smooth solutions in one dimension, relations with harmonic map heat flows, partial regularity and long time behaviors. The book is a valuable reference book for those who are interested in partial differential equations, geometric analysis and mathematical physics. It may also be used as an advanced textbook by graduate students in these fields.

Tens of thousands of chemicals are released into the environment every day. High-throughput screening (HTS) has offered a more efficient and cost-effective alternative to traditional toxicity tests that can profile these chemicals for potential adverse effects with the aim to prioritize a manageable number for more in depth testing and to provide clues to mechanism of toxicity. The Tox21 program, a collaboration between the National Institute of Environmental Health Sciences (NIEHS)/National Toxicology Program (NTP), the U.S. Environmental Protection Agency’s (EPA) National Center for Computational Toxicology (NCCT), the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS), and the U.S. Food and Drug Administration (FDA), has generated quantitative high-throughput screening (qHTS) data on a library of 10K compounds, including environmental chemicals and drugs, against a panel of nuclear receptor and stress response pathway assays during its production phase (phase II). The Tox21 Challenge, a worldwide modeling competition, was launched that asks a “crowd” of researchers to use these data to elucidate the extent to which the interference of biochemical and cellular pathways by compounds can be inferred from chemical structure data. In the Challenge participants were asked to model twelve assays related to nuclear receptor and stress response pathways using the data generated against the Tox21 10K compound library as the training set. The computational models built within this Challenge are expected to improve the community’s ability to prioritize novel chemicals with respect to potential concern to human health. This research topic presents the resulting computational models with good predictive performance from this Challenge.

Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. - Explains computer use in pharmacology using real-life case studies - Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research - Describes the role of AI in pharmacology and applications of CADD in various diseases