This volume provides a collection of protocols and approaches for the creation of novel ligand binding proteins, compiled and described by many of today's leaders in the field of protein engineering. Chapters focus on modeling protein ligand binding sites, accurate modeling of protein-ligand conformational sampling, scoring of individual docked solutions, structure-based design program such as ROSETTA, protein engineering, and additional methodological approaches. Examples of applications include the design of metal-binding proteins and light-induced ligand binding proteins, the creation of binding proteins that also display catalytic activity, and the binding of larger peptide, protein, DNA and RNA ligands. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field.

There is a compelling need for new drugs and efficient treatments against mosquito-borne diseases. Environmentally safe, but effective insecticides that address the problems of resistance are required. Computational Design of Chemicals for the Control of Mosquitoes and Their Diseases explains how the search for new substances effective against mosquitoes and their diseases has benefited from the use of in silico techniques. QSAR modeling is suited to identify the key structural features and/or physicochemical properties explaining an activity and to propose candidate molecules for further evaluation by laboratory tests. Homology modeling is useful to approximate the 3D structure of proteins of interest. Pharmacophore modeling is a powerful means to capture the chemical features responsible for an activity and to identify new potentially active compounds via the virtual screening of databases. Fugacity modeling and a wealth of other modeling paradigms are useful for risk assessment in vector borne disease control.

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

This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.

The binding of small ligands to biological molecules is central to most aspects of biological function. The past twenty years has seen the development of an increasing armoury of biophysical methods that not only detect such binding, but also provide varying degrees of information about the kinetics, thermodynamics and structural aspects of the process. These methods have received increasing attention with the growth in more rational approaches to drug discovery and design. This book reviews the latest advances in the application of biophysics to the study of ligand binding. It provides a complete overview of current techniques to identify ligands, characterise their binding sites and understand their binding mechanisms. Particular emphasis is given to the combined use of different techniques and their relative strengths and weaknesses. Consistency in the way each technique is described makes it easy for readers to select the most suitable protocol for their research. The introduction explains why some techniques are more suitable than others and emphasizes the possible synergies between them. The following chapters, all written by a specialist in the particular technique, focus on each method individually. The book finishes by describing how several complimentary techniques can be used together for maximum effectiveness. This book is suitable for biomolecular scientists at graduate or post-doctoral level in academia and industry. Biologists and chemists will also find it a useful introduction to the techniques available.

Computational Drug Discovery A comprehensive resource that explains a wide array of computational technologies and methods driving innovation in drug discovery Computational Drug Discovery: Methods and Applications (2 volume set) covers a wide range of cutting-edge computational technologies and computational chemistry methods that are transforming drug discovery. The book delves into recent advances, particularly focusing on artificial intelligence (AI) and its application for protein structure prediction, AI-enabled virtual screening, and generative modeling for compound design. Additionally, it covers key technological advancements in computing such as quantum and cloud computing that are driving innovations in drug discovery. Furthermore, dedicated chapters that addresses the recent trends in the field of computer aided drug design, including ultra-large-scale virtual screening for hit identification, computational strategies for designing new therapeutic modalities like PROTACs and covalent inhibitors that target residues beyond cysteine are also presented. To offer the most up-to-date information on computational methods utilized in computational drug discovery, it covers chapters highlighting the use of molecular dynamics and other related methods, application of QM and QM/MM methods in computational drug design, and techniques for navigating and visualizing the chemical space, as well as leveraging big data to drive drug discovery efforts. The book is thoughtfully organized into eight thematic sections, each focusing on a specific computational method or technology applied to drug discovery. Authored by renowned experts from academia, pharmaceutical industry, and major drug discovery software providers, it offers an overview of the latest advances in computational drug discovery. Key topics covered in the book include: Application of molecular dynamics simulations and related approaches in drug discovery The application of QM, hybrid approaches such as QM/MM, and fragment molecular orbital framework for understanding protein-ligand interactions Adoption of artificial intelligence in pre-clinical drug discovery, encompassing protein structure prediction, generative modeling for de novo design, and virtual screening. Techniques for navigating and visualizing the chemical space, along with harnessing big data to drive drug discovery efforts. Methods for performing ultra-large-scale virtual screening for hit identification. Computational strategies for designing new therapeutic models, including PROTACs and molecular glues. In silico ADMET approaches for predicting a variety of pharmacokinetic and physicochemical endpoints. The role of computing technologies like quantum computing and cloud computing in accelerating drug discovery This book will provide readers an overview of the latest advancements in computational drug discovery and serve as a valuable resource for professionals engaged in drug discovery.