This detailed book collects modern and established computer-based methods aimed at addressing the drug discovery challenge from disparate perspectives by exploiting information on ligand-protein recognition. Beginning with methods that allow for the exploration of specific areas of chemical space and the designing of virtual libraries, the volume continues with sections on methods based on docking, quantitative models, and molecular dynamics simulations, which are employed for ligand discovery or development, as well as methods exploiting an ensemble of protein structures for the…mehr
This detailed book collects modern and established computer-based methods aimed at addressing the drug discovery challenge from disparate perspectives by exploiting information on ligand-protein recognition. Beginning with methods that allow for the exploration of specific areas of chemical space and the designing of virtual libraries, the volume continues with sections on methods based on docking, quantitative models, and molecular dynamics simulations, which are employed for ligand discovery or development, as well as methods exploiting an ensemble of protein structures for the identification of potential protein targets. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Protein-Ligand Interactions and Drug Design provides detailed practical procedures of solid computer-aided drug design methodologies employed to rationalize and optimize protein-ligand interactions, for experienced researchers and novices alike.
Flavio Ballante is a researcher in the Department of Cell and Molecular Biology at Uppsala University (Sweden). He graduated in Medicinal Chemistry from Sapienza University in Rome (Italy) where he also obtained a Ph.D. in Pharmaceutical Sciences. During his academic career, he conducted research in France (University of Lorraine, Metz), the USA (Washington University School of Medicine in St. Louis, MO), and Sweden (Uppsala University, Uppsala), working on computer-aided drug design, chemistry, and biology experiments. His primary research goals are directed toward understanding the basis for molecular recognition at the atomic level, and his scientific activity is mainly focused on the design, development, and application of computational methods for ligand discovery.
Inhaltsangabe
Investigation of the Click-Chemical Space for Drug Design Using ZINClick.- Molecular Scaffold Hopping via Holistic Molecular Representation.- Biased Docking for Protein-Ligand Pose Prediction.- Binding Mode Prediction and Virtual Screening Applications by Covalent Docking.- Ligand-Receptor, Ligand-DNA Interactions and Drug Design.- Simulation of Ligand Transport in Receptors Using CaverDock.- Negative Image-Based Screening: Rigid Docking Using Cavity Information.- Negative Image-Based Rescoring: Using Cavity Information to Improve Docking Screening.- Fragment-Based Drug Design of Selective HDAC6 Inhibitors.- A Protocol to Use Comparative Binding Energy Analysis to Estimate Drug-Target Residence Time.- Dynamic Docking Using Multicanonical Molecular Dynamics: Simulating Complex Formation at the Atomistic Level.- Free Energy Calculations for Protein-Ligand Binding Prediction.- Exploiting Water Dynamics for Pharmacophore Screening.- Markov State Models to Elucidate Ligand Binding Mechanism.- From Homology Modeling to the Hit Identification and Drug Repurposing: A Structure-Based Approach in the Discovery of Novel Potential Anti-Obesity Compounds.- Multiple Target Drug Design Using LigBuilder 3.- Bionoi: A Voronoi Diagram-Based Representation of Ligand-Binding Sites in Proteins for Machine Learning Applications.- MDock: A Suite for Molecular Inverse Docking and Target Prediction.
Investigation of the Click-Chemical Space for Drug Design Using ZINClick.- Molecular Scaffold Hopping via Holistic Molecular Representation.- Biased Docking for Protein-Ligand Pose Prediction.- Binding Mode Prediction and Virtual Screening Applications by Covalent Docking.- Ligand-Receptor, Ligand-DNA Interactions and Drug Design.- Simulation of Ligand Transport in Receptors Using CaverDock.- Negative Image-Based Screening: Rigid Docking Using Cavity Information.- Negative Image-Based Rescoring: Using Cavity Information to Improve Docking Screening.- Fragment-Based Drug Design of Selective HDAC6 Inhibitors.- A Protocol to Use Comparative Binding Energy Analysis to Estimate Drug-Target Residence Time.- Dynamic Docking Using Multicanonical Molecular Dynamics: Simulating Complex Formation at the Atomistic Level.- Free Energy Calculations for Protein-Ligand Binding Prediction.- Exploiting Water Dynamics for Pharmacophore Screening.- Markov State Models to Elucidate Ligand Binding Mechanism.- From Homology Modeling to the Hit Identification and Drug Repurposing: A Structure-Based Approach in the Discovery of Novel Potential Anti-Obesity Compounds.- Multiple Target Drug Design Using LigBuilder 3.- Bionoi: A Voronoi Diagram-Based Representation of Ligand-Binding Sites in Proteins for Machine Learning Applications.- MDock: A Suite for Molecular Inverse Docking and Target Prediction.
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