Expanded Interaction Fingerprint Method for Analyzing Ligand Binding Modes in Docking and Structure-Based Drug Design.

ChemInform ◽  
2005 ◽  
Vol 36 (6) ◽  
Author(s):  
Matthew D. Kelly ◽  
Ricardo L. Mancera
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Zbigniew Dutkiewicz

AbstractDrug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.


Author(s):  
Sanchaita Rajkhowa ◽  
Ramesh C. Deka

Molecular docking is a key tool in structural biology and computer-assisted drug design. Molecular docking is a method which predicts the preferred orientation of a ligand when bound in an active site to form a stable complex. It is the most common method used as a structure-based drug design. Here, the authors intend to discuss the various types of docking methods and their development and applications in modern drug discovery. The important basic theories such as sampling algorithm and scoring functions have been discussed briefly. The performances of the different available docking software have also been discussed. This chapter also includes some application examples of docking studies in modern drug discovery such as targeted drug delivery using carbon nanotubes, docking of nucleic acids to find the binding modes and a comparative study between high-throughput screening and structure-based virtual screening.


2020 ◽  
Vol 14 ◽  
Author(s):  
Thao N. T. Ho ◽  
Nikita Abraham ◽  
Richard J. Lewis

Neuronal nicotinic acetylcholine receptors (nAChRs) are prototypical cation-selective, ligand-gated ion channels that mediate fast neurotransmission in the central and peripheral nervous systems. nAChRs are involved in a range of physiological and pathological functions and hence are important therapeutic targets. Their subunit homology and diverse pentameric assembly contribute to their challenging pharmacology and limit their drug development potential. Toxins produced by an extensive range of algae, plants and animals target nAChRs, with many proving pivotal in elucidating receptor pharmacology and biochemistry, as well as providing templates for structure-based drug design. The crystal structures of these toxins with diverse chemical profiles in complex with acetylcholine binding protein (AChBP), a soluble homolog of the extracellular ligand-binding domain of the nAChRs and more recently the extracellular domain of human α9 nAChRs, have been reported. These studies have shed light on the diverse molecular mechanisms of ligand-binding at neuronal nAChR subtypes and uncovered critical insights useful for rational drug design. This review provides a comprehensive overview and perspectives obtained from structure and function studies of diverse plant and animal toxins and their associated inhibitory mechanisms at neuronal nAChRs.


ChemBioChem ◽  
2002 ◽  
Vol 3 (2-3) ◽  
pp. 246-249 ◽  
Author(s):  
Milton T. Stubbs ◽  
Sabine Reyda ◽  
Frank Dullweber ◽  
Maren Möller ◽  
Gerhard Klebe ◽  
...  

2014 ◽  
Vol 20 (20) ◽  
pp. 3323-3337 ◽  
Author(s):  
M. Reddy ◽  
C. Reddy ◽  
R. Rathore ◽  
Mark Erion ◽  
P. Aparoy ◽  
...  

2021 ◽  
Author(s):  
Himanshu Goel ◽  
Anthony Hazel ◽  
Vincent D. Ustach ◽  
Sunhwan Jo ◽  
Wenbo Yu ◽  
...  

Predicting relative protein-ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design. The Site Identification by Ligand Competitive Saturation (SILCS) methodology is based on functional...


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