NMR in structure-based drug design

2017 ◽  
Vol 61 (5) ◽  
pp. 485-493 ◽  
Author(s):  
Marta G. Carneiro ◽  
Eiso AB ◽  
Stephan Theisgen ◽  
Gregg Siegal
Keyword(s):  
Drug Discovery ◽  
Nmr Spectroscopy ◽  
Structural Information ◽  
Paramagnetic Nmr ◽  
Structure Based Drug Design ◽  
Nmr Data ◽  
Data Collection And Analysis ◽  
Recent Developments ◽  
Speed Up ◽  
Different Levels

NMR spectroscopy is a powerful technique that can provide valuable structural information for drug discovery endeavors. Here, we discuss the strengths (and limitations) of NMR applications to structure-based drug discovery, highlighting the different levels of resolution and throughput obtainable. Additionally, the emerging field of paramagnetic NMR in drug discovery and recent developments in approaches to speed up and automate protein-observed NMR data collection and analysis are discussed.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Smart, Innovative and Intelligent Technologies Used in Drug Designing

2014 ◽  
pp. 285-301
Author(s):  
S. Deshpande ◽  
S. K. Basu ◽  
X. Li ◽  
X. Chen
Keyword(s):  
Drug Discovery ◽  
Protein Structures ◽  
Three Dimensional ◽  
New Drugs ◽  
Smart Manufacturing ◽  
Data Sets ◽  
Mathematical Methods ◽  
Structure Based Drug Design ◽  
Recent Developments ◽  
Therapeutic Compounds

Smart and intelligent computational methods are essential nowadays for designing, manufacturing and optimizing new drugs. New and innovative computational tools and algorithms are consistently developed and applied for the development of novel therapeutic compounds in many research projects. Rapid developments in the architecture of computers have also provided complex calculations to be performed in a smart, intelligent and timely manner for desired quality outputs. Research groups worldwide are developing drug discovery platforms and innovative tools following smart manufacturing ideas using highly advanced biophysical, statistical and mathematical methods for accelerated discovery and analysis of smaller molecules. This chapter discusses novel innovative applications in drug discovery involving use of structure-based drug design which utilizes geometrical knowledge of the three-dimensional protein structures. It discusses statistical and physics based methods such as quantum mechanics and classical molecular dynamics which can also play a major role in improving the performance and in prediction of computational drug discovery. Lastly, the authors provide insights on recent developments in cloud computing with significant increase in smart and intelligent computational power thus allowing larger data sets to be analyzed simultaneously on multi processor cloud systems. Future directions for the research are outlined.

scholarly journals Smart, Innovative and Intelligent Technologies Used in Drug Designing

2017 ◽  
pp. 1175-1191
Author(s):  
S. Deshpande ◽  
S. K. Basu ◽  
X. Li ◽  
X. Chen
Keyword(s):  
Drug Discovery ◽  
Protein Structures ◽  
Three Dimensional ◽  
New Drugs ◽  
Smart Manufacturing ◽  
Data Sets ◽  
Mathematical Methods ◽  
Structure Based Drug Design ◽  
Recent Developments ◽  
Therapeutic Compounds

Smart and intelligent computational methods are essential nowadays for designing, manufacturing and optimizing new drugs. New and innovative computational tools and algorithms are consistently developed and applied for the development of novel therapeutic compounds in many research projects. Rapid developments in the architecture of computers have also provided complex calculations to be performed in a smart, intelligent and timely manner for desired quality outputs. Research groups worldwide are developing drug discovery platforms and innovative tools following smart manufacturing ideas using highly advanced biophysical, statistical and mathematical methods for accelerated discovery and analysis of smaller molecules. This chapter discusses novel innovative applications in drug discovery involving use of structure-based drug design which utilizes geometrical knowledge of the three-dimensional protein structures. It discusses statistical and physics based methods such as quantum mechanics and classical molecular dynamics which can also play a major role in improving the performance and in prediction of computational drug discovery. Lastly, the authors provide insights on recent developments in cloud computing with significant increase in smart and intelligent computational power thus allowing larger data sets to be analyzed simultaneously on multi processor cloud systems. Future directions for the research are outlined.

scholarly journals Insights into Structures and Dynamics of Flavivirus Proteases from NMR Studies

2020 ◽  
Vol 21 (7) ◽  
pp. 2527 ◽  
Author(s):  
Qingxin Li ◽  
CongBao Kang
Keyword(s):  
Nmr Spectroscopy ◽  
Drug Design ◽  
Conformational Changes ◽  
Structural Information ◽  
Protein Structures ◽  
Rational Drug Design ◽  
Solution Nmr ◽  
Nmr Studies ◽  
Structure Based Drug Design ◽  
Additional Information

Nuclear magnetic resonance (NMR) spectroscopy plays important roles in structural biology and drug discovery, as it is a powerful tool to understand protein structures, dynamics, and ligand binding under physiological conditions. The protease of flaviviruses is an attractive target for developing antivirals because it is essential for the maturation of viral proteins. High-resolution structures of the proteases in the absence and presence of ligands/inhibitors were determined using X-ray crystallography, providing structural information for rational drug design. Structural studies suggest that proteases from Dengue virus (DENV), West Nile virus (WNV), and Zika virus (ZIKV) exist in open and closed conformations. Solution NMR studies showed that the closed conformation is predominant in solution and should be utilized in structure-based drug design. Here, we reviewed solution NMR studies of the proteases from these viruses. The accumulated studies demonstrated that NMR spectroscopy provides additional information to understand conformational changes of these proteases in the absence and presence of substrates/inhibitors. In addition, NMR spectroscopy can be used for identifying fragment hits that can be further developed into potent protease inhibitors.

The potential of cryo-electron microscopy for structure-based drug design

2017 ◽  
Vol 61 (5) ◽  
pp. 543-560 ◽  
Author(s):  
Andreas Boland ◽  
Leifu Chang ◽  
David Barford
Keyword(s):  
Electron Microscopy ◽  
Drug Discovery ◽  
Drug Design ◽  
Structural Information ◽  
Biological Molecules ◽  
Ligand Complex ◽  
Structure Based Drug Design ◽  
Technical Developments ◽  
Cryo Electron Microscopy ◽  
Therapeutic Development

Structure-based drug design plays a central role in therapeutic development. Until recently, protein crystallography and NMR have dominated experimental approaches to obtain structural information of biological molecules. However, in recent years rapid technical developments in single particle cryo-electron microscopy (cryo-EM) have enabled the determination to near-atomic resolution of macromolecules ranging from large multi-subunit molecular machines to proteins as small as 64 kDa. These advances have revolutionized structural biology by hugely expanding both the range of macromolecules whose structures can be determined, and by providing a description of macromolecular dynamics. Cryo-EM is now poised to similarly transform the discipline of structure-based drug discovery. This article reviews the potential of cryo-EM for drug discovery with reference to protein ligand complex structures determined using this technique.

scholarly journals Deciphering the structural attributes of protein–heparan sulfate interactions using chemo-enzymatic approaches and NMR spectroscopy

Glycobiology ◽  
2021 ◽  
Author(s):  
Aurélie Préchoux ◽  
Jean-Pierre Simorre ◽  
Hugues Lortat-Jacob ◽  
Cédric Laguri
Keyword(s):  
Nmr Spectroscopy ◽  
Structural Information ◽  
Protein Complexes ◽  
Nmr Data ◽  
Saccharide Binding ◽  
Heparan Sulfates ◽  
Chemical Groups ◽  
Oligosaccharide Structures ◽  
Sulfo Groups ◽  
Structural Determinant

Abstract Heparan sulfates (HS) is a polysaccharide found at the cell surface, where it mediates interactions with hundreds of proteins and regulates major pathophysiological processes. HS is highly heterogeneous and structurally complex and examples that define their structure–activity relationships remain limited. Here, in order to characterize a protein–HS interface and define the corresponding saccharide-binding domain, we present a chemo-enzymatic approach that generates 13C-labeled HS-based oligosaccharide structures. Nuclear magnetic resonance (NMR) spectroscopy, which efficiently discriminates between important or redundant chemical groups in the oligosaccharides, is employed to characterize these molecules alone and in interaction with proteins. Using chemokines as model system, docking based on NMR data on both proteins and oligosaccharides enable the identification of the structural determinant involved in the complex. This study shows that both the position of the sulfo groups along the chain and their mode of presentation, rather than their overall number, are key determinant and further points out the usefulness of these 13C-labeled oligosaccharides in obtaining detailed structural information on HS–protein complexes.

scholarly journals The Growing Role of Electron Microscopy in Anti-parasitic Drug Discovery

2019 ◽  
Vol 25 (39) ◽  
pp. 5279-5290
Author(s):  
R.M. Johnson ◽  
S. Rawson ◽  
M.J. McPhillie ◽  
C.W.G. Fishwick ◽  
S.P. Muench
Keyword(s):  
Electron Microscopy ◽  
Drug Discovery ◽  
High Resolution ◽  
Drug Design ◽  
Structural Information ◽  
Protein Structures ◽  
Parasite Protein ◽  
Structure Based Drug Design ◽  
Dramatic Rise ◽  
Review Reports

Background: Parasite diseases are a huge burden on human health causing significant morbidity and mortality. However, parasite structure based drug discovery programmes have been hindered by a lack of high resolution structural information from parasite derived proteins and have often relied upon homology models from mammalian systems. The recent renaissance in electron microscopy (EM) has caused a dramatic rise in the number of structures being determined at high resolution and subsequently enabled it to be thought of as a tool in drug discovery. Results: In this review, we discuss the challenges associated with the structural determination of parasite proteins including the difficulties in obtaining sufficient quantities of protein. We then discuss the reasons behind the resurgence in EM, how it may overcome some of these challenges and provide examples of EM derived parasite protein structures. Finally, we discuss the challenges which EM needs to overcome before it is used as a mainstream technique in anti-parasite drug discovery. Conclusions: This review reports the progress that has been made in obtaining sufficient quantities of proteins for structural studies and the role EM may play in future structure based drug design programs. The outlook for future structure based drug design programs against some of the most devastating parasite diseases looks promising.

Ligand- and Structure-Based Drug Design and Optimization using KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6458-6479 ◽  
Author(s):  
Michael P. Mazanetz ◽  
Charlotte H.F. Goode ◽  
Ewa I. Chudyk
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Candidate Selection ◽  
Structure Based Drug Design ◽  
Design And Optimization ◽  
Open Source Data ◽  
Source Data ◽  
Recent Developments ◽  
Hit Identification ◽  
Early Drug

In recent years there has been a paradigm shift in how data is being used to progress early drug discovery campaigns from hit identification to candidate selection. Significant developments in data mining methods and the accessibility of tools for research scientists have been instrumental in reducing drug discovery timelines and in increasing the likelihood of a chemical entity achieving drug development milestones. KNIME, the Konstanz Information Miner, is a leading open source data analytics platform and has supported drug discovery endeavours for over a decade. KNIME provides a rich palette of tools supported by an extensive community of contributors to enable ligandand structure-based drug design. This review will examine recent developments within the KNIME platform to support small-molecule drug design and provide a perspective on the challenges and future developments within this field.

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