Using molecular docking and molecular dynamics to investigate protein-ligand interactions

Background: Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators. Methods: DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening active and inactive datasets, GH scoring and ROC curve analysis. The best model was exposed as a 3D query to screen the hits from databases like GLASS (GPCR-Ligand Association), GPCR SARfari and Mini-Maybridge. Various filters were applied to retrieve the hit molecules having good drug-like properties. A known protein structure of hGPR40 (pdb: 4PHU) having TAK-875 as ligand complex was used to perform the molecular docking studies; using SYBYL-X 1.2 software. Results and Conclusion: Clustering both the models gave RMSD of 0.89. Therefore, the present approach explored the maximum features by combining both ligand and structure based pharmacophore models. A common structural motif as identified in combiphore for GPR40 modulation consists of the para-substituted phenyl propionic acid scaffold. Therefore, the combiphore approach, whereby maximum structural information (from both ligand and biological protein) is explored, gives maximum insights into the plausible protein-ligand interactions and provides potential lead candidates as exemplified in this study.

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A Frame Work for Learning Drug Designing through Molecular Modelling Software Techniques and Biological Databases for Protein-Ligand Interactions

International Journal of Engineering Research in Africa ◽

10.4028/www.scientific.net/jera.27.111 ◽

2016 ◽

Vol 27 ◽

pp. 111-118 ◽

Cited By ~ 2

Author(s):

R. Kannadasan ◽

M.S. Saleembasha ◽

I. Arnold Emerson

Keyword(s):

Molecular Docking ◽

Drug Discovery ◽

Ligand Docking ◽

Biological Databases ◽

Discovery Process ◽

Drug Discovery Process ◽

Protein Ligand Interactions ◽

Protein Receptors ◽

Ligand Interactions ◽

Strong Candidate

Applications of computer and information technology are indispensable in various fields especially in the field of biology. The use of computer aided tools plays a key role in solving biological problems. The spontaneous process of molecular docking is important for finding potentially strong candidate of drug for various viruses. The binding of protein receptors with ligand molecules is essential in drug discovery process. The aim of molecular docking tools is to predict the interaction between protein and ligand. This review outlines the major tools for protein - ligand docking which in turn emphasize the importance of molecular docking in modern drug discovery process.

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Scoring Functions of Protein-Ligand Interactions

Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery - Advances in Medical Technologies and Clinical Practice ◽

10.4018/978-1-5225-0115-2.ch009 ◽

2016 ◽

pp. 220-245 ◽

Cited By ~ 4

Author(s):

Zhiqiang Yan ◽

Jin Wang

Keyword(s):

Molecular Docking ◽

Drug Discovery ◽

Pharmaceutical Industry ◽

Academic Research ◽

Scoring Function ◽

Scoring Functions ◽

Virtual Database ◽

Protein Ligand Interactions ◽

Ligand Interactions ◽

Database Screening

Scoring function of protein-ligand interactions is used to recognize the “native” binding pose of a ligand on the protein and to predict the binding affinity, so that the active small molecules can be discriminated from the non-active ones. Scoring function is widely used in computationally molecular docking and structure-based drug discovery. The development and improvement of scoring functions have broad implications in pharmaceutical industry and academic research. During the past three decades, much progress have been made in methodology and accuracy for scoring functions, and many successful cases have be witnessed in virtual database screening. In this chapter, the authors introduced the basic types of scoring functions and their derivations, the commonly-used evaluation methods and benchmarks, as well as the underlying challenges and current solutions. Finally, the authors discussed the promising directions to improve and develop scoring functions for future molecular docking-based drug discovery.

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Recent Advances in Molecular Docking for the Research and Discovery of Potential Marine Drugs

Marine Drugs ◽

10.3390/md18110545 ◽

2020 ◽

Vol 18 (11) ◽

pp. 545

Author(s):

Guilin Chen ◽

Armel Jackson Seukep ◽

Mingquan Guo

Keyword(s):

Molecular Docking ◽

Drug Discovery ◽

Binding Mode ◽

Mechanisms Of Action ◽

Clinical Practices ◽

Drug Target Discovery ◽

Protein Ligand Interactions ◽

Active Chemical ◽

Ligand Interactions ◽

Discovery Potential

Marine drugs have long been used and exhibit unique advantages in clinical practices. Among the marine drugs that have been approved by the Food and Drug Administration (FDA), the protein–ligand interactions, such as cytarabine–DNA polymerase, vidarabine–adenylyl cyclase, and eribulin–tubulin complexes, are the important mechanisms of action for their efficacy. However, the complex and multi-targeted components in marine medicinal resources, their bio-active chemical basis, and mechanisms of action have posed huge challenges in the discovery and development of marine drugs so far, which need to be systematically investigated in-depth. Molecular docking could effectively predict the binding mode and binding energy of the protein–ligand complexes and has become a major method of computer-aided drug design (CADD), hence this powerful tool has been widely used in many aspects of the research on marine drugs. This review introduces the basic principles and software of the molecular docking and further summarizes the applications of this method in marine drug discovery and design, including the early virtual screening in the drug discovery stage, drug target discovery, potential mechanisms of action, and the prediction of drug metabolism. In addition, this review would also discuss and prospect the problems of molecular docking, in order to provide more theoretical basis for clinical practices and new marine drug research and development.

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Scoring Functions of Protein-Ligand Interactions

Oncology ◽

10.4018/978-1-5225-0549-5.ch036 ◽

2017 ◽

pp. 915-940

Author(s):

Zhiqiang Yan ◽

Jin Wang

Keyword(s):

Molecular Docking ◽

Drug Discovery ◽

Pharmaceutical Industry ◽

Academic Research ◽

Scoring Function ◽

Scoring Functions ◽

Virtual Database ◽

Protein Ligand Interactions ◽

Ligand Interactions ◽

Database Screening

Scoring function of protein-ligand interactions is used to recognize the “native” binding pose of a ligand on the protein and to predict the binding affinity, so that the active small molecules can be discriminated from the non-active ones. Scoring function is widely used in computationally molecular docking and structure-based drug discovery. The development and improvement of scoring functions have broad implications in pharmaceutical industry and academic research. During the past three decades, much progress have been made in methodology and accuracy for scoring functions, and many successful cases have be witnessed in virtual database screening. In this chapter, the authors introduced the basic types of scoring functions and their derivations, the commonly-used evaluation methods and benchmarks, as well as the underlying challenges and current solutions. Finally, the authors discussed the promising directions to improve and develop scoring functions for future molecular docking-based drug discovery.

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Evaluation of Scoring Function Performance on DNA-ligand Complexes

The Open Medicinal Chemistry Journal ◽

10.2174/1874104501913010040 ◽

2019 ◽

Vol 13 (1) ◽

pp. 40-49 ◽

Cited By ~ 2

Author(s):

Pedro Fong ◽

Hong-Kong Wong

Keyword(s):

Drug Discovery ◽

Scoring Function ◽

Binding Mode ◽

Scoring Functions ◽

Discriminative Power ◽

Ligand Complex ◽

Protein Ligand Interactions ◽

Minor Groove Binders ◽

Ligand Interactions ◽

Chemotherapy Agents

Background: DNA has been a pharmacological target for different types of treatment, such as antibiotics and chemotherapy agents, and is still a potential target in many drug discovery processes. However, most docking and scoring approaches were parameterised for protein-ligand interactions; their suitability for modelling DNA-ligand interactions is uncertain. Objective: This study investigated the performance of four scoring functions on DNA-ligand complexes. Material & Methods: Here, we explored the ability of four docking protocols and scoring functions to discriminate the native pose of 33 DNA-ligand complexes over a compiled set of 200 decoys for each DNA-ligand complexes. The four approaches were the AutoDock, ASP@GOLD, ChemScore@GOLD and GoldScore@GOLD. Results: Our results indicate that AutoDock performed the best when predicting binding mode and that ChemScore@GOLD achieved the best discriminative power. Rescoring of AutoDock-generated decoys with ChemScore@GOLD further enhanced their individual discriminative powers. All four approaches have no discriminative power in some DNA-ligand complexes, including both minor groove binders and intercalators. Conclusion: This study suggests that the evaluation for each DNA-ligand complex should be performed in order to obtain meaningful results for any drug discovery processes. Rescoring with different scoring functions can improve discriminative power.

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Molecular Dynamics Simulation of Bioactive Compounds Against Six Protein Target of Sars-Cov-2 As Covid-19 Antivirus Candidates

Jurnal Kimia VALENSI ◽

10.15408/jkv.v7i2.21634 ◽

2021 ◽

Vol 7 (2) ◽

pp. 178-187

Author(s):

Fikry Awaluddin ◽

Irmanida Batubara ◽

Setyanto Tri Wahyudi

Keyword(s):

Molecular Dynamics ◽

Free Energy ◽

Molecular Dynamics Simulation ◽

Bioactive Compounds ◽

Dynamics Simulation ◽

Ligand Complex ◽

Energy Value ◽

Protein Target ◽

Protein Ligand Interactions ◽

Ligand Interactions

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the virus that causes Coronavirus 2019 (COVID-19). To date, there has been no proven effective drug for the treatment or prevention of COVID-19. A study on developing inhibitors for this virus was performed using molecular dynamics simulation. 3CL-Pro, PL-Pro, Helicase, N, E, and M protein were used as protein targets. This study aimed to determine the stability of the selected protein-ligand complex through molecular dynamics simulation by Amber20 to propose bioactive compounds from natural products that have potential as a drug for COVID-19. Based on our previous study, the best value of free binding energy and protein-ligand interactions of the candidate compounds are obtained for each target protein through molecular docking. Corilagin (-14.42 kcal/mol), Scutellarein 7-rutinoside (-13.2 kcal/mol), Genistein 7-O-glucuronide (-10.52 kcal/mol), Biflavonoid-flavone base + 3O (-11.88 and -9.61 kcal/mol), and Enoxolone (-6.96 kcal/mol) has the best free energy value at each protein target. In molecular dynamics simulation, the 3CL-Pro-Corilagin complex was the most stable compared to other complexes, so that it was the most recommended compound. Further research is needed to test the selected ligand activity, which has the lowest free energy value of the six target proteins.

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19F-NMR in Target-based Drug Discovery

Current Medicinal Chemistry ◽

10.2174/0929867326666190610160534 ◽

2019 ◽

Vol 26 (26) ◽

pp. 4964-4983 ◽

Cited By ~ 7

Author(s):

CongBao Kang

Keyword(s):

Drug Discovery ◽

Conformational Changes ◽

Protein Structures ◽

19F Nmr ◽

Binding Affinities ◽

Protein Ligand Interactions ◽

Compound Libraries ◽

Ligand Interactions ◽

Reference Ligand ◽

Hit Identification

Solution NMR spectroscopy plays important roles in understanding protein structures, dynamics and protein-protein/ligand interactions. In a target-based drug discovery project, NMR can serve an important function in hit identification and lead optimization. Fluorine is a valuable probe for evaluating protein conformational changes and protein-ligand interactions. Accumulated studies demonstrate that 19F-NMR can play important roles in fragment- based drug discovery (FBDD) and probing protein-ligand interactions. This review summarizes the application of 19F-NMR in understanding protein-ligand interactions and drug discovery. Several examples are included to show the roles of 19F-NMR in confirming identified hits/leads in the drug discovery process. In addition to identifying hits from fluorinecontaining compound libraries, 19F-NMR will play an important role in drug discovery by providing a fast and robust way in novel hit identification. This technique can be used for ranking compounds with different binding affinities and is particularly useful for screening competitive compounds when a reference ligand is available.

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Thermodynamics of water mediating protein-ligand interactions in cytochrome P450cam: a molecular dynamics study

Biophysical Journal ◽

10.1016/s0006-3495(95)79955-6 ◽

1995 ◽

Vol 69 (3) ◽

pp. 810-824 ◽

Cited By ~ 59

Author(s):

V. Helms ◽

R.C. Wade

Keyword(s):

Molecular Dynamics ◽

Cytochrome P450cam ◽

Protein Ligand Interactions ◽

Ligand Interactions

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Halogen Bonding: An Underestimated Player in Membrane–drug Interactions

10.26434/chemrxiv.11894547.v1 ◽

2020 ◽

Author(s):

Rafael Nunes ◽

Diogo Vila Viçosa ◽

Paulo J. Costa

Keyword(s):

Drug Discovery ◽

Chemical Space ◽

Noncovalent Interactions ◽

Halogen Bonding ◽

Lewis Bases ◽

Protein Ligand Interactions ◽

Biochemical Systems ◽

Ligand Interactions ◽

Dynamics Simulations

<div>Halogen bonds (HaBs) are noncovalent interactions where halogen atoms act as electrophilic species interacting with Lewis bases. These interactions are relevant in biochemical systems being increasingly explored in drug discovery, mainly to modulate protein–ligand interactions. In this work, we report evidence for the existence of HaB-mediated halogen–phospholipid recognition phenomena as our molecular dynamics simulations support the existence of favorable interactions between halobenzene derivatives and both phosphate (PO) or ester (CO) oxygen acceptors from model phospholipid bilayers, thus providing insights into the role of HaBs in driving the permeation of halogenated drug like molecules across biological membranes. This represents a relevant molecular mechanism, previously overlooked, determining the pharmacological activity of halogenated molecules with implications in drug discovery and development, a place where halogenated molecules account for a significant part of the chemical space. Our data also shows that, as the ubiquitous hydrogen bond, HaBs should be accounted for in the development of membrane permeability models.</div>

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