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Design of Novel Dual-Target Hits Against Malaria and Tuberculosis Using Computational Docking

  • Manoj Kumar
  • Anuj SharmaEmail author
Protocol
Part of the Methods in Pharmacology and Toxicology book series (MIPT)

Abstract

Drugs which are purposefully designed to hit more than one target (multi-target drugs) promise a better safety profile and low resistance probability. Multi-target therapy also offers a cost-effective model for pharmaceutical R&D, making it quite an appealing strategy in the domain of neglected tropical diseases (NTDs) and other infections/coinfections of the global impact such as malaria, tuberculosis, and AIDS. We reviewed herein different approaches (knowledge base and screening base) for designing multi-target inhibitors with the special emphasis on the research work of the authors. Additionally, a step-by-step guide (protocol) and different computational resources are also discussed in detail to design multi-target hits for malaria and tuberculosis.

Keywords

AIDS AutoDock Computational docking Druglikeness Infectious diseases Ligand efficiency Malaria Multi-target drugs Multi-target screening Neglected tropical diseases Tuberculosis 

Abbreviations

2D

Two dimensional

3D

Three dimensional

ACD

Advanced Chemistry Development, Inc.

ADMET

Absorption, distribution, metabolism, excretion, and toxicity

ADT

AutoDock Tool

AIDS

Acquired immune deficiency syndrome

AM1

Austin model 1

AMBER

Assisted model building with energy refinement

AMR

Antimicrobial resistance

BE

Binding energy

BMRB

Biological magnetic resonance data bank

CCDC

The Cambridge Crystallographic Data Centre

CHARMM

Chemistry at Harvard Macromolecular Mechanics

ChEMBL or ChEMBLdb

Chemical database of bioactive molecules with drug-like properties

COX

Cyclooxygenase

DHFR

Dihydrofolate reductase

DMEs

Disease-modifying agents

DMLs

Designed multiple ligands

DSV

Discovery Studio Visualizer

DUD

Directory of useful decoys

EGFR

Epidermal growth factor receptor

EMBL-EBI

European Bioinformatics Institute

FDA

Food and Drug Administration, USA

GA

Genetic algorithm

HIV

Human immunodeficiency virus

In silico (syn in computo)

Performed on computer

LE

Ligand efficiency

LGA

Lamarckian genetic algorithm

LS

Local search

MAPK

Mitogen-activated protein kinase

MD

Molecular dynamics

MDR

Multidrug resistance

MGLTools

Molecular Graphics Laboratory tools

MM2

Molecular mechanics 2

MMV

Molegro Molecular Viewer

MTDs

Multi-target drugs

MW

Molecular weight

NSAIDs

Nonsteroidal anti-inflammatory drugs

NTDs

Neglected tropical diseases

OMICS

Genomics, proteomics, or metabolomics

PAINS

Pan-assay interference compounds

PDB

Protein Data Bank

PM3

Parameterized model number 3

QSAR

Quantitative structure activity relationship

R&D

Research and development

RCSB

Research Collaboratory for Structural Bioinformatics

RMSD/rmsd

Root-mean-square deviation

SA

Simulated annealing

SHAFTS

Shape-Feature Similarity

SITITCH

Search tool for interacting chemicals

STRING

Search tool for the retrieval of interacting genes/proteins

TB

Tuberculosis

TCM

Traditional Chinese medicines

TDR

Total drug resistance

TS

Thymidylate synthase

TTD

Therapeutic target database

WT

Wild type

XRD

Extreme drug resistance

ZINC

Zinc Is Not Commercial (ZINC database)

Notes

Acknowledgments

The authors gratefully acknowledge Science and Engineering Research Board (SERB), Govt. of India (Grant No. SER-892-CMD), to financially assist this work.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of ChemistryIndian Institute of Technology RoorkeeRoorkeeIndia
  2. 2.Department of Chemistry and Chemical BiologyMcMaster UniversityHamiltonCanada

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