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.
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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)
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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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Kumar, M., Sharma, A. (2018). Design of Novel Dual-Target Hits Against Malaria and Tuberculosis Using Computational Docking. In: Roy, K. (eds) Multi-Target Drug Design Using Chem-Bioinformatic Approaches. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/7653_2018_22
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DOI: https://doi.org/10.1007/7653_2018_22
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