Skip to main content

Protein Homology Modeling for Effective Drug Design

  • Protocol
  • First Online:
Homology Modeling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2627))

  • 540 Accesses

Abstract

The effective drug design, especially for combating the multi-drug-resistant bacterial pathogens, requires more and more sophisticated procedures to obtain novel lead-like compounds. New classes of enzymes should be explored, especially those that help bacteria overcome existing treatments. The homology modeling is useful in obtaining the models of new enzymes; however, the active sites of them are sometimes present in closed conformations in the crystal structures, not suitable for drug design purposes. In such difficult cases, the combination of homology modeling, molecular dynamics simulations, and fragment screening can give satisfactory results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Franca TC (2015) Homology modeling: an important tool for the drug discovery. J Biomol Struct Dyn 33:1780–1793. https://doi.org/10.1080/07391102.2014.971429

    Article  CAS  Google Scholar 

  2. Muhammed MT, Aki-Yalcin E (2019) Homology modeling in drug discovery: overview, current applications, and future perspectives. Chem Biol Drug Des 93:12–20. https://doi.org/10.1111/cbdd.13388

    Article  CAS  Google Scholar 

  3. Haddad Y, Adam V, Heger Z (2020) Ten quick tips for homology modeling of high-resolution protein 3D structures. PLoS Comput Biol 16:e1007449. https://doi.org/10.1371/journal.pcbi.1007449

    Article  CAS  PubMed Central  Google Scholar 

  4. Webb B, Sali A (2017) Protein structure modeling with MODELLER. Methods Mol Biol 1654:39–54. https://doi.org/10.1007/978-1-4939-7231-9_4

    Article  CAS  Google Scholar 

  5. Waterhouse A, Bertoni M, Bienert S et al (2018) SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 46:W296–W303. https://doi.org/10.1093/nar/gky427

    Article  CAS  PubMed Central  Google Scholar 

  6. Kelm S, Shi J, Deane CM (2010) MEDELLER: homology-based coordinate generation for membrane proteins. Bioinformatics 26:2833–2840. https://doi.org/10.1093/bioinformatics/btq554

    Article  CAS  PubMed Central  Google Scholar 

  7. Haas J, Barbato A, Behringer D et al (2018) Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12. Proteins 86(Suppl 1):387–398. https://doi.org/10.1002/prot.25431

    Article  CAS  Google Scholar 

  8. Robin X, Haas J, Gumienny R et al (2021) Continuous Automated Model EvaluatiOn (CAMEO)-Perspectives on the future of fully automated evaluation of structure prediction methods. Proteins 89:1977–1986. https://doi.org/10.1002/prot.26213

  9. Laskowski RA, MacArthur MW, Moss DS et al (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26:283–291. https://doi.org/10.1107/S0021889892009944

    Article  CAS  Google Scholar 

  10. Hooft RW, Vriend G, Sander C et al (1996) Errors in protein structures. Nature 381:272. https://doi.org/10.1038/381272a0

    Article  CAS  Google Scholar 

  11. Sippl MJ (1993) Recognition of errors in three-dimensional structures of proteins. Proteins 17:355–362. https://doi.org/10.1002/prot.340170404

    Article  CAS  Google Scholar 

  12. Chen VB, Arendall WB 3rd, Headd JJ et al (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr 66:12–21. https://doi.org/10.1107/S0907444909042073

    Article  CAS  Google Scholar 

  13. Mysinger MM, Carchia M, Irwin JJ et al (2012) Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J Med Chem 55:6582–6594. https://doi.org/10.1021/jm300687e

    Article  CAS  PubMed Central  Google Scholar 

  14. Latti S, Niinivehmas S, Pentikainen OT (2016) Rocker: open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization. J Cheminform 8:45. https://doi.org/10.1186/s13321-016-0158-y

    Article  PubMed Central  Google Scholar 

  15. Spyrakis F, Benedetti P, Decherchi S et al (2015) A pipeline to enhance ligand virtual screening: integrating molecular dynamics and fingerprints for ligand and proteins. J Chem Inf Model 55:2256–2274. https://doi.org/10.1021/acs.jcim.5b00169

    Article  CAS  Google Scholar 

  16. Pinzi L, Rastelli G (2019) Molecular docking: shifting paradigms in drug discovery. Int J Mol Sci 20:4331. https://doi.org/10.3390/ijms20184331

  17. Brott AS, Clarke AJ (2019) Peptidoglycan O-acetylation as a virulence factor: its effect on lysozyme in the innate immune system. Antibiotics (Basel) 8:94. https://doi.org/10.3390/antibiotics8030094

    Article  CAS  Google Scholar 

  18. Sychantha D, Jones CS, Little DJ et al (2017) In vitro characterization of the antivirulence target of Gram-positive pathogens, peptidoglycan O-acetyltransferase A (OatA). PLoS Pathog 13:e1006667. https://doi.org/10.1371/journal.ppat.1006667

    Article  CAS  PubMed Central  Google Scholar 

  19. Blum M, Chang HY, Chuguransky S et al (2021) The InterPro protein families and domains database: 20 years on. Nucleic Acids Res 49:D344–D354. https://doi.org/10.1093/nar/gkaa977

    Article  CAS  Google Scholar 

  20. Letunic I, Bork P (2021) Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 49:W293–W296. https://doi.org/10.1093/nar/gkab301

    Article  CAS  PubMed Central  Google Scholar 

  21. Sterling T, Irwin JJ (2015) ZINC 15--ligand discovery for everyone. J Chem Inf Model 55:2324–2337. https://doi.org/10.1021/acs.jcim.5b00559

    Article  CAS  PubMed Central  Google Scholar 

  22. Huang J, Rauscher S, Nawrocki G et al (2017) CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat Methods 14:71–73. https://doi.org/10.1038/nmeth.4067

    Article  CAS  Google Scholar 

  23. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph Model 14:33–38. https://doi.org/10.1016/0263-7855(96)00018-5

    Article  CAS  Google Scholar 

  24. Pisani P, Caporuscio F, Carlino L et al (2016) Molecular dynamics simulations and classical multidimensional scaling unveil new metastable states in the conformational landscape of CDK2. PLoS One 11:e0154066. https://doi.org/10.1371/journal.pone.0154066

    Article  CAS  PubMed Central  Google Scholar 

  25. Comitani F, Gervasio FL (2018) Exploring cryptic pockets formation in targets of pharmaceutical interest with SWISH. J Chem Theory Comput 14:3321–3331. https://doi.org/10.1021/acs.jctc.8b00263

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by UOTT grant Inkubator Innowacyjności 4.0 to A.K.-B.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sławomir Filipek .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Gniado, N., Krawczyk-Balska, A., Mehta, P., Miszta, P., Filipek, S. (2023). Protein Homology Modeling for Effective Drug Design. In: Filipek, S. (eds) Homology Modeling. Methods in Molecular Biology, vol 2627. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2974-1_18

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-2974-1_18

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2973-4

  • Online ISBN: 978-1-0716-2974-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics