Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

@article{Manoharan2010RationalizingFB,
  title={Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies},
  author={Prabu Manoharan and R. S. K. Vijayan and Nanda Ghoshal},
  journal={Journal of Computer-Aided Molecular Design},
  year={2010},
  volume={24},
  pages={843-864}
}
The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by… 

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References

SHOWING 1-10 OF 42 REFERENCES

Desirability‐based multiobjective optimization for global QSAR studies: Application to the design of novel NSAIDs with improved analgesic, antiinflammatory, and ulcerogenic profiles

This work proposed a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies considering simultaneously the pharmacological, pharmacokinetic and toxicological profile of a set of molecule candidates and suggests the relevant role of the bulkiness of alkyl substituents over the ulcerogenic properties for this family of compounds.

Structure-guided fragment screening for lead discovery.

This review describes the methods used for structure-based fragment screening and fragment-to-lead optimization and discusses a number of applications from the literature.

Fragonomics: fragment-based drug discovery.

Application of fragment screening by X-ray crystallography to the discovery of aminopyridines as inhibitors of beta-secretase.

Fragment-based lead discovery has been successfully applied to the aspartyl protease enzyme beta-secretase (BACE-1) and structure-based design approaches led to identification of low micromolar lead compounds that retain these interactions and additionally occupy adjacent hydrophobic pockets of the active site.

Beware of q2!

Pitfalls in QSAR

Application of fragment screening by X-ray crystallography to beta-secretase.

The fragment hits were weak inhibitors of BACE-1 in the millimolar range but were of interest because most of them displayed relatively good ligand efficiencies and exhibited a novel recognition motif that has not been seen before with aspartic proteases.

Molecular optimization using computational multi-objective methods.

This paper first presents a brief introduction to issues related to MOOP and then surveys the application of MOOP methods in the field of chemoinformatics.

Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery

The hypothesis that less complex molecules are more common starting points for the discovery of drugs is supported by the changes observed for these properties during the drug optimization phase.