Computational approaches and sigma-hole interactions: general discussion

Background: In view of many current mosquito-borne diseases there is a need for the design of novel repellents. Objective: The objective of this article is to review the results of the researches carried out by the authors in the computer-assisted design of novel mosquito repellents. Methods: Two methods in the computational design of repellents have been discussed: a) Quantitative Structure Activity Relationship (QSAR) studies from a set of repellents structurally related to DEET using computed mathematical descriptors, and b) Pharmacophore based modeling for design and discovery of novel repellent compounds including virtual screening of compound databases and synthesis of novel analogues. Results: Effective QSARs could be developed using mathematical structural descriptors. The pharmacophore based method is an effective tool for the discovery of new repellent molecules. Conclusion: Results reviewed in this article show that both QSAR and pharmacophore based methods can be used to design novel repellent molecules.

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Recent Advances and Computational Approaches in Peptide Drug Discovery

Current Pharmaceutical Design ◽

10.2174/1381612825666190911161106 ◽

2019 ◽

Vol 25 (31) ◽

pp. 3358-3366 ◽

Cited By ~ 2

Author(s):

Neha S. Maurya ◽

Sandeep Kushwaha ◽

Ashutosh Mani

Keyword(s):

Docking Studies ◽

Computational Approaches ◽

Simulation Tools ◽

Drug Candidates ◽

Recent Advances ◽

Long Duration ◽

Stability Of Complexes ◽

Therapeutic Peptides ◽

Target Binding ◽

Druggable Targets

Background: Drug design and development is a vast field that requires huge investment along with a long duration for providing approval to suitable drug candidates. With the advancement in the field of genomics, the information about druggable targets is being updated at a fast rate which is helpful in finding a cure for various diseases. Methods: There are certain biochemicals as well as physiological advantages of using peptide-based therapeutics. Additionally, the limitations of peptide-based drugs can be overcome by modulating the properties of peptide molecules through various biomolecular engineering techniques. Recent advances in computational approaches have been helpful in studying the effect of peptide drugs on the biomolecular targets. Receptor – ligand-based molecular docking studies have made it easy to screen compatible inhibitors against a target.Furthermore, there are simulation tools available to evaluate stability of complexes at the molecular level. Machine learning methods have added a new edge by enabling accurate prediction of therapeutic peptides. Results: Peptide-based drugs are expected to take over many popular drugs in the near future due to their biosafety, lower off-target binding chances and multifunctional properties. Conclusion: This article summarises the latest developments in the field of peptide-based therapeutics related to their usage, tools, and databases.

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