Advances in theoretical studies on the design of single boron atom compounds

Research output: Contribution to journalScientific review

1 Citation (Scopus)

Abstract

© 2018 Bentham Science Publishers. Background: Single Boron Atom Compounds (SBACs) have been used for drug discovery in disease-associated proteins due to the empty p-orbital in the atomic structure of boron, which allows it to experience diverse binding modes during molecular recognition with a range of proteins. Objective: During the molecular recognition process with a protein target, SBACs can assume an anionic tetragonal arrangement or a neutral trigonal planar structure to produce four possible reversible covalent or non-covalent binding modes with a protein. However, the development of new SBACs has been hampered by the fact that most of the force fields present in many of the software packages used in drug design lack the various types of boron atom parameters. Methods: We review in silico studies in which a series of theory-based computational strategies have been used to overcome the lack of boron parameters in most of the force fields used in drug design. Results: The modeling studies discussed in this review have provided substantial insight into the molecular recognition of SBACs targeting different receptors, including the elucidation of some of the key interactions, which serve as a guide for the development of selective SBACs. Conclusion: Although the strategies employed in many of the studies presented here should serve in the development of selective SBACs, it is clear that the development of the precise force field parameters, which include not only the individual atom types but also the entire molecule, is still lacking, yet it is a necessary requirement for the design of new SBACS as well as for gaining insight into their molecular recognition.
Original languageAmerican English
Pages (from-to)3466-3475
Number of pages3118
JournalCurrent Pharmaceutical Design
DOIs
StatePublished - 1 Jan 2018

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Boron Compounds
Theoretical Models
Boron
Drug Design
Proteins
Drug Discovery
Computer Simulation
Software

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title = "Advances in theoretical studies on the design of single boron atom compounds",
abstract = "{\circledC} 2018 Bentham Science Publishers. Background: Single Boron Atom Compounds (SBACs) have been used for drug discovery in disease-associated proteins due to the empty p-orbital in the atomic structure of boron, which allows it to experience diverse binding modes during molecular recognition with a range of proteins. Objective: During the molecular recognition process with a protein target, SBACs can assume an anionic tetragonal arrangement or a neutral trigonal planar structure to produce four possible reversible covalent or non-covalent binding modes with a protein. However, the development of new SBACs has been hampered by the fact that most of the force fields present in many of the software packages used in drug design lack the various types of boron atom parameters. Methods: We review in silico studies in which a series of theory-based computational strategies have been used to overcome the lack of boron parameters in most of the force fields used in drug design. Results: The modeling studies discussed in this review have provided substantial insight into the molecular recognition of SBACs targeting different receptors, including the elucidation of some of the key interactions, which serve as a guide for the development of selective SBACs. Conclusion: Although the strategies employed in many of the studies presented here should serve in the development of selective SBACs, it is clear that the development of the precise force field parameters, which include not only the individual atom types but also the entire molecule, is still lacking, yet it is a necessary requirement for the design of new SBACS as well as for gaining insight into their molecular recognition.",
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Advances in theoretical studies on the design of single boron atom compounds. / Bello, Martiniano.

In: Current Pharmaceutical Design, 01.01.2018, p. 3466-3475.

Research output: Contribution to journalScientific review

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