New leads of metallo-β-lactamase inhibitors from structure-based pharmacophore design

Olsen, Lars; Jost, Sandra; Adolph, Hans-Werner; Pettersson, Ingrid; Hemmingsen, Lars; Jørgensen, Flemming Steen

doi:10.1016/j.bmc.2005.11.046

Cited by 53 publications

(52 citation statements)

References 44 publications

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“…Compound 35 ( analysis revealed that the inhibitors' carboxylate groups interact with both Zn 2ϩ ions and active-site residues while displacing the bridging water (PDB 1JJE and 1JJT) (415). Disubstituted succinic acids have also been described as inhibitors of the L1 MBL and display binding modes similar to those in IMP-1 (284,303).…”

Section: Succinate Derivativesmentioning

confidence: 99%

Three Decades of β-Lactamase Inhibitors

Drawz¹,

2010

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SUMMARYSince the introduction of penicillin, β-lactam antibiotics have been the antimicrobial agents of choice. Unfortunately, the efficacy of these life-saving antibiotics is significantly threatened by bacterial β-lactamases. β-Lactamases are now responsible for resistance to penicillins, extended-spectrum cephalosporins, monobactams, and carbapenems. In order to overcome β-lactamase-mediated resistance, β-lactamase inhibitors (clavulanate, sulbactam, and tazobactam) were introduced into clinical practice. These inhibitors greatly enhance the efficacy of their partner β-lactams (amoxicillin, ampicillin, piperacillin, and ticarcillin) in the treatment of seriousEnterobacteriaceaeand penicillin-resistant staphylococcal infections. However, selective pressure from excess antibiotic use accelerated the emergence of resistance to β-lactam-β-lactamase inhibitor combinations. Furthermore, the prevalence of clinically relevant β-lactamases from other classes that are resistant to inhibition is rapidly increasing. There is an urgent need for effective inhibitors that can restore the activity of β-lactams. Here, we review the catalytic mechanisms of each β-lactamase class. We then discuss approaches for circumventing β-lactamase-mediated resistance, including properties and characteristics of mechanism-based inactivators. We next highlight the mechanisms of action and salient clinical and microbiological features of β-lactamase inhibitors. We also emphasize their therapeutic applications. We close by focusing on novel compounds and the chemical features of these agents that may contribute to a “second generation” of inhibitors. The goal for the next 3 decades will be to design inhibitors that will be effective for more than a single class of β-lactamases.

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Section: Succinate Derivativesmentioning

confidence: 99%

Three Decades of β-Lactamase Inhibitors

Drawz¹,

2010

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“…79 Pharmacophore models were generated based on succinic acid crystallized with IGF2 mRNA-binding protein 1 (IMP-1) (Protein Data Bank code 1JJT) and mercaptocarboxylate ligand crystallized with IMP-1 (Protein Data Bank code 1DD6). Catalyst 4.6 was used for pharmacophore generation as well as a database search.…”

Section: Gaurav and Gautammentioning

confidence: 99%

Structure-based three-dimensional pharmacophores as an alternative to traditional methodologies

Gaurav¹,

Gautam²

2014

JRLCR

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Journal of Receptor, Ligand and Channel Research DovepressAbstract: Structure-based pharmacophore approaches have become widely used in drug discovery and design. This can be attributed to the development of new tools and methods over the past decade. Various tools based on different premises have been developed, including active site information in traditional pharmacophores. These tools have been widely used in virtual screening, de novo design, and lead optimization and been proven to be highly successful. Studies based on simultaneous use of structure-based pharmacophores, ligand-based pharmacophores, and docking have also come into the picture recently. Here, the development of structure-based pharmacophores as an alternative to traditional drug discovery approaches is discussed, with emphasis on the advances and latest developments in tools and success stories involving their application.

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“…Catalyst includes a 3D database search program, and has been used extensively to design and optimize new ligands. [27][28][29] Some new directions in pharmacophore research involve the representation of the pharmacophore and how it is perceived and developed.…”

Section: Related Workmentioning

confidence: 99%

A self‐organizing algorithm for molecular alignment and pharmacophore development

Bandyopadhyay¹,

Agrafiotis²

2007

J Comput Chem

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We present a method for simultaneous three-dimensional (3D) structure generation and pharmacophorebased alignment using a self-organizing algorithm called Stochastic Proximity Embedding (SPE). Current flexible molecular alignment methods either start from a single low-energy structure for each molecule and tweak bonds or torsion angles, or choose from multiple conformations of each molecule. Methods that generate structures and align them iteratively (e.g., genetic algorithms) are often slow. In earlier work, we used SPE to generate good-quality 3D conformations by iteratively adjusting pairwise distances between atoms based on a set of geometric rules, and showed that it samples conformational space better and runs faster than earlier programs. In this work, we run SPE on the entire ensemble of molecules to be aligned. Additional information about which atoms or groups of atoms in each molecule correspond to points in the pharmacophore can come from an automatically generated hypothesis or be specified manually. We add distance terms to SPE to bring pharmacophore points from different molecules closer in space, and also to line up normal/direction vectors associated with these points. We also permit pharmacophore points to be constrained to lie near external coordinates from a binding site. The aligned 3D molecular structures are nearly correct if the pharmacophore hypothesis is chemically feasible; postprocessing by minimization of suitable distance and energy functions further improves the structures and weeds out infeasible hypotheses. The method can be used to test 3D pharmacophores for a diverse set of active ligands, starting from only a hypothesis about corresponding atoms or groups.

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New leads of metallo-β-lactamase inhibitors from structure-based pharmacophore design

Cited by 53 publications

References 44 publications

Three Decades of β-Lactamase Inhibitors

Three Decades of β-Lactamase Inhibitors

Structure-based three-dimensional pharmacophores as an alternative to traditional methodologies

A self‐organizing algorithm for molecular alignment and pharmacophore development

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