A comparison of conformational energies calculated by several molecular mechanics methods

Gundertofte, Klaus; Liljefors, Tommy; Norrby, Per‐Ola; Pettersson, Ingrid

doi:10.1002/(sici)1096-987x(199603)17:4<429::aid-jcc5>3.0.co;2-w

Cited by 147 publications

(120 citation statements)

References 47 publications

(1 reference statement)

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“…AFITT uses the Merck Molecular Mechanics Force Field (MMFF94; Halgren, 1996aHalgren, ,b,c,d, 1999Halgren & Nachbar, 1996). This force field was designed to reproduce ab initio accuracy in a broad range of chemical functionality and has been shown to produce satisfactory results with the small molecules typically encountered in biomolecular crystallography (Fu et al, 2011;Gundertofte et al, 1996;Halgren, 1999).…”

Section: Methodsmentioning

confidence: 99%

Improved ligand geometries in crystallographic refinement usingAFITTinPHENIX

Janowski

Moriarty

Kelley

et al. 2016

Acta Crystallogr D Struct Biol

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Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows. PHENIX-AFITT refinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentially difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows. PHENIX-AFITT refinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combining AFITT and the PHENIX software suite on a data set of 189 protein-ligand PDB structures are presented. Refinements using PHENIX-AFITT significantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. For the data presented, PHENIX-AFITT refinements result in more chemically accurate models for small-molecule ligands.

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Section: Methodsmentioning

confidence: 99%

Improved ligand geometries in crystallographic refinement usingAFITTinPHENIX

Janowski

Moriarty

Kelley

et al. 2016

Acta Crystallogr D Struct Biol

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“…Each structure was fully geometry optimized using a conjugate gradient procedure based on the TRIPOS force field and Gasteiger and Hückel charges. [47] The IC 50 values of all compounds towards MAO-A and MAO-B used to derive the CoMFA analyses model are listed in Tables 1 and 2. [48] The activity was expressed in terms of PIC 50 by the formula PIC 50 = −log 10 (IC 50 ).…”

Section: D-qsar Analysismentioning

confidence: 99%

Rapid synthesis of flavone‐based monoamine oxidase (MAO) inhibitors targeting two active sites using click chemistry

et al. 2016

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A new library of flavone derivatives targeting two active sites of monoamine oxidases ("aromatic cage" and substrate cavity) were designed and synthesized using click chemistry (CuAAC reaction) between 6-N -2-phenyl chromones (Az1-Az2) and a series of alkynes (k1-k20). Their inhibitory activities against MAO isoforms (MAO-A and MAO-B) are evaluated. Compounds with fluorine, amide bonds, or amino bonds have shown better inhibition. The most potent flavone MAO inhibitor studied is Az2k19 (1.6 μm for MAO-A, 2.1 μm for MAO-B), while Az1k15 and Az2k15 displayed better selectivity toward MAO-B (SI > 10). Docking studies are in accordance with our hypothesis that these inhibitors are most likely located at both the substrate cavity and the "aromatic cage". Our results show that it is considerable to develop new MAO inhibitors from C6 substitution of flavone derivatives and that these compounds are also potential for the treatment of diseases associated with MAOs.

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“…For the remainder of this paper, “MMFF” will collectively refer to both MMFF94 and MMFF94s variants. MMFF has shown robustness and quality in dealing with small molecules superior to the majority of generalized force fields in use at the time of its first introduction [[8],[13]], and also on par or better than the more recent OPLS2005 and GAFF force fields [[14]]. Its versatility and effectiveness warranted its implementation in all major commercial molecular modelling packages (CCG MOE, Schrödinger Maestro, MolSoft ICM, Certara SYBYL-X) and cheminformatics toolkits (ChemAxon, OpenEye) currently on the market.…”

Section: Introductionmentioning

confidence: 99%

Bringing the MMFF force field to the RDKit: implementation and validation

2014

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A general purpose force field such as MMFF94/MMFF94s, which can properly deal with a wide range of diverse structures, is very valuable in the context of a cheminformatics toolkit. Herein we present an open-source implementation of this force field within the RDKit. The new MMFF functionality can be accessed through a C++/C#/Python/Java application programming interface (API) developed along the lines of the one already available for UFF in the RDKit. Our implementation was fully validated against the official validation suite provided by the MMFF authors. All energies and gradients were correctly computed; moreover, atom type and force constants were correctly assigned for 3D molecules built from SMILES strings. To provide full flexibility, the available API provides direct access to include/exclude individual terms from the MMFF energy expression and to carry out constrained geometry optimizations. The availability of a MMFF-capable molecular mechanics engine coupled with the rest of the RDKit functionality and covered by the BSD license is appealing to researchers operating in both academia and industry.

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A comparison of conformational energies calculated by several molecular mechanics methods

Cited by 147 publications

References 47 publications

Improved ligand geometries in crystallographic refinement usingAFITTinPHENIX

Improved ligand geometries in crystallographic refinement usingAFITTinPHENIX

Rapid synthesis of flavone‐based monoamine oxidase (MAO) inhibitors targeting two active sites using click chemistry

Bringing the MMFF force field to the RDKit: implementation and validation

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