2023
DOI: 10.1021/acs.jcim.3c00563
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High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment

Thomas Seidel,
Christian Permann,
Oliver Wieder
et al.

Abstract: Knowledge of the putative bound-state conformation of a molecule is an essential prerequisite for the successful application of many computer-aided drug design methods that aim to assess or predict its capability to bind to a particular target receptor. An established approach to predict bioactive conformers in the absence of receptor structure information is to sample the low-energy conformational space of the investigated molecules and derive representative conformer ensembles that can be expected to compris… Show more

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Cited by 8 publications
(7 citation statements)
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“…Afterwards, protonation states of nitrogen atoms were adjusted for pH 7.4 according to their pKa values calculated by means of MarvinSketch ( https://docs.chemaxon.com/display/docs/pka-plugin.md , V17.27.0; default settings). Finally, for each ligand a conformer ensemble was generated using the software CONFORGE V1.0.0 ( Seidel et al, 2023 ). CONFORGE was executed with the following settings: max.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Afterwards, protonation states of nitrogen atoms were adjusted for pH 7.4 according to their pKa values calculated by means of MarvinSketch ( https://docs.chemaxon.com/display/docs/pka-plugin.md , V17.27.0; default settings). Finally, for each ligand a conformer ensemble was generated using the software CONFORGE V1.0.0 ( Seidel et al, 2023 ). CONFORGE was executed with the following settings: max.…”
Section: Methodsmentioning
confidence: 99%
“…com/display/docs/pka-plugin.md, V17.27.0; default settings). Finally, for each ligand a conformer ensemble was generated using the software CONFORGE V1.0.0 (Seidel et al, 2023). CONFORGE was executed with the following settings: max.…”
Section: Ligand Preparation For Docking Analysismentioning
confidence: 99%
“…However, more efficient conformation generation approaches may partly solve this issue and greatly reduce these costs. 150 Another issue is the complexity of different MIL representations and their processing. 9,45 Let B be the number of bags in a training set (e.g., molecules), N the number of instances (e.g., conformations), and D the dimensionality of a feature vector representing the instances.…”
Section: Computational Complexity and Costmentioning
confidence: 99%
“…Conformation generation may become a bottleneck of a whole modeling pipeline and take even more time than model building itself. However, more efficient conformation generation approaches may partly solve this issue and greatly reduce these costs 150 …”
Section: Computational Complexity and Costmentioning
confidence: 99%
“…These algorithms facilitate conformational sampling in both the gas and solution phases, allowing for a more thorough exploration of molecular flexibility. These include Confort, 86 ROTATE, 87 CON-FECT, 88 Catalyst, 89,90 MED-3DMC, 91 Multiconf-DOCK, 92 CONFECT, 93 BRIKARD, 94 ForceGen, 95 TCG (TrixX Conformer Generator), 96 and Cxcalc (ChemAxon). 97 These tools utilize a range of algorithms and methodologies to explore the conformational space of molecules and generate conformational ensembles.…”
Section: ■ Introductionmentioning
confidence: 99%