High-Quality Conformer Generation with CDPKit/CONFORT: Algorithm and Performance Assessment

Abstract

The majority of compounds in the drug-like chemical space show flexibility regarding their three-dimensional structure which, in solution, results in an equilibrium of multiple interconvertible conformational states. 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 of interest. 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 which can then be expected to comprise members that closely resemble possible bound-state ligand conformations. The high relevance of such conformer generation functionality led to the development of a wide panel of dedicated commercial and open-source software tools throughout the last decades. Several published benchmarking studies have shown that open-source tools lag behind their commercial competitors in many key aspects like accuracy in reproducing bioactive conformations, speed of processing, output ensemble size, range of applicability, stability and user-friendliness. In this work, we introduce the novel open-source conformer ensemble generator CONFORT, which builds upon proven concepts and algorithms and aims at delivering state-of-the-art performance for all types of organic molecules in the drug-like chemical space. The ability of CONFORT, and several well-known commercial and open-source conformer ensemble generators, to reproduce experimental 3D structures as well as their computational efficiency and robustness has been assessed thoroughly both for typical drug-like molecules and macrocyclic structures. For small molecules, CONFORT outperforms all other tested open-source conformer generators and is head-to-head with commercial generators, both in terms of processing speed and accuracy in the reproduction of bioactive conformations. In the case of macrocyclic structures, CONFORT is able to reproduce experimental 3D structures with clearly higher accuracy than all other tested generators. To our knowledge, CONFORT is the first open-source conformer ensemble generator that is able to truly keep up with commercial software in this field and thus represents a valuable addition to the open-source software toolbox for computer-aided drug design.

Apo2ph4: A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening

“…All active and decoy datasets were used in the form provided by the LIT-PCBA website. , By means of PyMol, the provided .mol2 files of ligands and targets were merged into a corresponding PDB file to apply apo2ph4 . Conformations of active and inactive compounds were generated using CDPKit’s CONFORT conformer generator (confgen) using default settings, allowing up to 25 conformations per molecule to be generated. , For VS, the generated multi-conformer SD files were then converted to LigandScout’s .ldb format via KNIME nodes provided by the LigandScout KNIME extension . To generate pharmacophore models for VS, apo2ph4 was run using all-default settings.…”

“…Conformations of active and inactive compounds were generated using CDPKit’s CONFORT conformer generator (confgen) using default settings, allowing up to 25 conformations per molecule to be generated. 30 , 37 For VS, the generated multi-conformer SD files were then converted to LigandScout’s .ldb format via KNIME nodes provided by the LigandScout KNIME extension. 38 To generate pharmacophore models for VS, apo2ph4 was run using all-default settings.…”

Chemical complexity challenge: Is multi‐instance machine learning a solution?

“…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 …”

Molecular Gas-Phase Conformational Ensembles

“…These algorithms facilitate conformational sampling in both the gas and solution phases, allowing for a more thorough exploration of molecular flexibility. These include Confort, ROTATE, CONFECT, Catalyst, , MED-3DMC, Multiconf-DOCK, CONFECT, BRIKARD, ForceGen, TCG (TrixX Conformer Generator), and Cxcalc (ChemAxon) . These tools utilize a range of algorithms and methodologies to explore the conformational space of molecules and generate conformational ensembles.…”