Combination of consensus and ensemble docking strategies for the discovery of human dihydroorotate dehydrogenase inhibitors

Abstract

The inconsistencies in the performance of the virtual screening (VS) process, depending on the used software and structural conformation of the protein, is a challenging issue in the drug design and discovery field. Varying performance, especially in terms of early recognition of the potential hit compounds, negatively affects the whole process and leads to unnecessary waste of the time and resources. Appropriate application of the ensemble docking and consensus-scoring approaches can significantly increase reliability of the VS results. Dihydroorotate dehydrogenase (DHODH) is a key enzyme in the pyrimidine biosynthesis pathway. It is considered as a valuable therapeutic target in cancer, autoimmune and viral diseases. Based on the conducted benchmark study and analysis of the effect of different combinations of the applied methods and approaches, here we suggested a structure-based virtual screening (SBVS) workflow that can be used to increase the reliability of VS.

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

“…When available, it is also possible to combine the docking of an ensemble of structures of the protein of interest and the consensus-scoring to determine their impact on the improvements of the VS method [112]. Nevertheless, the prediction accuracy of sampling and scoring power relies on the adequate selection of docking programs and VS workflows [90,113,114,122], and current scoring functions are still not reliable enough [90].…”

“…This is because the search of best poses depends on the protocols of parameterizations and the training sets used to fine-tune the algorithms. In addition, the performance of VS was shown to greatly vary for the different structural conformations of the proteins, which implies the selection and elimination of structures with the worst performance in the ensemble [112,113]. In the last two decades, several studies have been conducted to evaluate and compare the performance of different docking software on the same systems using known databases of binders and non-binders and using structure ensembles when available [112][113][114][115][116][117][118][119][120][121][122].…”

Combination of ligand and structure based virtual screening approaches for the discovery of potential PARP1 inhibitors

“…Virtual screening was performed using the ICM-PRO software package [ 30 ]. ICM-PRO demonstrated high accuracy based on the multiple benchmark studies for molecular docking and virtual screening software among both academic and commercial software [ 31 , 32 ]. The docking algorithm of the ICM-PRO software is based on the Monte Carlo minimization approach [ 33 ].…”

Identification of Novel Potential VEGFR-2 Inhibitors Using a Combination of Computational Methods for Drug Discovery

“…Molecular docking of potential VEGFR-2 binding compounds retrieved from previous stages was performed using the ICM-PRO [23] v. 3.9-2b software (MolSoft L.L.C., www. molsoft.com, accessed on 10 September 2021), that showed high performance and accuracy among both academic and commercial software based on benchmark studies for molecular docking and virtual screening software [24,25]. ICM-PRO software used docking algorithm that was based on the Monte Carlo minimization approach and scoring function and was a weighted sum of multiple parameters, including van der Waals energy of the ligandtarget interactions, internal force field energy of the ligand, hydrogen bonding interactions, hydrogen bond donor-acceptor desolvation energy and hydrophobic free energy gain, among others [23,26].…”