A novel interaction fingerprint derived from per atom score contributions: exhaustive evaluation of interaction fingerprint performance in docking based virtual screening

Jasper, Julia; Humbeck, Lina; Brinkjost, Tobias; Koch, Oliver

doi:10.1186/s13321-018-0264-0

Cited by 37 publications

(37 citation statements)

References 40 publications

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“…This represents an advantage over other parameters used to compare the binding modes of LR complexes such as the root‐mean‐square deviation (RMSD), whose limitations have been discussed elsewhere . The approach also differs from binary interaction fingerprints‐based similarity indices, commonly used for docking‐based virtual screening and scoring . The parameter allows for comparison of two complexes considering different receptor structures or conformations in each complex.…”

Section: Methodssupporting

confidence: 56%

Profiling the interaction of 1‐phenylbenzimidazoles to cyclooxygenases

Gómez-Castro

López‐Martínez

Hernández-Pineda

et al. 2019

J of Molecular Recognition

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In the design of 1-phenylbenzimidazoles as model cyclooxygenase (COX) inhibitors, docking to a series of crystallographic COX structures was performed to evaluate their potential for high-affinity binding and to reproduce the interaction profile of well-known COX inhibitors. The effect of ligand-specific induced fit on the calculations was also studied. To quantitatively compare the pattern of interactions of model compounds to the profile of several cocrystallized COX inhibitors, a geometric parameter, denominated ligand-receptor contact distance (LRCD), was developed. The interaction profile of several model complexes showed similarity to the profile of COX complexes with inhibitors such as iodosuprofen, iodoindomethacin, diclofenac, and flurbiprofen. Shaping of high-affinity binding sites upon ligand-specific induced fit mostly determined both the affinity and the binding mode of the ligands in the docking calculations. The results suggest potential of 1-phenylbenzimidazole derivatives as COX inhibitors on the basis of their predicted affinity and interaction profile to COX enzymes. The analyses also provided insights into the role of induced fit in COX enzymes. While inhibitors produce different local structural changes at the COX ligand binding site, induced fit allows inhibitors in diverse chemical classes to share characteristic interaction patterns that ensure key contacts to be achieved.Different interaction patterns may also be associated with different inhibitory mechanisms.

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Section: Methodssupporting

confidence: 56%

Profiling the interaction of 1‐phenylbenzimidazoles to cyclooxygenases

Gómez-Castro

López‐Martínez

Hernández-Pineda

et al. 2019

J of Molecular Recognition

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“…As mentioned in the Introduction, this study was based on the DUD datasets since a huge number of even very recent benchmarking studies utilizes them to assess the reliability of various VS techniques; these studies allow the here proposed consensus strategy to be extensively compared with other highly performing VS approaches. Firstly, attention was focused on a set of very recent papers which apply innovative VS methodologies, such as interaction fingerprints [27], machine learning based scoring [26] and ligand-based screening under shape constraints [25]. Along with the novelty of the implemented approach, these studies were chosen because they comprised all available DUD datasets thus allowing a precise comparison with the here reported results.…”

Section: Resultsmentioning

confidence: 99%

Rescoring and Linearly Combining: A Highly Effective Consensus Strategy for Virtual Screening Campaigns

Pedretti

Mazzolari

Gervasoni

et al. 2019

IJMS

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The study proposes a novel consensus strategy based on linear combinations of different docking scores to be used in the evaluation of virtual screening campaigns. The consensus models are generated by applying the recently proposed Enrichment Factor Optimization (EFO) method, which develops the linear equations by exhaustively combining the available docking scores and by optimizing the resulting enrichment factors. The performances of such a consensus strategy were evaluated by simulating the entire Directory of Useful Decoys (DUD datasets). In detail, the poses were initially generated by the PLANTS docking program and then rescored by ReScore+ with and without the minimization of the complexes. The so calculated scores were then used to generate the mentioned consensus models including two or three different scoring functions. The reliability of the generated models was assessed by a per target validation as performed by default by the EFO approach. The encouraging performances of the here proposed consensus strategy are emphasized by the average increase of the 17% in the Top 1% enrichment factor (EF) values when comparing the single best score with the linear combination of three scores. Specifically, kinases offer a truly convincing demonstration of the efficacy of the here proposed consensus strategy since their Top 1% EF average ranges from 6.4 when using the single best performing primary score to 23.5 when linearly combining scoring functions. The beneficial effects of this consensus approach are clearly noticeable even when considering the entire DUD datasets as evidenced by the area under the curve (AUC) averages revealing a 14% increase when combining three scores. The reached AUC values compare very well with those reported in literature by an extended set of recent benchmarking studies and the three-variable models afford the highest AUC average.

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“…Further, the binding interaction pattern through the protein‐ligand interaction fingerprint (PLIF) was analysed . The optimized protein structures were aligned to generate PLIF model in MOE 2019.01 PLIF module .…”

Section: Methodsmentioning

confidence: 99%

Structure‐guided screening of chemical database to identify NS3‐NS2B inhibitors for effective therapeutic application in dengue infection

Bhowmick

Alissa

Wabaidur

et al. 2020

J of Molecular Recognition

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Dengue infection is the most common arthropod-borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi-step virtual screening effort was conceived to screen out the entire "screening library" of the Asinex database. Initially, through "Lipinski rule of five" filtration criterion almost 0.6 million compounds were collected and docked with NS3-NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the "Virtual Screening Workflow" (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as -high-throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM-GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3-NS2B protein based on the investigation of molecular interactions map and protein-ligand fingerprint analyses. Different pharmacokinetics and drug-likeness parameters were also checked, which favour the potentiality of selected molecules for being drug-like candidates. The molecular dynamics (MD) simulation analyses of protein-ligand complexes were explained that NS3-NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM-GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3-NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3-NS2B protein subjected to experimental validation.

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A novel interaction fingerprint derived from per atom score contributions: exhaustive evaluation of interaction fingerprint performance in docking based virtual screening

Cited by 37 publications

References 40 publications

Profiling the interaction of 1‐phenylbenzimidazoles to cyclooxygenases

Profiling the interaction of 1‐phenylbenzimidazoles to cyclooxygenases

Rescoring and Linearly Combining: A Highly Effective Consensus Strategy for Virtual Screening Campaigns

Structure‐guided screening of chemical database to identify NS3‐NS2B inhibitors for effective therapeutic application in dengue infection

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