Assessing Molecular Docking Tools to Guide Targeted Drug Discovery of CD38 Inhibitors

Boittier, Eric; Tang, Yat Yin; Buckley, McKenna E; Schuurs, Zachariah P; Richard, Derek J.; Gandhi, Neha S.

doi:10.3390/ijms21155183

Cited by 56 publications

(42 citation statements)

References 31 publications

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“…However, AutoDock 4.2 suggested alternative poses for some of the compounds, than that obtained in AutoDock Vina. Interestingly, it has been reported by numerous studies that AutoDock Vina outperforms AutoDock 4.2 in pose prediction [ 69 , 96 , 97 , 98 , 99 , 100 ], which is why we rely on our presented AutoDock Vina poses and their respective protein-ligand interactions. Furthermore, a correlation has been suggested between Vina scores and in vitro pIC 50 values [ 100 ].…”

Section: Discussionmentioning

confidence: 99%

“…Interestingly, it has been reported by numerous studies that AutoDock Vina outperforms AutoDock 4.2 in pose prediction [ 69 , 96 , 97 , 98 , 99 , 100 ], which is why we rely on our presented AutoDock Vina poses and their respective protein-ligand interactions. Furthermore, a correlation has been suggested between Vina scores and in vitro pIC 50 values [ 100 ]. Vina has previously yielded multiple active ligands in vitro [ 101 , 102 , 103 , 104 ].…”

Section: Discussionmentioning

confidence: 99%

“…Vina’s algorithm is based on a hybrid scoring function (empirical and knowledge-based) [ 69 ], whereas AutoDock 4.2’s scoring algorithm is based on the Assisted Model Building with Energy Refinement (AMBER) force field [ 72 ]. Physics-based scoring functions, such as that employed by AutoDock 4.2, have previously been regarded as less accurate in pose prediction than knowledge-based scoring functions [ 100 ]. However, in another study AutoDock 4.2 has been reported as more accurate in predicting free energy of binding (scores), than AutoDock Vina [ 98 ].…”

Section: Discussionmentioning

confidence: 99%

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Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

2021

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The ongoing coronavirus pandemic has been a burden on the worldwide population, with mass fatalities and devastating socioeconomic consequences. It has particularly drawn attention to the lack of approved small-molecule drugs to inhibit SARS coronaviruses. Importantly, lessons learned from the SARS outbreak of 2002-2004, caused by severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), can be applied to current drug discovery ventures. SARS-CoV-1 and SARS-CoV-2 both possess two cysteine proteases, the main protease (Mpro) and the papain-like protease (PLpro), which play a significant role in facilitating viral replication, and are important drug targets. The non-covalent inhibitor, GRL-0617, which was found to inhibit replication of SARS-CoV-1, and more recently SARS-CoV-2, is the only PLpro inhibitor co-crystallised with the recently solved SARS-CoV-2 PLpro crystal structure. Therefore, the GRL-0617 structural template and pharmacophore features are instrumental in the design and development of more potent PLpro inhibitors. In this work, we conducted scaffold hopping using GRL-0617 as a reference to screen over 339,000 ligands in the chemical space using the ChemDiv, MayBridge, and Enamine screening libraries. Twenty-four distinct scaffolds with structural and electrostatic similarity to GRL-0617 were obtained. These proceeded to molecular docking against PLpro using the AutoDock tools. Of two compounds that showed the most favourable predicted binding affinities to the target site, as well as comparable protein-ligand interactions to GRL-0617, one was chosen for further analogue-based work. Twenty-seven analogues of this compound were further docked against the PLpro, which resulted in two additional hits with promising docking profiles. Our in silico pipeline consisted of an integrative four-step approach: (1) ligand-based virtual screening (scaffold-hopping), (2) molecular docking, (3) an analogue search, and, (4) evaluation of scaffold drug-likeness, to identify promising scaffolds and eliminate those with undesirable properties. Overall, we present four novel, and lipophilic, scaffolds obtained from an exhaustive search of diverse and uncharted regions of chemical space, which may be further explored in vitro through structure-activity relationship (SAR) studies in the search for more potent inhibitors. Furthermore, these scaffolds were predicted to have fewer off-target interactions than GRL-0617. Lastly, to our knowledge, this work contains the largest ligand-based virtual screen performed against GRL-0617.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

2021

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“…ID1 and UDCA structures were prepared using AutoDockTools 1.5.6 (Molecular Graphics Laboratory, CA). The docking parameters were set as previously described 17 . The optimal docking result was visualized using PyMOL software (The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC).…”

Section: Methodsmentioning

confidence: 99%

Ursodesoxycholic acid alleviates liver fibrosis via proregeneration by activation of the ID1‐WNT2/HGF signaling pathway

Xi¹,

Luo²,

Lu³

et al. 2021

Clinical & Translational Med

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Background The human liver possesses a remarkable capacity for self‐repair. However, liver fibrosis remains a serious medical concern, potentially progressing to end‐stage liver cirrhosis and even death. Liver fibrosis is characterized by excess accumulation of extracellular matrix in response to chronic injury. Liver regenerative ability, a strong indicator of liver health, is important in resisting fibrosis. In this study, we provide evidence that ursodesoxycholic acid (UDCA) can alleviate liver fibrosis by promoting liver regeneration via activation of the ID1‐WNT2/hepatocyte growth factor (HGF) pathway. Methods Bile duct ligation (BDL) and partial hepatectomy (PH) mouse models were used to verify the effects of UDCA on liver fibrosis, regeneration, and the ID1‐WNT2/HGF pathway. An Id1 knockdown mouse model was also used to assess the role of Id1 in UDCA alleviation of liver fibrosis. Results Our results demonstrate that UDCA can alleviate liver fibrosis in the BDL mice and promote liver regeneration via the ID1‐WNT2/HGF pathway in PH mice. In addition, Id1 knockdown abolished the protection afforded by UDCA in BDL mice. Conclusions We conclude that UDCA protects against liver fibrosis by proregeneration via activation of the ID1‐WNT2/HGF pathway.

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“…PLANTS has also been compared to other docking tools, among them are [ 16 , 17 , 18 , 19 , 20 ]. In [ 16 ], for instance PLANTS has been tested on the human cluster of differentiation 38 (CD38), in the ranking based on scoring power with 42 compounds PLANTS was in the upper class.…”

Section: Ant Intelligence In Molecular Docking With Plantsmentioning

confidence: 99%

VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

Gorgulla

Çınaroğlu

Fischer

et al. 2021

IJMS

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The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

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Assessing Molecular Docking Tools to Guide Targeted Drug Discovery of CD38 Inhibitors

Cited by 56 publications

References 31 publications

Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

Ursodesoxycholic acid alleviates liver fibrosis via proregeneration by activation of the ID1‐WNT2/HGF signaling pathway

VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

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