VirtualFlow 2.0 - The Next Generation Drug Discovery Platform Enabling Adaptive Screens of 69 Billion Molecules

Gorgulla, Christoph; Nigam, AkshatKumar; Koop, Matt; Çınaroğlu, Süleyman Selim; Secker, Christopher; Haddadnia, Mohammad; Kumar, Abhishek; Malets, Yehor S.; Hasson, Alexander; Levin‐Konigsberg, Roni; Radchenko, D.N.; Kumar, Aditya; Gehev, Minko; Tang, Ming; Li, Minkai; Aquilanti, Pierre-Yves; Gabb, Henry A.; Alhossary, Amr; Wagner, Gerhard; Aspuru‐Guzik, Alán; Moroz, Yurii S.; Fackeldey, Konstantin; Arthanari, Haribabu

doi:10.1101/2023.04.25.537981

Cited by 13 publications

(10 citation statements)

References 87 publications

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“…Encouragingly, by insisting on symmetry and excluding clashes, the method seems to capture the key features of the symmetrical ligand stacks despite ignoring higher-order energetic terms. We have implemented the symmetry docking approach in the program SymDOCK (freely available for academic research at ); we suspect that this approach may be readily adapted to most docking methods. − …”

Section: Discussionmentioning

confidence: 99%

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Smith,

Knight,

Kormos

et al. 2024

J. Chem. Inf. Model.

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Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand−ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

show abstract

Section: Discussionmentioning

confidence: 99%

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Smith,

Knight,

Kormos

et al. 2024

J. Chem. Inf. Model.

View full text Add to dashboard Cite

show abstract

“…We have implemented the symmetry docking approach in a program SymDOCK (freely available for academic research at https://dock.compbio.ucsf.edu/); we suspect that this approach may be readily adapted to most docking methods. [57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72][73]…”

Section: Discussionmentioning

confidence: 99%

Docking for molecules that bind in a symmetric stack with SymDOCK

Smith,

Knight,

Kormos

et al. 2023

Preprint

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Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of much current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein’s symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand’s docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in aprospectivestudy SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed, and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

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“…The process aimed to optimize the overall structure of the receptor-ligand complex, minimize potential clashes, and maximize binding interactions. For the molecular docking process, we employed Glide-SP and Glide-XP software [25], integrated within the VirtualFlow Unity [20] (VFU) pipeline (https://github.com/VirtualFlow/VFU). In the interest of scientific inclusivity, we provide a VFU setup that utilizes QuickVina [43] and Smina [44], two open-source docking programs.…”

Section: Methodsmentioning

confidence: 99%

“…Nsp10 has been demonstrated to stimulate the ExoN and MTase activities of nsp14, making it a critical cofactor for the functionality of the protein [19]. In summary, our research showcases an advanced computational pipeline, built upon the robust capabilities of VirtualFlow 2.0 [20], specifically the VirtualFlow Unity (VFU) module. This component not only accommodates a wide spectrum of docking programs, callable through a Python pipeline, but also allows scoring at diverse levels of precision, thereby facilitating the rapid and proficient detection of prospective nsp14 inhibitors.…”

Section: Introductionmentioning

confidence: 99%

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors

Nigam,

Hurley,

et al. 2023

Preprint

Self Cite

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The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 ± 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148 (PDB:8BWU), a potent inhibitor of methyltransferase activity at the nanomolar level (IC50value of 70 ± 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

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VirtualFlow 2.0 - The Next Generation Drug Discovery Platform Enabling Adaptive Screens of 69 Billion Molecules

Cited by 13 publications

References 87 publications

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Docking for molecules that bind in a symmetric stack with SymDOCK

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors

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