AutoModel: A Client-Server Tool for Intuitive and Interactive Homology Modeling of Protein-Ligand Complexes

Filho, João Luiz de Almeida; Tamariz, Annabell Del Real; Fernández, Jorge Hernández

doi:10.1007/978-3-030-01722-4_8

Cited by 2 publications

(1 citation statement)

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“…In this experiment, the three-dimensional structure for the C-terminal (PDB id 1O86) and Nterminal (PDB id 5amb) domains of ACE was retrieved from RSCB PDB. AutoModel modeling software [De A Filho et al, 2018] was used to complete the regions without structural information of both domains. The compound dataset was generated using the DUD/ACE (Database of Useful Decoys) [Mysinger et al 2012], which contains active (ligands) and inactive (decoys) challenging compounds.…”

Section: Methodsmentioning

confidence: 99%

HTP SurflexDock: a web tool for Structure-Based Virtual Screening analysis based on the Ensemble Docking protocol

Filho¹,

Fernández²

2022

Anais Do XVI Brazilian E-Science Workshop (BRESCI 2022)

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Structure-Based Virtual Screening (SVBS) is a technique traditionally used to find a set of specific inhibitors for a receptor structure during the preliminary stages of drug discovery studies. However, more than 90% of SBVS best ranks compounds do not have the expected biological effect at the end of the process. In this context, strategies to increase the success rate must be employed to ensure the experiment's success. Here, we introduce the HTP SurflexDock, a tool that improves the success rate of SBVS experiments through two strategies: First, the ensemble docking protocol enables the simulation of the implicit flexibility of the receptor structure. Second, a post-processing steps allows the user to rescore promising compounds by expanding the conformational space search or estimating the binding free energy through the MM/PBSA protocol. HTP SurflexDock is useful when dealing with flexible receptors and when structural information about the receptor contact area is insufficient or optimized for a specific ligand type. HTP SurflexDock is freely available as a web service or may be downloaded at https://htpsurflexdock.biocomp.uenf.br/.

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Section: Methodsmentioning

confidence: 99%