ArticleProtein science : a publication of the Protein Society2020
Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations.
Article in Protein science : a publication of the Protein Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Probe-Atom Distributions Obtained from Mixed-Solvent Molecular Dynamics Improve the Scoring of Docking Calculations.Journal of chemical information and modeling · 2026Article
- DruGUI 2.0: mapping protein druggability with probe-based molecular dynamics.Bioinformatics (Oxford, England) · 2026Article
- Allosteric Autoregulation of Ferroptosis Suppressor Protein 1 Activity by its N-myristoylated Tail.Journal of molecular biology · 2025Article
- MGAT1-Guided complex N-Glycans on CD73 regulate immune evasion in triple-negative breast cancer.Nature communications · 2025Article
- Article
- Cosolvent Molecular Dynamics Applied to DPP4, DPP8 and DPP9: Reproduction of Important Binding Features and Use in Inhibitor Design.Journal of chemical information and modeling · 2024Article
- PharmRL: Pharmacophore elucidation with Deep Geometric Reinforcement Learning.Research square · 2024Article
- Article
- Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART).Journal of cheminformatics · 2024Article
- Allo-targeting of the kinase domain: Insights from in silico studies and comparison with experiments.Current opinion in structural biology · 2024Review
- Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study.Journal of computer-aided molecular design · 2023Article
- ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement.ACS omega · 2022Article
- Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design.New journal of chemistry = Nouveau journal de chimie · 2022Article
- DCLK1 and its interaction partners: An effective therapeutic target for colorectal cancer.Oncology letters · 2021Review
- Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy.Journal of computer-aided molecular design · 2021Article
- Targeting the C-Terminal Domain Small Phosphatase 1.Life (Basel, Switzerland) · 2020Review
- Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations.Protein science : a publication of the Protein Society · 2020Article
- Revolutionizing antiretroviral therapy for human immunodeficiency virus/AIDS: A computational approach using molecular docking, virtual screening, and 3D pharmacophore building to address therapeutic failure and propose highly effective candidates.International journal of immunopathology and pharmacologyArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Recent years have seen progress in druggability simulations, that is, molecular dynamics simulations of target proteins in solutions containing drug-like probe molecules to characterize their drug-binding abilities, if any. An important consecutive step is to analyze the trajectories to construct pharmacophore models (PMs) to use for virtual screening of libraries of small molecules. While considerable success has been observed in this type of computer-aided drug discovery, a systematic tool encompassing multiple steps from druggability simulations to pharmacophore modeling, to identifying hits by virtual screening of libraries of compounds, has been lacking. We address this need here by developing a new tool, Pharmmaker, building on the DruGUI module of our ProDy application programming interface. Pharmmaker is composed of a suite of steps: (Step 1) identification of high affinity residues for each probe molecule type; (Step 2) selecting high affinity residues and hot spots in the vicinity of sites identified by DruGUI; (Step 3) ranking of the interactions between high affinity residues and specific probes; (Step 4) obtaining probe binding poses and corresponding protein conformations by collecting top-ranked snapshots; and (Step 5) using those snapshots for constructing PMs. The PMs are then used as filters for identifying hits in structure-based virtual screening. Pharmmaker, accessible online at http://prody.csb.pitt.edu/pharmmaker, can be used in conjunction with other tools available in ProDy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.