ReviewJournal of chemical theory and computation2023
Integrated Molecular Modeling and Machine Learning for Drug Design.
Review in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed.
- Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.Nature protocols · 2026Review
- Machine-Learned Extrapolation of Quantum Mechanical Energies in Implicit Solvent from Short to Long Oligopeptides.Journal of chemical information and modeling · 2026Article
- AGAPE (Computational G‑Quadruplex Stabilization Prediction): The First Machine Learning Workflow for G‑Quadruplex Stabilization Prediction.ACS omega · 2026Article
- Elucidating the Structure and Activation Mechanisms of GPCRs Using Modern Computational and AI Tools.Cell biochemistry and biophysics · 2026Review
- Integrating computational chemistry and machine learning to predict KRAS mutation-induced resistance.bioRxiv : the preprint server for biology · 2026Article
- Mechanistic inhibition of FtsZ-driven bacterial cytokinesis by natural products: an integrated machine learning and advanced drug discovery approach.Molecular diversity · 2026Article
- Structure-based discovery of Plasmodium falciparum DPAP-1 inhibitor and its experimental validation as an antimalarial agent.Folia microbiologica · 2026Article
- Antiviral Potential of Brown Algal Metabolites Against A179L Anti-apoptotic Protein: A Computational Strategy for African Swine Fever Treatment.Current topics in medicinal chemistry · 2026Article
- Molegro Data Modeller for Machine Learning.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The potential of deep learning on the discovery of new genes implicated in differences of sex development.Computational and structural biotechnology journal · 2026Article
- Salvianolic Acid B Exerts Antiphotoaging Effect on Ultraviolet B-Irradiated Human Keratinocytes by Alleviating Oxidative Stress via SIRT1 Protein.Chinese journal of integrative medicine · 2025Article
- Conceptual density functional theory in drug discovery: an overview.Journal of molecular modeling · 2025Review
- An Integrative Approach to Identifying Neuroprotective Natural Compounds for Neurodevelopmental Disorders.International journal of molecular sciences · 2025Article
- Multiple Strategies Confirm the Anti Hepatocellular Carcinoma Effect of Cinnamic Acid Based on the PI3k-AKT Pathway.Pharmaceuticals (Basel, Switzerland) · 2025Article
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- Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?Journal of chemical information and modeling · 2025Article
- An Amazing 30-Year Journey around the DABO Family: A Medicinal Chemistry Lesson on a Versatile Class of Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors.Journal of medicinal chemistry · 2025Review
- Emerging Trends in Bioinspired Superhydrophobic and Superoleophobic Sustainable Surfaces.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Normalized Protein-Ligand Distance Likelihood Score for End-to-End Blind Docking and Virtual Screening.Journal of chemical information and modeling · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on molecular mechanics optimized geometries. Meanwhile, we discuss remaining challenges and promising directions for further development and use a retrospective example of FDA approved kinase inhibitor Erlotinib to demonstrate the use of these newly developed computational tools.
Indexed as
Identifiers
What OpenQuestion holds
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.