ReviewChemical reviews2016
Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.
Review in Chemical reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 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
103 citing papers in PubMed, 234 citations in OpenAlex.
- A covalent PFKL activator suppresses tumor growth.Nature chemical biology · 2026Article
- Discovery of Small Molecule Ligands Targeting Orphan G Protein-Coupled Receptors GPR3, GPR6, and GPR12.Journal of medicinal chemistry · 2026Review
- Metastable Protein-Protein Interactions as a Design Principle for PROTACs: Insights from the RIPK1-VHL System.JACS Au · 2026Article
- A Practical Guide to Transition State Analysis in Biomolecular Simulations with TS-DAR.The journal of physical chemistry. B · 2025Article
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- A Covalent PFKL Activator Suppresses Tumor Growth.bioRxiv : the preprint server for biology · 2025Article
- Design Rules for Expanding PAM Compatibility in CRISPR-Cas9 from the VQR, VRER and EQR variants.bioRxiv : the preprint server for biology · 2025Article
- Memory kernel minimization-based neural networks for discovering slow collective variables of biomolecular dynamics.Nature computational science · 2025Article
- Conformational Dynamics and Activation of Membrane-Associated Human Group IVA Cytosolic Phospholipase AThe journal of physical chemistry letters · 2025Article
- The Quantum Paradox in Pharmaceutical Science: Understanding Without Comprehending-A Centennial Reflection.International journal of molecular sciences · 2025Review
- AMUSET-TICA: A Tensor-Based Approach for Identifying Slow Collective Variables in Biomolecular Dynamics.Journal of chemical theory and computation · 2025Article
- Benzylidenehydrazine Derivatives: Synthesis, Antidiabetic Evaluation, Antioxidation, Mode of Inhibition, DFT and Molecular Docking Studies.Chemistry & biodiversity · 2025Article
- Covalent-Allosteric Inhibitors: Do We Get the Best of Both Worlds?Journal of medicinal chemistry · 2025Review
- Computer-aided drug design for the double-membrane vesicle pore complex inhibitors against SARS-CoV-2.Frontiers in microbiology · 2025Article
- Allosteric activation of AMPK ADaM's site by structural analogs of Epigallocatechin and Galegine: computational molecular modeling investigation.In silico pharmacology · 2025Article
- Graph theory approaches for molecular dynamics simulations.Quarterly reviews of biophysics · 2024Article
- Global hinge sites of proteins as target sites for drug binding.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Maternal lipid mobilization is essential for embryonic development in the malaria vector Anopheles gambiae.PLoS biology · 2024Article
- MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model.Journal of cheminformatics · 2024Article
- Toward the Design of Allosteric Effectors: Gaining Comprehensive Control of Drug Properties and Actions.Journal of medicinal chemistry · 2024Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.
Indexed as
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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.