ReviewACS omega2020
Force Spectroscopy on Single Molecules of Life.
Review in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 38 citations in OpenAlex.
- Nanomechanical characterization of soft nanomaterial using atomic force microscopy.Materials today. Bio · 2025Review
- Concise Overview of Methodologies Employed in the Study of Bacterial DNA Replication.International journal of molecular sciences · 2025Review
- Insight into Single-Molecule Imaging Techniques for the Study of Prokaryotic Genome Maintenance.Chemical & biomedical imaging · 2024Review
- Structural Flexibility and Disassembly Kinetics of Single Ferritin Molecules Using Optical Nanotweezers.ACS nano · 2024Article
- Development of Single Molecule Techniques for Sensing and Manipulation of CRISPR and Polymerase Enzymes.Small (Weinheim an der Bergstrasse, Germany) · 2023Review
- Optical Monitoring ofNano letters · 2023Article
- Electromagnetic Forces and Torques: From Dielectrophoresis to Optical Tweezers.Chemical reviews · 2023Review
- Single-Molecule Optical Tweezers As a Tool for Delineating the Mechanisms of Protein-Processing Mechanoenzymes.ACS omega · 2023Review
- Advances in the Biological Application of Force-Induced Remnant Magnetization Spectroscopy.Molecules (Basel, Switzerland) · 2022Review
- Multi-parameter photon-by-photon hidden Markov modeling.Nature communications · 2022Article
- Force Spectroscopy in Mechanical Protein Domains Unfolding.Advances in experimental medicine and biology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomolecules such as nucleic acids and proteins constitute the cells and its organelles that form the crucial components in all living organisms. They are associated with a variety of cellular processes during which they undergo conformational orientations. The structural rearrangements resulting from protein-protein, protein-DNA, and protein-drug interactions vary in spatial and temporal length scales. Force is one of the important key factors which regulate these interactions. The magnitude of the force can vary from sub-piconewtons to several thousands of piconewtons. Single-molecule force spectroscopy acts as a powerful tool which is capable of investigating mechanical stability and conformational rearrangements arising in biomolecules due to the above interactions. Real-time observation of conformational dynamics including access to rare or transient states and the estimation of mean dwell times using these tools aids in the kinetic analysis of these interactions. In this review, we highlight the capabilities of common force spectroscopy techniques such as optical tweezers, magnetic tweezers, and atomic force microscopy with case studies on emerging applications.
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.