scholarly journals Arranging Small Molecules with Subnanometer Precision on DNA Origami Substrates for the Single‐Molecule Investigation of Protein–Ligand Interactions

2020 ◽  
Vol 1 (1) ◽  
pp. 2000038
Author(s):  
Jingyuan Huang ◽  
Antonio Suma ◽  
Meiying Cui ◽  
Guido Grundmeier ◽  
Vincenzo Carnevale ◽  
...  
Keyword(s):  
Small Molecules ◽  
Single Molecule ◽  
Dna Origami ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

scholarly journals A ClyA nanopore tweezer for analysis of functional states of protein-ligand interactions

2019 ◽  
Author(s):  
Xin Li ◽  
Kuohao Lee ◽  
Jianhan Chen ◽  
Min Chen
Keyword(s):  
Single Molecule ◽  
Conformational Changes ◽  
Bound States ◽  
Conformational Dynamics ◽  
Electrical Current ◽  
Label Free ◽  
Protein Motions ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Molecular Tweezer

AbstractConformational changes of proteins are essential to their functions. Yet it remains challenging to measure the amplitudes and timescales of protein motions. Here we show that the ClyA nanopore can be used as a molecular tweezer to trap a single maltose-binding protein (MBP) within its lumen, which allows conformation changes to be monitored as electrical current fluctuations in real time. The current measurements revealed three distinct ligand-bound states for MBP in the presence of reducing saccharides. Our biochemical and kinetic analysis reveal that these three states represented MBP bound to different isomers of reducing sugars. These findings shed light on the mechanism of substrate recognition by MBP and illustrate that the nanopore tweezer is a powerful, label-free, single-molecule approach for studying protein conformational dynamics under functional conditions.

scholarly journals Systematic domain-based aggregation of protein structures highlights DNA-, RNA- and other ligand-binding positions

2018 ◽  
Vol 47 (2) ◽  
pp. 582-593 ◽  
Author(s):  
Shilpa Nadimpalli Kobren ◽  
Mona Singh
Keyword(s):  
Ligand Binding ◽  
Small Molecules ◽  
Binding Sites ◽  
Protein Structures ◽  
Complex Structures ◽  
Disease Etiology ◽  
Systematic Assessment ◽  
Protein Ligand Interactions ◽  
Ligand Binding Sites ◽  
Ligand Interactions

Abstract Domains are fundamental subunits of proteins, and while they play major roles in facilitating protein–DNA, protein–RNA and other protein–ligand interactions, a systematic assessment of their various interaction modes is still lacking. A comprehensive resource identifying positions within domains that tend to interact with nucleic acids, small molecules and other ligands would expand our knowledge of domain functionality as well as aid in detecting ligand-binding sites within structurally uncharacterized proteins. Here, we introduce an approach to identify per-domain-position interaction ‘frequencies’ by aggregating protein co-complex structures by domain and ascertaining how often residues mapping to each domain position interact with ligands. We perform this domain-based analysis on ∼91000 co-complex structures, and infer positions involved in binding DNA, RNA, peptides, ions or small molecules across 4128 domains, which we refer to collectively as the InteracDome. Cross-validation testing reveals that ligand-binding positions for 2152 domains are highly consistent and can be used to identify residues facilitating interactions in ∼63–69% of human genes. Our resource of domain-inferred ligand-binding sites should be a great aid in understanding disease etiology: whereas these sites are enriched in Mendelian-associated and cancer somatic mutations, they are depleted in polymorphisms observed across healthy populations. The InteracDome is available at http://interacdome.princeton.edu.

Modern Biophysical Approaches to Study Protein–Ligand Interactions

2018 ◽  
Vol 13 (04) ◽  
pp. 133-155
Author(s):  
Priyanka Biswas
Keyword(s):  
Single Molecule ◽  
Analytical Ultracentrifugation ◽  
Correlation Spectroscopy ◽  
Titration Calorimetry ◽  
Resonance Fluorescence ◽  
Biological Interactions ◽  
Protein Ligand Interactions ◽  
Dual Polarization Interferometry ◽  
Ligand Interactions

Protein–ligand interactions act as a pivot to the understanding of most of the biological interactions. The study of interactions between proteins and cellular molecules has led to the establishment and identification of various important pathways that control biological systems. Investigators working in different fields of biological sciences have an intrinsic interest in this field and complement their findings by the application of different biophysical approaches and tools to quantify protein–ligand interactions that include protein–small molecules, protein–DNA, protein–RNA, protein–protein both in vitro and in vivo. In this paper, the various biophysical techniques that can be employed to study such interactions will be discussed. In addition to native gel electrophoresis and fluorescence-based methods, more details will be discussed, on the broad range of modern day biophysical tools such as Circular Dichroism, Fourier Transform Infrared (FTIR) Spectroscopy, Isothermal Titration Calorimetry, Analytical Ultracentrifugation, Surface Plasmon Resonance, Fluorescence Correlation Spectroscopy, Differential Scanning Fluorimetry, Nuclear Magnetic Resonance, Mass Spectroscopy, Single Molecule Spectroscopy, Dual Polarization Interferometry, Micro Scale Thermophoresis and Electro–switchable Biosensors that can be used to study the different aspects of protein–ligand interactions.

Printing Small Molecules as Microarrays and Detecting Protein−Ligand Interactions en Masse

1999 ◽  
Vol 121 (34) ◽  
pp. 7967-7968 ◽  
Author(s):  
Gavin MacBeath ◽  
Angela N. Koehler ◽  
Stuart L. Schreiber
Keyword(s):  
Small Molecules ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

scholarly journals The MIDAS domain of AAA mechanoenzyme Mdn1 forms catch bonds with two different substrates

2021 ◽  
Author(s):  
Keith J. Mickolajczyk ◽  
Paul Dominic B. Olinares ◽  
Brian T. Chait ◽  
Shixin Liu ◽  
Tarun M. Kapoor
Keyword(s):  
Optical Tweezers ◽  
Single Molecule ◽  
Ribosome Biogenesis ◽  
Bound States ◽  
Weakly Bound ◽  
Aaa Atpase ◽  
Protein Ligand Interactions ◽  
Single Protein ◽  
Ligand Interactions ◽  
Catch Bonds

ABSTRACTCatch bonds are a form of mechanoregulation wherein protein-ligand interactions are strengthened by the application of dissociative tension. Currently, the best-characterized examples of catch bonds are between single protein-ligand pairs. The essential AAA (ATPase associated with diverse cellular activities) mechanoenzyme Mdn1 drives two separate steps in ribosome biogenesis, using its MIDAS domain to extract the ubiquitin-like (UBL) domain-containing proteins Rsa4 and Ytm1 from ribosomal precursors. However, it must subsequently release these assembly factors to reinitiate the enzymatic cycle. The mechanism underlying MIDAS-UBL switching between strongly- and weakly-bound states is unknown. Here, we use single-molecule optical tweezers to investigate the force-dependence of MIDAS-UBL binding. Parallel experiments with Rsa4 and Ytm1 show that forces up to ~4 pN, matching the magnitude of force produced by AAA proteins similar to Mdn1, enhance the MIDAS domain binding lifetime up to tenfold, and higher forces accelerate dissociation. Together, our studies indicate that Mdn1’s MIDAS domain forms catch bonds with more than one UBL-substrate, and provide insights into how mechanoregulation may contribute to the Mdn1 enzymatic cycle during ribosome biogenesis.

scholarly journals Calculating the force-dependent unbinding rate of biological macromolecular bonds from the force-ramp optical trapping assays

2021 ◽  
Author(s):  
Apurba Paul ◽  
Joshua Alper
Keyword(s):  
Optical Tweezers ◽  
Single Molecule ◽  
Force Spectroscopy ◽  
Optical Tweezer ◽  
Stochastic Simulations ◽  
Cumulative Distribution ◽  
Cellular Functions ◽  
Single Molecule Force Spectroscopy ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

AbstractThe non-covalent biological bonds that constitute protein-protein or protein-ligand interactions play crucial roles in many cellular functions, including mitosis, motility, and cell-cell adhesion. The effect of external force (F) on the unbinding rate (koff(F)) of macromolecular interactions is a crucial parameter to understanding the mechanisms behind these functions. Optical tweezer-based single-molecule force spectroscopy is frequently used to obtain quantitative force-dependent dissociation data on slip, catch, and ideal bonds. However, analyses of this data using dissociation time or dissociation force histograms often quantitatively compare bonds without fully characterizing their underlying biophysical properties. Additionally, the results of histogram-based analyses can depend on the rate at which force was applied during the experiment and the experiment’s sensitivity. Here, we present an analytically derived cumulative distribution function-like approach to analyzing force-dependent dissociation force spectroscopy data. We demonstrate the benefits and limitations of the technique using stochastic simulations of various bond types. We show that it can be used to obtain the detachment rate and force sensitivity of biological macromolecular bonds from force spectroscopy experiments by explicitly accounting for loading rate and noisy data. We also discuss the implications of our results on using optical tweezers to collect force-dependent dissociation data.

scholarly journals Calculating the force-dependent unbinding rate of biological macromolecular bonds from force-ramp optical trapping assays

2021 ◽  
Author(s):  
Apurba Paul ◽  
Joshua Alper
Keyword(s):  
Optical Tweezers ◽  
Single Molecule ◽  
Force Spectroscopy ◽  
Optical Tweezer ◽  
Stochastic Simulations ◽  
Cumulative Distribution ◽  
Cellular Functions ◽  
Single Molecule Force Spectroscopy ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Abstract The non-covalent biological bonds that constitute protein-protein or protein-ligand interactions play crucial roles in many cellular functions, including mitosis, motility, and cell-cell adhesion. The effect of external force (𝐹) on the unbinding rate (𝑘off(𝐹)) of macromolecular interactions is a crucial parameter to understanding the mechanisms behind these functions. Optical tweezer-based single-molecule force spectroscopy is frequently used to obtain quantitative force-dependent dissociation data on slip, catch, and ideal bonds. However, analyses of this data using dissociation time or dissociation force histograms often quantitatively compare bonds without fully characterizing their underlying biophysical properties. Additionally, the results of histogram-based analyses can depend on the rate at which force was applied during the experiment and the experiment’s sensitivity. Here, we present an analytically derived cumulative distribution function-like approach to analyzing force-dependent dissociation force spectroscopy data. We demonstrate the benefits and limitations of the technique using stochastic simulations of various bond types. We show that it can be used to obtain the detachment rate and force sensitivity of biological macromolecular bonds from force spectroscopy experiments by explicitly accounting for loading rate and noisy data. We also discuss the implications of our results on using optical tweezers to collect force-dependent dissociation data.

scholarly journals Systematic domain-based aggregation of protein structures highlights DNA-, RNA-, and other ligand-binding positions

2018 ◽  
Author(s):  
Shilpa Nadimpalli Kobren ◽  
Mona Singh
Keyword(s):  
Ligand Binding ◽  
Small Molecules ◽  
Binding Sites ◽  
Protein Structures ◽  
Complex Structures ◽  
Disease Etiology ◽  
Systematic Assessment ◽  
Protein Ligand Interactions ◽  
Ligand Binding Sites ◽  
Ligand Interactions

AbstractDomains are fundamental subunits of proteins, and while they play major roles in facilitating protein–DNA, protein–RNA and other protein–ligand interactions, a systematic assessment of their various interaction modes is still lacking. A comprehensive resource identifying positions within domains that tend to interact with nucleic acids, small molecules and other ligands would expand our knowledge of domain functionality as well as aid in detecting ligand-binding sites within structurally uncharacterized proteins. Here we introduce an approach to identify per-domain-position interaction “propensities” by aggregating protein co-complex structures by domain and ascertaining how frequently residues mapping to each domain position interact with ligands. We perform this domain-based analysis on ∼82,000 co-complex structures, and infer positions involved in binding DNA, RNA, peptides, ions, or small molecules across 4,120 domains, which we refer to collectively as the InteracDome. Cross-validation testing reveals that ligand-binding positions for 1,327 domains can be confidently modeled and used to identify residues facilitating interactions in ∼60–69% of human genes. Our resource of domain-inferred ligand-binding sites should be a great aid in understanding disease etiology: whereas these sites are enriched in Mendelian-associated and cancer somatic mutations, they are depleted in polymorphisms observed across healthy populations. The InteracDome is available at http://interacdome.princeton.edu.

scholarly journals Calculating the force-dependent unbinding rate of biological macromolecular bonds from force-ramp optical trapping assays

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Apurba Paul ◽  
Joshua Alper
Keyword(s):  
Optical Tweezers ◽  
Single Molecule ◽  
Force Spectroscopy ◽  
Optical Tweezer ◽  
Stochastic Simulations ◽  
Cumulative Distribution ◽  
Cellular Functions ◽  
Single Molecule Force Spectroscopy ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

AbstractThe non-covalent biological bonds that constitute protein–protein or protein–ligand interactions play crucial roles in many cellular functions, including mitosis, motility, and cell–cell adhesion. The effect of external force ($$F$$ F ) on the unbinding rate ($${k}_{\text{off}}\left(F\right)$$ k off F ) of macromolecular interactions is a crucial parameter to understanding the mechanisms behind these functions. Optical tweezer-based single-molecule force spectroscopy is frequently used to obtain quantitative force-dependent dissociation data on slip, catch, and ideal bonds. However, analyses of this data using dissociation time or dissociation force histograms often quantitatively compare bonds without fully characterizing their underlying biophysical properties. Additionally, the results of histogram-based analyses can depend on the rate at which force was applied during the experiment and the experiment’s sensitivity. Here, we present an analytically derived cumulative distribution function-like approach to analyzing force-dependent dissociation force spectroscopy data. We demonstrate the benefits and limitations of the technique using stochastic simulations of various bond types. We show that it can be used to obtain the detachment rate and force sensitivity of biological macromolecular bonds from force spectroscopy experiments by explicitly accounting for loading rate and noisy data. We also discuss the implications of our results on using optical tweezers to collect force-dependent dissociation data.

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