Biophysical studies of protein dynamics

2014 ◽  
Author(s):  
◽  
Dongmei Yu
Keyword(s):  
Thermal Stability ◽  
Ligand Binding ◽  
Protein Dynamics ◽  
Binding Affinity ◽  
Single Molecule ◽  
Rna Structure ◽  
Protein Translation ◽  
Rna Structures ◽  
Functional States ◽  
Intersubunit Rotation

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The Ribosome is the compact nanomachine with multiple coordinated components working together to translate the genetic code in the mRNA into linear protein sequence. Since it was discovered in 1955 by George Emil Palade, the research around ribosome has been pushed forward by hundreds of labs worldwide. In 2000, the ribosome structures at atomic resolution were resolved, which open a new era for ribosome study. Structures help people design and explain the biochemical data deeper and better. However, ribosome is not static and it is a dynamic and highly regulated machine. The function of ribosome can be understood further only if we can follow the dynamics of individual components in different functional states. Solution NMR is a powerful technique for studying protein dynamics. However the gigantic nature of ribosome makes this task daunting. Thanks to the development of single molecule techniques, ribosome tRNA translocation and intersubunit rotation have been studied and produced new information about ribosome function Both single molecule FRET and optical tweezers have been successfully used to address the dynamic process of protein translation. In 2008, Dr. Peter Cornish and Dr. Dmitri Ermolenko followed the ribosome intersubunit rotation and L1 stalk dynamics in real time during the process of translocation, which was the first direct evidence of ribosome dynamics itself since the previous study inferred the ribosome dynamics from tRNA period. The previous study could not exclude the possibility that the observed dynamics resulted purely from tRNA. Cornish and Ermolenko concluded that ribosome dynamics is a spontaneous process that is driven by thermodynamic Brownian motion. This pioneering study open a window to address many unresolved problems such as the perturbation of dynamic effect by structured RNA, ribosome unwinding, and frameshifting. We found that the presence of RNA structure induces the ribosome into a new FRET state that we named it super rotated state. The population distribution of the super rotated state is correlated with the thermostability and the distance of RNA structure to the ribosome. Using other RNA structures like DNA:RNA hybrid and pseudoknot, the ribosome can also be induced into the super rotated state. Structured RNA inhibits the regular intersubunit rotation and drives the ribosome into the super rotated state. However, the structured RNA cannot stop the opento-close transition of the L1 stalk, which still can fluctuate between three different functional states. These results propose that the ribosome dynamics is composed of several independent units with their own identity. Since the super rotated state also can be induced by DNA:RNA hybrid, we can investigate how far when the RNA structure is away from the ribosome that the ribosome can sense the presence of RNA structures. When the DNA:RNA is 1-2 nucleotide away from the ribosome mRNA entrance tunnel, the intersubunit rotation still can fluctuate among three states and induce the hyper rotated state. We also studied the correlation between thermal stability and the percentage of hyper rotated state. The higher thermal stability indicates a higher percentage of hyper rotated state. The hyper rotated state is not RNA structure specific as long as the RNA structure is stably enough, which will create problem for ribosome to unwind. It is possible whenever ribosome cannot unwind the downstreat RNA structure is a specific time window such as the time for ribosome to read one genetic codon (~2s), ribosome's intersubunit rotation dynamics is out of balance and stay in a trapped hyper rotated state as long as the barrier is to not strong enough to hold it more than 2 seconds. The ribosome unwinding also can be observed when there is no additional factors present, which also confirms that ribosome itself is a helicase. Ribosome dynamics is the main theme of this dissertation. However, since I have worked on NMR dynamics for two years with Dr. Chun Tang, it is also an integral part of my technical Ph.D training. There are two proteins I worked on: mouse adiponectin, glutamine binding protein (QBP) and EIN-Hpr complex. The last three chapters include the summary of our study on these three proteins. We have completed backbone assignments for both adipotectin and QBP. For adiponectin, we characterized the ligand binding property by chemical shift perturbation and measured the calcium binding affinity with terbium luminescence resonance energy transfer. For the QBP, we designed a linker at the back of the glutamine binding pocket so we can control the magnitude of opening between two lobes of the binding site. We measured the glutamine binding affinity for different mutants and found the correlation with the ligand binding affinity and the magnitude of opening. In addition, we developed a new PRE method called differentially scaled PRE.

scholarly journals Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Lu Zhang ◽  
Shaowen Wu ◽  
Yitao Feng ◽  
Dan Wang ◽  
Xilin Jia ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Protein Dynamics ◽  
Single Molecule ◽  
Binding Sites ◽  
Binding Protein ◽  
Conformational Dynamics ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Binding Affinities ◽  
Binding Mechanism

AbstractProtein dynamics plays key roles in ligand binding. However, the microscopic description of conformational dynamics-coupled ligand binding remains a challenge. In this study, we integrate molecular dynamics simulations, Markov state model (MSM) analysis and experimental methods to characterize the conformational dynamics of ligand-bound glutamine binding protein (GlnBP). We show that ligand-bound GlnBP has high conformational flexibility and additional metastable binding sites, presenting a more complex energy landscape than the scenario in the absence of ligand. The diverse conformations of GlnBP demonstrate different binding affinities and entail complex transition kinetics, implicating a concerted ligand binding mechanism. Single molecule fluorescence resonance energy transfer measurements and mutagenesis experiments are performed to validate our MSM-derived structure ensemble as well as the binding mechanism. Collectively, our study provides deeper insights into the protein dynamics-coupled ligand binding, revealing an intricate regulatory network underlying the apparent binding affinity.

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

Distinct Modulation of Wild-Type and Selective Gene Mutated Vitamin D Receptor by Essential Poly Unsaturated Fatty Acids

2021 ◽  
Vol 21 ◽  
Author(s):  
Hari Balaji ◽  
Selvaraj Ayyamperuma ◽  
Niladri Saha ◽  
Shyam Sundar Pottabathula ◽  
Jubie Selvaraj ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Vitamin D ◽  
Ligand Binding ◽  
Vitamin D Deficiency ◽  
Binding Affinity ◽  
Unsaturated Fatty Acids ◽  
Binding Domain ◽  
Ligand Binding Domain ◽  
Binding Energies ◽  
Wild Type

: Vitamin-D deficiency is a global concern. Gene mutations in the vitamin D receptor’s (VDR) ligand binding domain (LBD) variously alter the ligand binding affinity, heterodimerization with retinoid X receptor (RXR) and inhibit coactivator interactions. These LBD mutations may result in partial or total hormone unresponsiveness. A plethora of evidence report that selective long chain polyunsaturated fatty acids (PUFAs) including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and arachidonic acid (AA) bind to the ligand-binding domain of VDR and lead to transcriptional activation. We therefore hypothesize that selective PUFAs would modulate the dynamics and kinetics of VDRs, irrespective bioactive of vitamin-D binding. The spatial arrangements of the selected PUFAs in VDR active site were examined by in-silico docking studies. The docking results revealed that PUFAs have fatty acid structure-specific binding affinity towards VDR. The calculated EPA, DHA & AA binding energies (Cdocker energy) were lesser compared to vitamin-D in wild type of VDR (PDB id: 2ZLC). Of note, the DHA has higher binding interactions to the mutated VDR (PDB id: 3VT7) when compared to the standard Vitamin-D. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding of DHA with mutated VDR complex. These findings suggest the unique roles of PUFAs in VDR activation and may offer alternate strategy to circumvent vitamin-D deficiency.

scholarly journals SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Surendra Kumar ◽  
Mi-hyun Kim
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Fingerprint Pattern ◽  
Comparable Performance ◽  
Direct Interpretation ◽  
Benchmark Datasets ◽  
Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

scholarly journals RNA thermoswitches modulate Staphylococcus aureus adaptation to ambient temperatures

2021 ◽  
Vol 49 (6) ◽  
pp. 3409-3426
Author(s):  
Arancha Catalan-Moreno ◽  
Marta Cela ◽  
Pilar Menendez-Gil ◽  
Naiara Irurzun ◽  
Carlos J Caballero ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Rna Structure ◽  
Cold Shock ◽  
Mrna Translation ◽  
Site Directed Mutagenesis ◽  
Rna Structures ◽  
Double Stranded Rna ◽  
Ambient Temperatures ◽  
Shock Proteins ◽  
Rna Hairpin

Abstract Thermoregulation of virulence genes in bacterial pathogens is essential for environment-to-host transition. However, the mechanisms governing cold adaptation when outside the host remain poorly understood. Here, we found that the production of cold shock proteins CspB and CspC from Staphylococcus aureus is controlled by two paralogous RNA thermoswitches. Through in silico prediction, enzymatic probing and site-directed mutagenesis, we demonstrated that cspB and cspC 5′UTRs adopt alternative RNA structures that shift from one another upon temperature shifts. The open (O) conformation that facilitates mRNA translation is favoured at ambient temperatures (22°C). Conversely, the alternative locked (L) conformation, where the ribosome binding site (RBS) is sequestered in a double-stranded RNA structure, is folded at host-related temperatures (37°C). These structural rearrangements depend on a long RNA hairpin found in the O conformation that sequesters the anti-RBS sequence. Notably, the remaining S. aureus CSP, CspA, may interact with a UUUGUUU motif located in the loop of this long hairpin and favour the folding of the L conformation. This folding represses CspB and CspC production at 37°C. Simultaneous deletion of the cspB/cspC genes or their RNA thermoswitches significantly decreases S. aureus growth rate at ambient temperatures, highlighting the importance of CspB/CspC thermoregulation when S. aureus transitions from the host to the environment.

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