scholarly journals Alpha-actinin binding kinetics modulate cellular dynamics and force generation

2015 ◽  
Vol 112 (21) ◽  
pp. 6619-6624 ◽  
Author(s):  
Allen J. Ehrlicher ◽  
Ramaswamy Krishnan ◽  
Ming Guo ◽  
Cécile M. Bidan ◽  
David A. Weitz ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Cell Structure ◽  
Point Mutations ◽  
Traction Force ◽  
Human Kidney ◽  
Cell Dynamics ◽  
Motile Cells ◽  
Cross Linker ◽  
The Impact ◽  
In Cells

The actin cytoskeleton is a key element of cell structure and movement whose properties are determined by a host of accessory proteins. Actin cross-linking proteins create a connected network from individual actin filaments, and though the mechanical effects of cross-linker binding affinity on actin networks have been investigated in reconstituted systems, their impact on cellular forces is unknown. Here we show that the binding affinity of the actin cross-linker α-actinin 4 (ACTN4) in cells modulates cytoplasmic mobility, cellular movement, and traction forces. Using fluorescence recovery after photobleaching, we show that an ACTN4 mutation that causes human kidney disease roughly triples the wild-type binding affinity of ACTN4 to F-actin in cells, increasing the dissociation time from 29 ± 13 to 86 ± 29 s. This increased affinity creates a less dynamic cytoplasm, as demonstrated by reduced intracellular microsphere movement, and an approximate halving of cell speed. Surprisingly, these less motile cells generate larger forces. Using traction force microscopy, we show that increased binding affinity of ACTN4 increases the average contractile stress (from 1.8 ± 0.7 to 4.7 ± 0.5 kPa), and the average strain energy (0.4 ± 0.2 to 2.1 ± 0.4 pJ). We speculate that these changes may be explained by an increased solid-like nature of the cytoskeleton, where myosin activity is more partitioned into tension and less is dissipated through filament sliding. These findings demonstrate the impact of cross-linker point mutations on cell dynamics and forces, and suggest mechanisms by which such physical defects lead to human disease.

scholarly journals How far are we in the rapid prediction of drug resistance caused by kinase mutations?

2020 ◽  
Author(s):  
Mehmet Erguven ◽  
Tülay Karakulak ◽  
M. Kasim Diril ◽  
Ezgi Karaca
Keyword(s):  
Protein Kinase ◽  
Protein Kinases ◽  
Binding Affinity ◽  
Point Mutations ◽  
Binding Pocket ◽  
Functional Study ◽  
Web Based ◽  
Diverse Range ◽  
Ligand Interactions ◽  
The Impact

ABSTRACTProtein kinases regulate various cell signaling events in a diverse range of species through phosphorylation. The phosphorylation occurs upon transferring the terminal phosphate of an ATP molecule to a designated target residue. Due to the central role of protein kinases in proliferative pathways, point mutations occurring within or in the vicinity of ATP binding pocket can render the enzyme overactive, leading to cancer. Combatting such mutation-induced effects with the available drugs has been a challenge, since these mutations usually happen to be drug resistant. Therefore, the functional study of naturally and/or artificially occurring kinase mutations have been at the center of attention in diverse biology-related disciplines. Unfortunately, rapid experimental exploration of the impact of such mutations remains to be a challenge due to technical and economical limitations. Therefore, the availability of kinase-ligand binding affinity prediction tools is of great importance. Within this context, we have tested six state-of-the-art web-based affinity predictors (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations with their ligand interactions. This assessment is performed on our structure-based protein kinase mutation benchmark, BINDKIN. BINDKIN contains 23 wild type-mutant pairs of kinase-small molecule complexes, together with their corresponding binding affinity data (in the form of IC50, Kd, and Ki). The web-server performances over BINDKIN show that the raw server predictions fail to produce good correlations with the experimental data. However, when we start looking in to the direction of change (whether a mutation improves/worsens the binding), we observe that over Ki data, DSX-ONLINE achieves a Pearson’s R correlation coefficient of 0.97. When we used homology models instead of crystal structures, this correlation drops to 0.45. These results highlight that there is still room to improve the available web-based predictors to estimate the impact of protein kinase point mutations. We present our BINDKIN benchmark and all the related results online for the sake of aiding such improvement efforts. Our files can be reached at https://github.com/CSB-KaracaLab/BINDKIN

scholarly journals Deep geometric representations for modeling effects of mutations on protein-protein binding affinity

2021 ◽  
Vol 17 (8) ◽  
pp. e1009284
Author(s):  
Xianggen Liu ◽  
Yunan Luo ◽  
Pengyong Li ◽  
Sen Song ◽  
Jian Peng
Keyword(s):  
Protein Binding ◽  
Binding Affinity ◽  
Protein Design ◽  
Protein Structures ◽  
Three Dimensional ◽  
Point Mutations ◽  
Dimensional Structure ◽  
Gradient Boosting ◽  
Benchmark Datasets ◽  
The Impact

Modeling the impact of amino acid mutations on protein-protein interaction plays a crucial role in protein engineering and drug design. In this study, we develop GeoPPI, a novel structure-based deep-learning framework to predict the change of binding affinity upon mutations. Based on the three-dimensional structure of a protein, GeoPPI first learns a geometric representation that encodes topology features of the protein structure via a self-supervised learning scheme. These representations are then used as features for training gradient-boosting trees to predict the changes of protein-protein binding affinity upon mutations. We find that GeoPPI is able to learn meaningful features that characterize interactions between atoms in protein structures. In addition, through extensive experiments, we show that GeoPPI achieves new state-of-the-art performance in predicting the binding affinity changes upon both single- and multi-point mutations on six benchmark datasets. Moreover, we show that GeoPPI can accurately estimate the difference of binding affinities between a few recently identified SARS-CoV-2 antibodies and the receptor-binding domain (RBD) of the S protein. These results demonstrate the potential of GeoPPI as a powerful and useful computational tool in protein design and engineering. Our code and datasets are available at: https://github.com/Liuxg16/GeoPPI.

The Impact of Bioconjugation on the Interfacial Activity of a Protein Biosurfactant

2018 ◽  
Author(s):  
Hossam H Tayeb ◽  
Marina Stienecker ◽  
Anton Middelberg ◽  
Frank Sainsbury
Keyword(s):  
Polyethylene Glycol ◽  
Colloidal Stability ◽  
Point Mutations ◽  
Pharmaceutical Formulations ◽  
Industrial Processes ◽  
Parent Molecule ◽  
Site Specific ◽  
Interfacial Activity ◽  
Surface Active ◽  
The Impact

Biosurfactants, are surface active molecules that can be produced by renewable, industrially scalable biologic processes. DAMP4, a designer biosurfactant, enables the modification of interfaces via genetic or chemical fusion to functional moieties. However, bioconjugation of addressable amines introduces heterogeneity that limits the precision of functionalization as well as the resolution of interfacial characterization. Here we designed DAMP4 variants with cysteine point mutations to allow for site-specific bioconjugation. The DAMP4 variants were shown to retain the structural stability and interfacial activity characteristic of the parent molecule, while permitting efficient and specific conjugation of polyethylene glycol (PEG). PEGylation results in a considerable reduction on the interfacial activity of both single and double mutants. Comparison of conjugates with one or two conjugation sites shows that both the number of conjugates as well as the mass of conjugated material impacts the interfacial activity of DAMP4. As a result, the ability of DAMP4 variants with multiple PEG conjugates to impart colloidal stability on peptide-stabilized emulsions is reduced. We suggest that this is due to constraints on the structure of amphiphilic helices at the interface. Specific and efficient bioconjugation permits the exploration and investigation of the interfacial properties of designer protein biosurfactants with molecular precision. Our findings should therefore inform the design and modification of biosurfactants for their increasing use in industrial processes, and nutritional and pharmaceutical formulations.

A New Series Of 1,3-Dimethylxanthine Based Adenosine A2a Receptor Antagonists As A Non-Dopaminergic Treatment Of Parkinson’s Disease

2020 ◽  
Vol 17 ◽  
Author(s):  
Suman Rohilla ◽  
Ranju Bansal ◽  
Puneet Chauhan ◽  
Sonja Kachler ◽  
Karl-Norbert Klotz
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Molecular Docking ◽  
Binding Affinity ◽  
Docking Studies ◽  
Binding Modes ◽  
Molecular Docking Studies ◽  
In Silico Docking ◽  
Adenosine A2a Receptor Antagonists ◽  
The Impact

Background: Adenosine receptors (AR) have emerged as competent and innovative nondopaminergic targets for the development of potential drug candidates and thus constitute an effective and safer treatment approach for Parkinson’s disease (PD). Xanthine derivatives are considered as potential candidates for the treatment Parkinson’s disease due to their potent A2A AR antagonistic properties. Objective: The objectives of the work are to study the impact of substituting N7-position of 8-m/pchloropropoxyphenylxanthine structure on in vitro binding affinity of compounds with various AR subtypes, in vivo antiparkinsonian activity and binding modes of newly synthesized xanthines with A2A AR in molecular docking studies. Methods: Several new 7-substituted 8-m/p-chloropropoxyphenylxanthine analogues have been prepared. Adenosine receptor binding assays were performed to study the binding interactions with various subtypes and perphenazine induced rat catatonia model was used for antiparkinsonian activity. Molecular docking studies were performed using Schrödinger molecular modeling interface. Results: 8-para-substituted xanthine 9b bearing an N7-propyl substituent displayed the highest affinity towards A2A AR (Ki = 0.75 µM) with moderate selectivity versus other AR subtypes. 7-Propargyl analogue 9d produced significantly longlasting antiparkinsonian effects and also produced potent and selective binding affinity towards A2A AR. In silico docking studies further highlighted the crucial structural components required to develop xanthine derived potential A2A AR ligands as antiparkinsonian agents. Conclusion: A new series of 7-substituted 8-m/p-chloropropoxyphenylxanthines having good affinity for A2A AR and potent antiparkinsonian activity has been developed.

scholarly journals Cell migration guided by long-lived spatial memory

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joseph d’Alessandro ◽  
Alex Barbier--Chebbah ◽  
Victor Cellerin ◽  
Olivier Benichou ◽  
René Marc Mège ◽  
...  
Keyword(s):  
Cell Migration ◽  
Spatial Memory ◽  
Large Scale ◽  
Single Cells ◽  
Environmental Perturbations ◽  
Motile Cells ◽  
Unicellular Organisms ◽  
Biochemical Signals ◽  
The Impact ◽  
Cell Trajectories

AbstractLiving cells actively migrate in their environment to perform key biological functions—from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion, and has been shown to also integrate various chemical or physical extracellular signals. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodelling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells can retrieve their path: by confining motile cells on 1D and 2D micropatterned surfaces, we demonstrate that they leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.

scholarly journals Poly(Lactic Acid)–Poly(Butylene Succinate)–Sugar Beet Pulp Composites; Part I: Mechanics of Composites with Fine and Coarse Sugar Beet Pulp Particles

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2531
Author(s):  
Rodion Kopitzky
Keyword(s):  
Mechanical Properties ◽  
Lactic Acid ◽  
Sugar Beet ◽  
Cell Structure ◽  
Sugar Beet Pulp ◽  
Poly Lactic Acid ◽  
Butylene Succinate ◽  
Fracture Patterns ◽  
Beet Pulp ◽  
The Impact

Sugar beet pulp (SBP) is a residue available in large quantities from the sugar industry, and can serve as a cost-effective bio-based and biodegradable filler for fully bio-based compounds based on bio-based polyesters. The heterogeneous cell structure of sugar beet suggests that the processing of SBP can affect the properties of the composite. An “Ultra-Rotor” type air turbulence mill was used to produce SBP particles of different sizes. These particles were processed in a twin-screw extruder with poly(lactic acid) (PLA) and poly(butylene succinate) (PBS) and fillers to granules for possible marketable formulations. Different screw designs, compatibilizers and the use of glycerol as a thermoplasticization agent for SBP were also tested. The spherical, cubic, or ellipsoidal-like shaped particles of SBP are not suitable for usage as a fiber-like reinforcement. In addition, the fineness of ground SBP affects the mechanical properties because (i) a high proportion of polar surfaces leads to poor compatibility, and (ii) due to the inner structure of the particulate matter, the strength of the composite is limited to the cohesive strength of compressed sugar-cell compartments of the SBP. The compatibilization of the polymer–matrix–particle interface can be achieved by using compatibilizers of different types. Scanning electron microscopy (SEM) fracture patterns show that the compatibilization can lead to both well-bonded particles and cohesive fracture patterns in the matrix. Nevertheless, the mechanical properties are limited by the impact and elongation behavior. Therefore, the applications of SBP-based composites must be well considered.

scholarly journals Experimental-numerical studies of the effect of cell structure on the mechanical properties of polypropylene foams

e-Polymers ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 713-723
Author(s):  
Wei Gong ◽  
Tuan-Hui Jiang ◽  
Xiang-Bu Zeng ◽  
Li He ◽  
Chun Zhang
Keyword(s):  
Mechanical Properties ◽  
Size Distribution ◽  
Cell Size ◽  
Cell Structure ◽  
Structure Parameters ◽  
Cell Size Distribution ◽  
Numerical Studies ◽  
Polypropylene Foam ◽  
The Impact ◽  
The Relationship

AbstractThe effects of the cell size and distribution on the mechanical properties of polypropylene foam were simulated and analyzed by finite element modeling with ANSYS and supporting experiments. The results show that the reduced cell size and narrow size distribution have beneficial influences on both the tensile and impact strengths. Decreasing the cell size or narrowing the cell size distribution was more effective for increasing the impact strength than the tensile strength in the same case. The relationship between the mechanical properties and cell structure parameters has a good correlation with the theoretical model.

scholarly journals In Planta Mutagenesis Determines the Functional Regions of the Wheat Puroindoline Proteins

Genetics ◽  
2009 ◽  
Vol 183 (3) ◽  
pp. 853-860 ◽  
Author(s):  
Leila Feiz ◽  
Brian S. Beecher ◽  
John M. Martin ◽  
Michael J. Giroux
Keyword(s):  
Functional Analysis ◽  
Allelic Variation ◽  
Screening Method ◽  
Point Mutations ◽  
Missense Mutations ◽  
Grain Hardness ◽  
In Planta ◽  
Rich Region ◽  
Critical Function ◽  
The Impact

In planta analysis of protein function in a crop plant could lead to improvements in understanding protein structure/function relationships as well as selective agronomic or end product quality improvements. The requirements for successful in planta analysis are a high mutation rate, an efficient screening method, and a trait with high heritability. Two ideal targets for functional analysis are the Puroindoline a and Puroindoline b (Pina and Pinb, respectively) genes, which together compose the wheat (Triticum aestivum L.) Ha locus that controls grain texture and many wheat end-use properties. Puroindolines (PINs) together impart soft texture, and mutations in either PIN result in hard seed texture. Studies of the PINs' mode of action are limited by low allelic variation. To create new Pin alleles and identify critical function-determining regions, Pin point mutations were created in planta via EMS treatment of a soft wheat. Grain hardness of 46 unique PIN missense alleles was then measured using segregating F2:F3 populations. The impact of individual missense alleles upon PIN function, as measured by grain hardness, ranged from neutral (74%) to intermediate to function abolishing. The percentage of function-abolishing mutations among mutations occurring in both PINA and PINB was higher for PINB, indicating that PINB is more critical to overall Ha function. This is contrary to expectations in that PINB is not as well conserved as PINA. All function-abolishing mutations resulted from structure-disrupting mutations or from missense mutations occurring near the Tryptophan-rich region. This study demonstrates the feasibility of in planta functional analysis of wheat proteins and that the Tryptophan-rich region is the most important region of both PINA and PINB.

scholarly journals Molecular Docking Senyawa Gingerol dan Zingiberol pada Tanaman Jahe sebagai Penanganan COVID-19

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Belinda D. P. M. Ratu ◽  
Widdhi Bodhi ◽  
Fona Budiarso ◽  
Billy J. Kepel ◽  
. Fatimawali ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Amino Acid Residues ◽  
Autodock Vina ◽  
Discovery Studio ◽  
Main Protease ◽  
Docking Method ◽  
Pubmed Database ◽  
Almost All ◽  
The Impact

Abstract: COVID-19 is a new disease. Many people feel the impact of this disease. There is no definite cure for COVID-19, so many people use traditional medicine to ward off COVID-19, including ginger. This study aims to determine whether there is an interaction between compounds in ginger (gingerol and zingiberol) and the COVID-19’s main protease (6LU7). This study uses a molecular docking method using 4 main applications, namely Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, and Open Babel GUI. The samples used were gingerol and zingiberol compounds in ginger plants downloaded from Pubchem. The data used in this study used Mendeley, Clinical Key, and PubMed database. The study showed that almost all of the amino acid residues in the gingerol compound acted on the 6LU7 active site, whereas the zingiberol did not. The results of the binding affinity of ginger compounds, both gingerol and zingiberol, do not exceed the binding affinity of remdesivir, a drug that is widely researched as a COVID-19 handling drug. In conclusion, gingerol and zingiberol compounds in ginger can’t be considered as COVID-19’s treatment.Keywords: molecular docking, gingerol, zingiberol Abstrak: COVID-19 merupakan sebuah penyakit yang baru. Banyak masyarakat yang merasakan dampak dari penyakit ini. Belum ada pengobatan pasti untuk menyembuhkan COVID-19, sehingga banyak masyarakat yang menggunakan pengobatan tradisional untuk menangkal COVID-19, termasuk jahe. Penelitian ini bertujuan untuk mengetahui apakah ada interaksi antara senyawa pada jahe (gingerol dan zingiberol) dengan main protease COVID-19 (6LU7). Penelitian ini menggunakan metode molecular docking dengan menggunakan 4 aplikasi utama, yaitu Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, dan Open Babel GUI. Sampel yang digunakan yaitu senyawa gingerol dan zingiberol pada tanaman jahe yang diunduh di Pubchem. Data yang digunakan dalam penelitian ini menggunakan database Mendeley, Clinical Key, dan PubMed. Penelitian menunjukkan bahwa hampir semua residu asam amino pada senyawa gingerol bekerja pada sisi aktif 6LU7, sedangkan tidak demikian pada zingiberol. Hasil binding affinity senyawa jahe, baik gingerol maupun zingiberol tidak  melebihi binding affinity remdesivir, obat yang banyak diteliti sebagai obat penanganan COVID-19. Sebagai simpulan, senyawa gingerol dan zingiberol pada tanaman jahe tidak dapat dipertimbangkan sebagai penanganan COVID-19Kata Kunci: molecular docking, gingerol, zingiberol

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