scholarly journals Understanding the Role of Geometric and Electronic Structure in Bioinspired Catalyst Design: the Case of Formate Dehydrogenase

2021 ◽  
Author(s):  
Mingjie Liu ◽  
Azadeh Nazemi ◽  
Michael Taylor ◽  
Aditya Nandy ◽  
Chenru Duan ◽  
...  
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Large Scale ◽  
Formate Dehydrogenase ◽  
Molecular Complexes ◽  
Catalyst Design ◽  
Local Geometry ◽  
Structural Variations ◽  
Screening Study ◽  
The Individual

The design of bioinspired synthetic inorganic molecular complexes is challenging, due to a lack of understanding of enzyme action and the degree to which that action can be translated into mimics. Exemplary of this challenge is the reversible conversion of formate into CO2 by formate dehydrogenase (FDH) enzymes with Mo/W centers in large molybdopterin cofactors. Despite numerous efforts to synthesize Mo/W-containing molecular complexes, none have been demonstrated to reproduce the full reactivity of FDH. Here, we carry out a large-scale, high-throughput screening study on all mononuclear Mo/W complexes currently deposited in Cambridge Structural Database (CSD). Using density functional theory, we systematically investigate the individual effects of metal identity, ligand identity, oxidation state, and coordination number on structural, electronic and catalytic properties. We compare our results on molecular complexes with quantum mechanics/molecular mechanics simulations on a representative FDH enzyme to further elucidate the influence of the enzyme environment. These comparisons reveal that the enzyme environment primarily influences the metal-local geometry, and these metal-local structural variations can improve catalysis. Through a series of computational mutations on molecular complexes, we extend beyond the CSD structures to further identify the limits of varied chalcogen and metal identity. This broad set and comparison reveal relatively little variation of electronic properties of the metal center due to the presence of the enzyme environment or changes in metal-distant ligand chemistry. Instead, these properties are found to be much more sensitive to the identity of the metal and the nature of the bound terminal chalcogen.

scholarly journals Cross-conjugation controls the stabilities and photophysical properties of heteroazoarene photoswitches

2021 ◽  
Author(s):  
Daniel Adrion ◽  
Steven Lopez
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Photophysical Properties ◽  
Photochemical Reactions ◽  
Free Energies ◽  
Excitation Energies ◽  
Functional Theory ◽  
Vertical Excitation ◽  
Screening Study

Azoarene photoswitches are versatile molecules that interconvert from their E-isomer to their Z-isomer with light. Azobenzene is a prototypical photoswitch but its derivatives can be poorly suited for in vivo applications such as photopharmacology due to undesired photochemical reactions promoted by ultraviolet light and its relatively short half-life (t1/2) of the Z-isomer (2 days). Experimental and computational studies suggest that these properties (λmax of the E isomer and t1/2 of the Z-isomer) are inversely related. We identified isomeric azobisthiophenes and azobisfurans from a high-throughput screening study of 1700 azoarenes as photoswitch candidates with improved λmax and t1/2 values relative to azobenzene. We used density functional theory to predict the activation free energies, reaction free energies, and vertical excitation energies of the E- and Z-isomers of 2,2- and 3,3-substituted azobisthiophenes and azobisfurans. The half-lives depend on whether the heterocycles are 𝜋-conjugated or cross-conjugated with the diazo 𝜋-bond. The 2,2-substituted azoarenes both have t1/2 values on the scale of 1 hour, while the 3,3-analogues have computed half-lives of 40 (thiophene) and 230 (furan) years. The 2,2-substituted heteroazoarenes have significantly higher λmax absorptions than their 3,3-substituted analogs: 76 nm for azofuran and 77 nm for azothiophene.

A tactile sensor based on thin-plate deformation

Robotica ◽  
1994 ◽  
Vol 12 (4) ◽  
pp. 343-351 ◽  
Author(s):  
R.E. Ellis ◽  
S.R. Ganeshan ◽  
S.J. Lederman
Keyword(s):  
Large Scale ◽  
Tactile Sensor ◽  
Thin Plates ◽  
Local Geometry ◽  
Normal Strain ◽  
Tactile Sensors ◽  
Accuracy Measurement ◽  
Scale Properties ◽  
Task Specification ◽  
The Individual

SUMMARYTraditionally, tactile sensors have been designed using compliant, rubber-like materials; when such a sensitized gripper grasps or otherwise manipulates an object, the normal strain deformation in the compliant material is sampled. The resulting information can be used to deduce simple local geometry of the contact, but the transduction process does not typically permit use of the individual strains in determining large-scale properties of the object (e.g., the inertia). Measurements of inertial parameters of grasped objects require accurate, low-hysteresis transduction that few tactile sensors currently provide.An alternative is to work from the task specification, and determine the tactile information that is necessary to accomplish the task. Here, we consider how to sense the length and mass of a uniform object that is gripped in a gravitational field, and show the design and assessment of a new kind of tactile sensor that is based on the theory of the deformation of thin plates. Features of this design include its potentially rugged realization, and its high-accuracy measurement that is more typical of force sensors than of tactile sensors.

Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: evaluation of electronic structure theory methods

2014 ◽  
Vol 16 (17) ◽  
pp. 7919-7926 ◽  
Author(s):  
Martin Korth
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Large Scale ◽  
Function Theory ◽  
Molecular Structures ◽  
Structure Theory ◽  
Quantum Mechanical ◽  
Functional Theory ◽  
Battery Electrolyte ◽  
Semi Empirical

The performance of semi-empirical quantum mechanical (SQM), density functional theory (DFT) and wave function theory (WFT) methods is evaluated for the purpose of screening a large number of molecular structures with respect to their electrochemical stability to identify new battery electrolyte solvents.

Models, Practices and Methods of Reading: Evolution in Time and Space

2009 ◽  
pp. 59-64
Author(s):  
Yulia P. Melentyeva
Keyword(s):  
Large Scale ◽  
Social Groups ◽  
National Program ◽  
Time And Space ◽  
Lack Of Information ◽  
The Individual

In recent years as public in general and specialist have been showing big interest to the matters of reading. According to discussion and launch of the “Support and Development of Reading National Program”, many Russian libraries are organizing the large-scale events like marathons, lecture cycles, bibliographic trainings etc. which should draw attention of different social groups to reading. The individual forms of attraction to reading are used much rare. To author’s mind the main reason of such an issue has to be the lack of information about forms and methods of attraction to reading.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

Towards a Design of Active Oxygen Evolution Catalysts: Insights from Automated Density Functional Theory Calculations and Machine Learning

2019 ◽  
Author(s):  
Seoin Back ◽  
Kevin Tran ◽  
Zachary Ulissi
Keyword(s):  
Machine Learning ◽  
Oxygen Evolution ◽  
Active Sites ◽  
Density Functional ◽  
Chemical Space ◽  
Density Functional Theory Calculations ◽  
Catalyst Design ◽  
Transition Metal Catalysts ◽  
Oxide Materials ◽  
Design Strategies

<div> <div> <div> <div><p>Developing active and stable oxygen evolution catalysts is a key to enabling various future energy technologies and the state-of-the-art catalyst is Ir-containing oxide materials. Understanding oxygen chemistry on oxide materials is significantly more complicated than studying transition metal catalysts for two reasons: the most stable surface coverage under reaction conditions is extremely important but difficult to understand without many detailed calculations, and there are many possible active sites and configurations on O* or OH* covered surfaces. We have developed an automated and high-throughput approach to solve this problem and predict OER overpotentials for arbitrary oxide surfaces. We demonstrate this for a number of previously-unstudied IrO2 and IrO3 polymorphs and their facets. We discovered that low index surfaces of IrO2 other than rutile (110) are more active than the most stable rutile (110), and we identified promising active sites of IrO2 and IrO3 that outperform rutile (110) by 0.2 V in theoretical overpotential. Based on findings from DFT calculations, we pro- vide catalyst design strategies to improve catalytic activity of Ir based catalysts and demonstrate a machine learning model capable of predicting surface coverages and site activity. This work highlights the importance of investigating unexplored chemical space to design promising catalysts.<br></p></div></div></div></div><div><div><div> </div> </div> </div>

Benchmark of Simplified Time-Dependent Density Functional Theory for UV-Vis Spectral Properties of Porphyrinoids

2019 ◽  
Author(s):  
Kamal Batra ◽  
Stefan Zahn ◽  
Thomas Heine
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Large Scale ◽  
Absolute Error ◽  
Time Dependent ◽  
Basis Set ◽  
Basis Sets ◽  
Functional Theory ◽  
Framework Materials ◽  
Dependent Density

<p>We thoroughly benchmark time-dependent density- functional theory for the predictive calculation of UV/Vis spectra of porphyrin derivatives. With the aim to provide an approach that is computationally feasible for large-scale applications such as biological systems or molecular framework materials, albeit performing with high accuracy for the Q-bands, we compare the results given by various computational protocols, including basis sets, density-functionals (including gradient corrected local functionals, hybrids, double hybrids and range-separated functionals), and various variants of time-dependent density-functional theory, including the simplified Tamm-Dancoff approximation. An excellent choice for these calculations is the range-separated functional CAM-B3LYP in combination with the simplified Tamm-Dancoff approximation and a basis set of double-ζ quality def2-SVP (mean absolute error [MAE] of ~0.05 eV). This is not surpassed by more expensive approaches, not even by double hybrid functionals, and solely systematic excitation energy scaling slightly improves the results (MAE ~0.04 eV). </p>

Large-scale High-throughput Screening Revealed 5'-(carbonylamino)-2,3'- bithiophene-4'-carboxylate as Novel Template for Antibacterial Agents

2020 ◽  
Vol 17 (5) ◽  
pp. 716-724
Author(s):  
Yan A. Ivanenkov ◽  
Renat S. Yamidanov ◽  
Ilya A. Osterman ◽  
Petr V. Sergiev ◽  
Vladimir A. Aladinskiy ◽  
...  
Keyword(s):  
Antibacterial Activity ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Antibacterial Agents ◽  
Sos Response ◽  
Luciferase Assay ◽  
Translational Machinery ◽  
E Coli ◽  
New Class

Background: The key issue in the development of novel antimicrobials is a rapid expansion of new bacterial strains resistant to current antibiotics. Indeed, World Health Organization has reported that bacteria commonly causing infections in hospitals and in the community, e.g. E. Coli, K. pneumoniae and S. aureus, have high resistance vs the last generations of cephalosporins, carbapenems and fluoroquinolones. During the past decades, only few successful efforts to develop and launch new antibacterial medications have been performed. This study aims to identify new class of antibacterial agents using novel high-throughput screening technique. Methods: We have designed library containing 125K compounds not similar in structure (Tanimoto coeff.< 0.7) to that published previously as antibiotics. The HTS platform based on double reporter system pDualrep2 was used to distinguish between molecules able to block translational machinery or induce SOS-response in a model E. coli system. MICs for most active chemicals in LB and M9 medium were determined using broth microdilution assay. Results: In an attempt to discover novel classes of antibacterials, we performed HTS of a large-scale small molecule library using our unique screening platform. This approach permitted us to quickly and robustly evaluate a lot of compounds as well as to determine the mechanism of action in the case of compounds being either translational machinery inhibitors or DNA-damaging agents/replication blockers. HTS has resulted in several new structural classes of molecules exhibiting an attractive antibacterial activity. Herein, we report as promising antibacterials. Two most active compounds from this series showed MIC value of 1.2 (5) and 1.8 μg/mL (6) and good selectivity index. Compound 6 caused RFP induction and low SOS response. In vitro luciferase assay has revealed that it is able to slightly inhibit protein biosynthesis. Compound 5 was tested on several archival strains and exhibited slight activity against gram-negative bacteria and outstanding activity against S. aureus. The key structural requirements for antibacterial potency were also explored. We found, that the unsubstituted carboxylic group is crucial for antibacterial activity as well as the presence of bulky hydrophobic substituents at phenyl fragment. Conclusion: The obtained results provide a solid background for further characterization of the 5'- (carbonylamino)-2,3'-bithiophene-4'-carboxylate derivatives discussed herein as new class of antibacterials and their optimization campaign.

scholarly journals Identification of a juvenile-hormone signaling inhibitor via high-throughput screening of a chemical library

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takumi Kayukawa ◽  
Kenjiro Furuta ◽  
Keisuke Nagamine ◽  
Tetsuro Shinoda ◽  
Kiyoaki Yonesu ◽  
...  
Keyword(s):  
Juvenile Hormone ◽  
Cell Line ◽  
Signaling Pathway ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Ex Vivo ◽  
Agricultural Field ◽  
Chemical Library ◽  
Field Development

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.

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