First principles computational study of the active site of arginase

2003 ◽  
Vol 54 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Ivaylo Ivanov ◽  
Michael L. Klein
Keyword(s):  
Active Site ◽  
First Principles ◽  
Computational Study

Theoretical Studies of the Acid-Base Equilibria in a Model Active Site of the Human 20S Proteasome

2020 ◽  
Author(s):  
Jon Uranga ◽  
Lukas Hasecke ◽  
Jonny Proppe ◽  
Jan Fingerhut ◽  
Ricardo A. Mata
Keyword(s):  
Active Site ◽  
Boronic Acid ◽  
Computational Study ◽  
Ubiquitin Proteasome System ◽  
Bayesian Optimization ◽  
Inhibition Mechanism ◽  
20S Proteasome ◽  
Acid Base ◽  
Ubiquitin Proteasome ◽  
Infection Cycles

The 20S Proteasome is a macromolecule responsible for the chemical step in the ubiquitin-proteasome system of degrading unnecessary and unused proteins of the cell. It plays a central role both in the rapid growth of cancer cells as well as in viral infection cycles. Herein, we present a computational study of the acid-base equilibria in an active site of the human proteasome, an aspect which is often neglected despite the crucial role protons play in the catalysis. As example substrates, we take the inhibition by epoxy and boronic acid containing warheads. We have combined cluster quantum mechanical calculations, replica exchange molecular dynamics and Bayesian optimization of non-bonded potential terms in the inhibitors. In relation to the latter, we propose an easily scalable approach to the reevaluation of non-bonded potentials making use of QM/MM dynamics information. Our results show that coupled acid-base equilibria need to be considered when modeling the inhibition mechanism. The coupling between a neighboring lysine and the reacting threonine is not affected by the presence of the inhibitor.

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>

scholarly journals A Ternary Map of Ni–Mn–Ga Heusler Alloys from Ab Initio Calculations

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 973
Author(s):  
Yulia Sokolovskaya ◽  
Olga Miroshkina ◽  
Danil Baigutlin ◽  
Vladimir Sokolovskiy ◽  
Mikhail Zagrebin ◽  
...  
Keyword(s):  
First Principles ◽  
Predictive Power ◽  
Computational Study ◽  
Heusler Alloys ◽  
Functional Materials ◽  
Ternary Diagram ◽  
Compositional Stability ◽  
Theoretical Predictions ◽  
Simultaneous Stability ◽  
Tetragonal Martensite

In the search for new magnetic functional materials, non-stoichiometric compounds remain a relatively unexplored territory. While experimentalists create new compositions looking for improved functional properties, their work is not guided by systematic theoretical predictions. Being designed for perfect periodic crystals, the majority of first-principles approaches struggle with the concept of a non-stoichiometric system. In this work, we attempt a systematic computational study of magnetic and structural properties of Ni–Mn–Ga, mapped onto ternary composition diagrams. Compositional stability was examined using the convex hull analysis. We show that the cubic austenite has its stability region close to the stoichiometric Ni2MnGa, in agreement with experimental data, while the tetragonal martensite spreads its stability over a wider range of Mn and Ni contents. The unstable compositions in both austenite and martensite states are located in the Ga-rich corner of the ternary diagram. We note that simultaneous stability of the austenite and martensite should be considered for potentially stable compounds suitable for synthesis. The majority of compounds are predicted to be ferrimagnetically ordered in both austenitic and martensitic states. The methodology used in this work is computationally tractable, yet it delivers some predictive power. For experimentalists who plan to synthesize stable Ni–Mn–Ga compounds with ferromagnetic order, we narrow the target compositional range substantially.

Identification of the active site of human mitochondrial malonyl-coenzyme a decarboxylase: A combined computational study

2016 ◽  
Vol 84 (6) ◽  
pp. 792-802 ◽  
Author(s):  
Baoping Ling ◽  
Yuxia Liu ◽  
Xiaoping Li ◽  
Zhiguo Wang ◽  
Siwei Bi
Keyword(s):  
Active Site ◽  
Coenzyme A ◽  
Computational Study

Factors Favoring Ferroelectricity in Hafnia: A First-Principles Computational Study

2017 ◽  
Vol 121 (8) ◽  
pp. 4139-4145 ◽  
Author(s):  
Rohit Batra ◽  
Tran Doan Huan ◽  
Jacob L. Jones ◽  
George Rossetti ◽  
Rampi Ramprasad
Keyword(s):  
First Principles ◽  
Computational Study

Atypical Protonation States in the Active Site of HIV-1 Protease: A Computational Study

2007 ◽  
Vol 47 (4) ◽  
pp. 1590-1598 ◽  
Author(s):  
Paul Czodrowski ◽  
Christoph A. Sotriffer ◽  
Gerhard Klebe
Keyword(s):  
Active Site ◽  
Computational Study ◽  
Hiv 1

Computational study of distortion effect of Fe-porphyrin found as a biological active site

2020 ◽  
Vol 59 (1) ◽  
pp. 010502 ◽  
Author(s):  
Yu Takano ◽  
Hiroko X. Kondo ◽  
Yusuke Kanematsu ◽  
Yasuhiro Imada
Keyword(s):  
Active Site ◽  
Computational Study ◽  
Distortion Effect

scholarly journals Aldose Reductase Differential Inhibitors in Green Tea

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1003 ◽  
Author(s):  
Francesco Balestri ◽  
Giulio Poli ◽  
Carlotta Pineschi ◽  
Roberta Moschini ◽  
Mario Cappiello ◽  
...  
Keyword(s):  
Gallic Acid ◽  
Green Tea ◽  
Aldose Reductase ◽  
Active Site ◽  
Inhibitory Action ◽  
Computational Study ◽  
Epigallocatechin Gallate ◽  
Polyol Pathway ◽  
Differential Inhibition ◽  
Tea Extract

Aldose reductase (AKR1B1), the first enzyme in the polyol pathway, is likely involved in the onset of diabetic complications. Differential inhibition of AKR1B1 has been proposed to counteract the damaging effects linked to the activity of the enzyme while preserving its detoxifying ability. Here, we show that epigallocatechin gallate (EGCG), one of the most representative catechins present in green tea, acts as a differential inhibitor of human recombinant AKR1B1. A kinetic analysis of EGCG, and of its components, gallic acid (GA) and epigallocatechin (EGC) as inhibitors of the reduction of L-idose, 4-hydroxy2,3-nonenal (HNE), and 3-glutathionyl l-4-dihydroxynonanal (GSHNE) revealed for the compounds a different model of inhibition toward the different substrates. While EGCG preferentially inhibited L-idose and GSHNE reduction with respect to HNE, gallic acid, which was still active in inhibiting the reduction of the sugar, was less active in inhibiting HNE and GSHNE reduction. EGC was found to be less efficient as an inhibitor of AKR1B1 and devoid of any differential inhibitory action. A computational study defined different interactive modes for the three substrates on the AKR1B1 active site and suggested a rationale for the observed differential inhibition. A chromatographic fractionation of an alcoholic green tea extract revealed that, besides EGCG and GA, other components may exhibit the differential inhibition of AKR1B1.

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