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Computation, Volume 10, Issue 5

2022 May - 14 articles

Cover Story: The Mpro enzyme is a validated target for developing SARS-CoV-2 antiviral drugs. A number of Mpro enzyme inhibitors, currently discovered, bear an electrophilic warhead, able to form a covalent bond with the active site cysteine residue, linked to a peptidic/peptidomimetic structure interacting with the non-prime subsites of the enzyme. We developed a computational protocol based on molecular docking, molecular dynamics, FEP, and covalent docking approaches for the evaluation of newly designed Mpro inhibitors. The results of our investigation highlighted that bifunctional warheads, engaging both prime and non-prime subsites of the active site, coupled to covalent reversible electrophilic warheads, could be exploited for expanding our armamentarium of Mpro inhibitors against SARS-CoV-2. View this paper
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Articles (14)

  • Article
  • Open Access
1 Citations
2,849 Views
23 Pages

In this work, nonadiabatic exchange-correlation (XC) potentials for time-dependent density-functional theory (TDDFT) for strongly correlated materials are derived in the limits of strong and weak correlations. After summarizing some essentials of the...

  • Article
  • Open Access
1 Citations
3,128 Views
12 Pages

A Mathematical and Numerical Framework for Traffic-Induced Air Pollution Simulation in Bamako

  • Abdoulaye Samaké,
  • Amadou Mahamane,
  • Mahamadou Alassane and
  • Ouaténi Diallo

We present a mathematical and numerical framework for the simulation of traffic-induced air pollution in Bamako. We consider a deterministic modeling approach where the spatio-temporal dynamics of the concentrations of air pollutants are governed by...

  • Article
  • Open Access
3 Citations
4,345 Views
28 Pages

Nowadays, the Oil and Gas (O&G) industry faces significant challenges due to the relentless pressure for rationalization of project expenditure and cost reduction, the demand for greener and renewable energy solutions and the recent outbreak of t...

  • Article
  • Open Access
13 Citations
4,849 Views
13 Pages

Regression Machine Learning Models Used to Predict DFT-Computed NMR Parameters of Zeolites

  • Robin Gaumard,
  • Dominik Dragún,
  • Jesús N. Pedroza-Montero,
  • Bruno Alonso,
  • Hazar Guesmi,
  • Irina Malkin Ondík and
  • Tzonka Mineva

Machine learning approaches can drastically decrease the computational time for the predictions of spectroscopic properties in materials, while preserving the quality of the computational approaches. We studied the performance of kernel-ridge regress...

  • Article
  • Open Access
2 Citations
3,390 Views
12 Pages

In this study, we theoretically investigate the structural, electronic and magnetic properties of the Cu2OX2 (X = Cl, Br, I) compounds. Previous studies reported potential spin-driven ferroelectricity in Cu2OCl2, originating from a non-collinear magn...

  • Article
  • Open Access
1 Citations
2,490 Views
18 Pages

In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great...

  • Article
  • Open Access
2,946 Views
31 Pages

Dependence in meta-analytic models can happen due to the same collected data or from the same researchers. The hierarchical Bayesian linear model in a meta-analysis that allows dependence in effect sizes is investigated in this paper. The interested...

  • Article
  • Open Access
9 Citations
4,408 Views
11 Pages

The electronic structure of coordination compounds with lanthanide ions is studied by means of density functional theory (DFT) calculations. This work deals with the electronic structure and properties of open-shell systems based on the calculation o...

  • Article
  • Open Access
7 Citations
4,400 Views
16 Pages

Despite the progress of therapeutic approaches for treating COVID-19 infection, the interest in developing effective antiviral agents is still high, due to the possibility of the insurgence of viable SARS-CoV-2-resistant strains. Accordingly, in this...

  • Communication
  • Open Access
19 Citations
4,592 Views
9 Pages

To better understand graphene and its interactions with polycyclic aromatic hydrocarbons (PAHs), density-functional-theory (DFT) computations were used. Adsorption energy is likely to rise with the number of aromatic rings in the adsorbates. The DFT...

  • Article
  • Open Access
5 Citations
2,847 Views
15 Pages

A Stochastic Model for Determining Static Stability Margins in Electric Power Systems

  • Yuri Bulatov,
  • Andrey Kryukov,
  • Vladislav Senko,
  • Konstantin Suslov and
  • Denis Sidorov

This paper aims to develop a method for determining margins of static aperiodic stability for electric power systems equipped with distributed generation plants. To this end, we used generalized equations of limiting modes in a stochastic formulation...

  • Article
  • Open Access
2 Citations
2,898 Views
16 Pages

The research refers to the modeling of the meaningful and relatively stable visual-figurative and verbal-sign representation of real problems in medical diagnostics of the human organs and systems. The core results of the research are presented. Here...

  • Article
  • Open Access
7 Citations
4,172 Views
13 Pages

Generation of Basis Sets for Accurate Molecular Calculations: Application to Helium Atom and Dimer

  • Ignacio Ema,
  • Guillermo Ramírez,
  • Rafael López and
  • José Manuel García de la Vega

A new approach for basis set generation is reported and tested in helium atom and dimer. The basis sets thus computed, named sigma, range from DZ to 5Z and consist of the same composition as Dunning basis sets but with a different treatment of contra...

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Computation - ISSN 2079-3197