Spin-state splittings, highest-occupied-molecular-orbital and lowest-unoccupied-molecular-orbital energies, and chemical hardness

Disruption of DYRK1A-induced hyperphosphorylation of amyloid-beta and tau protein in Alzheimer's disease: An integrative molecular modeling approach

Alzheimer's disease (AD) is a neurological disorder caused by the abnormal accumulation of hyperphosphorylated proteins. Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dual phosphorylation enzyme which phosphorylates the amyloid-β (Aβ) and neurofibrillary tangles (NFTs). A high throughput virtual screening approach was applied to screen a library of 98,071 compounds against DYRK1A using different programs including AutoDock Vina, Smina, and idock. Based on the binding affinities, we selected 330 compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Various pharmacokinetics parameters were predicted using the admetSAR server, and based on the pharmacokinetics results, 14 compounds were selected for cross-docking analysis using AutoDock. Cross-docking analysis revealed four compounds, namely, ZINC3843365 (-11.07 kcal/mol^-1), ZINC2123081 (-10.93 kcal/mol^-1), ZINC5220992 (-10.63 kcal/mol^-1), and ZINC68569602 (-10.35 kcal/mol^-1), which had the highest negative affinity scores compared to the 10 other molecules analyzed. Density functional theory (DFT) analysis was conducted for all the four top-ranked compounds. The molecular interaction stability of these four compounds with DYRK1A has been evaluated using molecular dynamics (MD) simulations on 100 nanoseconds followed by principal component analysis (PCA) and binding free energy calculations. The Gibbs free energy landscape analysis suggested the metastable state and folding pattern of selected docking complexes. Based on the present study outcome, we propose four antagonists, viz., ZINC3843365, ZINC2123081, ZINC5220992, and ZINC68569602 as potential inhibitors against DYRK1A and to reduce the amyloid-β and neurofibrillary tangle burden. These screened molecules can be further investigated using a number of in vitro and in vivo experiments.

Computer-aided identification of lead compounds as Staphylococcal epidermidis FtsZ inhibitors using molecular docking, virtual screening, DFT analysis, and molecular dynamic simulation

In an effort to face the multiple drug-resistant bacteria, various approaches have been discovered to design potent compounds and search new targets through computational design tools. With an aim to identify selective inhibitors against filamentous temperature-sensitive mutant Z (FtsZ), a library of Phase database compounds have been virtually screened. High-throughput virtual screening of compounds against Staphylococcal epidermidis FtsZ protein (4M8I) was performed using three sequential docking modes like high-throughput virtual screening, Glide standard precision, followed by Glide extra precision. Four top-ranked compounds were selected from molecular mechanics-generalized Born surface area (MM-GBSA) binding energy with better predicted free binding energies of - 89.309, - 54.382, - 53.667, and - 52.133 kcal/mol, respectively. It is also showed that the contribution of van der Waals and electrostatic solvation energy terms are playing a major part to make the hit molecule (T6288784) binding to S. epidermidis FtsZ protein. The result of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) and energy gap analysis predicts the molecular reactivity and stability of hit molecules. Subsequently, Lipinski's rule of five and properties of absorption, distribution, metabolism, and excretion (ADME) were to calculate their bioavailability. The average binding energy - 9.67 kcal/mol of the best proposed hit molecule (T6288784) was found with half-maximal inhibitory concentration (IC50) value to be 75.53 nM. A 15-ns molecular dynamics simulation study revealed the stable conformation of hit molecule. On a wide-range research discipline, in silico studies of our proposed compound confirm promising results and can be successfully used towards the development of novel FtsZ inhibitor with better binding affinity. Graphical Abstract.

Does the ionization potential condition employed in QTP functionals mitigate the self-interaction error?

Though contrary to conventional wisdom, the interpretation of all occupied Kohn-Sham eigenvalues as vertical ionization potentials is justified by several formal and numerical arguments. Similarly, the performance of density functional approximations (DFAs) for fractionally charged systems has been extensively studied as a measure of one- and many-electron self-interaction errors (MSIEs). These complementary perspectives (initially recognized in ab initio dft) are shown to lead to the unifying concept that satisfying Bartlett's IP theorem in DFA's mitigates self-interaction errors. In this contribution, we show that the IP-optimized QTP functionals (reparameterization of CAM-B3LYP where all eigenvalues are approximately equal to vertical IPs) display reduced self-interaction errors in a variety of tests including the He₂⁺ potential curve. Conversely, the MSIE-optimized rCAM-B3LYP functional also displays accurate orbital eigenvalues. It is shown that the CAM-QTP and rCAM-B3LYP functionals show improved dissociation limits, fundamental gaps and thermochemical accuracy compared to their parent functional CAM-B3LYP.