Exploration of the forbidden regions of the Ramachandran plot (ϕ-ψ) with QTAIM

Momen, Roya; Azizi, Alireza; Wang, Lingling; Yang, Ping; Xu, Ting; Kirk, Steven R.; Li, Wenxuan; Manzhos, Sergei; Jenkins, Samantha

doi:10.1039/c7cp05124g

Cited by 15 publications

(6 citation statements)

References 40 publications

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“…This promises better-than-force field accuracy as well as access to some electronic properties including electron density itself, which allow performing analyses which are in principle impossible with force fields. 21,22 Linear-scaling KS-DFT approaches have been proposed [23][24][25] but remain costly (large prefactors) and introduce additional approximations. OF-DFT inherently can have near-linear scaling, but not all KEF models are linear-scaling.…”

Section: Introductionmentioning

confidence: 99%

Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

Manzhos

Golub

2020

The Journal of Chemical Physics

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We study the dependence of kinetic energy densities (KED) on density-dependent variables that have been suggested in previous works on kinetic energy functionals (KEF) for orbitalfree DFT (OF-DFT). We focus on the role of data distribution and on data and regressor selection. We compare unweighted and weighted linear and Gaussian process regressions of KED for light metals and a semiconductor. We find that good quality linear regression resulting in good energy-volume dependence is possible over density-dependent variables suggested in previous literature. This is achieved with weighted fitting based on KED histogram. With Gaussian process regressions, excellent KED fit quality well exceeding that of linear regressions is obtained as well as a good energy-volume dependence which was somewhat better than that of best linear regressions. We find that while the use of the effective potential as a descriptor improves linear KED fitting, it does not improve the quality of the energy-volume dependence with linear regressions but substantially improves it with Gaussian process regression. Gaussian process regression is also able to perform well without data weighting.

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Section: Introductionmentioning

confidence: 99%

Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

Manzhos

Golub

2020

The Journal of Chemical Physics

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“…Figure E shows that the 3D molecular structures of P361, P362, P371, and P372 were modeled via the I-TASSER server, and the LeuA-P domain and the lysin domain are colored red and green, respectively. The Ramachandran plot analysis (Figure S4) showed that more than 90% of the φ and ψ dihedral angles of the 3D models of the four new chimeric lysins were distributed in the allowable area and proved that the structures of molecular modeling were accurate . It can be seen from Figure F that P362, P371, and P372 retained the α-helical amphiphilic cationic peptide structure of LeuA-P, while the LeuA-P structure of P361 was changed and its helical structure was shifted to the N-terminal.…”

Section: Resultsmentioning

confidence: 95%

“…The constructed structural models were analyzed by PyMol software. For model stability studies, the three-dimensional (3D) PDB models were subjected to evaluation by Ramachandran plot analysis (Discovery Studio 4.5) . Based on the CAMP data set, SVM, random forest, and discriminant analysis algorithms were used to determine the possibility that the C-terminal α-helical peptide chain of the chimeric lysin is an antimicrobial peptide .…”

Section: Materials and Methodsmentioning

confidence: 99%

“…For model stability studies, the threedimensional (3D) PDB models were subjected to evaluation by Ramachandran plot analysis (Discovery Studio 4.5). 22 Based on the CAMP data set, SVM, random forest, and discriminant analysis algorithms were used to determine the possibility that the C-terminal α-helical peptide chain of the chimeric lysin is an antimicrobial peptide. 20 The secondary structure of the C-terminal peptide chains was analyzed using the parameters of the 3D model of chimeric lysins.…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

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In Silico Development of Novel Chimeric Lysins with Highly Specific Inhibition against Salmonella by Computer-Aided Design

Meng

Zhou

Lü

et al. 2021

J. Agric. Food Chem.

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Four novel chimeric lysins (P361, P362, P371, and P372), which were the fusion of Salmonella phage lysins and novel antimicrobial peptide LeuA-P, were obtained using bioinformatics analysis and in silico design. The recombinant chimeric lysins were expressed in E. coli BL21(DE3) strain and showed highly specific inhibition against Salmonella. The minimal inhibitory concentrations (MICs) of P362 and P372 to S. typhi CMCC 50071 were 8 and 16 μg/mL, respectively. Both 1 × MIC P362 and P372 could increase the outer membrane permeability and cleave the cell wall peptidoglycan, causing the leakage of intracellular nucleic acids and proteins and ultimately killing Salmonella efficiently without drug resistance. The combination of P362, P372, and potassium sorbate reduced more than 3 log CFU/g counts of microorganisms in contaminated chilled chicken and extended the shelf life by 7 days. The strategy of antimicrobial peptide (AMP)−lysin chimera inspired the inability of phage lysin to specifically inhibit Gram-negative bacteria with dense outer membranes in vitro.

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“…As it is clear from the PROCHECK statistics of Ramachandran Plot (Table 1), a good quality model is expected to have over 90% in the most favoured regions [A, B, L] and the observed statistics show that the model has 92% residues in the favoured region possessing 303 residues out of 386 in favoured region. Therefore, on validating through statistics of Ramachandran plot (Figure 2) this model can be used as best model and used as target in docking studies [42]. End-residues (excl.…”

Section: Results and Discussion 31 In Silico Validation By Targeting Hbcatc In The Neuropathic Pains 311 Homology Modelingmentioning

confidence: 99%

In-Silico Validation and Fabrication of Matrix Diffusion-Based Polymeric Transdermal Patches for Repurposing Gabapentin Hydrochloride in Neuropathic Pain

Singh

Agarwal

Pancham

et al. 2021

CNSNDDT

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Background: Gabapentin (GBP) is an FDA approved drug for the treatment of partial and secondary generalized seizures, apart from being used for diabetic neuropathic pain. GBP displays highly intricate mechanism of action and its inhibitory response in elevated antagonism of NMDA (N-methyl-D-aspartate receptor) receptor and thus, can be repurposed for controlling neuropathic pain. Objective: Therefore, in the present study, we have selected hBCATc (human Pyridoxal 5’-phosphate dependent branched-chain aminotransferase cytosolic) gene that is highly expressed in neuropathic stressed conditions. Thereafter, have analyzed the GBP as its competitive inhibitor by homology modeling, molecular docking, also predicting its structural alerts and pharmacokinetic suitability through ADMET. However, GBP was found to be a potential drug in controlling neuropathic pain, still it has certain critical pharmacokinetics limitations therefore, the need for its targeted delivery was required and the same was attained by designing a GBP loaded trandermal patch (TDP). Methods: A suitable and equally efficacious GBP – TDP was developed by solvent evaporation method using PVP and HPMC in ratio of 2:1 as a polymer base for reservoir type of TDP. Also, PEG 400 was used as a plasticizer and PVA (4%) was taken for backing membrane preparation and then the optimized GBP-TDP was subjected for physical characterization, optimization and ex vivo release kinetics. Methods: A suitable and equally efficacious GBP – TDP was developed by solvent evaporation method using PVP and HPMC in ratio of 2:1 as a polymer base for reservoir type of TDP. Also, PEG 400 was used as a plasticizer and PVA (4%) was taken for backing membrane preparation and then the optimized GBP-TDP was subjected for physical characterization, optimization and ex vivo release kinetics. Results and conclusion: The results showed desired specifications with uneven and flaky surface appearance giving an avenue for controlled release of the drugs with 92.34 ± 1.43% of drug release in 10 h, further suggesting that GBP-TDP can be used as an effective tool against diabetic neuropathy pain.

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Exploration of the forbidden regions of the Ramachandran plot (ϕ-ψ) with QTAIM

Cited by 15 publications

References 40 publications

Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

In Silico Development of Novel Chimeric Lysins with Highly Specific Inhibition against Salmonella by Computer-Aided Design

In-Silico Validation and Fabrication of Matrix Diffusion-Based Polymeric Transdermal Patches for Repurposing Gabapentin Hydrochloride in Neuropathic Pain

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