Computational prediction of the pKas of small peptides through Conceptual DFT descriptors

Frau, Juan; Hernández-Haro, Noemí; Glossman‐Mitnik, Daniel

doi:10.1016/j.cplett.2017.01.038

Cited by 36 publications

(40 citation statements)

References 33 publications

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“…The previous discussion focused on the application of the conceptual DFT descriptors to evaluate the computation prediction of the pKas peptides where it was established that the pKa = 16.3088-0.868 η relationship would play an important role in the initial prediction of complex peptides, which are important in the manufacture of medical drugs [31]. Given the biological level of pH, the peptides under study exist as neutral molecules and are still considered to be neutral during the pKa computations [31]. The pKa relationship is also important in the optimization of the molecular structure of every conformer as well as the computation of the pKa values for all molecules given the η values shown in Table 2.…”

Section: Calculation Of the Pka Of The Clavanins A-e Peptidesmentioning

confidence: 99%

Conceptual DFT as a Helpful Chemoinformatics Tool for the Study of the Clavanin Family of Antimicrobial Marine Peptides

Flores-Holgúın¹,

Frau²,

Glossman‐Mitnik³

2021

Density Functional Theory Calculations

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A well-behaved model chemistry previously validated for the study of the chemical reactivity of peptides was considered for the calculation of the molecular properties and structures of the clavanin family of antimicrobial marine peptides. A methodology based on conceptual density functional theory (CDFT) was chosen for the determination of the reactivity descriptors. The molecular active sites were associated with the active regions of the molecules related to the nucleophilic and electrophilic Fukui functions. Finally, the drug-likenesses and the bioactivity scores for the clavanin peptides were predicted through a homology methodology relating them with the calculated reactivity descriptors, while other properties like the pKas were determined following a methodology developed by our group.

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Section: Calculation Of the Pka Of The Clavanins A-e Peptidesmentioning

confidence: 99%

Conceptual DFT as a Helpful Chemoinformatics Tool for the Study of the Clavanin Family of Antimicrobial Marine Peptides

Flores-Holgúın¹,

Frau²,

Glossman‐Mitnik³

2021

Density Functional Theory Calculations

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“…We have recently presented a study of the computational prediction of the pKas of small peptides through Conceptual DFT descriptors [13]. In that work, we concluded that the relationship pKa = 16.3088 -0.8268η could be a valuable starting point for the prediction of the pKa of larger peptides of interest for the development of AGE inhibitors.…”

Section: Determination Of Pka Value Of the Peptidementioning

confidence: 99%

“…Thus, the objective of this work is to study the chemical reactivity of the Leu-Enkephalin opioid peptide neurotransmitter using the techniques of the Conceptual DFT, determining its global properties (of the molecule as a whole) as well as the local properties that allow to understand and predict active reaction sites, both electrophilic and nucleophilic by considering the recent methodology proposed by us [5]- [12]. Likewise, the pKa value of the peptide will be predicted based on a methodology previously developed by us [13], the ability of this potentially therapeutic peptide to act as inhibitor of the formation of Advanced Glycation Endproducts (AGEs) will be established according to our previous ideas [14], and the descriptors of bioavailability and bioactivity (Bioactivity Scores) will be calculated through different procedures described in the literature. Thus, The knowledge of the values of the global and local descriptors of the molecular reac-tivity of the Leu-Enkephalin peptide studied could be useful in the development of new drugs based on this compound or some analogs.…”

Section: Introductionmentioning

confidence: 99%

Conceptual Density Functional Theory Study of the Chemical Reactivity Properties and Bioactivity Scores of the Leu-Enkephalin Opioid Peptide Neurotransmitter

Frau¹,

Flores-Holgúın²,

Glossman‐Mitnik³

2019

CMB

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The SMD solvation model (Solvation Model based on the Density) and eight density functionals, CAM-B3LYP, LC-ωPBE, M11, MN12SX, N12SX, ωB97, ωB97X, and ωB97XD, were assessed in link with the Def2TZVP basis set for the calculation of the structure of the Leu-Enkephalin Opioid Peptide Neurotransmitter as well as their molecular properties. Through the Conceptual Density Functional Theory (CDFT), the entire chemical descriptors for the system were calculated. The active regions of the molecules necessary for electrophilic, nucleophilic and radical attacks were chosen through linking them with the corresponding Fukui functions. Furthermore, the prediction of the pKa value for the peptide is done with great accuracy as well as the ability of the studied molecule in acting as an efficient inhibitor of the formation of Advanced Glycation Endproducts (AGEs), which comprises of a useful knowledge for the development of drugs for preventing Alzheimer, Diabetes and Parkinson diseases. Lastly, the bioactivity scores for the studied peptides are predicted via various methodologies.

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“…Applications of FFs to large/biological systems, in addition to small organic systems, can also be found in the literature. Studies have been conducted for purposes such as the determination of protonation states, the evaluation of interactions between residues and ligands as predicted by docking score functions, and the regioselectivity of enzymatic reactions . These descriptors have also been used as visual aid to study enzymatic reactions, as presented by Roos and coworkers in their study of the reaction between electrophilic arsenates/phosphates and nucleophilic thiolate/methanolate catalyzed by the arsenate reductase enzyme …”

Section: Introductionmentioning

confidence: 99%

Semiempirical methods do Fukui functions: Unlocking a modeling framework for biosystems

et al. 2020

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Obtaining reactivity information from the molecular electronic structure of a chemical system is a computationally intensive process. As a way of probing reactivity information around that, there exist electron density response variables, such as the Fukui functions (FFs), which are well‐established descriptors that summarize the local susceptibility to react. These properties only require few single‐point quantum chemical calculations, but even then, the intrinsic high cost and unfavorable computational complexity with respect to the number of atoms in the system makes this approach available only to small fragments and systems. In this study, we explore the computation of FFs, showing that semiempirical quantum chemical methods can be used to obtain the reactivity information equivalent to that of a Density Functional Theory (DFT) functional, for the eight entire polypeptide chains. The combination of semiempirical methods with the frozen orbital approximation allows for the obtention of these reactivity descriptors for biological systems with reasonable accuracy and speed, unlocking the utilization of these methods for such systems. These results for the frozen orbital approximation can be additionally improved when other molecular orbitals from the frontier band are employed in the computation. We also show the potential of this computational protocol in the ligand–protein complexes of HIV‐1 protease, predicting which of those ligands are active inhibitors.

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Computational prediction of the pKas of small peptides through Conceptual DFT descriptors

Cited by 36 publications

References 33 publications

Conceptual DFT as a Helpful Chemoinformatics Tool for the Study of the Clavanin Family of Antimicrobial Marine Peptides

Conceptual DFT as a Helpful Chemoinformatics Tool for the Study of the Clavanin Family of Antimicrobial Marine Peptides

Conceptual Density Functional Theory Study of the Chemical Reactivity Properties and Bioactivity Scores of the Leu-Enkephalin Opioid Peptide Neurotransmitter

Semiempirical methods do Fukui functions: Unlocking a modeling framework for biosystems

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