Integration of Methods in Cheminformatics and Biocalorimetry for the Design of Trypanosomatid Enzyme Inhibitors

Prokopczyk, Igor Muccilo; Ribeiro, Jean Francisco Rosa; Sartori, G.; Sesti-Costa, Renata; Silva, João; Freitas, Renato Ferreira de; Leitão, Andrei; Montanari, Carlos Alberto

doi:10.4155/fmc.13.185

Cited by 12 publications

(5 citation statements)

References 43 publications

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“…Current methods in our group involve the use of ligandand target-based molecular design aimed at identifying Cz inhibitors, which are also T. cruzi killers: As is evident from the discussion above, the one activity does not automatically predicate the other (Avelar et al, 2015;Prokopczyk et al, 2014;Wiggers et al, 2007Wiggers et al, , 2013Wiggers, Rocha, Cheleski, & Montanari, 2011). To date, little systematic literature data mining on cysteine protease inhibitors have been carried out that would be of utility in bridging the two chemical spaces (CS).…”

Section: In Silico Machine Learning Studiesmentioning

confidence: 99%

Molecular design aided by random forests and synthesis of potent trypanocidal agents as cruzain inhibitors for Chagas disease treatment

et al. 2020

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Cruzain is an established target for the identification of novel trypanocidal agents, but how good are in vitro/in vivo correlations? This work describes the development of a random forests model for the prediction of the bioavailability of cruzain inhibitors that are Trypanosoma cruzi killers. Some common properties that characterize druglikeness are poorly represented in many established cruzain inhibitors. This correlates with the evidence that many high-affinity cruzain inhibitors are not trypanocidal agents against T. cruzi. On the other hand, T. cruzi killers that present typical druglike characteristics are likely to show better trypanocidal action than those without such features. The random forests model was not outperformed by other machine learning methods (such as artificial neural networks and support vector machines), and it was validated with the synthesis of two new trypanocidal agents. Specifically, we report a new lead compound, Neq0565, which was tested on T. cruzi Tulahuen (β-galactosidase) with a pEC 50 of 4.9. It is inactive in the host cell line showing a selectivity index (SI = EC 50 cyto /EC 50 T. cruzi

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Section: In Silico Machine Learning Studiesmentioning

confidence: 99%

Molecular design aided by random forests and synthesis of potent trypanocidal agents as cruzain inhibitors for Chagas disease treatment

et al. 2020

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“…The ff12SB force field 35 was used for the protein, general AMBER force field (GAFF) 36 force field parameters were used for HEPES, and force field parameters for the phosphotyrosine (PTY) residue were taken from the set determined by Steinbrecher et al, 37,38 as available in the AMBER frcmod.phosaa10 file. The cyclized phosphotyrosine (CPY) parameters were the same as PTY with the exception of the cyclopropyl moiety, which used the GAFF parameters for sp 3 carbons in triangle systems (cx). Partial charges for both the HEPES molecules and the modified phosphotyrosine residues were determined using the restrained electrostatic potential (RESP) method, as available through the R.E.D.…”

Section: B Molecular Dynamics Simulationsmentioning

confidence: 99%

“…Calorimetric studies of protein-small molecule interactions decompose the standard free energy of binding into the binding enthalpy and entropy-the so-called thermodynamic signature of binding. [1][2][3][4] These components of the free energy may provide insight into the forces driving binding. [5][6][7] It has also been argued that one should aim to design ligands whose binding is enthalpy-driven, as these may be better drugs than ones whose binding is entropy-driven.…”

Section: Introductionmentioning

confidence: 99%

Protein-ligand binding enthalpies from near-millisecond simulations: Analysis of a preorganization paradox

Gilson

2018

The Journal of Chemical Physics

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Calorimetric studies of protein-ligand binding sometimes yield thermodynamic data that are difficult to understand. Today, molecular simulations can be used to seek insight into such calorimetric puzzles, and, when simulations and experiments diverge, the results can usefully motivate further improvements in computational methods. Here, we apply near-millisecond duration simulations to estimate the relative binding enthalpies of four peptidic ligands with the Grb2 SH2 domain. The ligands fall into matched pairs, where one member of each pair has an added bond that preorganizes the ligand for binding and thus may be expected to favor binding entropically, due to a smaller loss in configurational entropy. Calorimetric studies have shown that the constrained ligands do in fact bind the SH2 domain more tightly than the flexible ones, but, paradoxically, the improvement in affinity for the constrained ligands is enthalpic, rather than entropic. The present enthalpy calculations yield the opposite trend, as they suggest that the flexible ligands bind more exothermically. Additionally, the small relative binding enthalpies are found to be balances of large differences in the energies of structural components such as ligand and the binding site residues. As a consequence, the deviations from experiment in the relative binding enthalpies represent small differences between these large numbers and hence may be particularly susceptible to error, due, for example, to approximations in the force field. We also computed first-order estimates of changes in configurational entropy on binding. These too are, arguably, paradoxical, as they tend to favor binding of the flexible ligands. The paradox is explained in part by the fact that the more rigid constrained ligands reduce the entropy of binding site residues more than their flexible analogs do, at least in the simulations. This result offers a rather general counterargument to the expectation that preorganized ligands should be associated with more favorable binding entropies, other things being equal.

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“…Many published studies assume that the drug produces free radicals to which TC is particularly sensitive [7], but some of the proposed mechanisms of action have been challenged [8]. The inhibition of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) from TC (TC glyceraldehyde-3-phosphate dehydrogenase [TcGAPDH]), on the other hand, was also proposed as an explanation for the trypanocidal effect of drugs [9][10][11]. This enzyme is responsible, in the glycolytic pathway of the parasite, for the conversion of glyceraldehyde-3-phosphate into 1,3-bisphosphoglycerate in the presence of nicotinamide-adeninedinucleotide (NAD) + inorganic phosphate [12,13].…”

Section: Introductionmentioning

confidence: 99%

Molecular Fractionation With Conjugate Caps Study of the Interaction of the Anacardic Acid With the Active Site of Trypanosoma Cruzi Gapdh Enzyme: A Quantum Investigation

Marinho

Santos

Bezerra

et al. 2019

Asian J Pharm Clin Res

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Objective: The objective of this study was to use the molecular fractionation with conjugate caps (MFCC) method to elucidate the possible interaction mechanism of anacardic acid (AA) with the saturated alkyl chain (AA0) in the Trypanosoma cruzi glyceraldehyde-3-phosphate dehydrogenase (TcGAPHD) enzyme. Methods: Initially, the geometry optimization of the AA three-dimensional structure (with the pentadecyl chain) was performed using density functional theory (B3LYP) calculations. With the AA0 optimization data, it was possible to plot the molecular electrostatic potential (MESP) surface. Molecular docking simulation was performed using automated coupling with the AutoDock Vina program. The best-fit conformation in the docking simulation of AA0 is the binding site used for the construction of the TcGAPHD-AA0 complex. Interaction energies between the AA0 molecule and the amino acid residues of the TcGAPHD enzyme were estimated using the MFCC strategy. Results: To obtain more reliable quantitative information on the interaction of AA with the active site of the TcGAPHD enzyme, the fragmentation method was combined with conjugated layers (MFCC) and molecular docking. It can be observed that the AA0 molecule occupies a region near the active site of the chalepin molecule in the TcGAPHD enzyme, and the Ile13 residue has the strongest binding energy of approximately 25 kcal/mol with AA0, through a strong Van der Waals interaction. Conclusion: The paper presents an improved quantitative analysis approach for assessing the contribution of individual amino acids to the free energy of interaction between AA and TcGAPHD. Specifically, the paper illustrates the advantageous approach of combining molecular docking with the MFCC method.

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Integration of Methods in Cheminformatics and Biocalorimetry for the Design of Trypanosomatid Enzyme Inhibitors

Cited by 12 publications

References 43 publications

Molecular design aided by random forests and synthesis of potent trypanocidal agents as cruzain inhibitors for Chagas disease treatment

Molecular design aided by random forests and synthesis of potent trypanocidal agents as cruzain inhibitors for Chagas disease treatment

Protein-ligand binding enthalpies from near-millisecond simulations: Analysis of a preorganization paradox

Molecular Fractionation With Conjugate Caps Study of the Interaction of the Anacardic Acid With the Active Site of Trypanosoma Cruzi Gapdh Enzyme: A Quantum Investigation

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