Molecules

2021

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16 pages, 5696 KiB

Open AccessArticle

Tentative Peptide‒Lipid Bilayer Models Elucidating Molecular Behaviors and Interactions Driving Passive Cellular Uptake of Collagen-Derived Small Peptides

by Pathomwat Wongrattanakamon, Wipawadee Yooin, Busaban Sirithunyalug, Piyarat Nimmanpipug and Supat Jiranusornkul

Molecules 2021, 26(3), 710; https://doi.org/10.3390/molecules26030710 - 29 Jan 2021

Cited by 4 | Viewed by 2748

Abstract

Collagen contains hydroxyproline (Hyp), which is a unique amino acid. Three collagen-derived small peptides (Gly-Pro-Hyp, Pro-Hyp, and Gly-Hyp) interacting across a lipid bilayer (POPC model membrane) for cellular uptakes of these collagen-derived small peptides were studied using accelerated molecular dynamics simulation. The ligands [...] Read more.

Collagen contains hydroxyproline (Hyp), which is a unique amino acid. Three collagen-derived small peptides (Gly-Pro-Hyp, Pro-Hyp, and Gly-Hyp) interacting across a lipid bilayer (POPC model membrane) for cellular uptakes of these collagen-derived small peptides were studied using accelerated molecular dynamics simulation. The ligands were investigated for their binding modes, hydrogen bonds in each coordinate frame, and mean square displacement (MSD) in the Z direction. The lipid bilayers were evaluated for mass and electron density profiles of the lipid molecules, surface area of the head groups, and root mean square deviation (RMSD). The simulation results show that hydrogen bonding between the small collagen peptides and plasma membrane plays a significant role in their internalization. The translocation of the small collagen peptides across the cell membranes was shown. Pro-Hyp laterally condensed the membrane, resulting in an increase in the bilayer thickness and rigidity. Perception regarding molecular behaviors of collagen-derived peptides within the cell membrane, including their interactions, provides the novel design of specific bioactive collagen peptides for their applications. Full article

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2020

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16 pages, 4672 KiB

Open AccessArticle

l-Malate (−2) Protonation State is Required for Efficient Decarboxylation to l-Lactate by the Malolactic Enzyme of Oenococcus oeni

by Waldo Acevedo, Pablo Cañón, Felipe Gómez-Alvear, Jaime Huerta, Daniel Aguayo and Eduardo Agosin

Molecules 2020, 25(15), 3431; https://doi.org/10.3390/molecules25153431 - 28 Jul 2020

Cited by 7 | Viewed by 3966

Abstract

Malolactic fermentation (MLF) is responsible for the decarboxylation of l-malic into lactic acid in most red wines and some white wines. It reduces the acidity of wine, improves flavor complexity and microbiological stability. Despite its industrial interest, the MLF mechanism is not [...] Read more.

Malolactic fermentation (MLF) is responsible for the decarboxylation of l-malic into lactic acid in most red wines and some white wines. It reduces the acidity of wine, improves flavor complexity and microbiological stability. Despite its industrial interest, the MLF mechanism is not fully understood. The objective of this study was to provide new insights into the role of pH on the binding of malic acid to the malolactic enzyme (MLE) of Oenococcus oeni. To this end, sequence similarity networks and phylogenetic analysis were used to generate an MLE homology model, which was further refined by molecular dynamics simulations. The resulting model, together with quantum polarized ligand docking (QPLD), was used to describe the MLE binding pocket and pose of l-malic acid (MAL) and its l-malate (−1) and (−2) protonation states (MAL⁻ and MAL²⁻, respectively). MAL²⁻ has the lowest ∆G_binding, followed by MAL⁻ and MAL, with values of −23.8, −19.6, and −14.6 kJ/mol, respectively, consistent with those obtained by isothermal calorimetry thermodynamic (ITC) assays. Furthermore, molecular dynamics and MM/GBSA results suggest that only MAL²⁻ displays an extended open conformation at the binding pocket, satisfying the geometrical requirements for Mn²⁺ coordination, a critical component of MLE activity. These results are consistent with the intracellular pH conditions of O. oeni cells—ranging from pH 5.8 to 6.1—where the enzymatic decarboxylation of malate occurs. Full article

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16 pages, 1806 KiB

Open AccessReview

How ‘Protein-Docking’ Translates into the New Emerging Field of Docking Small Molecules to Nucleic Acids?

by Francesca Tessaro and Leonardo Scapozza

Molecules 2020, 25(12), 2749; https://doi.org/10.3390/molecules25122749 - 13 Jun 2020

Cited by 22 | Viewed by 5721

Abstract

In this review, we retraced the ‘40-year evolution’ of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called ‘rigid-docking’ searching methods to the more sophisticated ‘semi-flexible’ and ‘flexible docking’ algorithms. Together with the advancement of [...] Read more.

In this review, we retraced the ‘40-year evolution’ of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called ‘rigid-docking’ searching methods to the more sophisticated ‘semi-flexible’ and ‘flexible docking’ algorithms. Together with the advancement of computing architecture and power, molecular docking’s applications also exponentially increased, from a single-ligand binding calculation to large screening and polypharmacology profiles. Recently targeting nucleic acids with small molecules has emerged as a valuable therapeutic strategy especially for cancer treatment, along with bacterial and viral infections. For example, therapeutic intervention at the mRNA level allows to overcome the problematic of undruggable proteins without modifying the genome. Despite the promising therapeutic potential of nucleic acids, molecular docking programs have been optimized mostly for proteins. Here, we have analyzed literature data on nucleic acid to benchmark some of the widely used docking programs. Finally, the comparison between proteins and nucleic acid targets docking highlighted similarity and differences, which are intrinsically related to their chemical and structural nature. Full article

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2019

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19 pages, 2566 KiB

Open AccessArticle

Interactome Analysis and Docking Sites of MutS Homologs Reveal New Physiological Roles in Arabidopsis thaliana

by Mohamed Ragab AbdelGawwad, Aida Marić, Abdullah Ahmed Al-Ghamdi and Ashraf A. Hatamleh

Molecules 2019, 24(13), 2493; https://doi.org/10.3390/molecules24132493 - 8 Jul 2019

Cited by 4 | Viewed by 4017

Abstract

Due to their sedentary lifestyle, plants are constantly exposed to different stress stimuli. Stress comes in variety of forms where factors like radiation, free radicals, “replication errors, polymerase slippage”, and chemical mutagens result in genotoxic or cytotoxic damage. In order to face “the [...] Read more.

Due to their sedentary lifestyle, plants are constantly exposed to different stress stimuli. Stress comes in variety of forms where factors like radiation, free radicals, “replication errors, polymerase slippage”, and chemical mutagens result in genotoxic or cytotoxic damage. In order to face “the base oxidation or DNA replication stress”, plants have developed many sophisticated mechanisms. One of them is the DNA mismatch repair (MMR) pathway. The main part of the MMR is the MutS homologue (MSH) protein family. The genome of Arabidopsis thaliana encodes at least seven homologues of the MSH family: AtMSH1, AtMSH2, AtMSH3, AtMSH4, AtMSH5, AtMSH6, and AtMSH7. Despite their importance, the functions of AtMSH homologs have not been investigated. In this work, bioinformatics tools were used to obtain a better understanding of MSH-mediated DNA repair mechanisms in Arabidopsis thaliana and to understand the additional biological roles of AtMSH family members. In silico analysis, including phylogeny tracking, prediction of 3D structure, interactome analysis, and docking site prediction, suggested interactions with proteins were important for physiological development of A. thaliana. The MSH homologs extensively interacted with both TIL1 and TIL2 (DNA polymerase epsilon catalytic subunit), proteins involved in cell fate determination during plant embryogenesis and involved in flowering time repression. Additionally, interactions with the RECQ protein family (helicase enzymes) and proteins of nucleotide excision repair pathway were detected. Taken together, the results presented here confirm the important role of AtMSH proteins in mismatch repair and suggest important new physiological roles. Full article

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15 pages, 3542 KiB

Open AccessArticle

Investigation on the Enzymatic Profile of Mulberry Alkaloids by Enzymatic Study and Molecular Docking

by Zhihua Liu, Ying Yang, Wujun Dong, Quan Liu, Renyun Wang, Jianmei Pang, Xuejun Xia, Xiangyang Zhu, Shuainan Liu, Zhufang Shen, Zhiyan Xiao and Yuling Liu

Molecules 2019, 24(9), 1776; https://doi.org/10.3390/molecules24091776 - 8 May 2019

Cited by 39 | Viewed by 4698

Abstract

α-glucosidase inhibitors (AGIs) have been an important category of oral antidiabetic drugs being widely exploited for the effective management of type 2 diabetes mellitus. However, the marketed AGIs not only inhibited the disaccharidases, but also exhibited an excessive inhibitory effect on α-amylase, resulting [...] Read more.

α-glucosidase inhibitors (AGIs) have been an important category of oral antidiabetic drugs being widely exploited for the effective management of type 2 diabetes mellitus. However, the marketed AGIs not only inhibited the disaccharidases, but also exhibited an excessive inhibitory effect on α-amylase, resulting in undesirable gastrointestinal side effects. Compared to these agents, Ramulus Mori alkaloids (SZ-A), was a group of effective alkaloids from natural Morus alba L., and showed excellent hypoglycemic effect and fewer side effects in the Phase II/III clinical trials. Thus, this paper aims to investigate the selective inhibitory effect and mechanism of SZ-A and its major active ingredients (1-DNJ, FA and DAB) on different α-glucosidases (α-amylase and disaccharidases) by using a combination of kinetic analysis and molecular docking approaches. From the results, SZ-A displayed a strong inhibitory effect on maltase and sucrase with an IC₅₀ of 0.06 μg/mL and 0.03 μg/mL, respectively, which was similar to the positive control of acarbose with an IC₅₀ of 0.07 μg/mL and 0.68 μg/mL. With regard to α-amylase, SZ-A exhibited no inhibitory activity at 100 μg/mL, while acarbose showed an obvious inhibitory effect with an IC₅₀ of 1.74 μg/mL. The above analysis demonstrated that SZ-A could selectively inhibit disaccharidase to reduce hyperglycemia with a reversible competitive inhibition, which was primarily attributed to the three major active ingredients of SZ-A, especially 1-DNJ molecule. In the light of these findings, molecular docking study was utilized to analyze their inhibition mechanisms at molecular level. It pointed out that acarbose with a four-ring structure could perform desirable interactions with various α-glucosidases, while the three active ingredients of SZ-A, belonging to monocyclic compounds, had a high affinity to the active site of disaccharidases through forming a wide range of hydrogen bonds, whose affinity and consensus score with α-amylase was significantly lower than that of acarbose. Our study illustrates the selective inhibition mechanism of SZ-A on α-glucosidase for the first time, which is of great importance for the treatment of type 2 diabetes mellitus. Full article

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2017

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3283 KiB

Open AccessArticle

Synthesis of New Hydrazone Derivatives for MAO Enzymes Inhibitory Activity

by Nafiz Öncü Can, Derya Osmaniye, Serkan Levent, Begüm Nurpelin Sağlık, Beril İnci, Sinem Ilgın, Yusuf Özkay and Zafer Asım Kaplancıklı

Molecules 2017, 22(8), 1381; https://doi.org/10.3390/molecules22081381 - 20 Aug 2017

Cited by 51 | Viewed by 8742

Abstract

In the present work, 14 new 1-substituted-2-phenylhydrazone derivatives were synthesized to evaluate their inhibitory activity against hMAO enzymes. The structures of the newly synthesized hydrazones 2a–2n were characterized by IR, 1H-NMR, 13C-NMR, HR-MS spectroscopic methods. The inhibitory activity of compounds 2a–2n against hMAO-A [...] Read more.

In the present work, 14 new 1-substituted-2-phenylhydrazone derivatives were synthesized to evaluate their inhibitory activity against hMAO enzymes. The structures of the newly synthesized hydrazones 2a–2n were characterized by IR, 1H-NMR, 13C-NMR, HR-MS spectroscopic methods. The inhibitory activity of compounds 2a–2n against hMAO-A and hMAO-B enzymes was elucidated by using an in-vitro Amplex Red® reagent assay based on fluorometric methods. According to the activity studies, 2a and 2b were found to be the most active compounds against hMAO-A enzyme, with IC50 values of 0.342 µM and 0.028 µM, respectively. The most active compounds 2a–2b were evaluated by means of enzyme kinetics and docking studies. Moreover, these compounds were subjected to cytotoxicity and genotoxicity tests to establish their preliminary toxicological profiles and were found to be non-cytotoxic and non-genotoxic. Consequently, the findings of this study display the biological importance of compounds 2a, 2b as selective, irreversible and competitive inhibitors of hMAO-A. Docking studies revealed that there is a strong interaction between hMAO-A and the most active compound 2b. Full article

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873 KiB

Open AccessReview

Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors

by Damian Bartuzi, Agnieszka A. Kaczor, Katarzyna M. Targowska-Duda and Dariusz Matosiuk

Molecules 2017, 22(2), 340; https://doi.org/10.3390/molecules22020340 - 22 Feb 2017

Cited by 54 | Viewed by 10001

Abstract

The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in [...] Read more.

The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry. A deeper insight into the underlying mechanisms of interesting phenomena observed in GPCRs, such as biased signaling or allosteric modulation, can be gained with experimental and computational studies. The latter play an important role in this process, since they allow for observations on scales inaccessible for most other methods. One of the key steps in such studies is proper computational reconstruction of actual ligand-receptor or protein-protein interactions, a process called molecular docking. A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs. Full article

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2016

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5935 KiB

Open AccessArticle

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking

by Shota Uehara and Shigenori Tanaka

Molecules 2016, 21(11), 1604; https://doi.org/10.3390/molecules21111604 - 23 Nov 2016

Cited by 43 | Viewed by 14679

Abstract

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters [...] Read more.

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign. Full article

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3945 KiB

Open AccessArticle

Molecular Docking Optimization in the Context of Multi-Drug Resistant and Sensitive EGFR Mutants

by María Jesús García-Godoy, Esteban López-Camacho, José García-Nieto, Antonio J. Nebro and José F. Aldana-Montes

Molecules 2016, 21(11), 1575; https://doi.org/10.3390/molecules21111575 - 19 Nov 2016

Cited by 18 | Viewed by 6812

Abstract

The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, and, therefore, drug responses from lung cancer patients. In this context, candidate [...] Read more.

The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, and, therefore, drug responses from lung cancer patients. In this context, candidate drugs are being tested and in silico studies are necessary to know how these mutations affect the ligand binding site. This problem can be tackled by using a multi-objective approach applied to the molecular docking problem. According to the literature, few studies are related to the application of multi-objective approaches by minimizing two or more objectives in drug discovery. In this study, we have used four algorithms (NSGA-II, GDE3, SMPSO and MOEA/D) to minimize two objectives: the ligand–receptor intermolecular energy and the RMSD score. We have prepared a set of instances that includes the wild-type EGFR kinase domain and the same receptor with somatic mutations, and then we assessed the performance of the algorithms by applying a quality indicator to evaluate the convergence and diversity of the reference fronts. The MOEA/D algorithm yields the best solutions to these docking problems. The obtained solutions were analyzed, showing promising results to predict candidate EGFR inhibitors by using this multi-objective approach. Full article

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4438 KiB

Open AccessArticle

Molecular Modeling Studies of 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitors through Receptor-Based 3D-QSAR and Molecular Dynamics Simulations

by Haiyan Qian, Jiongjiong Chen, Youlu Pan and Jianzhong Chen

Molecules 2016, 21(9), 1222; https://doi.org/10.3390/molecules21091222 - 19 Sep 2016

Cited by 10 | Viewed by 7804

Abstract

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a potential target for the treatment of numerous human disorders, such as diabetes, obesity, and metabolic syndrome. In this work, molecular modeling studies combining molecular docking, 3D-QSAR, MESP, MD simulations and free energy calculations were performed on [...] Read more.

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a potential target for the treatment of numerous human disorders, such as diabetes, obesity, and metabolic syndrome. In this work, molecular modeling studies combining molecular docking, 3D-QSAR, MESP, MD simulations and free energy calculations were performed on pyridine amides and 1,2,4-triazolopyridines as 11β-HSD1 inhibitors to explore structure-activity relationships and structural requirement for the inhibitory activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by docking strategy. The derived pharmacophoric features were further supported by MESP and Mulliken charge analyses using density functional theory. In addition, MD simulations and free energy calculations were employed to determine the detailed binding process and to compare the binding modes of inhibitors with different bioactivities. The binding free energies calculated by MM/PBSA showed a good correlation with the experimental biological activities. Free energy analyses and per-residue energy decomposition indicated the van der Waals interaction would be the major driving force for the interactions between an inhibitor and 11β-HSD1. These unified results may provide that hydrogen bond interactions with Ser170 and Tyr183 are favorable for enhancing activity. Thr124, Ser170, Tyr177, Tyr183, Val227, and Val231 are the key amino acid residues in the binding pocket. The obtained results are expected to be valuable for the rational design of novel potent 11β-HSD1 inhibitors. Full article

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3467 KiB

Open AccessArticle

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

by Rui M. Almeida, Simone Dell’Acqua, Ludwig Krippahl, José J. G. Moura and Sofia R. Pauleta

Molecules 2016, 21(8), 1037; https://doi.org/10.3390/molecules21081037 - 9 Aug 2016

Cited by 8 | Viewed by 6328

Abstract

The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER [...] Read more.

The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields. Full article

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379 KiB

Open AccessArticle

Bioactive Molecule Prediction Using Extreme Gradient Boosting

by Ismail Babajide Mustapha and Faisal Saeed

Molecules 2016, 21(8), 983; https://doi.org/10.3390/molecules21080983 - 28 Jul 2016

Cited by 182 | Viewed by 11927

Abstract

Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which [...] Read more.

Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree (CART) and a variant of the Gradient Boosting Machine, was investigated for the prediction of biological activity based on quantitative description of the compound’s molecular structure. Seven datasets, well known in the literature were used in this paper and experimental results show that Xgboost can outperform machine learning algorithms like Random Forest (RF), Support Vector Machines (LSVM), Radial Basis Function Neural Network (RBFN) and Naïve Bayes (NB) for the prediction of biological activities. In addition to its ability to detect minority activity classes in highly imbalanced datasets, it showed remarkable performance on both high and low diversity datasets. Full article

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2015

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3299 KiB

Open AccessArticle

Identification of Hydrophobic Interfaces in Protein-Ligand Complexes by Selective Saturation Transfer NMR Spectroscopy

by Fabien Ferrage, Kaushik Dutta and David Cowburn

Molecules 2015, 20(12), 21992-21999; https://doi.org/10.3390/molecules201219824 - 9 Dec 2015

Cited by 3 | Viewed by 5837

Abstract

The proper characterization of protein-ligand interfaces is essential for structural biology, with implications ranging from the fundamental understanding of biological processes to pharmacology. Nuclear magnetic resonance is a powerful technique for such studies. We propose a novel approach to the direct determination of [...] Read more.

The proper characterization of protein-ligand interfaces is essential for structural biology, with implications ranging from the fundamental understanding of biological processes to pharmacology. Nuclear magnetic resonance is a powerful technique for such studies. We propose a novel approach to the direct determination of the likely pose of a peptide ligand onto a protein partner, by using frequency-selective cross-saturation with a low stringency isotopic labeling methods. Our method illustrates a complex of the Src homology 3 domain of C-terminal Src kinase with a peptide from the proline-enriched tyrosine phosphatase. Full article

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7136 KiB

Open AccessReview

Charting a Path to Success in Virtual Screening

by Stefano Forli

Molecules 2015, 20(10), 18732-18758; https://doi.org/10.3390/molecules201018732 - 15 Oct 2015

Cited by 66 | Viewed by 14216

Abstract

Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the [...] Read more.

Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the challenges and problems faced when running docking experiments are independent of the specific software used, and can be ascribed to either improper input preparation or to the simplified approaches applied to achieve high-throughput speed. Being aware of approximations and limitations of such methods is essential to prevent errors, deal with misleading results, and increase the success rate of virtual screening campaigns. In this review, best practices and most common issues of docking and virtual screening will be discussed, covering the journey from the design of the virtual experiment to the hit identification. Full article

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10313 KiB

Open AccessReview

Evolution of Macromolecular Docking Techniques: The Case Study of Nickel and Iron Metabolism in Pathogenic Bacteria

by Francesco Musiani and Stefano Ciurli

Molecules 2015, 20(8), 14265-14292; https://doi.org/10.3390/molecules200814265 - 5 Aug 2015

Cited by 5 | Viewed by 8355

Abstract

The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, [...] Read more.

The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, in the docking process, of experimentally derived information, together with the possibility of accounting for the flexibility of the interacting molecules. Here we review the results and the evolution of the techniques used to study the interaction between metallo-proteins and DNA operators, all involved in the nickel and iron metabolism of pathogenic bacteria, focusing in particular on Helicobacter pylori (Hp). In the first part of the article we discuss the methods used to calculate the structure of complexes of proteins involved in the activation of the nickel-dependent enzyme urease. In the second part of the article, we concentrate on two applications of protein-DNA docking conducted on the transcription factors HpFur (ferric uptake regulator) and HpNikR (nickel regulator). In both cases we discuss the technical expedients used to take into account the conformational variability of the multi-domain proteins involved in the calculations. Full article

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4565 KiB

Open AccessReview

Molecular Docking and Structure-Based Drug Design Strategies

by Leonardo G. Ferreira, Ricardo N. Dos Santos, Glaucius Oliva and Adriano D. Andricopulo

Molecules 2015, 20(7), 13384-13421; https://doi.org/10.3390/molecules200713384 - 22 Jul 2015

Cited by 1485 | Viewed by 94018

Abstract

Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of [...] Read more.

Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure- and ligand-based methods. Full article

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4535 KiB

Open AccessArticle

Molecular Docking and Multivariate Analysis of Xanthones as Antimicrobial and Antiviral Agents

by Freddy A. Bernal and Ericsson Coy-Barrera

Molecules 2015, 20(7), 13165-13204; https://doi.org/10.3390/molecules200713165 - 21 Jul 2015

Cited by 16 | Viewed by 9363

Abstract

Xanthones are secondary metabolites which have drawn considerable interest over the last decades due to their antimicrobial properties, among others. A great number of this kind of compounds has been therefore reported, but there is a limited amount of studies on screening for [...] Read more.

Xanthones are secondary metabolites which have drawn considerable interest over the last decades due to their antimicrobial properties, among others. A great number of this kind of compounds has been therefore reported, but there is a limited amount of studies on screening for biological activity. Thus, as part of our research on antimicrobial agents of natural origin, a set of 272 xanthones were submitted to molecular docking (MD) calculations with a group of seven fungal and two viral enzymes. The results indicated that prenylated xanthones are important hits for inhibition of the analyzed enzymes. The MD scores were also analyzed by multivariate statistics. Important structural details were found to be crucial for the inhibition of the tested enzymes by the xanthones. In addition, the classification of active xanthones can be achieved by statistical analysis on molecular docking scores by an affinity-antifungal activity relationship approach. The obtained results therefore are a suitable starting point for the development of antifungal and antiviral agents based on xanthones. Full article

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2813 KiB

Open AccessReview

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

by Romina Oliva, Edrisse Chermak and Luigi Cavallo

Molecules 2015, 20(7), 12045-12060; https://doi.org/10.3390/molecules200712045 - 1 Jul 2015

Cited by 15 | Viewed by 10062

Abstract

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, [...] Read more.

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions. Full article

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2526 KiB

Open AccessReview

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors

by Rushikesh Sable and Seetharama Jois

Molecules 2015, 20(6), 11569-11603; https://doi.org/10.3390/molecules200611569 - 23 Jun 2015

Cited by 59 | Viewed by 16309

Abstract

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases [...] Read more.

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers. Full article

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Open AccessArticle

Coarse-Grained Modeling of Peptide Docking Associated with Large Conformation Transitions of the Binding Protein: Troponin I Fragment–Troponin C System

by Jacek Wabik, Mateusz Kurcinski and Andrzej Kolinski

Molecules 2015, 20(6), 10763-10780; https://doi.org/10.3390/molecules200610763 - 11 Jun 2015

Cited by 9 | Viewed by 8727

Abstract

Most of the current docking procedures are focused on fine conformational adjustments of assembled complexes and fail to reproduce large-scale protein motion. In this paper, we test a new modeling approach developed to address this problem. CABS-dock is a versatile and efficient tool [...] Read more.

Most of the current docking procedures are focused on fine conformational adjustments of assembled complexes and fail to reproduce large-scale protein motion. In this paper, we test a new modeling approach developed to address this problem. CABS-dock is a versatile and efficient tool for modeling the structure, dynamics and interactions of protein complexes. The docking protocol employs a coarse-grained representation of proteins, a simplified model of interactions and advanced protocols for conformational sampling. CABS-dock is one of the very few tools that allow unrestrained docking with large conformational freedom of the receptor. In an example application we modeled the process of complex assembly between two proteins: Troponin C (TnC) and the N-terminal helix of Troponin I (TnI N-helix), which occurs in vivo during muscle contraction. Docking simulations illustrated how the TnC molecule undergoes significant conformational transition on complex formation, a phenomenon that can be modeled only when protein flexibility is properly accounted for. This way our procedure opens up a new possibility for studying mechanisms of protein complex assembly, which may be a supporting tool for rational drug design. Full article

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Computational Studies of Benzoxazinone Derivatives as Antiviral Agents against Herpes Virus Type 1 Protease

by Juliana F. R. Mello, Nathália C. Botelho, Alessandra M. T. Souza, Riethe Oliveira, Monique A. Brito, Bárbara De A. Abrahim-Vieira, Ana Carolina R. Sodero, Helena C. Castro, Lucio M. Cabral, Leonardo A. Miceli and Carlos R. Rodrigues

Molecules 2015, 20(6), 10689-10704; https://doi.org/10.3390/molecules200610689 - 10 Jun 2015

Cited by 7 | Viewed by 8270

Abstract

Herpes simplex virus infections have been described in the medical literature for centuries, yet the the drugs available nowadays for therapy are largely ineffective and low oral bioavailability plays an important role on the inefficacy of the treatments. Additionally, the details of the [...] Read more.

Herpes simplex virus infections have been described in the medical literature for centuries, yet the the drugs available nowadays for therapy are largely ineffective and low oral bioavailability plays an important role on the inefficacy of the treatments. Additionally, the details of the inhibition of Herpes Virus type 1 are still not fully understood. Studies have shown that several viruses encode one or more proteases required for the production new infectious virions. This study presents an analysis of the interactions between HSV-1 protease and benzoxazinone derivatives through a combination of structure-activity relationships, comparative modeling and molecular docking studies. The structure activity relationship results showed an important contribution of hydrophobic and polarizable groups and limitations for bulky groups in specific positions. Two Herpes Virus type 1 protease models were constructed and compared to achieve the best model which was obtained by MODELLER. Molecular docking results pointed to an important interaction between the most potent benzoxazinone derivative and Ser129, consistent with previous mechanistic data. Moreover, we also observed hydrophobic interactions that may play an important role in the stabilization of inhibitors in the active site. Finally, we performed druglikeness and drugscore studies of the most potent derivatives and the drugs currently used against Herpes virus. Full article

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Solving Molecular Docking Problems with Multi-Objective Metaheuristics

by María Jesús García-Godoy, Esteban López-Camacho, José García-Nieto, Antonio J. Nebro and José F. Aldana-Montes

Molecules 2015, 20(6), 10154-10183; https://doi.org/10.3390/molecules200610154 - 2 Jun 2015

Cited by 23 | Viewed by 9199

Abstract

Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal [...] Read more.

Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery. Full article

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DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations

by Alberto Cuzzolin, Mattia Sturlese, Ivana Malvacio, Antonella Ciancetta and Stefano Moro

Molecules 2015, 20(6), 9977-9993; https://doi.org/10.3390/molecules20069977 - 29 May 2015

Cited by 42 | Viewed by 12058

Abstract

Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses [...] Read more.

Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1) are discussed as validation test. Full article

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S4MPLE—Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking

by Laurent Hoffer, Camelia Chira, Gilles Marcou, Alexandre Varnek and Dragos Horvath

Molecules 2015, 20(5), 8997-9028; https://doi.org/10.3390/molecules20058997 - 19 May 2015

Cited by 27 | Viewed by 8596

Abstract

This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed [...] Read more.

This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications—docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters—were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å). Full article

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Development and Validation of a Docking-Based Virtual Screening Platform for the Identification of New Lactate Dehydrogenase Inhibitors

by Carlotta Granchi, Alice Capecchi, Gianluca Del Frate, Adriano Martinelli, Marco Macchia, Filippo Minutolo and Tiziano Tuccinardi

Molecules 2015, 20(5), 8772-8790; https://doi.org/10.3390/molecules20058772 - 15 May 2015

Cited by 23 | Viewed by 8056

Abstract

The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is linked to the vitality of tumors in hypoxic conditions. With the aim of identifying [...] Read more.

The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is linked to the vitality of tumors in hypoxic conditions. With the aim of identifying new hLDH5 inhibitors, a fully automated docking-based virtual screening platform was developed by considering different protein conformations and the consensus docking strategy. In order to verify the reliability of the reported platform, a small database of about 10,000 compounds was filtered by using this method, and the top-ranked compounds were tested for their hLDH5 inhibition activity. Enzymatic assays revealed that, among the ten selected compounds, two proved to efficiently inhibit enzyme activity with IC₅₀ values in the micromolar range. These results demonstrate the validity of the methodologies we followed, encouraging the application of larger virtual screening studies and further refinements of the platform. Furthermore, the two active compounds herein described may be considered as interesting leads for the development of new and more efficient LDH inhibitors. Full article

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Reduction of False Positives in Structure-Based Virtual Screening When Receptor Plasticity Is Considered

by Yaw Awuni and Yuguang Mu

Molecules 2015, 20(3), 5152-5164; https://doi.org/10.3390/molecules20035152 - 19 Mar 2015

Cited by 23 | Viewed by 8178

Abstract

Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor [...] Read more.

Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor can bind to different conformations of the binding site favorably was put forth, and related strategies to defeat this challenge were devised; reducing false positives when receptor plasticity is considered. The receptor in the study is the influenza A nucleoprotein, whose oligomerization is a requirement for RNA binding. The structural flexibility of influenza A nucleoprotein was explored by molecular dynamics simulations. The resultant distinctive structures and the crystal structure were used as receptor models in docking exercises in which two binding sites, the tail-loop binding pocket and the RNA binding site, were targeted with the Otava PrimScreen1 diversity-molecule library using the GOLD software. The intersection ligands that were listed in the top-ranked molecules from all receptor models were selected. Such selection strategy successfully distinguished high-affinity and low-affinity control molecules added to the molecule library. This work provides an applicable approach for reducing false positives and selecting true ligands from molecule libraries. Full article

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Open AccessReview

Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls

by Hezekiel Mathambo Kumalo, Soumendranath Bhakat and Mahmoud E. S. Soliman

Molecules 2015, 20(2), 1984-2000; https://doi.org/10.3390/molecules20021984 - 27 Jan 2015

Cited by 118 | Viewed by 17307

Abstract

he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds [...] Read more.

he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors. Full article

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