1
|
Kumar GS, Sobhia ME. Water network chemistry to exploit the nature of catalytic water molecules in Mtb DNA gyrase: a computational study to understand the binding mechanism of fluoroquinolones. J Biomol Struct Dyn 2024; 42:725-733. [PMID: 37121993 DOI: 10.1080/07391102.2023.2199869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 03/17/2023] [Indexed: 05/02/2023]
Abstract
The dynamics of DNA gyrase and mutants of DNA gyrA such as G88A, A90V, S91P, D94A, D94G, D94N, D94Y; and double-point mutant (S91P-D94G), are meticulously investigated using computational approaches. Molecular dynamics (MD) and hydration thermodynamics have shed light on the fundamental, mechanistic basis of mutations on the conformational stability of Quinolone Binding Pocket (QBP) of DNA gyrase. Analysis of MD results revealed the displacement of a single crystal water molecule (HOH201) from the catalytic site of wild-type (WT) and mutants of DNA gyrA. This prompted our research group to probe the five crystal water molecules present in the QBP of the enzyme using water thermodynamics. Hydration thermodynamics analysis revealed the displacement of HOH201 due to unstable thermodynamic signatures. Further, the analysis highlighted significant changes in thermodynamic signatures and locations of five crystal water hydration sites upon mutation. Integrated MD simulations and water thermodynamics provided promising insights into the conformational changes and inaccessibility of the catalytic water molecule that can influence the design of DNA gyrase inhibitors.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- G Siva Kumar
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Mohali, Punjab, India
| | - M Elizabeth Sobhia
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Mohali, Punjab, India
| |
Collapse
|
2
|
Chen J, Qiu Z, Huang J. Structure and Dynamics of Confined Water Inside Diphenylalanine Peptide Nanotubes. ACS OMEGA 2023; 8:42936-42950. [PMID: 38024738 PMCID: PMC10652825 DOI: 10.1021/acsomega.3c06071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/22/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023]
Abstract
Diphenylalanine (FF) peptides exhibit a unique ability to self-assemble into nanotubes with confined water molecules playing pivotal roles in their structure and function. This study investigates the structure and dynamics of diphenylalanine peptide nanotubes (FFPNTs) using all-atom molecular dynamics (MD) and grand canonical Monte Carlo combined with MD (GCMC/MD) simulations with both the CHARMM additive and Drude polarizable force fields. The occupancy and dynamics of confined water molecules were also examined. It was found that less than 2 confined water molecules per FF help stabilize the FFPNTs on the x-y plane. Analyses of the kinetics of confined water molecules revealed distinctive transport behaviors for bound and free water, and their respective diffusion coefficients were compared. Our results validate the importance of polarizable force field models in studying peptide nanotubes and provide insights into our understanding of nanoconfined water.
Collapse
Affiliation(s)
- Jinfeng Chen
- College
of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China
- Key
Laboratory of Structural Biology of Zhejiang Province, School of Life
Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
- Westlake
AI Therapeutics Lab, Westlake Laboratory
of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Zongyang Qiu
- Key
Laboratory of Structural Biology of Zhejiang Province, School of Life
Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
- Westlake
AI Therapeutics Lab, Westlake Laboratory
of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Jing Huang
- Key
Laboratory of Structural Biology of Zhejiang Province, School of Life
Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
- Westlake
AI Therapeutics Lab, Westlake Laboratory
of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| |
Collapse
|
3
|
Zsidó BZ, Bayarsaikhan B, Börzsei R, Szél V, Mohos V, Hetényi C. The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering. Int J Mol Sci 2023; 24:11784. [PMID: 37511543 PMCID: PMC10381018 DOI: 10.3390/ijms241411784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/18/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.
Collapse
Affiliation(s)
- Balázs Zoltán Zsidó
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| | - Bayartsetseg Bayarsaikhan
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| | - Rita Börzsei
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| | - Viktor Szél
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| | - Violetta Mohos
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| | - Csaba Hetényi
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, 7624 Pécs, Hungary
| |
Collapse
|
4
|
Eberhardt J, Forli S. WaterKit: Thermodynamic Profiling of Protein Hydration Sites. J Chem Theory Comput 2023; 19:2535-2556. [PMID: 37094087 PMCID: PMC10732097 DOI: 10.1021/acs.jctc.2c01087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
Water desolvation is one of the key components of the free energy of binding of small molecules to their receptors. Thus, understanding the energetic balance of solvation and desolvation resulting from individual water molecules can be crucial when estimating ligand binding, especially when evaluating different molecules and poses as done in High-Throughput Virtual Screening (HTVS). Over the most recent decades, several methods were developed to tackle this problem, ranging from fast approximate methods (usually empirical functions using either discrete atom-atom pairwise interactions or continuum solvent models) to more computationally expensive and accurate ones, mostly based on Molecular Dynamics (MD) simulations, such as Grid Inhomogeneous Solvation Theory (GIST) or Double Decoupling. On one hand, MD-based methods are prohibitive to use in HTVS to estimate the role of waters on the fly for each ligand. On the other hand, fast and approximate methods show an unsatisfactory level of accuracy, with low agreement with results obtained with the more expensive methods. Here we introduce WaterKit, a new grid-based sampling method with explicit water molecules to calculate thermodynamic properties using the GIST method. Our results show that the discrete placement of water molecules is successful in reproducing the position of crystallographic waters with very high accuracy, as well as providing thermodynamic estimates with accuracy comparable to more expensive MD simulations. Unlike these methods, WaterKit can be used to analyze specific regions on the protein surface, (such as the binding site of a receptor), without having to hydrate and simulate the whole receptor structure. The results show the feasibility of a general and fast method to compute thermodynamic properties of water molecules, making it well-suited to be integrated in high-throughput pipelines such as molecular docking.
Collapse
Affiliation(s)
- Jerome Eberhardt
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, California 92037, United States
| | - Stefano Forli
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, California 92037, United States
| |
Collapse
|
5
|
Barros EP, Ries B, Champion C, Rieder SR, Riniker S. Accounting for Solvation Correlation Effects on the Thermodynamics of Water Networks in Protein Cavities. J Chem Inf Model 2023; 63:1794-1805. [PMID: 36917685 PMCID: PMC10052353 DOI: 10.1021/acs.jcim.2c01610] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
Macromolecular recognition and ligand binding are at the core of biological function and drug discovery efforts. Water molecules play a significant role in mediating the protein-ligand interaction, acting as more than just the surrounding medium by affecting the thermodynamics and thus the outcome of the binding process. As individual water contributions are impossible to measure experimentally, a range of computational methods have emerged to identify hydration sites in protein pockets and characterize their energetic contributions for drug discovery applications. Even though several methods model solvation effects explicitly, they focus on determining the stability of specific water sites independently and neglect solvation correlation effects upon replacement of clusters of water molecules, which typically happens in hit-to-lead optimization. In this work, we rigorously determine the conjoint effects of replacing all combinations of water molecules in protein binding pockets through the use of the RE-EDS multistate free-energy method, which combines Hamiltonian replica exchange (RE) and enveloping distribution sampling (EDS). Applications on the small bovine pancreatic trypsin inhibitor and four proteins of the bromodomain family illustrate the extent of solvation correlation effects on water thermodynamics, with the favorability of replacement of the water sites by pharmacophore probes highly dependent on the composition of the water network and the pocket environment. Given the ubiquity of water networks in biologically relevant protein targets, we believe our approach can be helpful for computer-aided drug discovery by providing a pocket-specific and a priori systematic consideration of solvation effects on ligand binding and selectivity.
Collapse
Affiliation(s)
- Emilia P Barros
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Benjamin Ries
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Candide Champion
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Salomé R Rieder
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Sereina Riniker
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| |
Collapse
|
6
|
Tošović J, Fijan D, Jukič M, Bren U. Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data. J Chem Inf Model 2022; 62:6105-6117. [PMID: 36351288 DOI: 10.1021/acs.jcim.2c00801] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.
Collapse
Affiliation(s)
- Jelena Tošović
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia
| | | | - Marko Jukič
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia.,Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000Koper, Slovenia
| | - Urban Bren
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia.,Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000Koper, Slovenia.,Institute of Environmental Protection and Sensors, Beloruska ulica 7, SI-2000Maribor, Slovenia
| |
Collapse
|
7
|
Ahmed M, Ganesan A, Barakat K. Leveraging structural and 2D-QSAR to investigate the role of functional group substitutions, conserved surface residues and desolvation in triggering the small molecule-induced dimerization of hPD-L1. BMC Chem 2022; 16:49. [PMID: 35761353 PMCID: PMC9238240 DOI: 10.1186/s13065-022-00842-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 06/21/2022] [Indexed: 12/02/2022] Open
Abstract
Small molecules are rising as a new generation of immune checkpoints’ inhibitors, with compounds targeting the human Programmed death-ligand 1 (hPD-L1) protein are pioneering this area of research. Promising examples include the recently disclosed compounds from Bristol-Myers-Squibb (BMS). These molecules bind specifically to hPD-L1 through a unique mode of action. They induce dimerization between two hPD-L1 monomers through the hPD-1 binding interface in each monomer, thereby inhibiting the PD-1/PD-L1 axis. While the recently reported crystal structures of such small molecules bound to hPD-L1 reveal valuable insights regarding their molecular interactions, there is still limited information about the dynamics driving this unusual complex formation. The current study provides an in-depth computational structural analysis to study the interactions of five small molecule compounds in complex with hPD-L1. By employing a combination of molecular dynamic simulations, binding energy calculations and computational solvent mapping techniques, our analyses quantified the dynamic roles of different hydrophilic and lipophilic residues at the surface of hPD-L1 in mediating these interactions. Furthermore, ligand-based analyses, including Free-Wilson 2D-QSAR was conducted to quantify the impact of R-group substitutions at different sites of the phenoxy-methyl biphenyl core. Our results emphasize the importance of a terminal phenyl ring that must be present in any hPD-L1 small molecule inhibitor. This phenyl moiety overlaps with a very unfavorable hydration site, which can explain the ability of such small molecules to trigger hPD-L1 dimerization.
Collapse
Affiliation(s)
- Marawan Ahmed
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Aravindhan Ganesan
- ArGan's Lab, School of Pharmacy, University of Waterloo, Kitchener, ON, Canada
| | - Khaled Barakat
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada. .,Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB, Canada.
| |
Collapse
|
8
|
Biswal J, Jayaprakash P, Rayala SK, Venkatraman G, Rangaswamy R, Jeyaraman J. WaterMap and Molecular Dynamic Simulation-Guided Discovery of Potential PAK1 Inhibitors Using Repurposing Approaches. ACS OMEGA 2021; 6:26829-26845. [PMID: 34693105 PMCID: PMC8529594 DOI: 10.1021/acsomega.1c02032] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Indexed: 06/13/2023]
Abstract
p21-Activated kinase 1 (PAK1) is positioned at the nexus of several oncogenic signaling pathways. Currently, there are no approved inhibitors for disabling the transfer of phosphate in the active site directly, as they are limited by lower affinity, and poor kinase selectivity. In this work, a repurposing study utilizing FDA-approved drugs from the DrugBank database was pursued with an initial selection of 27 molecules out of ∼2162 drug molecules, based on their docking energies and molecular interaction patterns. From the molecules that were considered for WaterMap analysis, seven molecules, namely, Mitoxantrone, Labetalol, Acalabrutinib, Sacubitril, Flubendazole, Trazodone, and Niraparib, ascertained the ability to overlap with high-energy hydration sites. Considering many other displaced unfavorable water molecules, only Acalabrutinib, Flubendazole, and Trazodone molecules highlighted their prominence in terms of binding affinity gains through ΔΔG that ranges between 6.44 and 2.59 kcal/mol. Even if Mitoxantrone exhibited the highest docking score and greater interaction strength, it did not comply with the WaterMap and molecular dynamics simulation results. Moreover, detailed MD simulation trajectory analyses suggested that the drug molecules Flubendazole, Niraparib, and Acalabrutinib were highly stable, observed from their RMSD values and consistent interaction pattern with Glu315, Glu345, Leu347, and Asp407 including the hydrophobic interactions maintained in the three replicates. However, the drug molecule Trazodone displayed a loss of crucial interaction with Leu347, which was essential to inhibit the kinase activity of PAK1. The molecular orbital and electrostatic potential analyses elucidated the reactivity and strong complementarity potentials of the drug molecules in the binding pocket of PAK1. Therefore, the CADD-based reposition efforts, reported in this work, helped in the successful identification of new PAK1 inhibitors that requires further investigation by in vitro analysis.
Collapse
Affiliation(s)
- Jayashree Biswal
- Structural
Biology and Bio-Computing Laboratory, Department of Bioinformatics,
Science Block, Alagappa University, Karaikudi 630 004, Tamil Nadu, India
| | - Prajisha Jayaprakash
- Structural
Biology and Bio-Computing Laboratory, Department of Bioinformatics,
Science Block, Alagappa University, Karaikudi 630 004, Tamil Nadu, India
| | - Suresh Kumar Rayala
- Department
of Biotechnology, Indian Institute of Technology
Madras, Room No. BT 306, Chennai 600 036, Tamil Nadu, India
| | - Ganesh Venkatraman
- Department
of Human Genetics, College of Biomedical Sciences, Sri Ramachandra University, Porur, Chennai 600 116, Tamil Nadu, India
| | - Raghu Rangaswamy
- Structural
Biology and Bio-Computing Laboratory, Department of Bioinformatics,
Science Block, Alagappa University, Karaikudi 630 004, Tamil Nadu, India
| | - Jeyakanthan Jeyaraman
- Structural
Biology and Bio-Computing Laboratory, Department of Bioinformatics,
Science Block, Alagappa University, Karaikudi 630 004, Tamil Nadu, India
| |
Collapse
|
9
|
Huang P, Xing H, Zou X, Han Q, Liu K, Sun X, Wu J, Fan J. Accurate Prediction of Hydration Sites of Proteins Using Energy Model With Atom Embedding. Front Mol Biosci 2021; 8:756075. [PMID: 34616774 PMCID: PMC8488165 DOI: 10.3389/fmolb.2021.756075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 09/02/2021] [Indexed: 11/13/2022] Open
Abstract
We propose a method based on neural networks to accurately predict hydration sites in proteins. In our approach, high-quality data of protein structures are used to parametrize our neural network model, which is a differentiable score function that can evaluate an arbitrary position in 3D structures on proteins and predict the nearest water molecule that is not present. The score function is further integrated into our water placement algorithm to generate explicit hydration sites. In experiments on the OppA protein dataset used in previous studies and our selection of protein structures, our method achieves the highest model quality in terms of F1 score, compared to several previous studies.
Collapse
Affiliation(s)
- Pin Huang
- College of Life Sciences, Beijing Normal University, Beijing, China.,Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Haoming Xing
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Xun Zou
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Qi Han
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Ke Liu
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Xiangyan Sun
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Junqiu Wu
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| | - Jie Fan
- Accutar Biotechnology Inc., Brooklyn, NY, United States
| |
Collapse
|
10
|
Lukac I, Wyatt PG, Gilbert IH, Zuccotto F. Ligand binding: evaluating the contribution of the water molecules network using the Fragment Molecular Orbital method. J Comput Aided Mol Des 2021; 35:1025-1036. [PMID: 34458939 PMCID: PMC8523014 DOI: 10.1007/s10822-021-00416-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 08/09/2021] [Indexed: 11/15/2022]
Abstract
Water molecules play a crucial role in protein-ligand binding, and many tools exist that aim to predict the position and relative energies of these important, but challenging participants of biomolecular recognition. The available tools are, in general, capable of predicting the location of water molecules. However, predicting the effects of their displacement is still very challenging. In this work, a linear-scaling quantum mechanics-based approach was used to assess water network energetics and the changes in network stability upon ligand structural modifications. This approach offers a valuable way to improve understanding of SAR data and help guide compound design.
Collapse
Affiliation(s)
- Iva Lukac
- Drug Discovery Unit, Wellcome Centre for Anti-Infectives Research, Division of Biological Chemistry and Drug Discovery, University of Dundee, Dow Street, Dundee, DD1 5EH, UK
| | - Paul G Wyatt
- Drug Discovery Unit, Wellcome Centre for Anti-Infectives Research, Division of Biological Chemistry and Drug Discovery, University of Dundee, Dow Street, Dundee, DD1 5EH, UK.
| | - Ian H Gilbert
- Drug Discovery Unit, Wellcome Centre for Anti-Infectives Research, Division of Biological Chemistry and Drug Discovery, University of Dundee, Dow Street, Dundee, DD1 5EH, UK
| | - Fabio Zuccotto
- Drug Discovery Unit, Wellcome Centre for Anti-Infectives Research, Division of Biological Chemistry and Drug Discovery, University of Dundee, Dow Street, Dundee, DD1 5EH, UK.
| |
Collapse
|
11
|
Greene D, Barton M, Luchko T, Shiferaw Y. Computational Analysis of Binding Interactions between the Ryanodine Receptor Type 2 and Calmodulin. J Phys Chem B 2021; 125:10720-10735. [PMID: 34533024 DOI: 10.1021/acs.jpcb.1c03896] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Mutations in the cardiac ryanodine receptor type 2 (RyR2) have been linked to a variety of cardiac arrhythmias, such as catecholaminergic polymorphic ventricular tachycardia (CPVT). RyR2 is regulated by calmodulin (CaM), and mutations that disrupt their interaction can cause aberrant calcium release, leading to an arrhythmia. It was recently shown that increasing the RyR2-CaM binding affinity could rescue a defective CPVT-related RyR2 channel to near wild-type behavior. However, the interactions that determine the binding affinity at the RyR2-CaM binding interface are not well understood. In this study, we identify the key domains and interactions, including several new interactions, involved in the binding of CaM to RyR2. Also, our comparison between the wild-type and V3599K mutant suggests how the RyR2-CaM binding affinity can be increased via a change in the central and N-terminal lobe binding contacts for CaM. This computational approach provides new insights into the effect of a mutation at the RyR2-CaM binding interface, and it may find utility in drug design for the future treatment of cardiac arrhythmias.
Collapse
Affiliation(s)
- D'Artagnan Greene
- Department of Physics, California State University, Northridge, California 91330, United States
| | - Michael Barton
- Department of Physics, California State University, Northridge, California 91330, United States
| | - Tyler Luchko
- Department of Physics, California State University, Northridge, California 91330, United States
| | - Yohannes Shiferaw
- Department of Physics, California State University, Northridge, California 91330, United States
| |
Collapse
|
12
|
Samways ML, Taylor RD, Bruce Macdonald HE, Essex JW. Water molecules at protein-drug interfaces: computational prediction and analysis methods. Chem Soc Rev 2021; 50:9104-9120. [PMID: 34184009 DOI: 10.1039/d0cs00151a] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.
Collapse
Affiliation(s)
- Marley L Samways
- School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, UK.
| | | | | | | |
Collapse
|
13
|
Andreev S, Pantsar T, Tesch R, Kahlke N, El-Gokha A, Ansideri F, Grätz L, Romasco J, Sita G, Geibel C, Lämmerhofer M, Tarozzi A, Knapp S, Laufer SA, Koch P. Addressing a Trapped High-Energy Water: Design and Synthesis of Highly Potent Pyrimidoindole-Based Glycogen Synthase Kinase-3β Inhibitors. J Med Chem 2021; 65:1283-1301. [PMID: 34213342 DOI: 10.1021/acs.jmedchem.0c02146] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
In small molecule binding, water is not a passive bystander but rather takes an active role in the binding site, which may be decisive for the potency of the inhibitor. Here, by addressing a high-energy water, we improved the IC50 value of our co-crystallized glycogen synthase kinase-3β (GSK-3β) inhibitor by nearly two orders of magnitude. Surprisingly, our results demonstrate that this high-energy water was not displaced by our potent inhibitor (S)-3-(3-((7-ethynyl-9H-pyrimido[4,5-b]indol-4-yl)(methyl)amino)piperidin-1-yl)propanenitrile ((S)-15, IC50 value of 6 nM). Instead, only a subtle shift in the location of this water molecule resulted in a dramatic decrease in the energy of this high-energy hydration site, as shown by the WaterMap analysis combined with microsecond timescale molecular dynamics simulations. (S)-15 demonstrated both a favorable kinome selectivity profile and target engagement in a cellular environment and reduced GSK-3 autophosphorylation in neuronal SH-SY5Y cells. Overall, our findings highlight that even a slight adjustment in the location of a high-energy water can be decisive for ligand binding.
Collapse
Affiliation(s)
- Stanislav Andreev
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Tatu Pantsar
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Roberta Tesch
- Institute for Pharmaceutical Chemistry, Goethe University, Max-von-Laue-Straße 9, 60438 Frankfurt am Main, Germany.,Structural Genomics Consortium, Buchmann Institute for Life Sciences, Goethe University, Max-von-Laue-Straße 15, 60438 Frankfurt am Main, Germany
| | - Niclas Kahlke
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Ahmed El-Gokha
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany.,Chemistry Department, Faculty of Science, Menoufia University, Gamal Abdel-Nasser Street, 32511 Shebin El-Kom, Egypt
| | - Francesco Ansideri
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Lukas Grätz
- Department of Pharmaceutical/Medicinal Chemistry II, Institute of Pharmacy, University of Regensburg, Universitätsstraße 31, 93053 Regensburg, Germany
| | - Jenny Romasco
- Department for Life Quality Studies, Alma Mater Studiorum, University of Bologna, Corso D'Augusto 237, 47921 Rimini, Italy
| | - Giulia Sita
- Department of Pharmacy and Biotechnology, University of Bologna, Via Irnerio 48, 40126 Bologna, Italy
| | - Christian Geibel
- Institute of Pharmaceutical Sciences, Department of Pharmaceutical (Bio-)Analysis, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Michael Lämmerhofer
- Institute of Pharmaceutical Sciences, Department of Pharmaceutical (Bio-)Analysis, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Andrea Tarozzi
- Department for Life Quality Studies, Alma Mater Studiorum, University of Bologna, Corso D'Augusto 237, 47921 Rimini, Italy
| | - Stefan Knapp
- Institute for Pharmaceutical Chemistry, Goethe University, Max-von-Laue-Straße 9, 60438 Frankfurt am Main, Germany.,Structural Genomics Consortium, Buchmann Institute for Life Sciences, Goethe University, Max-von-Laue-Straße 15, 60438 Frankfurt am Main, Germany
| | - Stefan A Laufer
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany.,Tübingen Center for Academic Drug Discovery (TüCAD2), Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Pierre Koch
- Institute of Pharmaceutical Sciences, Department of Medicinal and Pharmaceutical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany.,Department of Pharmaceutical/Medicinal Chemistry II, Institute of Pharmacy, University of Regensburg, Universitätsstraße 31, 93053 Regensburg, Germany
| |
Collapse
|
14
|
Spoel D, Zhang J, Zhang H. Quantitative predictions from molecular simulations using explicit or implicit interactions. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1560] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- David Spoel
- Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology Uppsala University Uppsala Sweden
| | - Jin Zhang
- Department of Chemistry Southern University of Science and Technology Shenzhen China
| | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering University of Science and Technology Beijing Beijing China
| |
Collapse
|
15
|
Quantum Chemical Microsolvation by Automated Water Placement. Molecules 2021; 26:molecules26061793. [PMID: 33806731 PMCID: PMC8005176 DOI: 10.3390/molecules26061793] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/13/2021] [Accepted: 03/15/2021] [Indexed: 11/17/2022] Open
Abstract
We developed a quantitative approach to quantum chemical microsolvation. Key in our methodology is the automatic placement of individual solvent molecules based on the free energy solvation thermodynamics derived from molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). This protocol enabled us to rigorously define the number, position, and orientation of individual solvent molecules and to determine their interaction with the solute based on physical quantities. The generated solute-solvent clusters served as an input for subsequent quantum chemical investigations. We showcased the applicability, scope, and limitations of this computational approach for a number of small molecules, including urea, 2-aminobenzothiazole, (+)-syn-benzotriborneol, benzoic acid, and helicene. Our results show excellent agreement with the available ab initio molecular dynamics data and experimental results.
Collapse
|
16
|
Instantaneous generation of protein hydration properties from static structures. Commun Chem 2020; 3:188. [PMID: 36703451 PMCID: PMC9814540 DOI: 10.1038/s42004-020-00435-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/10/2020] [Indexed: 01/29/2023] Open
Abstract
Complex molecular simulation methods are typically required to calculate the thermodynamic properties of biochemical systems. One example thereof is the thermodynamic profiling of (de)solvation of proteins, which is an essential driving force for protein-ligand and protein-protein binding. The thermodynamic state of water molecules depends on its enthalpic and entropic components; the latter is governed by dynamic properties of the molecule. Here, we developed, to the best of our knowledge, two novel machine learning methods based on deep neural networks that are able to generate the converged thermodynamic state of dynamic water molecules in the heterogeneous protein environment based solely on the information of the static protein structure. The applicability of our machine learning methods to predict the hydration information is demonstrated in two different studies, the qualitative analysis and quantitative prediction of structure-activity relationships, and the prediction of protein-ligand binding modes.
Collapse
|
17
|
The role of water in ligand binding. Curr Opin Struct Biol 2020; 67:1-8. [PMID: 32942197 DOI: 10.1016/j.sbi.2020.08.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 08/11/2020] [Accepted: 08/13/2020] [Indexed: 02/06/2023]
|
18
|
Gerstenberger BS, Ambler C, Arnold EP, Banker ME, Brown MF, Clark JD, Dermenci A, Dowty ME, Fensome A, Fish S, Hayward MM, Hegen M, Hollingshead BD, Knafels JD, Lin DW, Lin TH, Owen DR, Saiah E, Sharma R, Vajdos FF, Xing L, Yang X, Yang X, Wright SW. Discovery of Tyrosine Kinase 2 (TYK2) Inhibitor (PF-06826647) for the Treatment of Autoimmune Diseases. J Med Chem 2020; 63:13561-13577. [PMID: 32787094 DOI: 10.1021/acs.jmedchem.0c00948] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Tyrosine kinase 2 (TYK2) is a member of the JAK kinase family that regulates signal transduction downstream of receptors for the IL-23/IL-12 pathways and type I interferon family, where it pairs with JAK2 or JAK1, respectively. On the basis of human genetic and emerging clinical data, a selective TYK2 inhibitor provides an opportunity to treat autoimmune diseases delivering a potentially differentiated clinical profile compared to currently approved JAK inhibitors. The discovery of an ATP-competitive pyrazolopyrazinyl series of TYK2 inhibitors was accomplished through computational and structurally enabled design starting from a known kinase hinge binding motif. With understanding of PK/PD relationships, a target profile balancing TYK2 potency and selectivity over off-target JAK2 was established. Lead optimization involved modulating potency, selectivity, and ADME properties which led to the identification of the clinical candidate PF-06826647 (22).
Collapse
Affiliation(s)
| | | | - Eric P Arnold
- Pfizer Inc., Groton, Connecticut 06340, United States
| | | | | | - James D Clark
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | | | - Martin E Dowty
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Andrew Fensome
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Susan Fish
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | | | - Martin Hegen
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | | | | | - David W Lin
- Pfizer Inc., Groton, Connecticut 06340, United States
| | - Tsung H Lin
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Dafydd R Owen
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Eddine Saiah
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Raman Sharma
- Pfizer Inc., Groton, Connecticut 06340, United States
| | | | - Li Xing
- Pfizer Inc., Cambridge, Massachusetts 02139, United States
| | - Xiaojing Yang
- Pfizer Inc., Groton, Connecticut 06340, United States
| | - Xin Yang
- Pfizer Inc., Groton, Connecticut 06340, United States
| | | |
Collapse
|
19
|
Jukič M, Konc J, Janežič D, Bren U. ProBiS H2O MD Approach for Identification of Conserved Water Sites in Protein Structures for Drug Design. ACS Med Chem Lett 2020; 11:877-882. [PMID: 32435399 PMCID: PMC7236268 DOI: 10.1021/acsmedchemlett.9b00651] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 03/19/2020] [Indexed: 01/06/2023] Open
Abstract
![]()
The ProBiS H2O MD
approach for identification of conserved waters
and water sites of interest in macromolecular systems, which is becoming
a typical step in a structure-based drug design or macromolecular
study in general, is described. This work explores an extension of
the ProBiS H2O approach introduced by Jukič et al. Indeed,
water molecules are key players in the interaction mechanisms of macromolecules
and small molecules and play structural roles. Our earlier developed
approach, ProBiS H2O, is a simple and transparent workflow for conserved
water detection. Here we have considered generalizing the idea by
supplementing the experimental data with data derived from molecular
dynamics to facilitate work on less known systems. Newly developed
ProBiS H2O MD workflow uses trajectory data, extracts and identifies
interesting water sites, and visualizes the results. ProBiS H2O MD
can thus robustly process molecular dynamic trajectory snapshots,
perform local superpositions, collect water location data, and perform
density-based clustering to identify discrete sites with high conservation
of water molecules. This is a new approach that uses experimental
data in silico to identify interesting water sites.
Methodology is fast and water-model or molecular dynamics software
independent. Trends in the conservation of water molecules can be
followed over a variety of trajectories, and our approach has been
successfully validated using reported protein systems with experimentally
observed conserved water molecules. ProBiS H2O MD is freely available
as PyMOL plugin at http://insilab.org.
Collapse
Affiliation(s)
- Marko Jukič
- University of Maribor, Faculty of Chemistry and Chemical Engineering, Laboratory of Physical Chemistry and Chemical Thermodynamics, Smetanova ulica 17, SI-2000 Maribor, Slovenia
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI-6000 Koper, Slovenia
| | - Janez Konc
- University of Maribor, Faculty of Chemistry and Chemical Engineering, Laboratory of Physical Chemistry and Chemical Thermodynamics, Smetanova ulica 17, SI-2000 Maribor, Slovenia
- National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia
| | - Dušanka Janežič
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI-6000 Koper, Slovenia
| | - Urban Bren
- University of Maribor, Faculty of Chemistry and Chemical Engineering, Laboratory of Physical Chemistry and Chemical Thermodynamics, Smetanova ulica 17, SI-2000 Maribor, Slovenia
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI-6000 Koper, Slovenia
| |
Collapse
|
20
|
Bodnarchuk MS, Packer MJ, Haywood A. Utilizing Grand Canonical Monte Carlo Methods in Drug Discovery. ACS Med Chem Lett 2020; 11:77-82. [PMID: 31938467 DOI: 10.1021/acsmedchemlett.9b00499] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 12/11/2019] [Indexed: 12/17/2022] Open
Abstract
The concepts behind targeting waters for potency and selectivity gains have been well documented and explored, although maximizing such potential gains can prove to be challenging. This problem is exacerbated in cases where there are multiple interacting waters, wherein perturbation of one water can affect the free energy landscape of the remaining waters. Knowing the right modification a priori is challenging, and computational approaches are ideally suited to help answer the key question of which substitution is best to try. Here, we use Grand Canonical Monte Carlo and the recent Grand Canonical Alchemical Perturbation methods to both understand and predict the effect of ligand-mediated water displacement when more than one water molecule is involved, as well as to understand how exploiting water networks can help govern selectivity.
Collapse
Affiliation(s)
- Michael S. Bodnarchuk
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Martin J. Packer
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Alexe Haywood
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| |
Collapse
|
21
|
Shareef MA, Sirisha K, Sayeed IB, Khan I, Ganapathi T, Akbar S, Ganesh Kumar C, Kamal A, Nagendra Babu B. Synthesis of new triazole fused imidazo[2,1-b]thiazole hybrids with emphasis on Staphylococcus aureus virulence factors. Bioorg Med Chem Lett 2019; 29:126621. [DOI: 10.1016/j.bmcl.2019.08.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 08/08/2019] [Accepted: 08/11/2019] [Indexed: 12/22/2022]
|
22
|
Geschwindner S, Ulander J. The current impact of water thermodynamics for small-molecule drug discovery. Expert Opin Drug Discov 2019; 14:1221-1225. [DOI: 10.1080/17460441.2019.1664468] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Stefan Geschwindner
- Structure, Biophysics and Fragment-based Lead Generation, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Johan Ulander
- Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| |
Collapse
|
23
|
Lee MH, Lee DY, Balupuri A, Jeong JW, Kang NS. Pharmacophoric Site Identification and Inhibitor Design for Autotaxin. Molecules 2019; 24:molecules24152808. [PMID: 31374894 PMCID: PMC6696049 DOI: 10.3390/molecules24152808] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 07/25/2019] [Accepted: 07/29/2019] [Indexed: 02/06/2023] Open
Abstract
Autotaxin (ATX) is a potential drug target that is associated with inflammatory diseases and various cancers. In our previous studies, we have designed several inhibitors targeting ATX using computational and experimental approaches. Here, we have analyzed topological water networks (TWNs) in the binding pocket of ATX. TWN analysis revealed a pharmacophoric site inside the pocket. We designed and synthesized compounds considering the identified pharmacophoric site. Furthermore, we performed biological experiments to determine their ATX inhibitory activities. High potency of the designed compounds supports the predictions of the TWN analysis.
Collapse
Affiliation(s)
- Myeong Hwi Lee
- Graduate School of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea
| | - Dae-Yon Lee
- LegoChem Biosciences, Inc., 8-26 Munoyeongseo-ro, Daedeok-gu, Daejeon 34302, Korea
| | - Anand Balupuri
- Graduate School of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea
| | - Jong-Woo Jeong
- Graduate School of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea
| | - Nam Sook Kang
- Graduate School of New Drug Discovery and Development, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea.
| |
Collapse
|
24
|
Schaller D, Pach S, Wolber G. PyRod: Tracing Water Molecules in Molecular Dynamics Simulations. J Chem Inf Model 2019; 59:2818-2829. [PMID: 31117512 DOI: 10.1021/acs.jcim.9b00281] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Ligands entering a protein binding pocket essentially compete with water molecules for binding to the protein. Hence, the location and thermodynamic properties of water molecules in protein structures have gained increased attention in the drug design community. Including corresponding data into 3D pharmacophore modeling is essential for efficient high throughput virtual screening. Here, we present PyRod, a free and open-source Python software that allows for visualization of pharmacophoric binding pocket characteristics, identification of hot spots for ligand binding, and subsequent generation of pharmacophore features for virtual screening. The implemented routines analyze the protein environment of water molecules in molecular dynamics (MD) simulations and can differentiate between hydrogen bonded waters as well as waters in a protein environment of hydrophobic, charged, or aromatic atom groups. The gathered information is further processed to generate dynamic molecular interaction fields (dMIFs) for visualization and pharmacophoric features for virtual screening. The described software was applied to 5 therapeutically relevant drug targets, and generated pharmacophores were evaluated using DUD-E benchmarking sets. The best performing pharmacophore was found for the HIV1 protease with an early enrichment factor of 54.6. PyRod adds a new perspective to structure-based screening campaigns by providing easy-to-interpret dMIFs and purely protein-based pharmacophores that are solely based on tracing water molecules in MD simulations. Since structural information about cocrystallized ligands is not needed, screening campaigns can be followed, for which less or no ligand information is available. PyRod is freely available at https://github.com/schallerdavid/pyrod .
Collapse
Affiliation(s)
- David Schaller
- Pharmaceutical and Medicinal Chemistry , Freie Universität Berlin , Königin-Luise-Strasse 2+4 , 14195 Berlin , Germany
| | - Szymon Pach
- Pharmaceutical and Medicinal Chemistry , Freie Universität Berlin , Königin-Luise-Strasse 2+4 , 14195 Berlin , Germany
| | - Gerhard Wolber
- Pharmaceutical and Medicinal Chemistry , Freie Universität Berlin , Königin-Luise-Strasse 2+4 , 14195 Berlin , Germany
| |
Collapse
|
25
|
Cao S, Konovalov KA, Unarta IC, Huang X. Recent Developments in Integral Equation Theory for Solvation to Treat Density Inhomogeneity at Solute–Solvent Interface. ADVANCED THEORY AND SIMULATIONS 2019. [DOI: 10.1002/adts.201900049] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Siqin Cao
- Department of Chemistrythe Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
- Center of System Biology and Human HealthState Key Laboratory of Molecular Neuroscience, Hong Kong Branch Clear Water Bay Kowloon Hong Kong
| | - Kirill A. Konovalov
- Department of Chemistrythe Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
- Center of System Biology and Human HealthState Key Laboratory of Molecular Neuroscience, Hong Kong Branch Clear Water Bay Kowloon Hong Kong
| | - Ilona Christy Unarta
- Center of System Biology and Human HealthState Key Laboratory of Molecular Neuroscience, Hong Kong Branch Clear Water Bay Kowloon Hong Kong
- Bioengineering Graduate Programthe Hong Kong University of Science and TechnologyHong Kong of Chinese National EngineeringResearch Center for Tissue Restoration and Reconstructionthe Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
| | - Xuhui Huang
- Department of Chemistrythe Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
- Center of System Biology and Human HealthState Key Laboratory of Molecular Neuroscience, Hong Kong Branch Clear Water Bay Kowloon Hong Kong
- Bioengineering Graduate Programthe Hong Kong University of Science and TechnologyHong Kong of Chinese National EngineeringResearch Center for Tissue Restoration and Reconstructionthe Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
- HKUST‐Shenzhen Research Institute Hi‐Tech Park, Nanshan Shenzhen 518057 China
| |
Collapse
|
26
|
Biswal J, Jayaprakash P, Suresh Kumar R, Venkatraman G, Poopandi S, Rangasamy R, Jeyaraman J. Identification of Pak1 inhibitors using water thermodynamic analysis. J Biomol Struct Dyn 2019; 38:13-31. [PMID: 30661460 DOI: 10.1080/07391102.2019.1567393] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.
Collapse
Affiliation(s)
- Jayashree Biswal
- Department of Bioinformatics, Science Block Alagappa University, Karaikudi Tamil Nadu, India
| | - Prajisha Jayaprakash
- Department of Bioinformatics, Science Block Alagappa University, Karaikudi Tamil Nadu, India
| | - Rayala Suresh Kumar
- Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Ganesh Venkatraman
- Department of Human Genetics College of Biomedical Sciences, Sri Ramachandra University, Porur, Chennai, Tamil Nadu, India
| | - Saritha Poopandi
- Department of Bioinformatics, Science Block Alagappa University, Karaikudi Tamil Nadu, India
| | - Raghu Rangasamy
- Department of Bioinformatics, Science Block Alagappa University, Karaikudi Tamil Nadu, India
| | - Jeyakanthan Jeyaraman
- Department of Bioinformatics, Science Block Alagappa University, Karaikudi Tamil Nadu, India
| |
Collapse
|
27
|
Yin Z, Ai H, Zhang L, Ren G, Wang Y, Zhao Q, Liu H. Predicting the cytotoxicity of chemicals using ensemble learning methods and molecular fingerprints. J Appl Toxicol 2019; 39:1366-1377. [PMID: 30763981 DOI: 10.1002/jat.3785] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 01/14/2019] [Accepted: 01/14/2019] [Indexed: 12/12/2022]
Abstract
The prediction of compound cytotoxicity is an important part of the drug discovery process. However, it usually appears as poor predictive performance because the datasets are high-throughput and have a class-imbalance problem. In this study, several strategies of performing a structure-activity relationship study for a cytotoxic endpoint in the AID364 dataset were explored to solve the class-imbalance problem. Random forest adaboost was used as the base learners for 10 types of molecular fingerprints and an ensemble method and six data-balancing methods were applied to balance the classes. As a result, the ensemble model using MACCS fingerprint was found to be the best, giving area under the curve of 85.2% ± 0.35%, sensitivity of 81.8% ± 0.65%, and specificity of 76.0% ± 0.12% in fivefold cross-validation and area under the curve of 78.8%, sensitivity of 55.5% and specificity of 78.5% in external validation. Good performance also appeared on other datasets with different sizes/degrees of imbalance. To explore the structural commonality of cytotoxic compounds, several substructures were identified as an important reference for substructure alerts. The convincing results indicate that the proposed models are helpful in predicting the cytotoxicity of chemicals.
Collapse
Affiliation(s)
- Zimo Yin
- School of Information, Liaoning University, Shenyang, 110036, China
| | - Haixin Ai
- School of Life Science, Liaoning University, Shenyang, 110036, China.,Research Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China.,Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China
| | - Li Zhang
- School of Life Science, Liaoning University, Shenyang, 110036, China.,Research Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China.,Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China
| | - Guofei Ren
- School of Information, Liaoning University, Shenyang, 110036, China
| | - Yuming Wang
- Department of Breast Surgery, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, China
| | - Qi Zhao
- School of Mathematics, Liaoning University, Shenyang, 110036, China
| | - Hongsheng Liu
- School of Life Science, Liaoning University, Shenyang, 110036, China.,Research Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China.,Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China
| |
Collapse
|
28
|
Nittinger E, Gibbons P, Eigenbrot C, Davies DR, Maurer B, Yu CL, Kiefer JR, Kuglstatter A, Murray J, Ortwine DF, Tang Y, Tsui V. Water molecules in protein–ligand interfaces. Evaluation of software tools and SAR comparison. J Comput Aided Mol Des 2019; 33:307-330. [DOI: 10.1007/s10822-019-00187-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 01/24/2019] [Indexed: 01/08/2023]
|
29
|
Maurer M, Hansen N, Oostenbrink C. Comparison of free-energy methods using a tripeptide-water model system. J Comput Chem 2018; 39:2226-2242. [PMID: 30280398 PMCID: PMC6220940 DOI: 10.1002/jcc.25537] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Revised: 06/29/2018] [Accepted: 06/30/2018] [Indexed: 11/24/2022]
Abstract
We investigate the ability of several free-energy calculation methods to combine two alchemical changes. We use Bennett acceptance ratio (BAR), thermodynamic integration (TI), extended TI (X-TI), and enveloping distribution sampling (EDS) to perturb a water molecule, which is restrained to an amino acid that is also being perturbed. In addition to these pairwise methods, we present two two-dimensional approaches, EDS-TI and two-dimensional TI (2D-TI). We compare feasibility, efficiency and usability of these methods in regard to our simple model system, which mimics the displacement of a water molecule in the active site of a protein on residue mutation. The correct treatment of structural water has been shown to greatly aid binding affinity calculations in some cases that remained elusive otherwise. This is of broad interest in, for example, drug design, and we conclude that thus far, the pairwise method BAR and also the newer X-TI remain the most suitable methods to treat this problem as long as few end states are involved. © 2018 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Manuela Maurer
- Department of Material Sciences and Process EngineeringInstitute of Molecular Modeling and Simulation, University of Natural Resources and Life SciencesMuthgasse 18, A‐1190, ViennaAustria
| | - Niels Hansen
- Department of Energy‐, Process‐ and Bio‐Engineering, University of StuttgartInstitute of Thermodynamics and Thermal Process EngineeringPfaffenwaldring 9, 70569, StuttgartGermany
| | - Chris Oostenbrink
- Department of Material Sciences and Process EngineeringInstitute of Molecular Modeling and Simulation, University of Natural Resources and Life SciencesMuthgasse 18, A‐1190, ViennaAustria
| |
Collapse
|
30
|
Guedes IA, Pereira FSS, Dardenne LE. Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges. Front Pharmacol 2018; 9:1089. [PMID: 30319422 PMCID: PMC6165880 DOI: 10.3389/fphar.2018.01089] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Accepted: 09/07/2018] [Indexed: 12/19/2022] Open
Abstract
Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions.
Collapse
Affiliation(s)
- Isabella A Guedes
- Grupo de Modelagem Molecular em Sistemas Biológicos, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Felipe S S Pereira
- Grupo de Modelagem Molecular em Sistemas Biológicos, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Laurent E Dardenne
- Grupo de Modelagem Molecular em Sistemas Biológicos, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| |
Collapse
|
31
|
Matter H, Güssregen S. Characterizing hydration sites in protein-ligand complexes towards the design of novel ligands. Bioorg Med Chem Lett 2018; 28:2343-2352. [PMID: 29880400 DOI: 10.1016/j.bmcl.2018.05.061] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 05/28/2018] [Accepted: 05/30/2018] [Indexed: 11/18/2022]
Abstract
Water is an essential part of protein binding sites and mediates interactions to ligands. Its displacement by ligand parts affects the free binding energy of resulting protein-ligand complexes. Therefore the characterization of solvation properties is important for design. Of particular interest is the propensity of localized water to be favorably displaced by a ligand. This review discusses two popular computational approaches addressing these questions, namely WaterMap based on statistical mechanics analysis of MD simulations and 3D RISM based on integral equation theory of liquids. The theoretical background and recent applications in structure-based design will be presented.
Collapse
Affiliation(s)
- Hans Matter
- Sanofi-Aventis Deutschland GmbH, Integrated Drug Discovery (IDD), Synthetic Molecular Design, Building G838, Industriepark Höchst, 65926 Frankfurt am Main, Germany.
| | - Stefan Güssregen
- Sanofi-Aventis Deutschland GmbH, Integrated Drug Discovery (IDD), Synthetic Molecular Design, Building G838, Industriepark Höchst, 65926 Frankfurt am Main, Germany
| |
Collapse
|
32
|
Pantsar T, Poso A. Binding Affinity via Docking: Fact and Fiction. Molecules 2018; 23:molecules23081899. [PMID: 30061498 PMCID: PMC6222344 DOI: 10.3390/molecules23081899] [Citation(s) in RCA: 232] [Impact Index Per Article: 38.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 07/22/2018] [Accepted: 07/26/2018] [Indexed: 01/03/2023] Open
Abstract
In 1982, Kuntz et al. published an article with the title “A Geometric Approach to Macromolecule-Ligand Interactions”, where they described a method “to explore geometrically feasible alignment of ligands and receptors of known structure”. Since then, small molecule docking has been employed as a fast way to estimate the binding pose of a given compound within a specific target protein and also to predict binding affinity. Remarkably, the first docking method suggested by Kuntz and colleagues aimed to predict binding poses but very little was specified about binding affinity. This raises the question as to whether docking is the right tool to estimate binding affinity. The short answer is no, and this has been concluded in several comprehensive analyses. However, in this opinion paper we discuss several critical aspects that need to be reconsidered before a reliable binding affinity prediction through docking is realistic. These are not the only issues that need to be considered, but they are perhaps the most critical ones. We also consider that in spite of the huge efforts to enhance scoring functions, the accuracy of binding affinity predictions is perhaps only as good as it was 10–20 years ago. There are several underlying reasons for this poor performance and these are analyzed. In particular, we focus on the role of the solvent (water), the poor description of H-bonding and the lack of the systems’ true dynamics. We hope to provide readers with potential insights and tools to overcome the challenging issues related to binding affinity prediction via docking.
Collapse
Affiliation(s)
- Tatu Pantsar
- School of Pharmacy, University of Eastern Finland, P.O. BOX 1627, 70211 Kuopio, Finland.
| | - Antti Poso
- School of Pharmacy, University of Eastern Finland, P.O. BOX 1627, 70211 Kuopio, Finland.
- Department of Internal Medicine VIII, University Hospital Tübingen, Otfried-Müller-Strasse 14, 72076 Tübingen, Germany.
| |
Collapse
|
33
|
|
34
|
Iglesias J, Saen‐oon S, Soliva R, Guallar V. Computational structure‐based drug design: Predicting target flexibility. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2018. [DOI: 10.1002/wcms.1367] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
| | | | | | - Victor Guallar
- Life Science DepartmentBarcelonaSpain
- ICREA, Passeig Lluís Companys 23BarcelonaSpain
| |
Collapse
|
35
|
Leidner F, Kurt Yilmaz N, Paulsen J, Muller YA, Schiffer CA. Hydration Structure and Dynamics of Inhibitor-Bound HIV-1 Protease. J Chem Theory Comput 2018; 14:2784-2796. [PMID: 29570286 DOI: 10.1021/acs.jctc.8b00097] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Water is essential in many biological processes, and the hydration structure plays a critical role in facilitating protein folding, dynamics, and ligand binding. A variety of biophysical spectroscopic techniques have been used to probe the water solvating proteins, often complemented with molecular dynamics (MD) simulations to resolve the spatial and dynamic features of the hydration shell, but comparing relative water structure is challenging. In this study 1 μs MD simulations were performed to identify and characterize hydration sites around HIV-1 protease bound to an inhibitor, darunavir (DRV). The water density, hydration site occupancy, extent and anisotropy of fluctuations, coordinated water molecules, and hydrogen bonds were characterized and compared to the properties of bulk water. The water density of the principal hydration shell was found to be higher than bulk, dependent on the topology and physiochemical identity of the biomolecular surface. The dynamics of water molecules occupying principal hydration sites was highly dependent on the number of water-water interactions and inversely correlated with hydrogen bonds to the protein-inhibitor complex. While many waters were conserved following the symmetry of homodimeric HIV protease, the asymmetry induced by DRV resulted in asymmetric lower-occupancy hydration sites at the concave surface of the active site. Key interactions between water molecules and the protease, that stabilize the protein in the inhibited form, were altered in a drug resistant variant of the protease indicating that modulation of solvent-solute interactions might play a key role in conveying drug resistance. Our analysis provides insights into the interplay between an enzyme inhibitor complex and the hydration shell and has implications in elucidating water structure in a variety of biological processes and applications including ligand binding, inhibitor design, and resistance.
Collapse
Affiliation(s)
- Florian Leidner
- Department of Biochemistry and Molecular Pharmacology , University of Massachusetts Medical School , Worcester , Massachusetts 01605 , United States
| | - Nese Kurt Yilmaz
- Department of Biochemistry and Molecular Pharmacology , University of Massachusetts Medical School , Worcester , Massachusetts 01605 , United States
| | - Janet Paulsen
- Department of Biochemistry and Molecular Pharmacology , University of Massachusetts Medical School , Worcester , Massachusetts 01605 , United States
| | - Yves A Muller
- Division of Biotechnology , Friedrich-Alexander-Universität Erlangen-Nürnberg , Erlangen 91052 , Germany
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology , University of Massachusetts Medical School , Worcester , Massachusetts 01605 , United States
| |
Collapse
|