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Bairagya HR. Dynamics of nucleoplasm in human leukemia cells: A thrust towards designing anti-leukemic agents. J Mol Graph Model 2024; 131:108807. [PMID: 38908255 DOI: 10.1016/j.jmgm.2024.108807] [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: 03/04/2024] [Revised: 04/20/2024] [Accepted: 06/02/2024] [Indexed: 06/24/2024]
Abstract
The human inosine monophosphate dehydrogenase (hIMPDH) is a metabolic enzyme that possesses a unique ability to self-assemble into higher-order structures, forming cytoophidia. The hIMPDH II isoform is more active in chronic myeloid leukemia (CML) cancer cells, making it a promising target for anti-leukemic therapy. However, the structural details and molecular mechanisms of the dynamics of hIMPDHcytoophidia assembly in vitro need to be better understood, and it is crucial to reconstitute the computational nucleoplasm model with cytophilic-like polymers in vitro to characterize their structure and function. Finally, a computational model and its dynamics of the nucleoplasm for CML cells have been proposed in this short review. This research on nucleoplasm aims to aid the scientific community's understanding of how metabolic enzymes like hIMPDH function in cancer and normal cells. However, validating and justifying the computational results from modeling and simulation with experimental data is essential. The new insights gained from this research could explain the structure/topology, geometrical, and electronic consequences of hIMPDH inhibitors on leukemic and normal cells. They could lead to further advancements in the knowledge of nucleoplasmic chemical reaction dynamics.
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Affiliation(s)
- Hridoy R Bairagya
- Computational Drug Design and Bio-molecular Simulation Lab, Department of Bioinformatics, Maulana Abul Kalam Azad University of Technology, West Bengal, 741249, India.
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2
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Accordino SR, Alarcón LM, Loubet NA, Appignanesi GA. Water at the nanoscale: From filling or dewetting hydrophobic pores and carbon nanotubes to "sliding" on graphene. J Chem Phys 2024; 161:044504. [PMID: 39037145 DOI: 10.1063/5.0215579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 07/08/2024] [Indexed: 07/23/2024] Open
Abstract
In this work, we study the effect of nanoconfinement on the hydration properties of model hydrophobic pores and carbon nanotubes, determining their wetting propensity and the conditions for geometrically induced dehydration. By employing a recently introduced water structural index, we aim at two main goals: (1) to accurately quantify the local hydrophobicity and predict the drying transitions in such systems, and (2) to provide a molecular rationalization of the wetting process. In this sense, we will further discuss the number and strength of the interactions required by the water molecules to promote wetting. In the case of graphene-like surfaces, an explanation for their unexpectedly significant hydrophilicity will also be provided. On the one hand, the structural index will show that the net attraction to the dense carbon network that a water molecule experiences through several simultaneous weak interactions is sufficient to give rise to hydrophilic behavior. On the other hand, we will show that an additional effect is also at play: the hydrating water molecule is retained on the surface by a smooth exchange of such simultaneous weak interactions, as if "sliding" on graphene.
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Affiliation(s)
- Sebastián R Accordino
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
| | - Laureano M Alarcón
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
| | - Nicolás A Loubet
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
| | - Gustavo A Appignanesi
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
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Mehrani R, Mondal J, Ghazanfari D, Goetz DJ, McCall KD, Bergmeier SC, Sharma S. Capturing the Effects of Single Atom Substitutions on the Inhibition Efficiency of Glycogen Synthase Kinase-3β Inhibitors via Markov State Modeling and Experiments. J Chem Theory Comput 2024; 20:6278-6286. [PMID: 38975986 DOI: 10.1021/acs.jctc.4c00311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
Small modifications in the chemical structure of ligands are known to dramatically change their ability to inhibit the activity of a protein. Unraveling the mechanisms that govern these dramatic changes requires scrutinizing the dynamics of protein-ligand binding and unbinding at the atomic level. As an exemplary case, we have studied Glycogen Synthase Kinase-3β (GSK-3β), a multifunctional kinase that has been implicated in a host of pathological processes. As such, there is a keen interest in identifying ligands that inhibit GSK-3β activity. One family of compounds that are highly selective and potent inhibitors of GSK-3β is exemplified by a molecule termed COB-187. COB-187 consists of a five-member heterocyclic ring with a thione at C2, a pyridine substituted methyl at N3, and a hydroxyl and phenyl at C4. We have studied the inhibition of GSK-3β by COB-187-related ligands that differ in a single heavy atom from each other (either in the location of nitrogen in their pyridine ring, or with the pyridine ring replaced by a phenyl ring), or in the length of the alkyl group joining the pyridine and the N3. The inhibition experiments show a large range of half-maximal inhibitory concentration (IC50) values from 10 nM to 10 μM, implying that these ligands exhibit vastly different propensities to inhibit GSK-3β. To explain these differences, we perform Markov State Modeling (MSM) using fully atomistic simulations. Our MSM results are in excellent agreement with the experiments in that they accurately capture differences in the binding propensities of the ligands. The simulations show that the binding propensities are related to the ligands' ability to attain a compact conformation where their two aromatic rings are spatially close. We rationalize this result by sampling numerous binding and unbinding events via funnel metadynamics simulations, which show that indeed while approaching the bound state, the ligands prefer to be in their compact conformation. We find that the presence of nitrogen in the aromatic ring increases the probability of attaining the compact conformation. Protein-ligand binding is understood to be dictated by the energetics of interactions and entropic factors, like the release of bound water from the binding pockets. This work shows that changes in the conformational distribution of ligands due to atom-level modifications in the structure play an important role in protein-ligand binding.
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Affiliation(s)
- Ramin Mehrani
- Department of Mechanical Engineering, Ohio University, Athens, Ohio 45701, United States
| | - Jagannath Mondal
- Center for Interdisciplinary Sciences, Tata Institute of Fundamental Research, Hyderabad 500046, India
| | - Davoud Ghazanfari
- Department of Chemical and Biomolecular Engineering, Ohio University, Athens, Ohio 45701, United States
| | - Douglas J Goetz
- Department of Chemical and Biomolecular Engineering, Ohio University, Athens, Ohio 45701, United States
- Biomedical Engineering Program, Ohio University, Athens, Ohio 45701, United States
| | - Kelly D McCall
- Biomedical Engineering Program, Ohio University, Athens, Ohio 45701, United States
- Department of Specialty Medicine, Ohio University, Athens, Ohio 45701, United States
- The Diabetes Institute, Ohio University, Athens, Ohio 45701, United States
- Molecular and Cellular Biology Program, Ohio University, Athens, Ohio 45701, United States
- Translational Biomedical Sciences Program, Ohio University, Athens, Ohio 45701, United States
| | - Stephen C Bergmeier
- Biomedical Engineering Program, Ohio University, Athens, Ohio 45701, United States
- Department of Chemistry and Biochemistry, Ohio University, Athens, Ohio 45701, United States
| | - Sumit Sharma
- Department of Chemical and Biomolecular Engineering, Ohio University, Athens, Ohio 45701, United States
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4
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Zhang H, Liu X, Cheng W, Wang T, Chen Y. Prediction of drug-target binding affinity based on deep learning models. Comput Biol Med 2024; 174:108435. [PMID: 38608327 DOI: 10.1016/j.compbiomed.2024.108435] [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: 01/29/2024] [Revised: 04/05/2024] [Accepted: 04/07/2024] [Indexed: 04/14/2024]
Abstract
The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, these techniques have not succeeded in reversing the low success rate of new drug development. In recent years, the continuous development of deep learning (DL) technology has brought new opportunities for drug discovery through the DTA prediction. This shift has moved the prediction of DTA from traditional machine learning methods to DL. The DL frameworks used for DTA prediction include convolutional neural networks (CNN), graph convolutional neural networks (GCN), and recurrent neural networks (RNN), and reinforcement learning (RL), among others. This review article summarizes the available literature on DTA prediction using DL models, including DTA quantification metrics and datasets, and DL algorithms used for DTA prediction (including input representation of models, neural network frameworks, valuation indicators, and model interpretability). In addition, the opportunities, challenges, and prospects of the application of DL frameworks for DTA prediction in the field of drug discovery are discussed.
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Affiliation(s)
- Hao Zhang
- College of Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xiaoqian Liu
- College of Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wenya Cheng
- College of Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Tianshi Wang
- College of Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuanyuan Chen
- College of Science, Nanjing Agricultural University, Nanjing, 210095, China.
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5
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Loubet NA, Verde AR, Appignanesi GA. A water structure indicator suitable for generic contexts: Two-liquid behavior at hydration and nanoconfinement conditions and a molecular approach to hydrophobicity and wetting. J Chem Phys 2024; 160:144502. [PMID: 38587223 DOI: 10.1063/5.0203989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 03/25/2024] [Indexed: 04/09/2024] Open
Abstract
In a recent work, we have briefly introduced a new structural index for water that, unlike previous indicators, was devised specifically for generic contexts beyond bulk conditions, making it suitable for hydration and nanoconfinement settings. In this work, we shall study this metric in detail, demonstrating its ability to reveal the existence of a fine-tuned interplay between the local structure and energetics in liquid water. This molecular principle enables the establishment of an extended hydrogen bond network, while simultaneously allowing for the existence of network defects by compensating for uncoordinated sites. By studying different water models and different temperatures encompassing both the normal liquid and the supercooled regime, this molecular mechanism will be shown to underlie the two-state behavior of bulk water. In addition, by studying functionalized self-assembled monolayers and diverse graphene-like surfaces, we shall show that this principle is also operative at hydration and nanoconfinement conditions, thus generalizing the validity of the two-liquid scenario of water to these contexts. This approach will allow us to define conditions for wettability, providing an accurate measure of hydrophobicity and a reliable predictor of filling and drying transitions. Hence, it might open the possibility of elucidating the active role of water in the broad fields of biophysics and materials science. As a preliminary step, we shall study the hydration structure and hydrophilicity of graphene-like systems (parallel graphene sheets and carbon nanotubes) as a function of the confinement dimensionality.
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Affiliation(s)
- Nicolás A Loubet
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
| | - Alejandro R Verde
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
| | - Gustavo A Appignanesi
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
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6
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Zhang Y, Zhou C. PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction. J Bioinform Comput Biol 2024; 22:2450004. [PMID: 38812467 DOI: 10.1142/s0219720024500045] [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] [Indexed: 05/31/2024]
Abstract
Biomolecular interaction recognition between ligands and proteins is an essential task, which largely enhances the safety and efficacy in drug discovery and development stage. Studying the interaction between proteins and ligands can improve the understanding of disease pathogenesis and lead to more effective drug targets. Additionally, it can aid in determining drug parameters, ensuring proper absorption, distribution, and metabolism within the body. Due to incomplete feature representation or the model's inadequate adaptation to protein-ligand complexes, the existing methodologies suffer from suboptimal predictive accuracy. To address these pitfalls, in this study, we designed a new deep learning method based on transformer and GCN. We first utilized the transformer network to grasp crucial information of the original protein sequences within the smile sequences and connected them to prevent falling into a local optimum. Furthermore, a series of dilation convolutions are performed to obtain the pocket features and smile features, subsequently subjected to graphical convolution to optimize the connections. The combined representations are fed into the proposed model for classification prediction. Experiments conducted on various protein-ligand binding prediction methods prove the effectiveness of our proposed method. It is expected that the PfgPDI can contribute to drug prediction and accelerate the development of new drugs, while also serving as a valuable partner for drug testing and Research and Development engineers.
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Affiliation(s)
- Yiqian Zhang
- School of Electrical and Information, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Changjian Zhou
- Department of Data and Computing, Northeast Agricultural University, Harbin 150030, P. R. China
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7
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Kaczor AA, Zięba A, Matosiuk D. The application of WaterMap-guided structure-based virtual screening in novel drug discovery. Expert Opin Drug Discov 2024; 19:73-83. [PMID: 37807912 DOI: 10.1080/17460441.2023.2267015] [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: 07/17/2023] [Accepted: 10/02/2023] [Indexed: 10/10/2023]
Abstract
INTRODUCTION Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface. AREAS COVERED In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023. EXPERT OPINION In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.
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Affiliation(s)
- Agnieszka A Kaczor
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Agata Zięba
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
| | - Dariusz Matosiuk
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
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Yoshida S, Sako Y, Nikaido E, Ueda T, Kozono I, Ichihashi Y, Nakahashi A, Onishi M, Yamatsu Y, Kato T, Nishikawa J, Tachibana Y. Peptide-to-Small Molecule: Discovery of Non-Covalent, Active-Site Inhibitors of β-Herpesvirus Proteases. ACS Med Chem Lett 2023; 14:1558-1566. [PMID: 37974946 PMCID: PMC10641906 DOI: 10.1021/acsmedchemlett.3c00359] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 10/21/2023] [Accepted: 10/24/2023] [Indexed: 11/19/2023] Open
Abstract
Viral proteases, the key enzymes that regulate viral replication and assembly, are promising targets for antiviral drug discovery. Herpesvirus proteases are enzymes with no crystallographically confirmed noncovalent active-site binders, owing to their shallow and polar substrate-binding pockets. Here, we applied our previously reported "Peptide-to-Small Molecule" strategy to generate novel inhibitors of β-herpesvirus proteases. Rapid selection with a display technology was used to identify macrocyclic peptide 1 bound to the active site of human cytomegalovirus protease (HCMVPro) with high affinity, and pharmacophore queries were defined based on the results of subsequent intermolecular interaction analyses. Membrane-permeable small molecule 19, designed de novo according to this hypothesis, exhibited enzyme inhibitory activity (IC50 = 10-6 to 10-7 M) against β-herpesvirus proteases, and the design concept was proved by X-ray cocrystal analysis.
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Affiliation(s)
- Shuhei Yoshida
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yusuke Sako
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Eiji Nikaido
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Taichi Ueda
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Iori Kozono
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yusuke Ichihashi
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Atsufumi Nakahashi
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Motoyasu Onishi
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yukiko Yamatsu
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Teruhisa Kato
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Junichi Nishikawa
- PeptiDream
Inc., 3-25-23 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-0821, Japan
| | - Yuki Tachibana
- Pharmaceutical
Research Division, Shionogi Pharmaceutical
Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
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Grimm LM, Setiadi J, Tkachenko B, Schreiner PR, Gilson MK, Biedermann F. The temperature-dependence of host-guest binding thermodynamics: experimental and simulation studies. Chem Sci 2023; 14:11818-11829. [PMID: 37920355 PMCID: PMC10619620 DOI: 10.1039/d3sc01975f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 09/24/2023] [Indexed: 11/04/2023] Open
Abstract
The thermodynamic parameters of host-guest binding can be used to describe, understand, and predict molecular recognition events in aqueous systems. However, interpreting binding thermodynamics remains challenging, even for these relatively simple molecules, as they are determined by both direct and solvent-mediated host-guest interactions. In this contribution, we focus on the contributions of water to binding by studying binding thermodynamics, both experimentally and computationally, for a series of nearly rigid, electrically neutral host-guest systems and report the temperature-dependent thermodynamic binding contributions ΔGb(T), ΔHb(T), ΔSb(T), and ΔCp,b. Combining isothermal titration calorimetry (ITC) measurements with molecular dynamics (MD) simulations, we provide insight into the binding forces at play for the macrocyclic hosts cucurbit[n]uril (CBn, n = 7-8) and β-cyclodextrin (β-CD) with a range of guest molecules. We find consistently negative changes in heat capacity on binding (ΔCp,b) for all systems studied herein - as well as for literature host-guest systems - indicating increased enthalpic driving forces for binding at higher temperatures. We ascribe these trends to solvation effects, as the solvent properties of water deteriorate as temperature rises. Unlike the entropic and enthalpic contributions to binding, with their differing signs and magnitudes for the classical and non-classical hydrophobic effect, heat capacity changes appear to be a unifying and more general feature of host-guest complex formation in water. This work has implications for understanding protein-ligand interactions and other complex systems in aqueous environments.
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Affiliation(s)
- Laura M Grimm
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT) Hermann-von-Helmholtz Platz 1 76344 Eggenstein-Leopoldshafen Germany
| | - Jeffry Setiadi
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego 9255 Pharmacy Lane La Jolla CA 92093 USA
| | - Boryslav Tkachenko
- Institute of Organic Chemistry, Justus Liebig University Giessen Heinrich-Buff-Ring 17 35392 Giessen Germany
| | - Peter R Schreiner
- Institute of Organic Chemistry, Justus Liebig University Giessen Heinrich-Buff-Ring 17 35392 Giessen Germany
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego 9255 Pharmacy Lane La Jolla CA 92093 USA
| | - Frank Biedermann
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT) Hermann-von-Helmholtz Platz 1 76344 Eggenstein-Leopoldshafen Germany
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Pourhajibagher M, Bahador A. Natural photosensitizers potentiate the targeted antimicrobial photodynamic therapy as the Monkeypox virus entry inhibitors: An in silico approach. Photodiagnosis Photodyn Ther 2023; 43:103656. [PMID: 37336465 PMCID: PMC10275794 DOI: 10.1016/j.pdpdt.2023.103656] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/13/2023] [Accepted: 06/13/2023] [Indexed: 06/21/2023]
Abstract
BACKGROUND Monkeypox is a viral zoonotic disease that has emerged as a threat to public health. Currently, there is no treatment approved specifically targeting Monkeypox disease. Hence, it is essential to identify and develop therapeutic approaches to the Monkeypox virus. In the current in silico paper, we comprehensively involve using computer simulations and modeling to insights and predict hypotheses on the potential of natural photosensitizers-mediated targeted antimicrobial photodynamic therapy (aPDT) against D8L as a Monkeypox virus protein involved in viral cell entry. MATERIALS AND METHODS In the current study, computational techniques such as molecular docking were combined with in silico ADMET predictions to examine how Curcumin (Cur), Quercetin (Qct), and Riboflavin (Rib) as the natural photosensitizers bind to the D8L protein in Monkeypox virus, as well as to determine pharmacokinetic properties of these photosensitizers. RESULTS The three-dimensional structure of the D8L protein in the Monkeypox virus was constructed using homology modeling (PDB ID: 4E9O). According to the physicochemical properties and functional characterization, 4E9O was a stable protein with the nature of a hydrophilic structure. The docking studies employing a three-dimensional model of 4E9O with natural photosensitizers exhibited good binding affinity. D8L protein illustrated the best docking score (-7.6 kcal/mol) in relation to the Rib and displayed good docking scores in relation to the Cur (-7.0 kcal/mol) and Qct (-7.5 kcal/mol). CONCLUSIONS The findings revealed that all three photosensitizers were found to obey the criteria of Lipinski's rule of five and displayed drug-likeness. Moreover, all the tested photosensitizers were found to be non-hepatotoxic and non-cytotoxic. In summary, our investigation identified Cur, Qct, and Rib could efficiently interact with D8L protein with a strong binding affinity. It can be concluded that aPDT using these natural photosensitizers may be considered an adjuvant treatment against Monkeypox disease.
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Affiliation(s)
- Maryam Pourhajibagher
- Dental Research Center, Dentistry Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Abbas Bahador
- Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Fellowship in Clinical Laboratory Sciences, BioHealth Lab, Tehran, Iran.
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11
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Afshinpour M, Parsi P, Mahdiuni H. Investigation of molecular details of a bacterial cationic amino acid transporter (GkApcT) during arginine transportation using molecular dynamics simulation and umbrella sampling techniques. J Mol Model 2023; 29:260. [PMID: 37479900 DOI: 10.1007/s00894-023-05670-w] [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: 05/01/2023] [Accepted: 07/17/2023] [Indexed: 07/23/2023]
Abstract
CONTEXT Cationic amino acid transporters (CATs) facilitate arginine transport across membranes and maintain its levels in various tissues and organs, but their overexpression has been associated with severe cancers. A recent study identified the alternating access mechanism and critical residues involved in arginine transportation in a cationic amino acid transporter from Geobacillus kaustophilus (GkApcT). Here, we used molecular dynamics (MD) simulation methods to investigate the transportation mechanism of arginine (Arg) through GkApcT. The results revealed that arginine strongly interacts with specific binding site residues (Thr43, Asp111, Glu115, Lys191, Phe231, Ile234, and Asp237). Based on the umbrella sampling, the main driving force for arginine transport is the polar interactions of the arginine with channel-lining residues. An in-depth description of the dissociation mechanism and binding energy analysis brings valuable insight into the interactions between arginine and transporter residues, facilitating the design of effective CAT inhibitors in cancer cells. METHODS The membrane-protein system was constructed by uploading the prokaryotic CAT (PDB ID: 6F34) to the CHARMM-GUI web server. Molecular dynamics simulations were done using the GROMACS package, version 5.1.4, with the CHARMM36 force field and TIP3P water model. The MM-PBSA approach was performed for determining the arginine binding free energy. Furthermore, the hotspot residues were identified through per-residue decomposition analysis. The characteristics of the channel such as bottleneck radius and channel length were analyzed using the CaverWeb 1.1 web server. The proton wire inside the transporter was investigated based on the classic Grotthuss mechanism. We also investigated the atomistic details of arginine transportation using the path-based free energy umbrella sampling technique (US).
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Affiliation(s)
- Maral Afshinpour
- Bioinformatics Lab, Department of Biology, School of Sciences, Razi University, P.O. Box, Kermanshah, 67149-67346, Iran
- Department of Chemistry and Biochemistry, South Dakota State University (SDSU), Brookings, SD, USA
| | - Parinaz Parsi
- Bioinformatics Lab, Department of Biology, School of Sciences, Razi University, P.O. Box, Kermanshah, 67149-67346, Iran
| | - Hamid Mahdiuni
- Bioinformatics Lab, Department of Biology, School of Sciences, Razi University, P.O. Box, Kermanshah, 67149-67346, Iran.
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12
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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.
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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
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13
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Jin Z, Wu T, Chen T, Pan D, Wang X, Xie J, Quan L, Lyu Q. CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism. Bioinformatics 2023; 39:6998204. [PMID: 36688724 PMCID: PMC9900214 DOI: 10.1093/bioinformatics/btad049] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/07/2023] [Accepted: 01/21/2023] [Indexed: 01/24/2023] Open
Abstract
MOTIVATION Accurate and rapid prediction of protein-ligand binding affinity is a great challenge currently encountered in drug discovery. Recent advances have manifested a promising alternative in applying deep learning-based computational approaches for accurately quantifying binding affinity. The structure complementarity between protein-binding pocket and ligand has a great effect on the binding strength between a protein and a ligand, but most of existing deep learning approaches usually extracted the features of pocket and ligand by these two detached modules. RESULTS In this work, a new deep learning approach based on the cross-attention mechanism named CAPLA was developed for improved prediction of protein-ligand binding affinity by learning features from sequence-level information of both protein and ligand. Specifically, CAPLA employs the cross-attention mechanism to capture the mutual effect of protein-binding pocket and ligand. We evaluated the performance of our proposed CAPLA on comprehensive benchmarking experiments on binding affinity prediction, demonstrating the superior performance of CAPLA over state-of-the-art baseline approaches. Moreover, we provided the interpretability for CAPLA to uncover critical functional residues that contribute most to the binding affinity through the analysis of the attention scores generated by the cross-attention mechanism. Consequently, these results indicate that CAPLA is an effective approach for binding affinity prediction and may contribute to useful help for further consequent applications. AVAILABILITY AND IMPLEMENTATION The source code of the method along with trained models is freely available at https://github.com/lennylv/CAPLA. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Zhi Jin
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Tingfang Wu
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.,Province Key Lab for Information Processing Technologies, Soochow University, Suzhou 215006, China.,Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China
| | - Taoning Chen
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Deng Pan
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Xuejiao Wang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Jingxin Xie
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Lijun Quan
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.,Province Key Lab for Information Processing Technologies, Soochow University, Suzhou 215006, China.,Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China
| | - Qiang Lyu
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.,Province Key Lab for Information Processing Technologies, Soochow University, Suzhou 215006, China.,Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China
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14
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Chen W, He H, Wang J, Wang J, Chang CEA. Uncovering water effects in protein-ligand recognition: importance in the second hydration shell and binding kinetics. Phys Chem Chem Phys 2023; 25:2098-2109. [PMID: 36562309 PMCID: PMC9970846 DOI: 10.1039/d2cp04584b] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Developing a ligand with high affinity for a specific protein target is essential for drug design, and water molecules are well known to play a key role in protein-drug recognition. However, predicting the role of particularly ordered water molecules in drug binding remains challenging. Furthermore, hydration free energy contributed from the water network, including the second shell of water molecules, is far from being well studied. In this research we focused on these aspects to accurately and efficiently evaluate water effects in protein-ligand binding affinity. We developed a new strategy using a free-energy calculation method, VM2. We successfully predicted the stable ordered water molecules in a number of protein systems: PDE 10a, HSP90, tryptophan synthase (TRPS), CDK2 and Factor Xa. In some of these, the second shell of water molecules appeared to be critical in protein-ligand binding. We also applied the strategy to largely improve binding free energy calculation using the MM/PBSA method. When applying MM/PBSA alone for two systems, CDK2 and Factor Xa, the computed binding free energy resulted in poor to moderate R2 values with experimental data. However, including water free energy correction greatly improved the free energy calculation. Furthermore, our work helped to explain how xk263 is a 1000 times faster binder to HIVp than ritonavir, a potentially useful tool for investigating binding kinetics. Our studies reveal the importance of fully considering water effects in therapeutic developments in pharmaceutical and biotechnology industries and for fundamental research in protein-ligand recognition.
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Affiliation(s)
- Wei Chen
- School of Pharmacy, Fuzhou Medical College of NanChang University, Fuzhou, JiangXi 344000, P. R. China.
| | - Huan He
- School of Pharmacy, Fuzhou Medical College of NanChang University, Fuzhou, JiangXi 344000, P. R. China.
| | - Jing Wang
- School of Pharmacy, Fuzhou Medical College of NanChang University, Fuzhou, JiangXi 344000, P. R. China.
| | - Jiahui Wang
- School of Pharmacy, Fuzhou Medical College of NanChang University, Fuzhou, JiangXi 344000, P. R. China.
| | - Chia-en A. Chang
- Department of Chemistry, University of California at Riverside, Riverside, CA 92521, USA,Corresponding Authors Wei Chen: School of Pharmacy, Fuzhou Medical College of NanChang University, Fuzhou, JiangXi 344000, China. , Chia-en A. Chang: Department of Chemistry, University of California at Riverside, Riverside, CA 92521, USA.
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15
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Chang Y, Hawkins BA, Du JJ, Groundwater PW, Hibbs DE, Lai F. A Guide to In Silico Drug Design. Pharmaceutics 2022; 15:pharmaceutics15010049. [PMID: 36678678 PMCID: PMC9867171 DOI: 10.3390/pharmaceutics15010049] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/16/2022] [Accepted: 12/17/2022] [Indexed: 12/28/2022] Open
Abstract
The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.
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Affiliation(s)
- Yiqun Chang
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Bryson A. Hawkins
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Jonathan J. Du
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Paul W. Groundwater
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - David E. Hibbs
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Felcia Lai
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
- Correspondence:
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16
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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.
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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
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17
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Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:5104464. [PMID: 36226242 PMCID: PMC9550495 DOI: 10.1155/2022/5104464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 09/15/2022] [Indexed: 11/17/2022]
Abstract
Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules' physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins' binding sites.
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18
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Yoshida S, Uehara S, Kondo N, Takahashi Y, Yamamoto S, Kameda A, Kawagoe S, Inoue N, Yamada M, Yoshimura N, Tachibana Y. Peptide-to-Small Molecule: A Pharmacophore-Guided Small Molecule Lead Generation Strategy from High-Affinity Macrocyclic Peptides. J Med Chem 2022; 65:10655-10673. [PMID: 35904556 DOI: 10.1021/acs.jmedchem.2c00919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Recent technological innovations have led to the development of methods for the rapid identification of high-affinity macrocyclic peptides for a wide range of targets; however, it is still challenging to achieve the desired activity and membrane permeability at the same time. Here, we propose a novel small molecule lead discovery strategy, ″Peptide-to-Small Molecule″, which is a combination of rapid identification of high-affinity macrocyclic peptides via peptide display screening followed by pharmacophore-guided de novo design of small molecules, and demonstrate the applicability using nicotinamide N-methyltransferase (NNMT) as a target. Affinity selection by peptide display technology identified macrocyclic peptide 1 that exhibited good enzymatic inhibitory activity but no cell-based activity. Thereafter, a peptide pharmacophore-guided de novo design and further structure-based optimization resulted in highly potent and cell-active small molecule 14 (cell-free IC50 = 0.0011 μM, cell-based IC50 = 0.40 μM), indicating that this strategy could be a new option for drug discovery.
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Affiliation(s)
- Shuhei Yoshida
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shota Uehara
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Noriyasu Kondo
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yu Takahashi
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shiho Yamamoto
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Atsushi Kameda
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Soichiro Kawagoe
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Naoko Inoue
- PeptiDream Inc. 3-25-23 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-0821, Japan
| | - Masami Yamada
- PeptiDream Inc. 3-25-23 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-0821, Japan
| | - Norito Yoshimura
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yuki Tachibana
- Pharmaceutical Research Division, Shionogi Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
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19
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Umar AB, Uzairu A, Shallangwa GA, Uba S. Ligand-based drug design and molecular docking simulation studies of some novel anticancer compounds on MALME-3M melanoma cell line. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2021. [DOI: 10.1186/s43042-020-00126-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Melanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy. The pGI50 anticancer activity values of 70 compounds from the NCI (National Cancer Institute) on MALME-3M cell line was modeled to describe the quantitative structure-activity relationships (QSARs) of the compounds, and some selected compounds were docked.
Results
The generated QSAR model was found to be statistically significant based on the obtained values of the validation keys such as R2 (0.885), $$ {R}_{\mathrm{adjusted}}^2 $$
R
adjusted
2
(0.868), Q2cv (0.842), and $$ {R}_{pred}^2 $$
R
pred
2
(0.738) required to evaluate the strength and robustness of QSAR model. Compound 39 was selected as a template due to its good pGI50 (9.205) and was modified to design new potent compounds. The predicted pGI50 activity of the designed compounds by the built model was N1 (9.836), N2 (12.876), N3 (10.901), and N4 (11.263) respectively. These proposed compounds were docked with V600E-BRAF receptor and the result shows that, N1, N2, N3, and N4 with free binding energy (FBE) of − 11.7 kcal mol−1, − 12.8 kcal mol−1, − 12.7 kcal mol−1, and − 12.9 kcal mol−1 respectively were better than the parent structure of the template (compound 39, FBE = − 7.0 kcal mol−1) and the standard V600E-BRAF inhibitor (Vemurafenib, FBE = − 11.3 kcal mol−1). Additionally, these compounds passed the drug-likeness criteria successfully to be orally bioavailable.
Conclusion
The proposed compounds were considered optimal as their performances are comparable to vemurafenib and possessed enhanced physicochemical properties. Thus recommends further research such as synthesis, in vivo, and ex-vivo evaluation.
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20
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Corti HR, Appignanesi GA, Barbosa MC, Bordin JR, Calero C, Camisasca G, Elola MD, Franzese G, Gallo P, Hassanali A, Huang K, Laria D, Menéndez CA, de Oca JMM, Longinotti MP, Rodriguez J, Rovere M, Scherlis D, Szleifer I. Structure and dynamics of nanoconfined water and aqueous solutions. THE EUROPEAN PHYSICAL JOURNAL. E, SOFT MATTER 2021; 44:136. [PMID: 34779954 DOI: 10.1140/epje/s10189-021-00136-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 10/06/2021] [Indexed: 06/13/2023]
Abstract
This review is devoted to discussing recent progress on the structure, thermodynamic, reactivity, and dynamics of water and aqueous systems confined within different types of nanopores, synthetic and biological. Currently, this is a branch of water science that has attracted enormous attention of researchers from different fields interested to extend the understanding of the anomalous properties of bulk water to the nanoscopic domain. From a fundamental perspective, the interactions of water and solutes with a confining surface dramatically modify the liquid's structure and, consequently, both its thermodynamical and dynamical behaviors, breaking the validity of the classical thermodynamic and phenomenological description of the transport properties of aqueous systems. Additionally, man-made nanopores and porous materials have emerged as promising solutions to challenging problems such as water purification, biosensing, nanofluidic logic and gating, and energy storage and conversion, while aquaporin, ion channels, and nuclear pore complex nanopores regulate many biological functions such as the conduction of water, the generation of action potentials, and the storage of genetic material. In this work, the more recent experimental and molecular simulations advances in this exciting and rapidly evolving field will be reported and critically discussed.
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Affiliation(s)
- Horacio R Corti
- Departmento de Física de la Materia Condensada & Instituto de Nanociencia y Nanotecnología (CNEA-CONICET), Comisión Nacional de Energía Atómica, B1650LWP, Buenos Aires, Argentina.
| | - Gustavo A Appignanesi
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, 8000, Bahía Blanca, Argentina
| | - Marcia C Barbosa
- Institute of Physics, Federal University of Rio Grande do Sul, 91501-970, Porto Alegre, Brazil
| | - J Rafael Bordin
- Department of Physics, Institute of Physics and Mathematics, 96050-500, Pelotas, RS, Brazil
| | - Carles Calero
- Secció de Física Estadística i Interdisciplinària - Departament de Física de la Matèria Condensada, Universitat de Barcelona & Institut de Nanociència i Nanotecnologia (IN2UB), Universitat de Barcelona, 08028, Barcelona, Spain
| | - Gaia Camisasca
- Dipartimento di Matematica e Fisica, Università degli Studi Roma Tre, 00146, Roma, Italy
| | - M Dolores Elola
- Departmento de Física de la Materia Condensada & Instituto de Nanociencia y Nanotecnología (CNEA-CONICET), Comisión Nacional de Energía Atómica, B1650LWP, Buenos Aires, Argentina
| | - Giancarlo Franzese
- Secció de Física Estadística i Interdisciplinària - Departament de Física de la Matèria Condensada, Universitat de Barcelona & Institut de Nanociència i Nanotecnologia (IN2UB), Universitat de Barcelona, 08028, Barcelona, Spain
| | - Paola Gallo
- Dipartimento di Matematica e Fisica, Università degli Studi Roma Tre, 00146, Roma, Italy
| | - Ali Hassanali
- Condensed Matter and Statistical Physics Section (CMSP), The International Center for Theoretical Physics (ICTP), Trieste, Italy
| | - Kai Huang
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Daniel Laria
- Departmento de Física de la Materia Condensada & Instituto de Nanociencia y Nanotecnología (CNEA-CONICET), Comisión Nacional de Energía Atómica, B1650LWP, Buenos Aires, Argentina
- Instituto de Química Física de los Materiales, Medio Ambiente y Energía (INQUIMAE-CONICET), Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Cintia A Menéndez
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, 8000, Bahía Blanca, Argentina
| | - Joan M Montes de Oca
- INQUISUR, Departamento de Química, Universidad Nacional del Sur (UNS)-CONICET, 8000, Bahía Blanca, Argentina
| | - M Paula Longinotti
- Instituto de Química Física de los Materiales, Medio Ambiente y Energía (INQUIMAE-CONICET), Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Javier Rodriguez
- Departmento de Física de la Materia Condensada & Instituto de Nanociencia y Nanotecnología (CNEA-CONICET), Comisión Nacional de Energía Atómica, B1650LWP, Buenos Aires, Argentina
- Escuela de Ciencia y Tecnología, Universidad Nacional de General San Martín, San Martín, Buenos Aires, Argentina
| | - Mauro Rovere
- Dipartimento di Matematica e Fisica, Università degli Studi Roma Tre, 00146, Roma, Italy
| | - Damián Scherlis
- Instituto de Química Física de los Materiales, Medio Ambiente y Energía (INQUIMAE-CONICET), Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Igal Szleifer
- Biomedical Engineering Department, Northwestern University, Evanston, USA
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21
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Zhou S, Zhang Y, Cheng LT, Li B. Prediction of multiple dry-wet transition pathways with a mesoscale variational approach. J Chem Phys 2021; 155:124110. [PMID: 34598586 DOI: 10.1063/5.0061773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Water fluctuates in a hydrophobic confinement, forming multiple dry and wet hydration states through evaporation and condensation. Transitions between such states are critical to both thermodynamics and kinetics of solute molecular processes, such as protein folding and protein-ligand binding and unbinding. To efficiently predict such dry-wet transition paths, we develop a hybrid approach that combines a variational implicit solvation model, a generalized string method for minimum free-energy paths, and the level-set numerical implementation. This approach is applied to three molecular systems: two hydrophobic plates, a carbon nanotube, and a synthetic host molecule Cucurbit[7]uril. Without an explicit description of individual water molecules, our mesoscale approach effectively captures multiple dry and wet hydration states, multiple dry-wet transition paths, such as those geometrically symmetric and asymmetric paths, and transition states, providing activation energy barriers between different states. Further analysis shows that energy barriers depend on mesoscopic lengths, such as the separation distance between the two plates and the cross section diameter of the nanotube, and that the electrostatic interactions strongly influence the dry-wet transitions. With the inclusion of solute atomic motion, general collective variables as reaction coordinates, and the finite-temperature string method, together with an improved treatment of continuum electrostatics, our approach can be further developed to sample an ensemble of transition paths, providing more accurate predictions of the transition kinetics.
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Affiliation(s)
- Shenggao Zhou
- School of Mathematical Sciences and MOE-LSC, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yanan Zhang
- School of Mathematical Sciences, Soochow University, Suzhou 215006, China
| | - Li-Tien Cheng
- Department of Mathematics, University of California San Diego, La Jolla, California 92093-0112, USA
| | - Bo Li
- Department of Mathematics, University of California San Diego, La Jolla, California 92093-0112, USA
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22
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Kumar SU, Priya Doss CG. Residue interaction networks of K-Ras protein with water molecules identifies the potential role of switch II and P-loop. Comput Biol Med 2021; 135:104597. [PMID: 34237589 DOI: 10.1016/j.compbiomed.2021.104597] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/01/2021] [Accepted: 06/17/2021] [Indexed: 02/07/2023]
Abstract
The mutant K-Ras with aberrant signaling is the primary cause of several cancers. The proposed study investigated the influence of water molecules in K-Ras crystal structure, where they have a significant function by understanding their residue interaction networks (RINs). We analyzed the RINs of K-Ras with and without water molecules and determined their interaction properties. RINs were developed with the help of StructureViz2 and RINspector; further, the changes in K-Ras backbone flexibility were predicted with the DynaMine. We found that the residues K42, I142, and L159 are the hotspots from water, including the K-Ras-GTP complex with the highest residue centrality analysis (RCA) Z-score. The DynaMine prediction calculated the NMR S2 value for the frequently mutated positions G12, G13, and Q61 showing a minor shift in flexibility, which make up the P-Loop and switch II of the K-Ras protein. This flexibility shift can account for changes in conformational activity and the protein's GTPase activity, making it difficult to recognize by the effectors and exchange factors. Taken together, our study helps in understanding the functional importance of the water molecules in K-Ras protein and the impact of mutation that modulate the conformational state of the protein.
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Affiliation(s)
- S Udhaya Kumar
- School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - C George Priya Doss
- School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
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23
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Wang K, Zhou R, Li Y, Li M. DeepDTAF: a deep learning method to predict protein-ligand binding affinity. Brief Bioinform 2021; 22:6214647. [PMID: 33834190 DOI: 10.1093/bib/bbab072] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/27/2021] [Accepted: 02/14/2021] [Indexed: 01/10/2023] Open
Abstract
Biomolecular recognition between ligand and protein plays an essential role in drug discovery and development. However, it is extremely time and resource consuming to determine the protein-ligand binding affinity by experiments. At present, many computational methods have been proposed to predict binding affinity, most of which usually require protein 3D structures that are not often available. Therefore, new methods that can fully take advantage of sequence-level features are greatly needed to predict protein-ligand binding affinity and accelerate the drug discovery process. We developed a novel deep learning approach, named DeepDTAF, to predict the protein-ligand binding affinity. DeepDTAF was constructed by integrating local and global contextual features. More specifically, the protein-binding pocket, which possesses some special properties for directly binding the ligand, was firstly used as the local input feature for protein-ligand binding affinity prediction. Furthermore, dilated convolution was used to capture multiscale long-range interactions. We compared DeepDTAF with the recent state-of-art methods and analyzed the effectiveness of different parts of our model, the significant accuracy improvement showed that DeepDTAF was a reliable tool for affinity prediction. The resource codes and data are available at https: //github.com/KailiWang1/DeepDTAF.
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Affiliation(s)
| | - Renyi Zhou
- School of Computer Science and Engineering, Central South University, China
| | - Yaohang Li
- Department of Computer Science at Old Dominion University, Norfolk, USA
| | - Min Li
- School of Computer Science and Engineering, Central South University, China
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24
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Kim KH. Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein-ligand interactions and quantitative structure-activity relationship studies. J Comput Aided Mol Des 2021; 35:371-396. [PMID: 33712973 DOI: 10.1007/s10822-021-00377-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/05/2021] [Indexed: 11/30/2022]
Abstract
It is frequently mentioned that QSARs have not generally lived up to expectations, especially in cases where high predictability is expected yet failed to deliver satisfactory results. Even though outliers can provide an increased opportunity in drug discovery research, outliers in SAR and QSAR can contort predictions and affect the accuracy if proper attention is not given. The percentages of outliers in QSARs have not changed appreciably over the last decade. In our previous studies, we suggested two possible sources of outliers in SAR and QSAR. In this paper, we suggest an additional possible source of outliers in QSAR. We presented several literature examples that show one or more water molecules that play a critical role in protein-ligand binding interactions as observed in their crystal structures. These examples illustrate that failing to account for the effects of water molecules in protein-ligand interactions could mislead interpretation and possibly yield outliers in SAR and QSAR. Examples include cases where QSAR, considering the role of water molecules in protein-ligand crystal structures, provided deeper insight into the understanding and interpretation of the developed QSAR.
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25
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Escobar L, Ballester P. Molecular Recognition in Water Using Macrocyclic Synthetic Receptors. Chem Rev 2021; 121:2445-2514. [PMID: 33472000 DOI: 10.1021/acs.chemrev.0c00522] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Molecular recognition in water using macrocyclic synthetic receptors constitutes a vibrant and timely research area of supramolecular chemistry. Pioneering examples on the topic date back to the 1980s. The investigated model systems and the results derived from them are key for furthering our understanding of the remarkable properties exhibited by proteins: high binding affinity, superior binding selectivity, and extreme catalytic performance. Dissecting the different effects contributing to the proteins' properties is severely limited owing to its complex nature. Molecular recognition in water is also involved in other appreciated areas such as self-assembly, drug discovery, and supramolecular catalysis. The development of all these research areas entails a deep understanding of the molecular recognition events occurring in aqueous media. In this review, we cover the past three decades of molecular recognition studies of neutral and charged, polar and nonpolar organic substrates and ions using selected artificial receptors soluble in water. We briefly discuss the intermolecular forces involved in the reversible binding of the substrates, as well as the hydrophobic and Hofmeister effects operating in aqueous solution. We examine, from an interdisciplinary perspective, the design and development of effective water-soluble synthetic receptors based on cyclic, oligo-cyclic, and concave-shaped architectures. We also include selected examples of self-assembled water-soluble synthetic receptors. The catalytic performance of some of the presented receptors is also described. The latter process also deals with molecular recognition and energetic stabilization, but instead of binding ground-state species, the targets become elusive counterparts: transition states and other high-energy intermediates.
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Affiliation(s)
- Luis Escobar
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Av. Països Catalans 16, 43007 Tarragona, Spain.,Departament de Química Analítica i Química Orgánica, Universitat Rovira i Virgili, c/Marcel·lí Domingo 1, 43007 Tarragona, Spain
| | - Pablo Ballester
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Av. Països Catalans 16, 43007 Tarragona, Spain.,ICREA, Passeig Lluís Companys 23, 08010 Barcelona, Spain
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26
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Monroe JI, Jiao S, Davis RJ, Robinson Brown D, Katz LE, Shell MS. Affinity of small-molecule solutes to hydrophobic, hydrophilic, and chemically patterned interfaces in aqueous solution. Proc Natl Acad Sci U S A 2021; 118:e2020205118. [PMID: 33372161 PMCID: PMC7821046 DOI: 10.1073/pnas.2020205118] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Performance of membranes for water purification is highly influenced by the interactions of solvated species with membrane surfaces, including surface adsorption of solutes upon fouling. Current efforts toward fouling-resistant membranes often pursue surface hydrophilization, frequently motivated by macroscopic measures of hydrophilicity, because hydrophobicity is thought to increase solute-surface affinity. While this heuristic has driven diverse membrane functionalization strategies, here we build on advances in the theory of hydrophobicity to critically examine the relevance of macroscopic characterizations of solute-surface affinity. Specifically, we use molecular simulations to quantify the affinities to model hydroxyl- and methyl-functionalized surfaces of small, chemically diverse, charge-neutral solutes represented in produced water. We show that surface affinities correlate poorly with two conventional measures of solute hydrophobicity, gas-phase water solubility and oil-water partitioning. Moreover, we find that all solutes show attraction to the hydrophobic surface and most to the hydrophilic one, in contrast to macroscopically based hydrophobicity heuristics. We explain these results by decomposing affinities into direct solute interaction energies (which dominate on hydroxyl surfaces) and water restructuring penalties (which dominate on methyl surfaces). Finally, we use an inverse design algorithm to show how heterogeneous surfaces, with multiple functional groups, can be patterned to manipulate solute affinity and selectivity. These findings, importantly based on a range of solute and surface chemistries, illustrate that conventional macroscopic hydrophobicity metrics can fail to predict solute-surface affinity, and that molecular-scale surface chemical patterning significantly influences affinity-suggesting design opportunities for water purification membranes and other engineered interfaces involving aqueous solute-surface interactions.
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Affiliation(s)
- Jacob I Monroe
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106
| | - Sally Jiao
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106
| | - R Justin Davis
- Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712
| | - Dennis Robinson Brown
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106
| | - Lynn E Katz
- Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712
| | - M Scott Shell
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106;
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Rizzi V, Bonati L, Ansari N, Parrinello M. The role of water in host-guest interaction. Nat Commun 2021; 12:93. [PMID: 33397926 PMCID: PMC7782548 DOI: 10.1038/s41467-020-20310-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 11/23/2020] [Indexed: 12/13/2022] Open
Abstract
One of the main applications of atomistic computer simulations is the calculation of ligand binding free energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the system's degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding free energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail.
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Affiliation(s)
- Valerio Rizzi
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8092, Zurich, Switzerland
- Facoltà di Informatica, Istituto di Scienze Computazionali, Università della Svizzera Italiana, Via G. Buffi 13, 6900, Lugano, Switzerland
| | - Luigi Bonati
- Facoltà di Informatica, Istituto di Scienze Computazionali, Università della Svizzera Italiana, Via G. Buffi 13, 6900, Lugano, Switzerland
- Department of Physics, ETH Zurich, 8092, Zurich, Switzerland
| | - Narjes Ansari
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8092, Zurich, Switzerland
- Facoltà di Informatica, Istituto di Scienze Computazionali, Università della Svizzera Italiana, Via G. Buffi 13, 6900, Lugano, Switzerland
| | - Michele Parrinello
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8092, Zurich, Switzerland.
- Facoltà di Informatica, Istituto di Scienze Computazionali, Università della Svizzera Italiana, Via G. Buffi 13, 6900, Lugano, Switzerland.
- Italian Institute of Technology, Via Morego 30, 16163, Genova, Italy.
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28
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Iida S, Fukunishi Y. Asymmetric dynamics of dimeric SARS-CoV-2 and SARS-CoV main proteases in an apo form: Molecular dynamics study on fluctuations of active site, catalytic dyad, and hydration water. BBA ADVANCES 2021; 1:100016. [PMID: 34235495 PMCID: PMC8214910 DOI: 10.1016/j.bbadva.2021.100016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world. It is necessary to examine the viral proteins that play a notorious role in the invasion of our body. The main protease (3CLpro) facilitates the maturation of the coronavirus. It is thought that the dimerization of 3CLpro leads to its catalytic activity; the detailed mechanism has, however, not been suggested. Furthermore, the structural differences between the predecessor SARS-CoV 3CLpro and SARS-CoV-2 3CLpro have not been fully understood. Here, we show the structural and dynamical differences between the two main proteases, and demonstrate the relationship between the dimerization and the activity via atomistic molecular dynamics simulations. Simulating monomeric and dimeric 3CLpro systems for each protease, we show that (i) global dynamics between the two different proteases are not conserved, (ii) the dimerization stabilizes the catalytic dyad and hydration water molecules behind the dyad, and (iii) the substrate-binding site (active site) and hydration water molecules in each protomer fluctuate asymmetrically. We then speculate the roles of hydration water molecules in their catalytic activity.
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Affiliation(s)
- Shinji Iida
- Technology Research Association for Next-Generation Natural Products Chemistry, 2-3-26, Aomi, Koto-ku, Tokyo, Japan 135-0064
- Corresponding author.
| | - Yoshifumi Fukunishi
- Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo, Japan 135-0064
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29
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Huai Z, Shen Z, Sun Z. Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields. J Chem Inf Model 2020; 61:284-297. [PMID: 33307679 DOI: 10.1021/acs.jcim.0c01217] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Mouse major urinary protein (MUP) plays a key role in the pheromone communication system. The one-end-closed β-barrel of MUP-I forms a small, deep, and hydrophobic central cavity, which could accommodate structurally diverse ligands. Previous computational studies employed old protein force fields and short simulation times to determine the binding thermodynamics or investigated only a small number of structurally similar ligands, which resulted in sampled regions far from the experimental structure, nonconverged sampling outcomes, and limited understanding of the possible interaction patterns that the cavity could produce. In this work, extensive end-point and alchemical free-energy calculations with advanced protein force fields were performed to determine the binding thermodynamics of a series of MUP-inhibitor systems and investigate the inter- and intramolecular interaction patterns. Three series of inhibitors with a total of 14 ligands were simulated. We independently simulated the MUP-inhibitor complexes under two advanced AMBER force fields. Our benchmark test showed that the advanced AMBER force fields including AMBER19SB and AMBER14SB provided better descriptions of the system, and the backbone root-mean-square deviation (RMSD) was significantly lowered compared with previous computational studies with old protein force fields. Surprisingly, although the latest AMBER force field AMBER19SB provided better descriptions of various observables, it neither improved the binding thermodynamics nor lowered the backbone RMSD compared with the previously proposed and widely used AMBER14SB. The older but widely used AMBER14SB actually achieved better performance in the prediction of binding affinities from the alchemical and end-point free-energy calculations. We further analyzed the protein-ligand interaction networks to identify important residues stabilizing the bound structure. Six residues including PHE38, LEU40, PHE90, ALA103, LEU105, and TYR120 were found to contribute the most significant part of protein-ligand interactions, and 10 residues were found to provide favorable interactions stabilizing the bound state. The two AMBER force fields gave extremely similar interaction networks, and the secondary structures also showed similar behavior. Thus, the intra- and intermolecular interaction networks described with the two AMBER force fields are similar. Therefore, AMBER14SB could still be the default option in free-energy calculations to achieve highly accurate binding thermodynamics and interaction patterns.
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Affiliation(s)
- Zhe Huai
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
| | - Zhaoxi Shen
- Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Zhaoxi Sun
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
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30
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The AP2/ERF Gene Family in Triticum durum: Genome-Wide Identification and Expression Analysis under Drought and Salinity Stresses. Genes (Basel) 2020; 11:genes11121464. [PMID: 33297327 PMCID: PMC7762271 DOI: 10.3390/genes11121464] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 11/30/2020] [Accepted: 12/03/2020] [Indexed: 12/27/2022] Open
Abstract
Members of the AP2/ERF transcription factor family play critical roles in plant development, biosynthesis of key metabolites, and stress response. A detailed study was performed to identify TtAP2s/ERFs in the durum wheat (Triticum turgidum ssp. durum) genome, which resulted in the identification of 271 genes distributed on chromosomes 1A-7B. By carrying 27 genes, chromosome 6A had the highest number of TtAP2s/ERFs. Furthermore, a duplication assay of TtAP2s/ERFs demonstrated that 70 duplicated gene pairs had undergone purifying selection. According to RNA-seq analysis, the highest expression levels in all tissues and in response to stimuli were associated with DRF and ERF subfamily genes. In addition, the results revealed that TtAP2/ERF genes have tissue-specific expression patterns, and most TtAP2/ERF genes were significantly induced in the root tissue. Additionally, 13 TtAP2/ERF genes (six ERFs, three DREBs, two DRFs, one AP2, and one RAV) were selected for further analysis via qRT-PCR of their potential in coping with drought and salinity stresses. The TtAP2/ERF genes belonging to the DREB subfamily were markedly induced under both drought-stress and salinity-stress conditions. Furthermore, docking simulations revealed several residues in the pocket sites of the proteins associated with the stress response, which may be useful in future site-directed mutagenesis studies to increase the stress tolerance of durum wheat. This study could provide valuable insights for further evolutionary and functional assays of this important gene family in durum wheat.
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31
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Comparing Fragment Binding Poses Prediction Using HSP90 as a Key Study: When Bound Water Makes the Difference. Molecules 2020; 25:molecules25204651. [PMID: 33053878 PMCID: PMC7587341 DOI: 10.3390/molecules25204651] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 10/05/2020] [Accepted: 10/08/2020] [Indexed: 12/03/2022] Open
Abstract
Fragment-Based Drug Discovery (FBDD) approaches have gained popularitynot only in industry but also in academic research institutes. However, the computational prediction of the binding mode adopted by fragment-like molecules within a protein binding site is still a very challenging task. One of the most crucial aspects of fragment binding is related to the large amounts of bound waters in the targeted binding pocket. The binding affinity of fragmentsmay not be sufficientto displace the bound water molecules. In the present work, we confirmed the importance of the bound water molecules in the correct prediction of the fragment binding mode. Moreover, we investigate whether the use of methods based on explicit solvent molecular dynamics simulations can improve the accuracy of fragment posing. The protein chosen for this study is HSP-90.
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32
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FEP+ calculations predict a stereochemical SAR switch for first-in-class indoline NIK inhibitors for multiple myeloma. FUTURE DRUG DISCOVERY 2020. [DOI: 10.4155/fdd-2020-0004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
In the search for first-in-class NIK inhibitors for multiple myeloma, we discovered an azaindoline hit class generated from a biochemical NIK autophosphorylation high-throughput screening assay which was optimized to the final cyanoindoline compound class. During the hit-to-lead phase, a prominent stereochemical SAR switch was observed which was accurately predicted by in silico FEP+ calculations. Crystallographic and computational analysis showed that for both stereoisomers comparable contacts, both in nature and number, could be formed by the switching hydroxyl group, making this system particularly interesting from an interaction energy viewpoint. We provide a detailed analysis of our FEP+ and WaterMap calculations and show how this type of computational chemistry methods are useful during hit-to-lead and lead optimization phases.
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33
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Luukkonen S, Belloni L, Borgis D, Levesque M. Predicting Hydration Free Energies of the FreeSolv Database of Drug-like Molecules with Molecular Density Functional Theory. J Chem Inf Model 2020; 60:3558-3565. [DOI: 10.1021/acs.jcim.0c00526] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Sohvi Luukkonen
- Maison de la Simulation, CNRS-CEA-Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Luc Belloni
- LIONS, NIMBE, CEA, CNRS, Université Paris-Saclay, Gif-sur-Yvette 91191 France
| | - Daniel Borgis
- Maison de la Simulation, CNRS-CEA-Université Paris-Saclay, Gif-sur-Yvette 91191, France
- PASTEUR, Département de Chimie, École normale supérieure, PSL University, Sorbonne Université, CNRS, Paris 75005, France
| | - Maximilien Levesque
- PASTEUR, Département de Chimie, École normale supérieure, PSL University, Sorbonne Université, CNRS, Paris 75005, France
- Aqemia, Paris 75001, France
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34
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Mechanism of biomolecular recognition of trimethyllysine by the fluorinated aromatic cage of KDM5A PHD3 finger. Commun Chem 2020; 3:69. [PMID: 36703460 PMCID: PMC9814790 DOI: 10.1038/s42004-020-0313-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 05/06/2020] [Indexed: 01/29/2023] Open
Abstract
The understanding of biomolecular recognition of posttranslationally modified histone proteins is centrally important to the histone code hypothesis. Despite extensive binding and structural studies on the readout of histones, the molecular language by which posttranslational modifications on histone proteins are read remains poorly understood. Here we report physical-organic chemistry studies on the recognition of the positively charged trimethyllysine by the electron-rich aromatic cage containing PHD3 finger of KDM5A. The aromatic character of two tryptophan residues that solely constitute the aromatic cage of KDM5A was fine-tuned by the incorporation of fluorine substituents. Our thermodynamic analyses reveal that the wild-type and fluorinated KDM5A PHD3 fingers associate equally well with trimethyllysine. This work demonstrates that the biomolecular recognition of trimethyllysine by fluorinated aromatic cages is associated with weaker cation-π interactions that are compensated by the energetically more favourable trimethyllysine-mediated release of high-energy water molecules that occupy the aromatic cage.
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35
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Duan J, Lupyan D, Wang L. Improving the Accuracy of Protein Thermostability Predictions for Single Point Mutations. Biophys J 2020; 119:115-127. [PMID: 32533939 DOI: 10.1016/j.bpj.2020.05.020] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 04/30/2020] [Accepted: 05/18/2020] [Indexed: 01/17/2023] Open
Abstract
Accurately predicting the protein thermostability changes upon single point mutations in silico is a challenge that has implications for understanding diseases as well as industrial applications of protein engineering. Free energy perturbation (FEP) has been applied to predict the effect of single point mutations on protein stability for over 40 years and emerged as a potentially reliable prediction method with reasonable throughput. However, applications of FEP in protein stability calculations in industrial settings have been hindered by a number of limitations, including the inability to model mutations to and from prolines in which the bonded topology of the backbone is modified and the complexity in modeling charge-changing mutations. In this study, we have extended the FEP+ protocol to enable the accurate modeling of the effects on protein stability from proline mutations and from charge-changing mutations. We also evaluated the influence of the unfolded model in the stability calculations using increasingly longer peptides with native sequence and conformations. With the abovementioned improvements, the accuracy of FEP predictions of protein stability over a data set of 87 mutations on five different proteins has drastically improved compared with previous studies, with a mean unsigned error of 0.86 kcal/mol and root mean square error of 1.11 kcal/mol, comparable with the accuracy of previously published state-of-the-art small-molecule relative binding affinity calculations, which have been shown to be capable of driving discovery projects.
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36
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Asquith CRM, Tizzard GJ, Bennett JM, Wells CI, Elkins JM, Willson TM, Poso A, Laitinen T. Targeting the Water Network in Cyclin G‐Associated Kinase (GAK) with 4‐Anilino‐quin(az)oline Inhibitors. ChemMedChem 2020; 15:1200-1215. [DOI: 10.1002/cmdc.202000150] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Christopher R. M. Asquith
- Department of Pharmacology, School of MedicineUniversity of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
- Structural Genomics Consortium, UNC Eshelman School of PharmacyUniversity of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | - Graham J. Tizzard
- UK National Crystallography Service, School of ChemistryUniversity of Southampton Southampton SO17 1BJ UK
| | - James M. Bennett
- Structural Genomics Consortium and Target Discovery Institute Nuffield Department of Clinical MedicineUniversity of Oxford Old Road Campus Research Building Oxford OX3 7DQ UK)
| | - Carrow I. Wells
- Structural Genomics Consortium, UNC Eshelman School of PharmacyUniversity of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | - Jonathan M. Elkins
- Structural Genomics Consortium and Target Discovery Institute Nuffield Department of Clinical MedicineUniversity of Oxford Old Road Campus Research Building Oxford OX3 7DQ UK)
- Structural Genomics ConsortiumUniversidade Estadual de Campinas – UNICAMP Campinas São Paulo 13083-886 Brazil
| | - Timothy M. Willson
- Structural Genomics Consortium, UNC Eshelman School of PharmacyUniversity of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | - Antti Poso
- School of Pharmacy, Faculty of Health SciencesUniversity of Eastern Finland 70211 Kuopio Finland
- University Hospital Tübingen Department of Internal Medicine VIIIUniversity of Tübingen 72076 Tübingen Germany
| | - Tuomo Laitinen
- School of Pharmacy, Faculty of Health SciencesUniversity of Eastern Finland 70211 Kuopio Finland
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37
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Robert A, Luukkonen S, Levesque M. Pressure correction for solvation theories. J Chem Phys 2020; 152:191103. [DOI: 10.1063/5.0002029] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Affiliation(s)
- Anton Robert
- PASTEUR, Département de Chimie, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Sohvi Luukkonen
- Maison de la Simulation, CNRS-CEA-Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Maximilien Levesque
- PASTEUR, Département de Chimie, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
- Aqemia, Paris, France
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38
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Hu X, Maffucci I, Contini A. Advances in the Treatment of Explicit Water Molecules in Docking and Binding Free Energy Calculations. Curr Med Chem 2020; 26:7598-7622. [DOI: 10.2174/0929867325666180514110824] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 02/26/2018] [Accepted: 04/18/2018] [Indexed: 12/30/2022]
Abstract
Background:
The inclusion of direct effects mediated by water during the ligandreceptor
recognition is a hot-topic of modern computational chemistry applied to drug discovery
and development. Docking or virtual screening with explicit hydration is still debatable,
despite the successful cases that have been presented in the last years. Indeed, how to select
the water molecules that will be included in the docking process or how the included waters
should be treated remain open questions.
Objective:
In this review, we will discuss some of the most recent methods that can be used in
computational drug discovery and drug development when the effect of a single water, or of a
small network of interacting waters, needs to be explicitly considered.
Results:
Here, we analyse the software to aid the selection, or to predict the position, of water
molecules that are going to be explicitly considered in later docking studies. We also present
software and protocols able to efficiently treat flexible water molecules during docking, including
examples of applications. Finally, we discuss methods based on molecular dynamics
simulations that can be used to integrate docking studies or to reliably and efficiently compute
binding energies of ligands in presence of interfacial or bridging water molecules.
Conclusions:
Software applications aiding the design of new drugs that exploit water molecules,
either as displaceable residues or as bridges to the receptor, are constantly being developed.
Although further validation is needed, workflows that explicitly consider water will
probably become a standard for computational drug discovery soon.
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Affiliation(s)
- Xiao Hu
- Università degli Studi di Milano, Dipartimento di Scienze Farmaceutiche, Sezione di Chimica Generale e Organica “A. Marchesini”, Via Venezian, 21 20133 Milano, Italy
| | - Irene Maffucci
- Pasteur, Département de Chimie, École Normale Supérieure, PSL Research University, Sorbonne Universités, UPMC Univ. Paris 06, CNRS, 75005 Paris, France
| | - Alessandro Contini
- Università degli Studi di Milano, Dipartimento di Scienze Farmaceutiche, Sezione di Chimica Generale e Organica “A. Marchesini”, Via Venezian, 21 20133 Milano, Italy
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39
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Mey ASJS, Allen BK, Macdonald HEB, Chodera JD, Hahn DF, Kuhn M, Michel J, Mobley DL, Naden LN, Prasad S, Rizzi A, Scheen J, Shirts MR, Tresadern G, Xu H. Best Practices for Alchemical Free Energy Calculations [Article v1.0]. LIVING JOURNAL OF COMPUTATIONAL MOLECULAR SCIENCE 2020; 2:18378. [PMID: 34458687 PMCID: PMC8388617 DOI: 10.33011/livecoms.2.1.18378] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Alchemical free energy calculations are a useful tool for predicting free energy differences associated with the transfer of molecules from one environment to another. The hallmark of these methods is the use of "bridging" potential energy functions representing alchemical intermediate states that cannot exist as real chemical species. The data collected from these bridging alchemical thermodynamic states allows the efficient computation of transfer free energies (or differences in transfer free energies) with orders of magnitude less simulation time than simulating the transfer process directly. While these methods are highly flexible, care must be taken in avoiding common pitfalls to ensure that computed free energy differences can be robust and reproducible for the chosen force field, and that appropriate corrections are included to permit direct comparison with experimental data. In this paper, we review current best practices for several popular application domains of alchemical free energy calculations performed with equilibrium simulations, in particular relative and absolute small molecule binding free energy calculations to biomolecular targets.
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Affiliation(s)
- Antonia S. J. S. Mey
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | | | - Hannah E. Bruce Macdonald
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York NY, USA
| | - John D. Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York NY, USA
| | - David F. Hahn
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - Maximilian Kuhn
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
- Cresset, Cambridgeshire, UK
| | - Julien Michel
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | - David L. Mobley
- Departments of Pharmaceutical Sciences and Chemistry, University of California, Irvine, Irvine, USA
| | - Levi N. Naden
- Molecular Sciences Software Institute, Blacksburg VA, USA
| | | | - Andrea Rizzi
- Silicon Therapeutics, Boston, MA, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Jenke Scheen
- EaStCHEM School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh, EH9 3FJ, UK
| | | | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
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40
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Ferenczy GG, Keserű GM. Thermodynamic profiling for fragment-based lead discovery and optimization. Expert Opin Drug Discov 2019; 15:117-129. [PMID: 31741402 DOI: 10.1080/17460441.2020.1691166] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction: The enthalpic and entropic components of the ligand-protein binding free energy reflect the type and quality of the interactions and relate to the physicochemical properties of the ligands. These findings have significance in medicinal chemistry optimizations since they suggest that the thermodynamic profiling of the binding may help monitor and control the unfavorable size and hydrophobicity increase typically accompanying affinity improvements and leading to suboptimal pharmacokinetic properties.Areas covered: This review describes the ligand-protein binding event in terms of elementary steps, their associated interactions, and their enthalpic and entropic consequences. The relationships among the breaking and forming interactions, the binding thermodynamic profile, and the physicochemical properties of the ligands are also discussed.Expert opinion: Analysis of the size dependence of available affinity and favorable enthalpy highlights the limitation of the simultaneous optimization of these quantities. Indeed, moderate, rather than very high affinities can be conciliated with favorable physicochemical and pharmacokinetic profiles as it is supported by the affinity range of historical oral drugs. Although thermodynamic quantities are not suitable endpoints for medicinal chemistry optimizations owing to the complexity of the binding thermodynamics, thermodynamic profiling together with structural studies can be advantageously used to understand the details of the binding process and to optimize it.
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Affiliation(s)
- György G Ferenczy
- Medicinal Chemistry Research Group, Research Center for Natural Sciences, Budapest, Hungary
| | - György M Keserű
- Medicinal Chemistry Research Group, Research Center for Natural Sciences, Budapest, Hungary
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41
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Escalante DE, Aksan A. Prediction of Ligand Transport along Hydrophobic Enzyme Nanochannels. Comput Struct Biotechnol J 2019; 17:757-760. [PMID: 31303980 PMCID: PMC6606821 DOI: 10.1016/j.csbj.2019.06.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 05/08/2019] [Accepted: 06/01/2019] [Indexed: 12/22/2022] Open
Abstract
Buried active sites of enzymes are connected to the bulk solvent through a network of hydrophobic channels. We developed a discretized model that can accurately predict ligand transport along hydrophobic channels up to six orders of magnitude faster than any other existing method. The non-dimensional nature of the model makes it applicable to any hydrophobic channel/ligand combination.
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Affiliation(s)
- Diego E. Escalante
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Alptekin Aksan
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
- BioTechnology Institute, University of Minnesota, St. Paul, MN 55108, United States
- Corresponding author at: Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, United States.
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42
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Variational implicit-solvent predictions of the dry-wet transition pathways for ligand-receptor binding and unbinding kinetics. Proc Natl Acad Sci U S A 2019; 116:14989-14994. [PMID: 31270236 DOI: 10.1073/pnas.1902719116] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Ligand-receptor binding and unbinding are fundamental biomolecular processes and particularly essential to drug efficacy. Environmental water fluctuations, however, impact the corresponding thermodynamics and kinetics and thereby challenge theoretical descriptions. Here, we devise a holistic, implicit-solvent, multimethod approach to predict the (un)binding kinetics for a generic ligand-pocket model. We use the variational implicit-solvent model (VISM) to calculate the solute-solvent interfacial structures and the corresponding free energies, and combine the VISM with the string method to obtain the minimum energy paths and transition states between the various metastable ("dry" and "wet") hydration states. The resulting dry-wet transition rates are then used in a spatially dependent multistate continuous-time Markov chain Brownian dynamics simulation and the related Fokker-Planck equation calculations of the ligand stochastic motion, providing the mean first-passage times for binding and unbinding. We find the hydration transitions to significantly slow down the binding process, in semiquantitative agreement with existing explicit-water simulations, but significantly accelerate the unbinding process. Moreover, our methods allow the characterization of nonequilibrium hydration states of pocket and ligand during the ligand movement, for which we find substantial memory and hysteresis effects for binding vs. unbinding. Our study thus provides a significant step forward toward efficient, physics-based interpretation and predictions of the complex kinetics in realistic ligand-receptor systems.
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43
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Fang H. Halogen substituent effect on the water-assisted excited-state tautomerization of 2, 7-diazaindole-H 2O complex in aqueous solution: A theoretical study. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 214:152-160. [PMID: 30776716 DOI: 10.1016/j.saa.2019.02.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Revised: 01/18/2019] [Accepted: 02/10/2019] [Indexed: 06/09/2023]
Abstract
We studied the ESPT process in the 2-DAI-H2O complex theoretically for the first time, and compared the kinetics of 2-DAI-H2O with those features of 7-DAI-H2O. The substituted effect on the dynamics of excited-state double proton transfer in 2-DAI-H2O and 7-DAI-H2O clusters in water were also investigated at the TD-M06-2X/6-311+G(d, p) level. In this work, 2,7-DAI-H2O is also expressed as 2-DAI-H2O and 7-DAI-H2O, in which correspond to different ESPT reactions and generate two tautomers (N2H form and N7H form). In both the 2-DAI-H2O and 7-DAI-H2O complexes, ESPT processes happened in a concertedly but asynchronously protolysis pathway. The ESPT process preferred to occur in the 7-DAI-H2O complex due to its lower barrier height. For the 3-X-2-DAI-H2O and 3-X-7-DAI-H2O (X = H, F, Cl, Br) complexes, the replacement of halogen atom did not influence the ESPT mechanism. However, the replacement of halogen atom changed the structural parameters evidently, reduced the barrier height up to 4-5 kcal/mol, and enlarged the asynchronicity of ESPT apparently. ∆(R1+R2) values in the 3X-2-DAI-H2O and 3X-7-DAI-H2O complexes have linear correlation to the ZPE-corrected ESPT barrier height linearly.
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Affiliation(s)
- Hua Fang
- Department of Chemistry and Material Science, College of Science, Nanjing Forestry University, Nanjing 210037, People's Republic of China.
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44
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Ghasemi M, Ramsheh SM, Sharma S. Quantitative Assessment of Thermodynamic Theory in Elucidating the Behavior of Water under Hydrophobic Confinement. J Phys Chem B 2018; 122:12087-12096. [PMID: 30475618 DOI: 10.1021/acs.jpcb.8b09026] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A macroscopic thermodynamics-based theory that can quantitatively describe the behavior of water confined between hydrophobic solutes has so far remained elusive. In this work, we progress toward this goal by comparing the predictions of macroscopic theory with the results from computer simulations. We have determined free energy profiles of water confined between two nanometer-sized surfaces of varying hydrophobicity using molecular simulations and have estimated thermodynamic properties such as contact angle, line tension, and size of the critical vapor tube from independent simulations. We show that the scaling of free energy barrier to evaporation is fairly well captured by the factor ( D/2 + λ/ϒLV)2, where D is the confinement gap and λ/ ϒLV is the ratio of line-tension and liquid-vapor surface tension. The radius of the critical vapor tube necessary for nucleating evaporation scales by the factor ( D/2 + λ/ϒLV). Exclusion of the line-tension term from thermodynamic theory leads to a qualitative disagreement between theoretical predictions and results from molecular simulations. We also demonstrate that macroscopic theory that includes the line-tension term is able to quantitatively match the entire free energy profile associated with the formation of a vapor-tube inside the confined region for conditions when the vapor state is the most stable state. The match is however only qualitatively correct for the conditions when the liquid state is more stable. Overall, the conclusion is that the inclusion of line-tension in macroscopic theory is necessary to describe the behavior of water under nanoscale confinement between two hydrophobic solutes.
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Affiliation(s)
- Mohsen Ghasemi
- Department of Mechanical Engineering , Ohio University , Athens , Ohio 45701 , United States
| | - Saeed Miri Ramsheh
- Department of Chemical and Biomolecular Engineering , Ohio University , Athens , Ohio 45701 , United States
| | - Sumit Sharma
- Department of Chemical and Biomolecular Engineering , Ohio University , Athens , Ohio 45701 , United States
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45
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Brysbaert G, Blossey R, Lensink MF. The Inclusion of Water Molecules in Residue Interaction Networks Identifies Additional Central Residues. Front Mol Biosci 2018; 5:88. [PMID: 30364190 PMCID: PMC6193073 DOI: 10.3389/fmolb.2018.00088] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 09/18/2018] [Indexed: 12/13/2022] Open
Abstract
The relevance of water molecules for the recognition and the interaction of biomolecules is widely appreciated. In this paper we address the role that water molecules associated to protein complexes play for the functional relevance of residues by considering their residue interaction networks (RINs). These are commonly defined on the basis of the amino acid composition of the proteins themselves, disregarding the solvation state of the protein. We determine properties of the RINs of two protein complexes, colicin E2/Im2 and barnase/barstar, with and without associated water molecules, using a previously developed methodology and its associated application RINspector. We find that the inclusion of water molecules in RINs leads to an increase in the number of central residues which adds a novel mechanism to the relevance of water molecules for protein function.
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Affiliation(s)
- Guillaume Brysbaert
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
| | - Ralf Blossey
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
| | - Marc F Lensink
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
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46
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Ricci CG, McCammon JA. Heterogeneous Solvation in Distinctive Protein-Protein Interfaces Revealed by Molecular Dynamics Simulations. J Phys Chem B 2018; 122:11695-11701. [PMID: 30252476 DOI: 10.1021/acs.jpcb.8b07773] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Water, despite being a driving force in biochemical processes, has an elusively complex microscopic behavior. While water can increase its local density near amphiphilic protein surfaces, water is also thought to evaporate from hydrophobic surfaces and cavities, an effect known as "dewetting". The existence and extent of dewetting effects remains elusive due to the difficulty in observing clear "drying" transitions in experiments or simulations. Here, we use explicit solvent molecular dynamics (MD) simulations to study the molecular solvation at the binding interfaces of two distinctive molecular complexes: the highly hydrophilic barnase-barstar and the highly hydrophobic MDM2-p53. Our simulations, in conjunction with simple volumetric analyses, reveal a strikingly different water behavior at the binding interfaces of these two molecular complexes. In both complexes, we observe significant changes in the water local density as the two proteins approach, supporting the existence of a clear dewetting transition in the case of MDM2-p53, with an onset distance of 5.6-7.6 Å. Furthermore, the solvation analysis reported herein is a valuable tool to capture and quantify persistent or transient dewetting events in future explicit solvent MD simulations.
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47
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Masters MR, Mahmoud AH, Yang Y, Lill MA. Efficient and Accurate Hydration Site Profiling for Enclosed Binding Sites. J Chem Inf Model 2018; 58:2183-2188. [PMID: 30289252 DOI: 10.1021/acs.jcim.8b00544] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Matthew R. Masters
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Amr H. Mahmoud
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Ying Yang
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
| | - Markus A. Lill
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47906, United States
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48
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Schiebel J, Gaspari R, Wulsdorf T, Ngo K, Sohn C, Schrader TE, Cavalli A, Ostermann A, Heine A, Klebe G. Intriguing role of water in protein-ligand binding studied by neutron crystallography on trypsin complexes. Nat Commun 2018; 9:3559. [PMID: 30177695 PMCID: PMC6120877 DOI: 10.1038/s41467-018-05769-2] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 07/26/2018] [Indexed: 11/09/2022] Open
Abstract
Hydrogen bonds are key interactions determining protein-ligand binding affinity and therefore fundamental to any biological process. Unfortunately, explicit structural information about hydrogen positions and thus H-bonds in protein-ligand complexes is extremely rare and similarly the important role of water during binding remains poorly understood. Here, we report on neutron structures of trypsin determined at very high resolutions ≤1.5 Å in uncomplexed and inhibited state complemented by X-ray and thermodynamic data and computer simulations. Our structures show the precise geometry of H-bonds between protein and the inhibitors N-amidinopiperidine and benzamidine along with the dynamics of the residual solvation pattern. Prior to binding, the ligand-free binding pocket is occupied by water molecules characterized by a paucity of H-bonds and high mobility resulting in an imperfect hydration of the critical residue Asp189. This phenomenon likely constitutes a key factor fueling ligand binding via water displacement and helps improving our current view on water influencing protein-ligand recognition.
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Affiliation(s)
- Johannes Schiebel
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany.,Computational Sciences, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy
| | - Roberto Gaspari
- Computational Sciences, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy
| | - Tobias Wulsdorf
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany
| | - Khang Ngo
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany
| | - Christian Sohn
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany
| | - Tobias E Schrader
- Jülich Centre for Neutron Science at Heinz Maier-Leibnitz Zentrum, Forschungszentrum Jülich, Lichtenbergstraße 1, 85748, Garching, Germany
| | - Andrea Cavalli
- Computational Sciences, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy
| | - Andreas Ostermann
- Heinz Maier-Leibnitz Zentrum, Technische Universität München, Lichtenbergstraße 1, 85748, Garching, Germany
| | - Andreas Heine
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany
| | - Gerhard Klebe
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg, Marbacher Weg 6, 35032, Marburg, Germany.
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49
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Scapin G, Potter CS, Carragher B. Cryo-EM for Small Molecules Discovery, Design, Understanding, and Application. Cell Chem Biol 2018; 25:1318-1325. [PMID: 30100349 DOI: 10.1016/j.chembiol.2018.07.006] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 05/11/2018] [Accepted: 07/05/2018] [Indexed: 12/13/2022]
Abstract
We present a perspective of our view of the application of cryoelectron microscopy (cryo-EM) to structure-based drug design (SBDD). We discuss the basic needs and requirements for SBDD, the current state of cryo-EM, and the challenges that need to be overcome for this technique to reach its full potential in facilitating the process of drug discovery.
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Affiliation(s)
- Giovanna Scapin
- Department of Biochemical Engineering & Structure, Merck & Co., Inc., 2000 Galloping Hill Rd., Kenilworth, NJ 07033, USA
| | - Clinton S Potter
- Simons Electron Microscopy Center, National Resource for Automated Molecular Microscopy, New York Structural Biology Center, 89 Convent Avenue, New York NY 10027, USA; NanoImaging Services, 4940 Carroll Canyon Road, Suite 115, San Diego, CA 92121, USA
| | - Bridget Carragher
- Simons Electron Microscopy Center, National Resource for Automated Molecular Microscopy, New York Structural Biology Center, 89 Convent Avenue, New York NY 10027, USA; NanoImaging Services, 4940 Carroll Canyon Road, Suite 115, San Diego, CA 92121, USA.
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50
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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.
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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
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