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Menchon G, Maveyraud L, Czaplicki G. Molecular Dynamics as a Tool for Virtual Ligand Screening. Methods Mol Biol 2024; 2714:33-83. [PMID: 37676592 DOI: 10.1007/978-1-0716-3441-7_3] [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: 09/08/2023]
Abstract
Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or nucleic acid is known. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on docking methods which allow predicting the binding of a molecule to a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of full protein flexibility information, no solvation and ion effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological complex and ranking these complexes with more accurate binding energy calculations. In this chapter, we describe the up-to-date MD, which plays the role of supporting tools in the virtual ligand screening (VS) process.Without a doubt, using docking in combination with MD is an attractive approach in structure-based drug discovery protocols nowadays. It has proved its efficiency through many examples in the literature and is a powerful method to significantly reduce the amount of required wet experimentations (Tarcsay et al, J Chem Inf Model 53:2990-2999, 2013; Barakat et al, PLoS One 7:e51329, 2012; De Vivo et al, J Med Chem 59:4035-4061, 2016; Durrant, McCammon, BMC Biol 9:71-79, 2011; Galeazzi, Curr Comput Aided Drug Des 5:225-240, 2009; Hospital et al, Adv Appl Bioinforma Chem 8:37-47, 2015; Jiang et al, Molecules 20:12769-12786, 2015; Kundu et al, J Mol Graph Model 61:160-174, 2015; Mirza et al, J Mol Graph Model 66:99-107, 2016; Moroy et al, Future Med Chem 7:2317-2331, 2015; Naresh et al, J Mol Graph Model 61:272-280, 2015; Nichols et al, J Chem Inf Model 51:1439-1446, 2011; Nichols et al, Methods Mol Biol 819:93-103, 2012; Okimoto et al, PLoS Comput Biol 5:e1000528, 2009; Rodriguez-Bussey et al, Biopolymers 105:35-42, 2016; Sliwoski et al, Pharmacol Rev 66:334-395, 2014).
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Affiliation(s)
- Grégory Menchon
- Inserm U1242, Oncogenesis, Stress and Signaling (OSS), Université de Rennes 1, Rennes, France
| | - Laurent Maveyraud
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, Université Toulouse III - Paul Sabatier (UT3), Toulouse, France
| | - Georges Czaplicki
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, Université Toulouse III - Paul Sabatier (UT3), Toulouse, France.
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2
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Talevi A. Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects. Methods Mol Biol 2024; 2714:1-20. [PMID: 37676590 DOI: 10.1007/978-1-0716-3441-7_1] [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: 09/08/2023]
Abstract
Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.
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Affiliation(s)
- Alan Talevi
- Laboratory of Bioactive Compound Research and Development (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata, Argentina.
- Argentinean National Council of Scientific and Technical Research (CONICET), La Plata, Argentina.
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3
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Liu X, Zheng L, Cong Y, Gong Z, Yin Z, Zhang JZH, Liu Z, Sun Z. Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: II. regression and dielectric constant. J Comput Aided Mol Des 2022; 36:879-894. [PMID: 36394776 DOI: 10.1007/s10822-022-00487-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: 08/26/2022] [Accepted: 10/29/2022] [Indexed: 11/18/2022]
Abstract
End-point free energy calculations as a powerful tool have been widely applied in protein-ligand and protein-protein interactions. It is often recognized that these end-point techniques serve as an option of intermediate accuracy and computational cost compared with more rigorous statistical mechanic models (e.g., alchemical transformation) and coarser molecular docking. However, it is observed that this intermediate level of accuracy does not hold in relatively simple and prototypical host-guest systems. Specifically, in our previous work investigating a set of carboxylated-pillar[6]arene host-guest complexes, end-point methods provide free energy estimates deviating significantly from the experimental reference, and the rank of binding affinities is also incorrectly computed. These observations suggest the unsuitability and inapplicability of standard end-point free energy techniques in host-guest systems, and alteration and development are required to make them practically usable. In this work, we consider two ways to improve the performance of end-point techniques. The first one is the PBSA_E regression that varies the weights of different free energy terms in the end-point calculation procedure, while the second one is considering the interior dielectric constant as an additional variable in the end-point equation. By detailed investigation of the calculation procedure and the simulation outcome, we prove that these two treatments (i.e., regression and dielectric constant) are manipulating the end-point equation in a somehow similar way, i.e., weakening the electrostatic contribution and strengthening the non-polar terms, although there are still many detailed differences between these two methods. With the trained end-point scheme, the RMSE of the computed affinities is improved from the standard ~ 12 kcal/mol to ~ 2.4 kcal/mol, which is comparable to another altered end-point method (ELIE) trained with system-specific data. By tuning PBSA_E weighting factors with the host-specific data, it is possible to further decrease the prediction error to ~ 2.1 kcal/mol. These observations along with the extremely efficient optimized-structure computation procedure suggest the regression (i.e., PBSA_E as well as its GBSA_E extension) as a practically applicable solution that brings end-point methods back into the library of usable tools for host-guest binding. However, the dielectric-constant-variable scheme cannot effectively minimize the experiment-calculation discrepancy for absolute binding affinities, but is able to improve the calculation of affinity ranks. This phenomenon is somehow different from the protein-ligand case and suggests the difference between host-guest and biomacromolecular (protein-ligand and protein-protein) systems. Therefore, the spectrum of tools usable for protein-ligand complexes could be unsuitable for host-guest binding, and numerical validations are necessary to screen out really workable solutions in these 'prototypical' situations.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China.
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
| | - Yalong Cong
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China
| | - Zhihao Gong
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China.,Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310027, China
| | - Zhixiang Yin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China
| | - John Z H Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China. .,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China. .,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China. .,Department of Chemistry, New York University, NY, NY, 10003, USA.
| | - Zhirong Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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4
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Liu X, Zheng L, Qin C, Zhang JZH, Sun Z. Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure. J Comput Aided Mol Des 2022; 36:735-752. [PMID: 36136209 DOI: 10.1007/s10822-022-00475-0] [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: 07/06/2022] [Accepted: 09/06/2022] [Indexed: 10/14/2022]
Abstract
Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China.
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
| | - Chu Qin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China
| | - John Z H Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China.,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China.,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.,Department of Chemistry, New York University, New York, NY, 10003, USA
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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Zaccaria F, Zhang B, Goldoni L, Imran M, Zito J, van Beek B, Lauciello S, De Trizio L, Manna L, Infante I. The Reactivity of CsPbBr 3 Nanocrystals toward Acid/Base Ligands. ACS NANO 2022; 16:1444-1455. [PMID: 35005882 PMCID: PMC8793808 DOI: 10.1021/acsnano.1c09603] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 12/23/2021] [Indexed: 05/20/2023]
Abstract
The interaction of lead bromide perovskite nanocrystals with charged ligands, such as salts, zwitterions, or acid-base pairs, has been extensively documented over the past few years. On the other hand, little is known about the reactivity of perovskite nanocrystals toward neutral ligands. To fill this gap, in this work we study the interaction of CsPbBr3 nanocrystals passivated with didodecyldimethylammonium bromide (DDABr) toward a series of exogenous acid/base ligands using a combined computational and experimental approach. Our analysis indicates that DDABr-capped nanocrystals are inert toward most ligands, except for carboxylic, phosphonic, and sulfonic acids. In agreement with the calculations, our experimental results indicate that the higher the acidity of the ligands employed in the treatment, the more etching is observed. In detail, dodecylbenzenesulfonic acid (pKa = -1.8) is found to etch the nanocrystals, causing their complete degradation. On the other hand, oleic and oleylphosphonic acids (pKa 9.9 and 2, respectively) interact with surface-bound DDA molecules, causing their displacement as DDABr in various amounts, which can be as high as 40% (achieved with oleylphosphonic acid). Despite the stripping of DDA ligands, the optical properties of the nanocrystals, as well as structure and morphology, remain substantially unaffected, empirically demonstrating the defect tolerance characterizing such materials. Our study provides not only a clear overview on the interaction between perovskite nanocrystals and neutral ligands but also presents an effective ligand stripping strategy.
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Affiliation(s)
- Francesco Zaccaria
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Baowei Zhang
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
- Dipartimento
di Chimica e Chimica Industriale, Università
degli Studi di Genova, Via Dodecaneso 31, 16146 Genova, Italy
| | - Luca Goldoni
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Muhammad Imran
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Juliette Zito
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
- Dipartimento
di Chimica e Chimica Industriale, Università
degli Studi di Genova, Via Dodecaneso 31, 16146 Genova, Italy
| | - Bas van Beek
- Department
of Theoretical Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, de Boelelaan 1083, 1081 HV Amsterdam, The Netherlands
| | - Simone Lauciello
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Luca De Trizio
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Liberato Manna
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Ivan Infante
- Department
of Nanochemistry, Analytical Chemistry Lab, and Electron Microscopy Facility, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
- Department
of Theoretical Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, de Boelelaan 1083, 1081 HV Amsterdam, The Netherlands
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Menchon G, Maveyraud L, Czaplicki G. Molecular Dynamics as a Tool for Virtual Ligand Screening. Methods Mol Biol 2018; 1762:145-178. [PMID: 29594772 DOI: 10.1007/978-1-4939-7756-7_9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or catalytic enzyme is known experimentally. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to inhibit a particular protein interaction or biological activity. The virtual ligand screening process often relies on docking methods which allow predicting the binding of a molecule into a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of protein flexibility information, no solvation effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions and even in membrane-like environments, and ranking complexes with more accurate binding energy calculations. In this chapter we describe the up-to-date MD protocols that are mandatory supporting tools in the virtual ligand screening (VS) process. Using docking in combination with MD is one of the best computer-aided drug design protocols nowadays. It has proved its efficiency through many examples, described below.
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Affiliation(s)
- Grégory Menchon
- Laboratory of Biomolecular Research, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Laurent Maveyraud
- Institute of Pharmacology and Structural Biology, UMR 5089, University of Toulouse III, Toulouse, France
| | - Georges Czaplicki
- Institute of Pharmacology and Structural Biology, UMR 5089, University of Toulouse III, Toulouse, France.
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7
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Abstract
The term drug design describes the search of novel compounds with biological activity, on a systematic basis. In its most common form, it involves modification of a known active scaffold or linking known active scaffolds, although de novo drug design (i.e., from scratch) is also possible. Though highly interrelated, identification of active scaffolds should be conceptually separated from drug design. Traditionally, the drug design process has focused on the molecular determinants of the interactions between the drug and its known or intended molecular target. Nevertheless, current drug design also takes into consideration other relevant processes than influence drug efficacy and safety (e.g., bioavailability, metabolic stability, interaction with antitargets).This chapter provides an overview on possible approaches to identify active scaffolds (including in silico approximations to approach that task) and computational methods to guide the subsequent optimization process. It also discusses in which situations each of the overviewed techniques is more appropriate.
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Affiliation(s)
- Alan Talevi
- Laboratorio de Investigación y Desarrollo de Bioactivos (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), Buenos Aires, Argentina.
- Argentinean National Council of Scientific and Technical Research (CONICET), Buenos Aires, Argentina.
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Procacci P, Chelli R. Statistical Mechanics of Ligand–Receptor Noncovalent Association, Revisited: Binding Site and Standard State Volumes in Modern Alchemical Theories. J Chem Theory Comput 2017; 13:1924-1933. [DOI: 10.1021/acs.jctc.6b01192] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Piero Procacci
- Department of Chemistry, University of Florence, Via Lastruccia
n. 3, Sesto
Fiorentino I-50019, Italy
| | - Riccardo Chelli
- Department of Chemistry, University of Florence, Via Lastruccia
n. 3, Sesto
Fiorentino I-50019, Italy
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9
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Alchemical determination of drug-receptor binding free energy: Where we stand and where we could move to. J Mol Graph Model 2017; 71:233-241. [DOI: 10.1016/j.jmgm.2016.11.018] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 11/24/2016] [Accepted: 11/29/2016] [Indexed: 01/05/2023]
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