1
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Tänzel V, Jäger M, Wolf S. Learning Protein-Ligand Unbinding Pathways via Single-Parameter Community Detection. J Chem Theory Comput 2024; 20:5058-5067. [PMID: 38865714 DOI: 10.1021/acs.jctc.4c00250] [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: 06/14/2024]
Abstract
Understanding the dynamics of biomolecular complexes, e.g., of protein-ligand (un)binding, requires the comprehension of paths such systems take between metastable states. In MD simulations, paths are usually not observable per se, but they need to be inferred from simulation trajectories. Here, we present a novel approach to cluster trajectories based on a community detection algorithm that necessitates only the definition of a single parameter. The unbinding of the streptavidin-biotin complex is used as a benchmark system and the A2a adenosine receptor in complex with the inhibitor ZM241385 as an elaborate application. We demonstrate how such clusters of trajectories correspond to pathways and how the approach helps in the identification of reaction coordinates for a considered (un)binding process.
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Affiliation(s)
- Victor Tänzel
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
| | - Miriam Jäger
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
| | - Steffen Wolf
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
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2
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Basciu A, Athar M, Kurt H, Neville C, Malloci G, Muredda FC, Bosin A, Ruggerone P, Bonvin AMJJ, Vargiu AV. Predicting binding events in very flexible, allosteric, multi-domain proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.02.597018. [PMID: 38895346 PMCID: PMC11185556 DOI: 10.1101/2024.06.02.597018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Knowledge of the structures formed by proteins and small ligands is of fundamental importance for understanding molecular principles of chemotherapy and for designing new and more effective drugs. Due to the still high costs and to the several limitations of experimental techniques, it is most often desirable to predict these ligand-protein complexes in silico, particularly when screening for new putative drugs from databases of millions of compounds. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology aimed at generating bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites. Validation was performed on the enzyme adenylate kinase (ADK), a paradigmatic example of proteins that undergo very large conformational changes upon ligand binding. By only exploiting the unbound structure and the putative binding sites of the protein, we generated a significant fraction of bound-like structures, which employed in ensemble-docking calculations allowed to find native-like poses of substrates, inhibitors, and catalytically incompetent binders. Our protocol provides a general framework for the generation of bound-like conformations of flexible proteins that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening for difficult targets, prediction of the impact of amino acid mutations on structure and dynamics, and protein engineering.
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Affiliation(s)
- Andrea Basciu
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Mohd Athar
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Han Kurt
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Christine Neville
- Institute for Computational Molecular Science, Temple University, Philadelphia, PA 19122, USA
- Department of Biology, Temple University, Philadelphia, PA 19122, USA
| | - Giuliano Malloci
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Fabrizio C. Muredda
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Andrea Bosin
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Paolo Ruggerone
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Alexandre M. J. J. Bonvin
- Bijvoet Centre for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Attilio V. Vargiu
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
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3
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Yuan L, Liang X, He L. Unveiling dissociation mechanisms and binding patterns in the UHRF1-DPPA3 complex via multi-replica molecular dynamics simulations. J Mol Model 2024; 30:173. [PMID: 38767734 DOI: 10.1007/s00894-024-05946-9] [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: 12/10/2023] [Accepted: 04/16/2024] [Indexed: 05/22/2024]
Abstract
CONTEXT Ubiquitin-like with PHD and RING finger domain containing protein 1 (UHRF1) is responsible for preserving the stability of genomic methylation through the recruitment of DNA methyltransferase 1 (DNMT1). However, the interaction between Developmental pluripotency associated 3 (DPPA3) and the pre-PHD-PHD (PPHD) domain of UHRF1 hinders the nuclear localization of UHRF1. This disruption has implications for potential cancer treatment strategies. Drugs that mimic the binding pattern between DPPA3 and PPHD could offer a promising approach to cancer treatment. Our study reveals that DPPA3 undergoes dissociation from the C-terminal through three different modes of helix unfolding. Furthermore, we have identified key residue pairs involved in this dissociation process and potential drug-targeting residues. These findings offer valuable insights into the dissociation mechanism of DPPA3 from PPHD and have the potential to inform the design of novel drugs targeting UHRF1 for cancer therapy. METHODS To comprehend the dissociation process and binding patterns of PPHD-DPPA3, we employed enhanced sampling techniques, including steered molecular dynamics (SMD) and conventional molecular dynamics (cMD). Additionally, we utilized self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. The Gromacs software was used for performing molecular dynamics simulations, and the AMBER FF14SB force field was applied to the protein.
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Affiliation(s)
- Longxiao Yuan
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy, Nankai University, Tianjin, 300353, China
| | - Xiaodan Liang
- School of Computer Sciences and Technology, Tiangong University, Tianjin, 300387, China.
| | - Lei He
- Institute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
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4
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Yuan L, Liang X, He L. Insights into the Dissociation Process and Binding Pattern of the BRCT7/8-PHF8 Complex. ACS OMEGA 2024; 9:20819-20831. [PMID: 38764655 PMCID: PMC11097150 DOI: 10.1021/acsomega.3c09433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 02/27/2024] [Accepted: 04/24/2024] [Indexed: 05/21/2024]
Abstract
DNA topoisomerase 2-binding protein 1 (Topbp1) plays a crucial role in activating the ataxia-telangiectasia mutated and rad3-related (ATR) complex to initiate DNA damage repair responses. For this process to occur, it is necessary for PHF8 to dissociate from Topbp1. Topbp1 binds to the acidic patch sequence (APS) of PHF8 through its C-terminal BRCT7/8 domain, and disrupting this interaction could be a promising strategy for cancer treatment. To investigate the dissociation process and binding pattern of BRCT7/8-PHF8, we employed enhanced sampling techniques, such as steered molecular dynamics (SMD) simulations and accelerated molecular dynamics (aMD) simulations, along with self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. Our results demonstrate that the dissociation of PHF8 from BRCT7/8 starts from the N-terminus, leading to the unfolding of the N-terminal helix. Additionally, we identified critical residues that play a pivotal role in this dissociation process. These findings provide valuable insights into the disassociation of PHF8 from BRCT7/8, which could potentially guide the development of novel drugs targeting Topbp1 for cancer therapy.
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Affiliation(s)
- Longxiao Yuan
- State
Key Laboratory of Medicinal Chemical Biology, College of Pharmacy, Nankai University, Tianjin 300353, China
| | - Xiaodan Liang
- School
of Computer Sciences and Technology, Tiangong
University, Tianjin 300387, China
| | - Lei He
- Institute
for Fetology, The First Affiliated Hospital
of Soochow University, Suzhou 215006, China
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5
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Ray D, Parrinello M. Data-driven classification of ligand unbinding pathways. Proc Natl Acad Sci U S A 2024; 121:e2313542121. [PMID: 38412121 DOI: 10.1073/pnas.2313542121] [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: 08/07/2023] [Accepted: 01/26/2024] [Indexed: 02/29/2024] Open
Abstract
Studying the pathways of ligand-receptor binding is essential to understand the mechanism of target recognition by small molecules. The binding free energy and kinetics of protein-ligand complexes can be computed using molecular dynamics (MD) simulations, often in quantitative agreement with experiments. However, only a qualitative picture of the ligand binding/unbinding paths can be obtained through a conventional analysis of the MD trajectories. Besides, the higher degree of manual effort involved in analyzing pathways limits its applicability in large-scale drug discovery. Here, we address this limitation by introducing an automated approach for analyzing molecular transition paths with a particular focus on protein-ligand dissociation. Our method is based on the dynamic time-warping algorithm, originally designed for speech recognition. We accurately classified molecular trajectories using a very generic descriptor set of contacts or distances. Our approach outperforms manual classification by distinguishing between parallel dissociation channels, within the pathways identified by visual inspection. Most notably, we could compute exit-path-specific ligand-dissociation kinetics. The unbinding timescale along the fastest path agrees with the experimental residence time, providing a physical interpretation to our entirely data-driven protocol. In combination with appropriate enhanced sampling algorithms, this technique can be used for the initial exploration of ligand-dissociation pathways as well as for calculating path-specific thermodynamic and kinetic properties.
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Affiliation(s)
- Dhiman Ray
- Simulations Research Line, Italian Institute of Technology, Via Enrico Melen 83, Genova GE 16152, Italy
| | - Michele Parrinello
- Simulations Research Line, Italian Institute of Technology, Via Enrico Melen 83, Genova GE 16152, Italy
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6
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Frigerio G, Donadoni E, Siani P, Vertemara J, Motta S, Bonati L, Gioia LD, Valentin CD. Mechanism of RGD-conjugated nanodevice binding to its target protein integrin α Vβ 3 by atomistic molecular dynamics and machine learning. NANOSCALE 2024; 16:4063-4081. [PMID: 38334981 DOI: 10.1039/d3nr05123d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVβ3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.
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Affiliation(s)
- Giulia Frigerio
- Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Edoardo Donadoni
- Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Paulo Siani
- Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Jacopo Vertemara
- Dipartimento di Biotecnologie e Bioscienze, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Stefano Motta
- Dipartimento di Scienze dell'Ambiente e del Territorio, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Laura Bonati
- Dipartimento di Scienze dell'Ambiente e del Territorio, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Luca De Gioia
- Dipartimento di Biotecnologie e Bioscienze, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Cristiana Di Valentin
- Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
- BioNanoMedicine Center NANOMIB, Università di Milano-Bicocca, Italy
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7
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Rubina, Moin ST. Attempting Well-Tempered Funnel Metadynamics Simulations for the Evaluation of the Binding Kinetics of Methionine Aminopeptidase-II Inhibitors. J Chem Inf Model 2023; 63:7729-7743. [PMID: 38059911 DOI: 10.1021/acs.jcim.3c01130] [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: 12/08/2023]
Abstract
Understanding the unbinding kinetics of protein-ligand complexes is considered a significant approach for the design of ligands with desired specificity and safety. In recent years, enhanced sampling methods have emerged as effective tools for studying the unbinding kinetics of protein-ligand complexes at the atomistic level. MetAP-II is a target for the treatment of cancer for which not a single effective drug is available yet. The identification of the dissociation rate of ligands from the complexes often serves as a better predictor for in vivo efficacy than the ligands' binding affinity. Here, funnel-based restraint well-tempered metadynamics simulations were applied to predict the residence time of two ligands bound to MetAP-II, along with the ligand association and dissociation mechanism involving the identification of the binding hotspot during ligand egress. The ligand-egressing route revealed by metadynamics simulations also correlated with the identified pathways from the CAVER analysis and by the enhanced sampling simulation using PLUMED. Ligand 1 formed a strong H-bond interaction with GLU364 estimating a higher residence time of 28.22 ± 5.29 ns in contrast to ligand 2 with a residence time of 19.05 ± 3.58 ns, which easily dissociated from the binding pocket of MetAP-II. The results obtained from the simulations were consistent to reveal ligand 1 being superior to ligand 2; however, the experimental data related to residence time were close for both ligands, and no kinetic data were available for ligand 2. The current study could be considered the first attempt to apply an enhanced sampling method for the evaluation of the binding kinetics and thermodynamics of two different classes of ligands to a binuclear metalloprotein.
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Affiliation(s)
- Rubina
- Third World Center for Science and Technology H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Science University of Karachi, Karachi 75270, Pakistan
| | - Syed Tarique Moin
- Third World Center for Science and Technology H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Science University of Karachi, Karachi 75270, Pakistan
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8
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Donadoni E, Frigerio G, Siani P, Motta S, Vertemara J, De Gioia L, Bonati L, Di Valentin C. Molecular Dynamics for the Optimal Design of Functionalized Nanodevices to Target Folate Receptors on Tumor Cells. ACS Biomater Sci Eng 2023; 9:6123-6137. [PMID: 37831005 PMCID: PMC10646887 DOI: 10.1021/acsbiomaterials.3c00942] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023]
Abstract
Atomistic details on the mechanism of targeting activity by biomedical nanodevices of specific receptors are still scarce in the literature, where mostly ligand/receptor pairs are modeled. Here, we use atomistic molecular dynamics (MD) simulations, free energy calculations, and machine learning approaches on the case study of spherical TiO2 nanoparticles (NPs) functionalized with folic acid (FA) as the targeting ligand of the folate receptor (FR). We consider different FA densities on the surface and different anchoring approaches, i.e., direct covalent bonding of FA γ-carboxylate or through polyethylene glycol spacers. By molecular docking, we first identify the lowest energy conformation of one FA inside the FR binding pocket from the X-ray crystal structure, which becomes the starting point of classical MD simulations in a realistic physiological environment. We estimate the binding free energy to be compared with the existing experimental data. Then, we increase complexity and go from the isolated FA to a nanosystem decorated with several FAs. Within the simulation time framework, we confirm the stability of the ligand-receptor interaction, even in the presence of the NP (with or without a spacer), and no significant modification of the protein secondary structure is observed. Our study highlights the crucial role played by the spacer, FA protonation state, and density, which are parameters that can be controlled during the nanodevice preparation step.
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Affiliation(s)
- Edoardo Donadoni
- Dipartimento
di Scienza dei Materiali, Università
di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy
| | - Giulia Frigerio
- Dipartimento
di Scienza dei Materiali, Università
di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy
| | - Paulo Siani
- Dipartimento
di Scienza dei Materiali, Università
di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy
| | - Stefano Motta
- Dipartimento
di Scienze dell’Ambiente e del Territorio, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Jacopo Vertemara
- Dipartimento
di Biotecnologie e Bioscienze, Università
di Milano-Bicocca, Piazza
della Scienza 1, 20126 Milano, Italy
| | - Luca De Gioia
- Dipartimento
di Biotecnologie e Bioscienze, Università
di Milano-Bicocca, Piazza
della Scienza 1, 20126 Milano, Italy
| | - Laura Bonati
- Dipartimento
di Scienze dell’Ambiente e del Territorio, Università di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Cristiana Di Valentin
- Dipartimento
di Scienza dei Materiali, Università
di Milano-Bicocca, via R. Cozzi 55, 20125 Milano, Italy
- BioNanoMedicine
Center NANOMIB, Università di Milano-Bicocca, via R. Follereau 3, 20854 Vedano al Lambro, Italy
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9
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Tripathi S, Nair NN. Temperature Accelerated Sliced Sampling to Probe Ligand Dissociation from Protein. J Chem Inf Model 2023; 63:5182-5191. [PMID: 37540828 DOI: 10.1021/acs.jcim.3c00376] [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: 08/06/2023]
Abstract
Modeling ligand unbinding in proteins to estimate the free energy of binding and probing the mechanism presents several challenges. They primarily pertain to the entropic bottlenecks resulting from protein and solvent conformations. While exploring the unbinding processes using enhanced sampling techniques, very long simulations are required to sample all of the conformational states as the system gets trapped in local free energy minima along transverse coordinates. Here, we demonstrate that temperature accelerated sliced sampling (TASS) is an ideal approach to overcome some of the difficulties faced by conventional sampling methods in studying ligand unbinding. Using TASS, we study the unbinding of avibactam inhibitor molecules from the Class C β-lactamase (CBL) active site. Extracting CBL-avibactam unbinding free energetics, unbinding pathways, and identifying critical interactions from the TASS simulations are demonstrated.
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Affiliation(s)
- Shubhandra Tripathi
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India
| | - Nisanth N Nair
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India
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10
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Bandyopadhyay S, Mondal J. A deep encoder-decoder framework for identifying distinct ligand binding pathways. J Chem Phys 2023; 158:2890463. [PMID: 37184003 DOI: 10.1063/5.0145197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 04/25/2023] [Indexed: 05/16/2023] Open
Abstract
The pathway(s) that a ligand would adopt en route to its trajectory to the native pocket of the receptor protein act as a key determinant of its biological activity. While Molecular Dynamics (MD) simulations have emerged as the method of choice for modeling protein-ligand binding events, the high dimensional nature of the MD-derived trajectories often remains a barrier in the statistical elucidation of distinct ligand binding pathways due to the stochasticity inherent in the ligand's fluctuation in the solution and around the receptor. Here, we demonstrate that an autoencoder based deep neural network, trained using an objective input feature of a large matrix of residue-ligand distances, can efficiently produce an optimal low-dimensional latent space that stores necessary information on the ligand-binding event. In particular, for a system of L99A mutant of T4 lysozyme interacting with its native ligand, benzene, this deep encoder-decoder framework automatically identifies multiple distinct recognition pathways, without requiring user intervention. The intermediates involve the spatially discrete location of the ligand in different helices of the protein before its eventual recognition of native pose. The compressed subspace derived from the autoencoder provides a quantitatively accurate measure of the free energy and kinetics of ligand binding to the native pocket. The investigation also recommends that while a linear dimensional reduction technique, such as time-structured independent component analysis, can do a decent job of state-space decomposition in cases where the intermediates are long-lived, autoencoder is the method of choice in systems where transient, low-populated intermediates can lead to multiple ligand-binding pathways.
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Affiliation(s)
- Satyabrata Bandyopadhyay
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad 500046, India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad 500046, India
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11
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Motta S, Siani P, Donadoni E, Frigerio G, Bonati L, Di Valentin C. Metadynamics simulations for the investigation of drug loading on functionalized inorganic nanoparticles. NANOSCALE 2023; 15:7909-7919. [PMID: 37066796 DOI: 10.1039/d3nr00397c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Inorganic nanoparticles show promising properties that allow them to be efficiently used as drug carriers. The main limitation in this type of application is currently the drug loading capacity, which can be overcome with a proper functionalization of the nanoparticle surface. In this study, we present, for the first time, a computational approach based on metadynamics to estimate the binding free energy of the doxorubicin drug (DOX) to a functionalized TiO2 nanoparticle under different pH conditions. On a thermodynamic basis, we demonstrate the robustness of our approach to capture the overall mechanism behind the pH-triggered release of DOX due to environmental pH changes. Notably, binding free energy estimations align well with what is expected for a pH-sensitive drug delivery system. Based on our results, we envision the use of metadynamics as a promising computational tool for the rational design and in silico optimization of organic ligands with improved drug carrier properties.
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Affiliation(s)
- Stefano Motta
- Dipartimento di Scienze dell'Ambiente e del Territorio, Università di Milano Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Paulo Siani
- Dipartimento di Scienza dei Materiali, Università di Milano Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Edoardo Donadoni
- Dipartimento di Scienza dei Materiali, Università di Milano Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Giulia Frigerio
- Dipartimento di Scienza dei Materiali, Università di Milano Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
| | - Laura Bonati
- Dipartimento di Scienze dell'Ambiente e del Territorio, Università di Milano Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Cristiana Di Valentin
- Dipartimento di Scienza dei Materiali, Università di Milano Bicocca, via R. Cozzi 55, 20125 Milano, Italy.
- BioNanoMedicine Center NANOMIB, University of Milano-Bicocca, Italy
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12
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Hendrix E, Motta S, Gahl RF, He Y. Insight into the Initial Stages of the Folding Process in Onconase Revealed by UNRES. J Phys Chem B 2022; 126:7934-7942. [PMID: 36179061 DOI: 10.1021/acs.jpcb.2c04770] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The unfolded state of proteins presents many challenges to elucidate the structural basis for biological function. This state is characterized by a large degree of structural heterogeneity which makes it difficult to generate structural models. However, recent experiments into the initial folding events of the 104-residue ribonuclease homologue onconase (ONC) were able to identify the regions in the protein that participate in the initial folding of this protein. Therefore, to gain additional structural insight into the unfolded state of proteins, this study utilized molecular dynamics simulations using the UNited-RESidue (UNRES) force field to evaluate whether there is a good agreement between the experimentally determined initial structures and the structures identified by computer simulations along a folding pathway. Indeed, these UNRES simulations accurately identified the two regions experimentally observed to form the initial native structure along the folding pathway of ONC. In addition, these regions are determined to be chain folding initiation sites (CFIS) according to methods developed previously. Subsequent self-organization maps (SOM) analysis has revealed key structural states involved in these early folding events.
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Affiliation(s)
- Emily Hendrix
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico87131, United States
| | - Stefano Motta
- Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan20126, Italy
| | - Robert F Gahl
- Division of Extramural Activities, National Cancer Institute, National Institutes of Health, Bethesda, Maryland20850, United States
| | - Yi He
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico87131, United States.,Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico87131, United States
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13
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Li T, Motta S, Stevens AO, Song S, Hendrix E, Pandini A, He Y. Recognizing the Binding Pattern and Dissociation Pathways of the p300 Taz2-p53 TAD2 Complex. JACS AU 2022; 2:1935-1945. [PMID: 36032526 PMCID: PMC9400049 DOI: 10.1021/jacsau.2c00358] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/14/2022] [Accepted: 07/15/2022] [Indexed: 05/21/2023]
Abstract
The dynamic association and dissociation between proteins are the basis of cellular signal transduction. This process becomes much more complicated if one or both interaction partners are intrinsically disordered because intrinsically disordered proteins can undergo disorder-to-order transitions upon binding to their partners. p53, a transcription factor with disordered regions, plays significant roles in many cellular signaling pathways. It is critical to understand the binding/unbinding mechanism involving these disordered regions of p53 at the residue level to reveal how p53 performs its biological functions. Here, we studied the dissociation process of the intrinsically disordered N-terminal transactivation domain 2 (TAD2) of p53 and the transcriptional adaptor zinc-binding 2 (Taz2) domain of transcriptional coactivator p300 using a combination of classical molecular dynamics, steered molecular dynamics, self-organizing maps, and time-resolved force distribution analysis (TRFDA). We observed two different dissociation pathways with different probabilities. One dissociation pathway starts from the TAD2 N-terminus and propagates to the α-helix and finally the C-terminus. The other dissociation pathway is in the opposite order. Subsequent TRFDA results reveal that key residues in TAD2 play critical roles. Besides the residues in agreement with previous experimental results, we also highlighted some other residues that play important roles in the disassociation process. In the dissociation process, non-native interactions were formed to partially compensate for the energy loss due to the breaking of surrounding native interactions. Moreover, our statistical analysis results of other experimentally determined complex structures involving either Taz2 or TAD2 suggest that the binding of the Taz2-TAD2 complex is mainly governed by the binding site of Taz2, which includes three main binding regions. Therefore, the complexes involving Taz2 may follow similar binding/unbinding behaviors, which could be studied together to generate common principles.
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Affiliation(s)
- Tongtong Li
- Department
of Chemistry & Chemical Biology, The
University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Stefano Motta
- Department
of Earth and Environmental Sciences, University
of Milano-Bicocca, Milan 20126, Italy
| | - Amy O. Stevens
- Department
of Chemistry & Chemical Biology, The
University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Shenghan Song
- Department
of Chemistry & Chemical Biology, The
University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Emily Hendrix
- Department
of Chemistry & Chemical Biology, The
University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Alessandro Pandini
- Department
of Computer Science, Brunel University London, Uxbridge UB8 3PH, U.K.
- The
Thomas Young Centre for Theory and Simulation of Materials, London SW7 2AZ, U.K.
| | - Yi He
- Department
of Chemistry & Chemical Biology, The
University of New Mexico, Albuquerque, New Mexico 87131, United States
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14
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Challenges and frontiers of computational modelling of biomolecular recognition. QRB DISCOVERY 2022. [DOI: 10.1017/qrd.2022.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Abstract
Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.
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15
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Basciu A, Callea L, Motta S, Bonvin AM, Bonati L, Vargiu AV. No dance, no partner! A tale of receptor flexibility in docking and virtual screening. VIRTUAL SCREENING AND DRUG DOCKING 2022. [DOI: 10.1016/bs.armc.2022.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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