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Pawnikar S, Magenheimer BS, Joshi K, Nevarez-Munoz E, Haldane A, Maser RL, Miao Y. Activation of polycystin-1 signaling by binding of stalk-derived peptide agonists. eLife 2024; 13:RP95992. [PMID: 39373641 PMCID: PMC11458180 DOI: 10.7554/elife.95992] [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: 10/08/2024] Open
Abstract
Polycystin-1 (PC1) is the protein product of the PKD1 gene whose mutation causes autosomal dominant Polycystic Kidney Disease (ADPKD). PC1 is an atypical G protein-coupled receptor (GPCR) with an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal and membrane-embedded C-terminal (CTF) fragments. Recently, activation of PC1 CTF signaling was shown to be regulated by a stalk tethered agonist (TA), resembling the mechanism observed for adhesion GPCRs. Here, synthetic peptides of the first 9- (p9), 17- (p17), and 21-residues (p21) of the PC1 stalk TA were shown to re-activate signaling by a stalkless CTF mutant in human cell culture assays. Novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) simulations elucidated binding conformations of p9, p17, and p21 and revealed multiple specific binding regions to the stalkless CTF. Peptide agonists binding to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of stalk TA-mediated PC1 CTF activation. Additional sequence coevolution analyses showed the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. These insights into the structural dynamic mechanism of PC1 activation by TA peptide agonists provide an in-depth understanding that will facilitate the development of therapeutics targeting PC1 for ADPKD treatment.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of KansasLawrenceUnited States
| | - Brenda S Magenheimer
- Clinical Laboratory Sciences, University of Kansas Medical CenterKansas CityUnited States
- The Jared Grantham Kidney Institute, University of Kansas Medical CenterKansas CityUnited States
| | - Keya Joshi
- Department of Pharmacology and Computational Medicine Program, University of North CarolinaChapel HillUnited States
| | - Ericka Nevarez-Munoz
- Clinical Laboratory Sciences, University of Kansas Medical CenterKansas CityUnited States
| | - Allan Haldane
- Department of Physics, and Center for Biophysics and Computational Biology, Temple UniversityPhiladelphiaUnited States
| | - Robin L Maser
- Clinical Laboratory Sciences, University of Kansas Medical CenterKansas CityUnited States
- The Jared Grantham Kidney Institute, University of Kansas Medical CenterKansas CityUnited States
- Department of Biochemistry and Molecular Biology, University of Kansas Medical CenterKansas CityUnited States
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North CarolinaChapel HillUnited States
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2
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Joshi K, Miao Y. Mechanisms of peptide agonist dissociation and deactivation of adhesion G-protein-coupled receptors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.07.611823. [PMID: 39314495 PMCID: PMC11419055 DOI: 10.1101/2024.09.07.611823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Adhesion G protein-coupled receptors (ADGRs) belong to Class B2 of GPCRs and are involved in a wide array of important physiological processes. ADGRs contain a GPCR autoproteolysis-inducing (GAIN) domain that is proximal to the receptor N-terminus and undergoes autoproteolysis during biosynthesis to generate two fragments: the N-terminal fragment (NTF) and C-terminal fragment (CTF). Dissociation of NTF reveals a tethered agonist to activate CTF of ADGRs for G protein signaling. Synthetic peptides that mimic the tethered agonist can also activate the ADGRs. However, mechanisms of peptide agonist dissociation and deactivation of ADGRs remain poorly understood. In this study, we have performed all-atom enhanced sampling simulations using a novel Protein-Protein Interaction-Gaussian accelerated Molecular Dynamics (PPI-GaMD) method on the ADGRG2-IP15 and ADGRG1-P7 complexes. The PPI-GaMD simulations captured dissociation of the IP15 and P7 peptide agonists from their target receptors. We were able to identify important low-energy conformations of ADGRG2 and ADGRG1 in the active, intermediate, and inactive states, as well as exploring different states of the peptide agonists IP15 and P7 during dissociation. Therefore, our PPI-GaMD simulations have revealed dynamic mechanisms of peptide agonist dissociation and deactivation of ADGRG1 and ADGRG2, which will facilitate rational design of peptide regulators of the two receptors and other ADGRs.
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Affiliation(s)
- Keya Joshi
- Department of Pharmacology and Computational Medicine Program, University of North Carolina - Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North Carolina - Chapel Hill, Chapel Hill, NC 27599, USA
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3
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Chen J, Wang J, Yang W, Zhao L, Hu G. Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning. J Chem Inf Model 2024; 64:6880-6898. [PMID: 39197061 DOI: 10.1021/acs.jcim.4c01174] [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: 08/30/2024]
Abstract
Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and principal component analysis (PCA) were carried out to probe the effect of G12C and binding of three partners NF1, RAF1, and SOS1 on the conformation alterations of KRAS4B. DL reveals that G12C and binding of partners result in alterations in the contacts of key structure domains, such as the switch domains SW1 and SW2 together with the loops L4, L5, and P-loop. Binding of NF1, RAF1, and SOS1 constrains the structural fluctuation of SW1, SW2, L4, and L5; on the contrary, G12C leads to the instability of these four structure domains. The analyses of free energy landscapes (FELs) and PCA also show that binding of partners maintains the stability of the conformational states of KRAS4B while G12C induces greater mobility of the switch domains SW1 and SW2, which produces significant impacts on the interactions of GTP with SW1, L4, and L5. Our findings suggest that partner binding and G12C play important roles in the activity and allosteric regulation of KRAS4B, which may theoretically aid in further understanding the function of KRAS4B.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
| | - Jian Wang
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Wanchun Yang
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Lu Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
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4
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Wang J, Koirala K, Do HN, Miao Y. PepBinding: A Workflow for Predicting Peptide Binding Structures by Combining Peptide Docking and Peptide Gaussian Accelerated Molecular Dynamics Simulations. J Phys Chem B 2024; 128:7332-7340. [PMID: 39041172 DOI: 10.1021/acs.jpcb.4c02047] [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: 07/24/2024]
Abstract
Predicting protein-peptide interactions is crucial for understanding peptide binding processes and designing peptide drugs. However, traditional computational modeling approaches face challenges in accurately predicting peptide-protein binding structures due to the slow dynamics and high flexibility of the peptides. Here, we introduce a new workflow termed "PepBinding" for predicting peptide binding structures, which combines peptide docking, all-atom enhanced sampling simulations using the Peptide Gaussian accelerated Molecular Dynamics (Pep-GaMD) method, and structural clustering. PepBinding has been demonstrated on seven distinct model peptides. In peptide docking using HPEPDOCK, the peptide backbone root-mean-square deviations (RMSDs) of their bound conformations relative to X-ray structures ranged from 3.8 to 16.0 Å, corresponding to the medium to inaccurate quality models according to the Critical Assessment of PRediction of Interactions (CAPRI) criteria. The Pep-GaMD simulations performed for only 200 ns significantly improved the docking models, resulting in five medium and two acceptable quality models. Therefore, PepBinding is an efficient workflow for predicting peptide binding structures and is publicly available at https://github.com/MiaoLab20/PepBinding.
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Affiliation(s)
- Jinan Wang
- Computational Medicine Program and Department of Pharmacology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Kushal Koirala
- Computational Medicine Program and Department of Pharmacology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Hung N Do
- Computational Biology Program, Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yinglong Miao
- Computational Medicine Program and Department of Pharmacology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
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5
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Wang B, Wang J, Yang W, Zhao L, Wei B, Chen J. Unveiling Allosteric Regulation and Binding Mechanism of BRD9 through Molecular Dynamics Simulations and Markov Modeling. Molecules 2024; 29:3496. [PMID: 39124901 PMCID: PMC11314499 DOI: 10.3390/molecules29153496] [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: 06/25/2024] [Revised: 07/15/2024] [Accepted: 07/24/2024] [Indexed: 08/12/2024] Open
Abstract
Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9.
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Affiliation(s)
- Bin Wang
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China;
| | - Jian Wang
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.)
| | - Wanchun Yang
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.)
| | - Lu Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.)
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China;
| | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.)
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6
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Wang J, Miao Y. Ligand Gaussian Accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides. J Chem Theory Comput 2024; 20:5829-5841. [PMID: 39002136 DOI: 10.1021/acs.jctc.4c00502] [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: 07/15/2024]
Abstract
Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional molecular dynamics (cMD), due to limited simulation time scales. Based on our previously developed ligand Gaussian accelerated molecular dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3″, in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding, and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as the model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 μs simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 were in agreement with the available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligands and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.
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Affiliation(s)
- Jinan Wang
- Computational Medicine Program and Department of Pharmacology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Yinglong Miao
- Computational Medicine Program and Department of Pharmacology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States
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7
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Yang W, Wang J, Zhao L, Chen J. Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning. Molecules 2024; 29:3377. [PMID: 39064955 PMCID: PMC11279683 DOI: 10.3390/molecules29143377] [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: 06/19/2024] [Revised: 07/15/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024] Open
Abstract
Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.
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Affiliation(s)
- Wanchun Yang
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (L.Z.)
| | | | | | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (L.Z.)
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8
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Pawnikar S, Magenheimer BS, Joshi K, Munoz EN, Haldane A, Maser RL, Miao Y. Activation of Polycystin-1 Signaling by Binding of Stalk-derived Peptide Agonists. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.06.574465. [PMID: 38260358 PMCID: PMC10802338 DOI: 10.1101/2024.01.06.574465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Polycystin-1 (PC1) is the membrane protein product of the PKD1 gene whose mutation is responsible for 85% of the cases of autosomal dominant polycystic kidney disease (ADPKD). ADPKD is primarily characterized by the formation of renal cysts and potential kidney failure. PC1 is an atypical G protein-coupled receptor (GPCR) consisting of 11 transmembrane helices and an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Recently, signaling activation of the PC1 CTF was shown to be regulated by a stalk tethered agonist (TA), a distinct mechanism observed in the adhesion GPCR family. A novel allosteric activation pathway was elucidated for the PC1 CTF through a combination of Gaussian accelerated molecular dynamics (GaMD), mutagenesis and cellular signaling experiments. Here, we show that synthetic, soluble peptides with 7 to 21 residues derived from the stalk TA, in particular, peptides including the first 9 residues (p9), 17 residues (p17) and 21 residues (p21) exhibited the ability to re-activate signaling by a stalkless PC1 CTF mutant in cellular assays. To reveal molecular mechanisms of stalk peptide-mediated signaling activation, we have applied a novel Peptide GaMD (Pep-GaMD) algorithm to elucidate binding conformations of selected stalk peptide agonists p9, p17 and p21 to the stalkless PC1 CTF. The simulations revealed multiple specific binding regions of the stalk peptide agonists to the PC1 protein including an "intermediate" bound yet inactive state. Our Pep-GaMD simulation findings were consistent with the cellular assay experimental data. Binding of peptide agonists to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of the PC1 CTF signaling activation mechanism. Using sequence covariation analysis of PC1 homologs, we further showed that the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. Therefore, structural dynamic insights into the mechanisms of PC1 activation by stalk-derived peptide agonists have enabled an in-depth understanding of PC1 signaling. They will form a foundation for development of PC1 as a therapeutic target for the treatment of ADPKD.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Brenda S. Magenheimer
- Clinical Laboratory Sciences, University of Kansas Medical Center, Kansas City, KS 66160
- The Jared Grantham Kidney Institute, University of Kansas Medical Center, Kansas City, KS 66160
| | - Keya Joshi
- Department of Pharmacology and Computational Medicine Program, University of North Carolina – Chapel Hill, Chapel Hill, NC 27599
| | - Ericka Nevarez Munoz
- Clinical Laboratory Sciences, University of Kansas Medical Center, Kansas City, KS 66160
| | - Allan Haldane
- Dept of Physics, and Center for Biophysics and Computational Biology, Temple University, Philadelphia, PA 19122
| | - Robin L. Maser
- Departments of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS 66160
- Clinical Laboratory Sciences, University of Kansas Medical Center, Kansas City, KS 66160
- The Jared Grantham Kidney Institute, University of Kansas Medical Center, Kansas City, KS 66160
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North Carolina – Chapel Hill, Chapel Hill, NC 27599
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9
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Balogh G, Bereczky Z. Molecular Mechanisms of the Impaired Heparin Pentasaccharide Interactions in 10 Antithrombin Heparin Binding Site Mutants Revealed by Enhanced Sampling Molecular Dynamics. Biomolecules 2024; 14:657. [PMID: 38927061 PMCID: PMC11201378 DOI: 10.3390/biom14060657] [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] [Received: 04/17/2024] [Revised: 05/27/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
Antithrombin (AT) is a critical regulator of the coagulation cascade by inhibiting multiple coagulation factors including thrombin and FXa. Binding of heparinoids to this serpin enhances the inhibition considerably. Mutations located in the heparin binding site of AT result in thrombophilia in affected individuals. Our aim was to study 10 antithrombin mutations known to affect their heparin binding in a heparin pentasaccharide bound state using two molecular dynamics (MD) based methods providing enhanced sampling, GaMD and LiGaMD2. The latter provides an additional boost to the ligand and the most important binding site residues. From our GaMD simulations we were able to identify four variants (three affecting amino acid Arg47 and one affecting Lys114) that have a particularly large effect on binding. The additional acceleration provided by LiGaMD2 allowed us to study the consequences of several other mutants including those affecting Arg13 and Arg129. We were able to identify several conformational types by cluster analysis. Analysis of the simulation trajectories revealed the causes of the impaired pentasaccharide binding including pentasaccharide subunit conformational changes and altered allosteric pathways in the AT protein. Our results provide insights into the effects of AT mutations interfering with heparin binding at an atomic level and can facilitate the design or interpretation of in vitro experiments.
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Affiliation(s)
- Gábor Balogh
- Division of Clinical Laboratory Science, Department of Laboratory Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
| | - Zsuzsanna Bereczky
- Division of Clinical Laboratory Science, Department of Laboratory Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
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10
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Chen J, Wang J, Yang W, Zhao L, Zhao J, Hu G. Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning. Molecules 2024; 29:2317. [PMID: 38792177 PMCID: PMC11123822 DOI: 10.3390/molecules29102317] [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: 04/23/2024] [Revised: 05/09/2024] [Accepted: 05/12/2024] [Indexed: 05/26/2024] Open
Abstract
The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg2+ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.); (J.Z.)
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
| | - Jian Wang
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.); (J.Z.)
| | - Wanchun Yang
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.); (J.Z.)
| | - Lu Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.); (J.Z.)
| | - Juan Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (L.Z.); (J.Z.)
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
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11
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Wang J, Miao Y. Ligand Gaussian accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592668. [PMID: 38766067 PMCID: PMC11100592 DOI: 10.1101/2024.05.06.592668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional Molecular Dynamics (cMD), due to limited simulation timescales. Based on our previously developed Ligand Gaussian accelerated Molecular Dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3", in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 microsecond simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 agreed with available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligand and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.
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Affiliation(s)
- Jinan Wang
- Computational Medicine Program and Department of Pharmacology, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, USA 27599
| | - Yinglong Miao
- Computational Medicine Program and Department of Pharmacology, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, USA 27599
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12
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Wang J, Yang W, Zhao L, Wei B, Chen J. Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning. Molecules 2024; 29:1857. [PMID: 38675678 PMCID: PMC11054187 DOI: 10.3390/molecules29081857] [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: 04/03/2024] [Revised: 04/16/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.
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Affiliation(s)
- Jian Wang
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Wanchun Yang
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Lu Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China
| | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China
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13
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Bao H, Wang W, Sun H, Chen J. The switch states of the GDP-bound HRAS affected by point mutations: a study from Gaussian accelerated molecular dynamics simulations and free energy landscapes. J Biomol Struct Dyn 2024; 42:3363-3381. [PMID: 37216340 DOI: 10.1080/07391102.2023.2213355] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023]
Abstract
Point mutations play a vital role in the conformational transformation of HRAS. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by constructions of free energy landscapes (FELs) were adopted to explore the effect of mutations D33K, A59T and L120A on conformation states of the GDP-bound HRAS. The results from the post-processing analyses on GaMD trajectories suggest that mutations alter the flexibility and motion modes of the switch domains from HRAS. The analyses from FELs show that mutations induce more disordered states of the switch domains and affect interactions of GDP with HRAS, implying that mutations yield a vital effect on the binding of HRAS to effectors. The GDP-residue interaction network revealed by our current work indicates that salt bridges and hydrogen bonding interactions (HBIs) play key roles in the binding of GDP to HRAS. Furthermore, instability in the interactions of magnesium ions and GDP with the switch SI leads to the extreme disorder of the switch domains. This study is expected to provide the energetic basis and molecular mechanism for further understanding the function of HRAS.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Huayin Bao
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan, China
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14
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Shen C, Yin J, Wang M, Yu Z, Xu X, Zhou Z, Hu Y, Xia C, Hu G. Mutations influence the conformational dynamics of the GDP/KRAS complex. J Biomol Struct Dyn 2024:1-14. [PMID: 38529923 DOI: 10.1080/07391102.2024.2331627] [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: 01/22/2024] [Accepted: 02/20/2024] [Indexed: 03/27/2024]
Abstract
Mutations near allosteric sites can have a significant impact on the function of KRAS. Three specific mutations, K104Q, G12D/K104Q, and G12D/G75A, which are located near allosteric positions, were selected to investigate the molecular mechanisms behind mutation-induced influences on the activity of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations followed by the principal component analysis (PCA) were performed to improve the sampling of conformational states. The results revealed that these mutations significantly alter the structural flexibility, correlated motions, and dynamic behavior of the switch regions that are essential for KRAS binding to effectors or regulators. Furthermore, the mutations have a significant impact on the hydrogen bonding interactions between GDP and the switch regions, as well as on the electrostatic interactions of magnesium ions (Mg2+) with these regions. Our results verified that these mutations strongly influence the binding of KRAS to its effectors or regulators and allosterically regulate the activity. We believe that this work can provide valuable theoretical insights into a deeper understanding of KRAS function.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Congcong Shen
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou, China
| | - Jie Yin
- Qingyun People's Hospital, Dezhou, China
| | - Min Wang
- Qingyun People's Hospital, Dezhou, China
| | - Zhiping Yu
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou, China
| | - Xin Xu
- School of Science, Xi'an Polytechnic University, Xi'an, China
| | - Zhongshun Zhou
- School of Science, Xi'an Polytechnic University, Xi'an, China
| | - Yingshi Hu
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou, China
| | - Caijuan Xia
- School of Science, Xi'an Polytechnic University, Xi'an, China
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou, China
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15
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Ngo K, Lopez Mateos D, Han Y, Rouen KC, Ahn SH, Wulff H, Clancy CE, Yarov-Yarovoy V, Vorobyov I. Elucidating molecular mechanisms of protoxin-II state-specific binding to the human NaV1.7 channel. J Gen Physiol 2024; 156:e202313368. [PMID: 38127314 PMCID: PMC10737443 DOI: 10.1085/jgp.202313368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 09/08/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells, and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-II (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.
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Affiliation(s)
- Khoa Ngo
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Diego Lopez Mateos
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Yanxiao Han
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Kyle C. Rouen
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Surl-Hee Ahn
- Department of Chemical Engineering, University of California, Davis, Davis, CA, USA
| | - Heike Wulff
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
- Center for Precision Medicine and Data Science, University of California, Davis, Davis, CA, USA
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Anesthesiology and Pain Medicine, University of California, Davis, Davis, CA, USA
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
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16
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Yu Z, Wang Z, Cui X, Cao Z, Zhang W, Sun K, Hu G. Conformational States of the GDP- and GTP-Bound HRAS Affected by A59E and K117R: An Exploration from Gaussian Accelerated Molecular Dynamics. Molecules 2024; 29:645. [PMID: 38338389 PMCID: PMC10856033 DOI: 10.3390/molecules29030645] [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] [Received: 11/27/2023] [Revised: 01/01/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
The HRAS protein is considered a critical target for drug development in cancers. It is vital for effective drug development to understand the effects of mutations on the binding of GTP and GDP to HRAS. We conducted Gaussian accelerated molecular dynamics (GaMD) simulations and free energy landscape (FEL) calculations to investigate the impacts of two mutations (A59E and K117R) on GTP and GDP binding and the conformational states of the switch domain. Our findings demonstrate that these mutations not only modify the flexibility of the switch domains, but also affect the correlated motions of these domains. Furthermore, the mutations significantly disrupt the dynamic behavior of the switch domains, leading to a conformational change in HRAS. Additionally, these mutations significantly impact the switch domain's interactions, including their hydrogen bonding with ligands and electrostatic interactions with magnesium ions. Since the switch domains are crucial for the binding of HRAS to effectors, any alterations in their interactions or conformational states will undoubtedly disrupt the activity of HRAS. This research provides valuable information for the design of drugs targeting HRAS.
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Affiliation(s)
- Zhiping Yu
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou 253023, China; (Z.Y.); (Z.C.)
| | - Zhen Wang
- Pingyin People’s Hospital, Jinan 250400, China; (Z.W.); (X.C.)
| | - Xiuzhen Cui
- Pingyin People’s Hospital, Jinan 250400, China; (Z.W.); (X.C.)
| | - Zanxia Cao
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou 253023, China; (Z.Y.); (Z.C.)
| | - Wanyunfei Zhang
- School of Science, Xi’an Polytechnic University, Xi’an 710048, China; (W.Z.); (K.S.)
| | - Kunxiao Sun
- School of Science, Xi’an Polytechnic University, Xi’an 710048, China; (W.Z.); (K.S.)
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Dezhou University, Dezhou 253023, China; (Z.Y.); (Z.C.)
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17
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Ohnuki J, Jaunet-Lahary T, Yamashita A, Okazaki KI. Accelerated Molecular Dynamics and AlphaFold Uncover a Missing Conformational State of Transporter Protein OxlT. J Phys Chem Lett 2024; 15:725-732. [PMID: 38215403 DOI: 10.1021/acs.jpclett.3c03052] [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: 01/14/2024]
Abstract
Transporter proteins change their conformations to carry their substrate across the cell membrane. The conformational dynamics is vital to understanding the transport function. We have studied the oxalate transporter (OxlT), an oxalate:formate antiporter from Oxalobacter formigenes, significant in avoiding kidney stone formation. The atomic structure of OxlT has been recently solved in the outward-open and occluded states. However, the inward-open conformation is still missing, hindering a complete understanding of the transporter. Here, we performed a Gaussian accelerated molecular dynamics simulation to sample the extensive conformational space of OxlT and successfully predicted the inward-open conformation where cytoplasmic substrate formate binding was preferred over oxalate binding. We also identified critical interactions for the inward-open conformation. The results were complemented by an AlphaFold2 structure prediction. Although AlphaFold2 solely predicted OxlT in the outward-open conformation, mutation of the identified critical residues made it partly predict the inward-open conformation, identifying possible state-shifting mutations.
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Affiliation(s)
- Jun Ohnuki
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Okazaki, Aichi 444-8585, Japan
| | - Titouan Jaunet-Lahary
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
| | - Atsuko Yamashita
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
| | - Kei-Ichi Okazaki
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Okazaki, Aichi 444-8585, Japan
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18
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Chang L, Mondal A, Singh B, Martínez-Noa Y, Perez A. Revolutionizing Peptide-Based Drug Discovery: Advances in the Post-AlphaFold Era. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2024; 14:e1693. [PMID: 38680429 PMCID: PMC11052547 DOI: 10.1002/wcms.1693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 09/18/2023] [Indexed: 05/01/2024]
Abstract
Peptide-based drugs offer high specificity, potency, and selectivity. However, their inherent flexibility and differences in conformational preferences between their free and bound states create unique challenges that have hindered progress in effective drug discovery pipelines. The emergence of AlphaFold (AF) and Artificial Intelligence (AI) presents new opportunities for enhancing peptide-based drug discovery. We explore recent advancements that facilitate a successful peptide drug discovery pipeline, considering peptides' attractive therapeutic properties and strategies to enhance their stability and bioavailability. AF enables efficient and accurate prediction of peptide-protein structures, addressing a critical requirement in computational drug discovery pipelines. In the post-AF era, we are witnessing rapid progress with the potential to revolutionize peptide-based drug discovery such as the ability to rank peptide binders or classify them as binders/non-binders and the ability to design novel peptide sequences. However, AI-based methods are struggling due to the lack of well-curated datasets, for example to accommodate modified amino acids or unconventional cyclization. Thus, physics-based methods, such as docking or molecular dynamics simulations, continue to hold a complementary role in peptide drug discovery pipelines. Moreover, MD-based tools offer valuable insights into binding mechanisms, as well as the thermodynamic and kinetic properties of complexes. As we navigate this evolving landscape, a synergistic integration of AI and physics-based methods holds the promise of reshaping the landscape of peptide-based drug discovery.
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Affiliation(s)
- Liwei Chang
- Department of Chemistry, University of Florida, Gainesville, FL 32611
| | - Arup Mondal
- Department of Chemistry, University of Florida, Gainesville, FL 32611
| | - Bhumika Singh
- Department of Chemistry, University of Florida, Gainesville, FL 32611
| | | | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL 32611
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19
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Cieślak D, Kabelka I, Bartuzi D. Molecular Dynamics Simulations in Protein-Protein Docking. Methods Mol Biol 2024; 2780:91-106. [PMID: 38987465 DOI: 10.1007/978-1-0716-3985-6_6] [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: 07/12/2024]
Abstract
Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.
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Affiliation(s)
- Dominika Cieślak
- Laboratory of Plant Protein Phosphorylation, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Ivo Kabelka
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Damian Bartuzi
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland.
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20
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Chen J, Wang W, Sun H, He W. Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters. Mini Rev Med Chem 2024; 24:1323-1333. [PMID: 38265367 DOI: 10.2174/0113895575252165231122095555] [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] [Received: 03/06/2023] [Revised: 09/05/2023] [Accepted: 10/16/2023] [Indexed: 01/25/2024]
Abstract
Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Weikai He
- School of Science, Shandong Jiaotong University, Jinan-250357, China
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21
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Do HN, Malvankar SR, Wolfe MS, Miao Y. Molecular Dynamics Activation of γ-Secretase for Cleavage of the Notch1 Substrate. ACS Chem Neurosci 2023; 14:4216-4226. [PMID: 37942767 PMCID: PMC10900880 DOI: 10.1021/acschemneuro.3c00594] [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: 11/10/2023] Open
Abstract
γ-Secretase is an intramembrane aspartyl protease complex that cleaves the transmembrane domain of over 150 peptide substrates, including amyloid precursor protein (APP) and the Notch family of receptors, via two conserved aspartates D257 and D385 in the presenilin-1 (PS1) catalytic subunit. However, while the activation of γ-secretase for cleavage of APP has been widely studied, the cleavage of Notch by γ-secretase remains poorly explored. Here, we combined Gaussian accelerated molecular dynamics (GaMD) simulations and mass spectrometry (MS) analysis of proteolytic products to present the first dynamic models for cleavage of Notch by γ-secretase. MS showed that γ-secretase cleaved the WT Notch at Notch residue G34, while cleavage of the L36F mutant Notch occurred at Notch residue C33. Initially, we prepared our simulation systems starting from the cryoEM structure of Notch-bound γ-secretase (PDB: 6IDF) and failed to capture the proper cleavages of WT and L36F Notch by γ-secretase. We then discovered an incorrect registry of the Notch substrate in the PS1 active site through alignment of the experimental structure of Notch-bound (PDB: 6IDF) and APP-bound γ-secretase (PDB: 6IYC). Every residue of the APP substrate was systematically mutated to the corresponding Notch residue to prepare a resolved model of Notch-bound γ-secretase complexes. GaMD simulations of the resolved model successfully captured γ-secretase activation for proper cleavages of both WT and L36F mutant Notch. Our findings presented here provided mechanistic insights into the structural dynamics and enzyme-substrate interactions required for γ-secretase activation for cleavage of Notch and other substrates.
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22
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Conflitti P, Raniolo S, Limongelli V. Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness. J Chem Theory Comput 2023; 19:6047-6061. [PMID: 37656199 PMCID: PMC10536999 DOI: 10.1021/acs.jctc.3c00641] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Indexed: 09/02/2023]
Abstract
Computational techniques applied to drug discovery have gained considerable popularity for their ability to filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus of these studies has historically been the search for compounds endowed with high affinity for a specific molecular target to ensure the formation of stable and long-lasting complexes. Recent evidence has also correlated the in vivo drug efficacy with its binding kinetics, thus opening new fascinating scenarios for ligand/protein binding kinetic simulations in drug discovery. The present article examines the state of the art in the field, providing a brief summary of the most popular and advanced ligand/protein binding kinetics techniques and evaluating their current limitations and the potential solutions to reach more accurate kinetic models. Particular emphasis is put on the need for a paradigm change in the present methodologies toward ligand and protein parametrization, the force field problem, characterization of the transition states, the sampling issue, and algorithms' performance, user-friendliness, and data openness.
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Affiliation(s)
- Paolo Conflitti
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
| | - Stefano Raniolo
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
| | - Vittorio Limongelli
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
- Department
of Pharmacy, University of Naples “Federico
II”, 80131 Naples, Italy
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23
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Gracia Carmona O, Oostenbrink C. Flexible Gaussian Accelerated Molecular Dynamics to Enhance Biological Sampling. J Chem Theory Comput 2023; 19:6521-6531. [PMID: 37649349 PMCID: PMC10536968 DOI: 10.1021/acs.jctc.3c00619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Indexed: 09/01/2023]
Abstract
Molecular dynamics simulations often struggle to obtain sufficient sampling to study complex molecular events due to high energy barriers separating the minima of interest. Multiple enhanced sampling techniques have been developed and improved over the years to tackle this issue. Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that works by adding a biasing potential, lifting the energy landscape up, and decreasing the height of its barriers. GaMD allows one to increase the sampling of events of interest without the need of a priori knowledge of the system or the relevant coordinates. All required acceleration parameters can be obtained from a previous search run. Upon its development, several improvements for the methodology have been proposed, among them selective GaMD in which the boosting potential is selectively applied to the region of interest. There are currently four selective GaMD methods that have shown promising results. However, all of these methods are constrained on the number, location, and scenarios in which this selective boosting potential can be applied to ligands, peptides, or protein-protein interactions. In this work, we showcase a GROMOS implementation of the GaMD methodology with a fully flexible selective GaMD approach that allows the user to define, in a straightforward way, multiple boosting potentials for as many regions as desired. We show and analyze the advantages of this flexible selective approach on two previously used test systems, the alanine dipeptide and the chignolin peptide, and extend these examples to study its applicability and potential to study conformational changes of glycans and glycosylated proteins.
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Affiliation(s)
- Oriol Gracia Carmona
- Institute
for Molecular Modeling and Simulation, Department of Material Sciences
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
| | - Chris Oostenbrink
- Institute
for Molecular Modeling and Simulation, Department of Material Sciences
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
- Christian
Doppler Laboratory for Molecular Informatics in the Biosciences, University of Natural Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
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24
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Xing C, Chen P, Zhang L. Computational insight into stability-enhanced systems of anthocyanin with protein/peptide. FOOD CHEMISTRY. MOLECULAR SCIENCES 2023; 6:100168. [PMID: 36923156 PMCID: PMC10009195 DOI: 10.1016/j.fochms.2023.100168] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/24/2022] [Accepted: 02/18/2023] [Indexed: 02/24/2023]
Abstract
Anthocyanins, which belong to the flavonoid group, are commonly found in the organs of plants native to South and Central America. However, these pigments are unstable under conditions of varying pH, heat, etc., which limits their potential applications. One method for preserving the stability of anthocyanins is through encapsulation using proteins or peptides. Nevertheless, the complex and diverse structure of these molecules, as well as the limitation of experimental technologies, have hindered a comprehensive understanding of the encapsulation processes and the mechanisms by which stability is enhanced. To address these challenges, computational methods, such as molecular docking and molecular dynamics simulation have been used to study the binding affinity and dynamics of interactions between proteins/peptides and anthocyanins. This review summarizes the mechanisms of interaction between these systems, based on computational approaches, and highlights the role of proteins and peptides in the stability enhancement of anthocyanins. It also discusses the current limitations of these methods and suggests possible solutions.
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Affiliation(s)
- Cheng Xing
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L3G1, Canada
- School of Science, Beijing Jiaotong University, 100044 Beijing, China
| | - P. Chen
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L3G1, Canada
| | - Lei Zhang
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L3G1, Canada
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25
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Hickey J, Sindhikara D, Zultanski SL, Schultz DM. Beyond 20 in the 21st Century: Prospects and Challenges of Non-canonical Amino Acids in Peptide Drug Discovery. ACS Med Chem Lett 2023; 14:557-565. [PMID: 37197469 PMCID: PMC10184154 DOI: 10.1021/acsmedchemlett.3c00037] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 03/29/2023] [Indexed: 05/19/2023] Open
Abstract
Life is constructed primarily using a toolbox of 20 canonical amino acids-relying upon these building blocks for the assembly of proteins and peptides that regulate nearly every cellular task, including cell structure, function, and maintenance. While Nature continues to be a source of inspiration for drug discovery, medicinal chemists are not beholden to only 20 canonical amino acids and have begun to explore non-canonical amino acids (ncAAs) for the construction of designer peptides with improved drug-like properties. However, as our toolbox of ncAAs expands, drug hunters are encountering new challenges in approaching the iterative peptide design-make-test-analyze cycle with a seemingly boundless set of building blocks. This Microperspective focuses on new technologies that are accelerating ncAA interrogation in peptide drug discovery (including HELM notation, late-stage functionalization, and biocatalysis) while shedding light on areas where further investment could not only accelerate the discovery of new medicines but also improve downstream development.
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Affiliation(s)
- Jennifer
L. Hickey
- Department
of Medicinal Chemistry, Merck & Co.,
Inc., Kenilworth, New Jersey 07033, United States
| | - Dan Sindhikara
- Department
of Modeling and Informatics, Merck &
Co., Inc., Kenilworth, New Jersey 07033, United States
| | - Susan L. Zultanski
- Department
of Process Research & Development, Merck
& Co., Inc., Rahway, New Jersey 07065, United States
| | - Danielle M. Schultz
- Department
of Process Research & Development, Merck
& Co., Inc., Rahway, New Jersey 07065, United States
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26
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Coppa C, Bazzoli A, Barkhordari M, Contini A. Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models. J Chem Inf Model 2023; 63:3030-3042. [PMID: 37163419 DOI: 10.1021/acs.jcim.3c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are β-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for β-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.
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Affiliation(s)
- Crescenzo Coppa
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Andrea Bazzoli
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Maral Barkhordari
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Alessandro Contini
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
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27
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Wang J, Do HN, Koirala K, Miao Y. Predicting Biomolecular Binding Kinetics: A Review. J Chem Theory Comput 2023; 19:2135-2148. [PMID: 36989090 DOI: 10.1021/acs.jctc.2c01085] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Biomolecular binding kinetics including the association (kon) and dissociation (koff) rates are critical parameters for therapeutic design of small-molecule drugs, peptides, and antibodies. Notably, the drug molecule residence time or dissociation rate has been shown to correlate with their efficacies better than binding affinities. A wide range of modeling approaches including quantitative structure-kinetic relationship models, Molecular Dynamics simulations, enhanced sampling, and Machine Learning has been developed to explore biomolecular binding and dissociation mechanisms and predict binding kinetic rates. Here, we review recent advances in computational modeling of biomolecular binding kinetics, with an outlook for future improvements.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Hung N Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Kushal Koirala
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
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28
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Pawnikar S, Bhattarai A, Ouyang SX, Vega R, Chen Y, Miao Y. Critical Non-Covalent Binding Intermediate for an Allosteric Covalent Inhibitor of SUMO E1. J Phys Chem Lett 2023; 14:2792-2799. [PMID: 36898086 PMCID: PMC10373441 DOI: 10.1021/acs.jpclett.3c00253] [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: 06/18/2023]
Abstract
Post-translational modifications by small ubiquitin-like modifiers (SUMOs) are dysregulated in many types of cancers. The SUMO E1 enzyme has recently been suggested as a new immuno-oncology target. COH000 was recently identified as a highly specific allosteric covalent inhibitor of SUMO E1. However, a marked discrepancy was found between the X-ray structure of the covalent COH000-bound SUMO E1 complex and the available structure-activity relationship (SAR) data of inhibitor analogues due to unresolved noncovalent protein-ligand interactions. Here, we have investigated noncovalent interactions between COH000 and SUMO E1 during inhibitor dissociation through novel Ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations. Our simulations have identified a critical low-energy non-covalent binding intermediate conformation of COH000 that agreed excellently with published and new SAR data of the COH000 analogues, which were otherwise inconsistent with the X-ray structure. Altogether, our biochemical experiments and LiGaMD simulations have uncovered a critical non-covalent binding intermediate during allosteric inhibition of the SUMO E1 complex.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Apurba Bhattarai
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - S. Xiaohu Ouyang
- SUMO Biosciences, Inc., 2265 E Foothill Boulevard, Pasadena, CA 91107, USA
| | - Ramir Vega
- Department of Molecular Medicine, The Beckman Research Institute, City of Hope National Medical Center, Duarte, CA, USA
| | - Yuan Chen
- Department of Surgery and Moores Cancer Center, UC San Diego Health, 3855 Health Sciences Dr, La Jolla, CA 92037
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
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29
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Shi S, Zheng L, Ren Y, Wang Z. Impacts of Mutations in the P-Loop on Conformational Alterations of KRAS Investigated with Gaussian Accelerated Molecular Dynamics Simulations. Molecules 2023; 28:molecules28072886. [PMID: 37049650 PMCID: PMC10095679 DOI: 10.3390/molecules28072886] [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] [Received: 02/19/2023] [Revised: 03/19/2023] [Accepted: 03/20/2023] [Indexed: 04/14/2023] Open
Abstract
G12 mutations heavily affect conformational transformation and activity of KRAS. In this study, Gaussian accelerated molecular dynamics (GaMD) simulations were performed on the GDP-bound wild-type (WT), G12A, G12D, and G12R KRAS to probe mutation-mediated impacts on conformational alterations of KRAS. The results indicate that three G12 mutations obviously affect the structural flexibility and internal dynamics of the switch domains. The analyses of the free energy landscapes (FELs) suggest that three G12 mutations induce more conformational states of KRAS and lead to more disordered switch domains. The principal component analysis shows that three G12 mutations change concerted motions and dynamics behavior of the switch domains. The switch domains mostly overlap with the binding region of KRAS to its effectors. Thus, the high disorder states and concerted motion changes of the switch domains induced by G12 mutations affect the activity of KRAS. The analysis of interaction network of GDP with KRAS signifies that the instability in the interactions of GDP and magnesium ion with the switch domain SW1 drives the high disordered state of the switch domains. This work is expected to provide theoretical aids for understanding the function of KRAS.
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Affiliation(s)
- Shuhua Shi
- School of Science, Shandong Jianzhu University, Jinan 250101, China
| | - Linqi Zheng
- School of Science, Shandong Jianzhu University, Jinan 250101, China
| | - Yonglian Ren
- School of Science, Shandong Jianzhu University, Jinan 250101, China
| | - Ziyu Wang
- School of Science, Shandong Jianzhu University, Jinan 250101, China
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
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30
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Wang L, Wang Y, Yu Y, Liu D, Zhao J, Zhang L. Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations. Molecules 2023; 28:molecules28062583. [PMID: 36985555 PMCID: PMC10052767 DOI: 10.3390/molecules28062583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/14/2023] Open
Abstract
BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor–residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).
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31
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Calugi L, Sautariello G, Lenci E, Mattei ML, Coppa C, Cini N, Contini A, Trabocchi A. Identification of a short ACE2-derived stapled peptide targeting the SARS-CoV-2 spike protein. Eur J Med Chem 2023; 249:115118. [PMID: 36682293 PMCID: PMC9842534 DOI: 10.1016/j.ejmech.2023.115118] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/04/2023] [Accepted: 01/11/2023] [Indexed: 01/18/2023]
Abstract
The design and synthesis of a series of peptide derivatives based on a short ACE2 α-helix 1 epitope and subsequent [i - i+4] stapling of the secondary structure resulted in the identification of a 9-mer peptide capable to compete with recombinant ACE2 towards Spike RBD in the micromolar range. Specifically, SARS-CoV-2 Spike inhibitor screening based on colorimetric ELISA assay and structural studies by circular dichroism showed the ring-closing metathesis cyclization being capable to stabilize the helical structure of the 9-mer 34HEAEDLFYQ42 epitope better than the triazole stapling via click chemistry. MD simulations showed the stapled peptide being able not only to bind the Spike RBD, sterically interfering with ACE2, but also showing higher affinity to the target as compared to parent epitope.
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Affiliation(s)
- Lorenzo Calugi
- Department of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 13, 50019, Sesto Fiorentino, Florence, Italy
| | - Giulia Sautariello
- Department of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 13, 50019, Sesto Fiorentino, Florence, Italy
| | - Elena Lenci
- Department of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 13, 50019, Sesto Fiorentino, Florence, Italy
| | - Mauro Leucio Mattei
- General Laboratory, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy
| | - Crescenzo Coppa
- Department of Pharmaceutical Sciences, University of Milan, Via Venezian 21, 20133, Milan, Italy
| | - Nicoletta Cini
- General Laboratory, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy
| | - Alessandro Contini
- Department of Pharmaceutical Sciences, University of Milan, Via Venezian 21, 20133, Milan, Italy
| | - Andrea Trabocchi
- Department of Chemistry "Ugo Schiff", University of Florence, Via della Lastruccia 13, 50019, Sesto Fiorentino, Florence, Italy.
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32
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Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket. J Chem Theory Comput 2023; 19:733-745. [PMID: 36706316 DOI: 10.1021/acs.jctc.2c01194] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics, especially in the ligand binding pocket, often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics.
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33
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Bao HY, Wang W, Sun HB, Chen JZ. Binding modes of GDP, GTP and GNP to NRAS deciphered by using Gaussian accelerated molecular dynamics simulations. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2023; 34:65-89. [PMID: 36762439 DOI: 10.1080/1062936x.2023.2165542] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 12/31/2022] [Indexed: 06/18/2023]
Abstract
Probing binding modes of GDP, GTP and GNP to NRAS are of significance for understanding the regulation mechanism on the activity of RAS proteins. Four separate Gaussian accelerated molecular dynamics (GaMD) simulations were performed on the apo, GDP-, GTP- and GNP-bound NRAS. Dynamics analyses suggest that binding of three ligands highly affects conformational states of the switch domains from NRAS, which disturbs binding of NRAS to its effectors. The analyses of free energy landscapes (FELs) indicate that binding of GDP, GTP and GNP induces more energetic states of NRAS compared to the apo NRAS but the presence of GNP makes the switch domains more ordered than binding of GDP and GNP. The information of interaction networks of ligands with NRAS reveals that the π-π interaction of residue F28 and the salt bridge interactions of K16 and D119 with ligands stabilize binding of GDP, GTP and GNP to NRAS. Meanwhile magnesium ion plays a bridge role in interactions of ligands with NRAS, which is favourable for associations of GDP, GTP and GNP with NRAS. This work is expected to provide useful information for deeply understanding the function and activity of NRAS.
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Affiliation(s)
- H Y Bao
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - W Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - H B Sun
- School of Science, Shandong Jiaotong University, Jinan, China
| | - J Z Chen
- School of Science, Shandong Jiaotong University, Jinan, China
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34
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Rogals M, Eletsky A, Huang C, Morris LC, Moremen KW, Prestegard JH. Glycan Conformation in the Heavily Glycosylated Protein, CEACAM1. ACS Chem Biol 2022; 17:3527-3534. [PMID: 36417668 PMCID: PMC9764281 DOI: 10.1021/acschembio.2c00714] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Glycans attached to glycoproteins can contribute to stability, mediate interactions with other proteins, and initiate signal transduction. Glycan conformation, which is critical to these processes, is highly variable and often depicted as sampling a multitude of conformers. These conformers can be generated by molecular dynamics simulations, and more inclusively by accelerated molecular dynamics, as well as other extended sampling methods. However, experimental assessments of the contribution that various conformers make to a native ensemble are rare. Here, we use long-range pseudo-contact shifts (PCSs) of NMR resonances from an isotopically labeled glycoprotein to identify preferred conformations of its glycans. The N-terminal domain from human Carcinoembryonic Antigen Cell Adhesion Molecule 1, hCEACAM1-Ig1, was used as the model glycoprotein in this study. It has been engineered to include a lanthanide-ion-binding loop that generates PCSs, as well as a homogeneous set of three 13C-labeled N-glycans. Analysis of the PCSs indicates that preferred glycan conformers have extensive contacts with the protein surface. Factors leading to this preference appear to include interactions between N-acetyl methyls of GlcNAc residues and hydrophobic surface pockets on the protein surface.
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35
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Chen J, Zeng Q, Wang W, Sun H, Hu G. Decoding the Identification Mechanism of an SAM-III Riboswitch on Ligands through Multiple Independent Gaussian-Accelerated Molecular Dynamics Simulations. J Chem Inf Model 2022; 62:6118-6132. [PMID: 36440874 DOI: 10.1021/acs.jcim.2c00961] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
S-Adenosyl-l-methionine (SAM)-responsive riboswitches play a central role in the regulation of bacterial gene expression at the level of transcription attenuation or translation inhibition. In this study, multiple independent Gaussian-accelerated molecular dynamics simulations were performed to decipher the identification mechanisms of SAM-III (SMK) on ligands SAM, SAH, and EEM. The results reveal that ligand binding highly affects the structural flexibility, internal dynamics, and conformational changes of SAM-III. The dynamic analysis shows that helices P3 and P4 as well as two junctions J23 and J24 of SAM-III are highly susceptible to ligand binding. Analyses of free energy landscapes suggest that ligand binding induces different free energy profiles of SAM-III, which leads to the difference in identification sites of SAM-III on ligands. The information on ligand-nucleotide interactions not only uncovers that the π-π, cation-π, and hydrogen bonding interactions drive identification of SAM-III on the three ligands but also reveals that different electrostatic properties of SAM, SAH, and EEM alter the active sites of SAM-III. Meanwhile, the results also verify that the adenine group of SAM, SAH, and EEM is well recognized by conserved nucleotides G7, A29, U37, A38, and G48. We expect that this study can provide useful information for understanding the applications of SAM-III in chemical, synthetic RNA biology, and biomedical fields.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan250357, China
| | - Qingkai Zeng
- School of Science, Shandong Jiaotong University, Jinan250357, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan250357, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan250357, China
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou253023, China
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36
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Chang L, Mondal A, Perez A. Towards rational computational peptide design. FRONTIERS IN BIOINFORMATICS 2022; 2:1046493. [PMID: 36338806 PMCID: PMC9634169 DOI: 10.3389/fbinf.2022.1046493] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/11/2022] [Indexed: 11/16/2022] Open
Abstract
Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available-and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery.
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Affiliation(s)
- Liwei Chang
- Department of Chemistry, University of Florida, Gainesville, FL, United States
- Quantum Theory Project, University of Florida, Gainesville, FL, United States
| | - Arup Mondal
- Department of Chemistry, University of Florida, Gainesville, FL, United States
- Quantum Theory Project, University of Florida, Gainesville, FL, United States
| | - Alberto Perez
- Department of Chemistry, University of Florida, Gainesville, FL, United States
- Quantum Theory Project, University of Florida, Gainesville, FL, United States
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37
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Yu YX, Wang W, Sun HB, Zhang LL, Wang LF, Yin YY. Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2022; 33:805-831. [PMID: 36322686 DOI: 10.1080/1062936x.2022.2140708] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Mutations V32I, I50V and I84V in the HIV-1 protease (PR) induce drug resistance towards drug amprenavir (APV). Multiple short molecular dynamics (MSMD) simulations and molecular mechanics generalized Born surface area (MM-GBSA) method were utilized to investigate drug-resistant mechanism of V32I, I50V and I84V towards APV. Dynamic information arising from MSMD simulations suggest that V32I, I50V and I84V highly affect structural flexibility, motion modes and conformational behaviours of two flaps in the PR. Binding free energies calculated by MM-GBSA method suggest that the decrease in binding enthalpy and the increase in binding entropy induced by mutations V32I, I50V and I84V are responsible for drug resistance of the mutated PRs on APV. The energetic contributions of separate residues on binding of APV to the PR show that V32I, I50V and I84V highly disturb the interactions of two flaps with APV and mostly drive the decrease in binding ability of APV to the PR. Thus, the conformational changes of two flaps in the PR caused by V32I, I50V and I84V play key roles in drug resistance of three mutated PR towards APV. This study can provide useful dynamics information for the design of potent inhibitors relieving drug resistance.
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Affiliation(s)
- Y X Yu
- School of Science, Shandong Jiaotong University, Jinan, China
| | - W Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - H B Sun
- School of Science, Shandong Jiaotong University, Jinan, China
| | - L L Zhang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - L F Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Y Y Yin
- School of Science, Shandong Jiaotong University, Jinan, China
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38
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Wang YT, Liao JM, Lin WW, Li CC, Huang BC, Cheng TL, Chen TC. Structural insights into Nirmatrelvir (PF-07321332)-3C-like SARS-CoV-2 protease complexation: a ligand Gaussian accelerated molecular dynamics study. Phys Chem Chem Phys 2022; 24:22898-22904. [PMID: 36124909 DOI: 10.1039/d2cp02882d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Coronavirus 3C-like protease (3CLpro) is found in SARS-CoV-2 virus, which causes COVID-19. 3CLpro controls virus replication and is a major target for target-based antiviral discovery. As reported by Pfizer, Nirmatrelvir (PF-07321332) is a competitive protein inhibitor and a clinical candidate for orally delivered medication. However, the binding mechanisms between Nirmatrelvir and 3CLpro complex structures remain unknown. This study incorporated ligand Gaussian accelerated molecular dynamics, the one-dimensional and two-dimensional potential of mean force, normal molecular dynamics, and Kramers' rate theory to determine the binding and dissociation rate constants (koff and kon) associated with the binding of the 3CLpro protein to the Nirmatrelvir inhibitor. The proposed approach addresses the challenges in designing small-molecule antiviral drugs.
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Affiliation(s)
- Yeng-Tseng Wang
- School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Taiwan. .,Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan
| | - Jun-Min Liao
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Wen-Wei Lin
- School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Taiwan. .,Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chia-Ching Li
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Bo-Cheng Huang
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Tian-Lu Cheng
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Tun-Chieh Chen
- Department of Internal Medicine, College of Medicine, Kaohsiung Medical University, Taiwan
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39
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Chen JN, Jiang F, Wu YD. Accurate Prediction for Protein-Peptide Binding Based on High-Temperature Molecular Dynamics Simulations. J Chem Theory Comput 2022; 18:6386-6395. [PMID: 36149394 DOI: 10.1021/acs.jctc.2c00743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The structural characterization of protein-peptide interactions is fundamental to elucidating biological processes and designing peptide drugs. Molecular dynamics (MD) simulations are extensively used to study biomolecular systems. However, simulating the protein-peptide binding process is usually quite expensive. Based on our previous studies, herein, we propose a simple and effective method to predict the binding site and pose of the peptide simultaneously using high-temperature (high-T) MD simulations with the RSFF2C force field. Thousands of binding events (nonspecific or specific) can be sampled during microseconds of high-T MD. From density-based clustering analysis, the structures of all of the 12 complexes (nine with linear peptides and three with cyclic peptides) can be successfully predicted with root-mean-square deviation (RMSD) < 2.5 Å. By directly simulating the process of the ligand binding onto the receptor, our method approaches experimental precision for the first time, significantly surpassing previous protein-peptide docking methods in terms of accuracy.
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Affiliation(s)
- Jia-Nan Chen
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Fan Jiang
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Yun-Dong Wu
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China.,Shenzhen Bay Laboratory, Shenzhen 518132, China.,College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
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40
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Yu Z, Su H, Chen J, Hu G. Deciphering Conformational Changes of the GDP-Bound NRAS Induced by Mutations G13D, Q61R, and C118S through Gaussian Accelerated Molecular Dynamic Simulations. Molecules 2022; 27:5596. [PMID: 36080363 PMCID: PMC9457619 DOI: 10.3390/molecules27175596] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 11/29/2022] Open
Abstract
The conformational changes in switch domains significantly affect the activity of NRAS. Gaussian-accelerated molecular dynamics (GaMD) simulations of three separate replicas were performed to decipher the effects of G13D, Q16R, and C118S on the conformational transformation of the GDP-bound NRAS. The analyses of root-mean-square fluctuations and dynamics cross-correlation maps indicated that the structural flexibility and motion modes of the switch domains involved in the binding of NRAS to effectors are highly altered by the G13D, Q61R, and C118Smutations. The free energy landscapes (FELs) suggested that mutations induce more energetic states in NRAS than the GDP-bound WT NRAS and lead to high disorder in the switch domains. The FELs also indicated that the different numbers of sodium ions entering the GDP binding regions compensate for the changes in electrostatic environments caused by mutations, especially for G13D. The GDP-residue interactions revealed that the disorder in the switch domains was attributable to the unstable hydrogen bonds between GDP and two residues, V29 and D30. This work is expected to provide information on the energetic basis and dynamics of conformational changes in switch domains that can aid in deeply understanding the target roles of NRAS in anticancer treatment.
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Affiliation(s)
- Zhiping Yu
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
| | - Hongyi Su
- Laoling People’s Hospital, Dezhou 253600, China
| | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Guodong Hu
- Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China
- Laoling People’s Hospital, Dezhou 253600, China
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41
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Chen J, Wang J, Zeng Q, Wang W, Sun H, Wei B. Exploring the deactivation mechanism of human β2 adrenergic receptor by accelerated molecular dynamic simulations. Front Mol Biosci 2022; 9:972463. [PMID: 36111136 PMCID: PMC9468641 DOI: 10.3389/fmolb.2022.972463] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
The β2 adrenergic receptor (β2AR), one of important members of the G protein coupled receptors (GPCRs), has been suggested as an important target for cardiac and asthma drugs. Two replicas of Gaussian accelerated molecular dynamics (GaMD) simulations are performed to explore the deactivation mechanism of the active β2AR bound by three different substrates, including the agonist (P0G), antagonist (JTZ) and inverse agonist (JRZ). The simulation results indicate that the Gs protein is needed to stabilize the active state of the β2AR. Without the Gs protein, the receptor could transit from the active state toward the inactive state. During the transition process, helix TM6 moves toward TM3 and TM5 in geometric space and TM5 shrinks upwards. The intermediate state is captured during the transition process of the active β2AR toward the inactive one, moreover the changes in hydrophobic interaction networks between helixes TM3, TM5, and TM6 and the formation of a salt bridge between residues Arg3.50 and Glu6.30 drive the transition process. We expect that this finding can provide energetic basis and molecular mechanism for further understanding the function and target roles of the β2AR.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan, China
- *Correspondence: Jianzhong Chen, ; Benzheng Wei,
| | - Jian Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Qingkai Zeng
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- *Correspondence: Jianzhong Chen, ; Benzheng Wei,
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42
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Copeland M, Do HN, Votapka L, Joshi K, Wang J, Amaro RE, Miao Y. Gaussian Accelerated Molecular Dynamics in OpenMM. J Phys Chem B 2022; 126:5810-5820. [PMID: 35895977 PMCID: PMC9773147 DOI: 10.1021/acs.jpcb.2c03765] [Citation(s) in RCA: 6] [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
Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.
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Affiliation(s)
- Matthew Copeland
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Hung N. Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Lane Votapka
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA 92093
| | - Keya Joshi
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Rommie E. Amaro
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA 92093
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047,To whom correspondence should be addressed:
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43
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Ahmad K, Rizzi A, Capelli R, Mandelli D, Lyu W, Carloni P. Enhanced-Sampling Simulations for the Estimation of Ligand Binding Kinetics: Current Status and Perspective. Front Mol Biosci 2022; 9:899805. [PMID: 35755817 PMCID: PMC9216551 DOI: 10.3389/fmolb.2022.899805] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 05/09/2022] [Indexed: 12/12/2022] Open
Abstract
The dissociation rate (k off) associated with ligand unbinding events from proteins is a parameter of fundamental importance in drug design. Here we review recent major advancements in molecular simulation methodologies for the prediction of k off. Next, we discuss the impact of the potential energy function models on the accuracy of calculated k off values. Finally, we provide a perspective from high-performance computing and machine learning which might help improve such predictions.
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Affiliation(s)
- Katya Ahmad
- Computational Biomedicine (IAS-5/INM-9), Forschungszentrum Jülich, Jülich, Germany
| | - Andrea Rizzi
- Computational Biomedicine (IAS-5/INM-9), Forschungszentrum Jülich, Jülich, Germany
- Atomistic Simulations, Istituto Italiano di Tecnologia, Genova, Italy
| | - Riccardo Capelli
- Department of Applied Science and Technology (DISAT), Politecnico di Torino, Torino, Italy
| | - Davide Mandelli
- Computational Biomedicine (IAS-5/INM-9), Forschungszentrum Jülich, Jülich, Germany
| | - Wenping Lyu
- Warshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong (Shenzhen), Shenzhen, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, China
| | - Paolo Carloni
- Computational Biomedicine (IAS-5/INM-9), Forschungszentrum Jülich, Jülich, Germany
- Molecular Neuroscience and Neuroimaging (INM-11), Forschungszentrum Jülich, Jülich, Germany
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44
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Chen J, Zhang S, Zeng Q, Wang W, Zhang Q, Liu X. Free Energy Profiles Relating With Conformational Transition of the Switch Domains Induced by G12 Mutations in GTP-Bound KRAS. Front Mol Biosci 2022; 9:912518. [PMID: 35586192 PMCID: PMC9108337 DOI: 10.3389/fmolb.2022.912518] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 04/15/2022] [Indexed: 01/21/2023] Open
Abstract
Mutations of G12 in KRAS have been involved in different cancers. Multiple replica-Gaussian accelerated molecular dynamics (MR-GaMD) simulations are applied to investigate conformational changes of the switch domains caused by G12C, G12D and G12R. Free energy landscapes suggest that G12C, G12D and G12R induce more energetic states compared to the GTP-bound WT KRAS and make the conformations of the switch domains more disordered, which disturbs bindings of KRAS to effectors. Dynamics analyses based on MR-GaMD trajectory show that G12C, G12D and G12R not only change structural flexibility of the switch domains but also affect their motion behavior, indicating that these three mutations can be used to tune the activity of KRAS. The analyses of interaction networks verify that the instability in interactions of the GTP with the switch SⅠ plays an important role in the high disorder states of the switch domain. This work is expected to provide useful information for deeply understanding the function of KRAS.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan, China
- *Correspondence: Jianzhong Chen, ; Xinguo Liu,
| | - Shaolong Zhang
- School of Physics and Electronics, Shandong Normal University, Jinan, China
| | - Qingkai Zeng
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Qinggang Zhang
- School of Physics and Electronics, Shandong Normal University, Jinan, China
| | - Xinguo Liu
- School of Physics and Electronics, Shandong Normal University, Jinan, China
- *Correspondence: Jianzhong Chen, ; Xinguo Liu,
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45
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Bhattarai A, Devkota S, Do HN, Wang J, Bhattarai S, Wolfe MS, Miao Y. Mechanism of Tripeptide Trimming of Amyloid β-Peptide 49 by γ-Secretase. J Am Chem Soc 2022; 144:6215-6226. [PMID: 35377629 PMCID: PMC9798850 DOI: 10.1021/jacs.1c10533] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The membrane-embedded γ-secretase complex processively cleaves within the transmembrane domain of amyloid precursor protein (APP) to produce 37-to-43-residue amyloid β-peptides (Aβ) of Alzheimer's disease (AD). Despite its importance in pathogenesis, the mechanism of processive proteolysis by γ-secretase remains poorly understood. Here, mass spectrometry and Western blotting were used to quantify the efficiency of tripeptide trimming of wild-type (WT) and familial AD (FAD) mutant Aβ49. In comparison to WT Aβ49, the efficiency of tripeptide trimming was similar for the I45F, A42T, and V46F Aβ49 FAD mutants but substantially diminished for the I45T and T48P mutants. In parallel with biochemical experiments, all-atom simulations using a novel peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method were applied to investigate the tripeptide trimming of Aβ49 by γ-secretase. The starting structure was the active γ-secretase bound to Aβ49 and APP intracellular domain (AICD), as generated from our previous study that captured the activation of γ-secretase for the initial endoproteolytic cleavage of APP (Bhattarai, A., ACS Cent. Sci. 2020, 6, 969-983). Pep-GaMD simulations captured remarkable structural rearrangements of both the enzyme and substrate, in which hydrogen-bonded catalytic aspartates and water became poised for tripeptide trimming of Aβ49 to Aβ46. These structural changes required a positively charged N-terminus of endoproteolytic coproduct AICD, which could dissociate during conformational rearrangements of the protease and Aβ49. The simulation findings were highly consistent with biochemical experimental data. Taken together, our complementary biochemical experiments and Pep-GaMD simulations have enabled elucidation of the mechanism of tripeptide trimming of Aβ49 by γ-secretase.
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Affiliation(s)
- Apurba Bhattarai
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Sujan Devkota
- Department of Medicinal Chemistry, School of Pharmacy, University of Kansas, Lawrence, Kansas 66047, United States
| | - Hung Nguyen Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Sanjay Bhattarai
- Department of Medicinal Chemistry, School of Pharmacy, University of Kansas, Lawrence, Kansas 66047, United States
| | - Michael S. Wolfe
- Department of Medicinal Chemistry, School of Pharmacy, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
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46
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Wang J, Bhattarai A, Do HN, Akhter S, Miao Y. Molecular Simulations and Drug Discovery of Adenosine Receptors. Molecules 2022; 27:2054. [PMID: 35408454 PMCID: PMC9000248 DOI: 10.3390/molecules27072054] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 02/02/2023] Open
Abstract
G protein-coupled receptors (GPCRs) represent the largest family of human membrane proteins. Four subtypes of adenosine receptors (ARs), the A1AR, A2AAR, A2BAR and A3AR, each with a unique pharmacological profile and distribution within the tissues in the human body, mediate many physiological functions and serve as critical drug targets for treating numerous human diseases including cancer, neuropathic pain, cardiac ischemia, stroke and diabetes. The A1AR and A3AR preferentially couple to the Gi/o proteins, while the A2AAR and A2BAR prefer coupling to the Gs proteins. Adenosine receptors were the first subclass of GPCRs that had experimental structures determined in complex with distinct G proteins. Here, we will review recent studies in molecular simulations and computer-aided drug discovery of the adenosine receptors and also highlight their future research opportunities.
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Affiliation(s)
| | | | | | | | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA; (J.W.); (A.B.); (H.N.D.); (S.A.)
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47
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Pawnikar S, Miao Y. Mechanism of Peptide Agonist Binding in CXCR4 Chemokine Receptor. Front Mol Biosci 2022; 9:821055. [PMID: 35359589 PMCID: PMC8963245 DOI: 10.3389/fmolb.2022.821055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/14/2022] [Indexed: 01/07/2023] Open
Abstract
Chemokine receptors are key G-protein-coupled receptors (GPCRs) that control cell migration in immune system responses, development of cardiovascular and central nervous systems, and numerous diseases. In particular, the CXCR4 chemokine receptor promotes metastasis, tumor growth and angiogenesis in cancers. CXCR4 is also used as one of the two co-receptors for T-tropic HIV-1 entry into host cells. Therefore, CXCR4 serves as an important therapeutic target for treating cancers and HIV infection. Apart from the CXCL12 endogenous peptide agonist, previous studies suggested that the first 17 amino acids of CXCL12 are sufficient to activate CXCR4. Two 17-residue peptides with positions 1-4 mutated to RSVM and ASLW functioned as super and partial agonists of CXCR4, respectively. However, the mechanism of peptide agonist binding in CXCR4 remains unclear. Here, we have investigated this mechanism through all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method. The Pep-GaMD simulations have allowed us to explore representative binding conformations of each peptide and identify critical low-energy states of CXCR4 activated by the super versus partial peptide agonists. Our simulations have provided important mechanistic insights into peptide agonist binding in CXCR4, which are expected to facilitate rational design of new peptide modulators of CXCR4 and other chemokine receptors.
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48
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Wang J, Miao Y. Protein-Protein Interaction-Gaussian Accelerated Molecular Dynamics (PPI-GaMD): Characterization of Protein Binding Thermodynamics and Kinetics. J Chem Theory Comput 2022; 18:1275-1285. [PMID: 35099970 DOI: 10.1021/acs.jctc.1c00974] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Protein-protein interactions (PPIs) play key roles in many fundamental biological processes such as cellular signaling and immune responses. However, it has proven challenging to simulate repetitive protein association and dissociation in order to calculate binding free energies and kinetics of PPIs due to long biological timescales and complex protein dynamics. To address this challenge, we have developed a new computational approach to all-atom simulations of PPIs based on a robust Gaussian accelerated molecular dynamics (GaMD) technique. The method, termed "PPI-GaMD", selectively boosts interaction potential energy between protein partners to facilitate their slow dissociation. Meanwhile, another boost potential is applied to the remaining potential energy of the entire system to effectively model the protein's flexibility and rebinding. PPI-GaMD has been demonstrated on a model system of the ribonuclease barnase interactions with its inhibitor barstar. Six independent 2 μs PPI-GaMD simulations have captured repetitive barstar dissociation and rebinding events, which enable calculations of the protein binding thermodynamics and kinetics simultaneously. The calculated binding free energies and kinetic rate constants agree well with the experimental data. Furthermore, PPI-GaMD simulations have provided mechanistic insights into barstar binding to barnase, which involves long-range electrostatic interactions and multiple binding pathways, being consistent with previous experimental and computational findings of this model system. In summary, PPI-GaMD provides a highly efficient and easy-to-use approach for binding free energy and kinetics calculations of PPIs.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
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49
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Do HN, Wang J, Bhattarai A, Miao Y. GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling. J Chem Theory Comput 2022; 18:1423-1436. [PMID: 35200019 PMCID: PMC9773012 DOI: 10.1021/acs.jctc.1c01055] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A1 receptor (A1AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A1AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.
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Affiliation(s)
- Hung N. Do
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Jinan Wang
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Apurba Bhattarai
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Yinglong Miao
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047,Corresponding author:
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50
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Célerse F, Inizan TJ, Lagardère L, Adjoua O, Monmarché P, Miao Y, Derat E, Piquemal JP. An Efficient Gaussian-Accelerated Molecular Dynamics (GaMD) Multilevel Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems. J Chem Theory Comput 2022; 18:968-977. [PMID: 35080892 DOI: 10.1021/acs.jctc.1c01024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We introduce a novel multilevel enhanced sampling strategy grounded on Gaussian-accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups, thanks to the use of fast multiple-time step integrators. To further reduce the time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD─US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the solvated CD2-CD58 system (168 000 atoms), allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added, enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling-US-GaMD (ASUS-GaMD) scheme. The highly parallel ASUS-GaMD setup decreases time to convergence by, respectively, 10 and 20 times, compared to GaMD-US and US. Overall, beside the acceleration of PMF computations, Tinker-HP now allows for the simultaneous use of Adaptive Sampling and GaMD-"dual water" enhanced sampling approaches increasing the applicability of polarizable force fields to large-scale simulations of biological systems.
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Affiliation(s)
- Frédéric Célerse
- LCT, UMR 7616 CNRS, Sorbonne Université, Paris 75005, France.,IPCM, UMR 8232 CNRS, Sorbonne Université, Paris 75005, France
| | | | - Louis Lagardère
- LCT, UMR 7616 CNRS, Sorbonne Université, Paris 75005, France.,IP2CT, FR 2622 CNRS, Sorbonne Université, Paris 75005, France
| | - Olivier Adjoua
- LCT, UMR 7616 CNRS, Sorbonne Université, Paris 75005, France
| | - Pierre Monmarché
- LCT, UMR 7616 CNRS, Sorbonne Université, Paris 75005, France.,LJLL, UMR 7598 CNRS, Sorbonne Université, Paris 75005, France
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66045, United States
| | - Etienne Derat
- IPCM, UMR 8232 CNRS, Sorbonne Université, Paris 75005, France
| | - Jean-Philip Piquemal
- LCT, UMR 7616 CNRS, Sorbonne Université, Paris 75005, France.,The University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas 78705, United States.,Institut Universitaire de France, Paris 75005, France
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