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Sundar S, Thangamani L, Piramanayagam S, Rahul CN, Aiswarya N, Sekar K, Natarajan J. Screening of FDA-approved compound library identifies potential small-molecule inhibitors of SARS-CoV-2 non-structural proteins NSP1, NSP4, NSP6 and NSP13: molecular modeling and molecular dynamics studies. ACTA ACUST UNITED AC 2021; 12:161-175. [PMID: 34121824 PMCID: PMC8188161 DOI: 10.1007/s42485-021-00067-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 05/08/2021] [Accepted: 05/31/2021] [Indexed: 12/28/2022]
Abstract
COVID-19, the current global pandemic has caused immense damage to human lives and the global economy. It is instigated by the SARS-CoV-2 virus and there is an immediate need for the identification of effective drugs against this deadly virus. SARS-CoV-2 genome codes for four structural proteins, sixteen non-structural proteins (NSPs) and several accessory proteins for its survival inside the host cells. In the present study, through in silico approaches, we aim to identify compounds that are effective against the four NSPs namely, NSP1, NSP4, NSP6 and NSP13 of SARS-CoV-2. The selection criteria of these four NSP proteins are they are least explored and potential targets. First, we have modeled the 3D structures of these proteins using homology modeling methods. Further, through molecular docking studies, we have screened the FDA-approved compounds against these modeled proteins and reported their docking scores. To gain dynamic insights, molecular dynamics studies have also been carried out for the best scored ligand against the NSPs. This study can further pave way for exposing more number of compounds against these proteins and enhance COVID-19 treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s42485-021-00067-w.
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Affiliation(s)
- Shobana Sundar
- Computational Biology Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, India
| | - Lokesh Thangamani
- Computational Biology Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, India
| | | | | | - Natarajan Aiswarya
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka India
| | - Kanagaraj Sekar
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka India
| | - Jeyakumar Natarajan
- Data Mining and Text Mining Laboratory, Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu India
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Lange A, Patel PH, Heames B, Damry AM, Saenger T, Jackson CJ, Findlay GD, Bornberg-Bauer E. Structural and functional characterization of a putative de novo gene in Drosophila. Nat Commun 2021; 12:1667. [PMID: 33712569 PMCID: PMC7954818 DOI: 10.1038/s41467-021-21667-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 02/03/2021] [Indexed: 11/26/2022] Open
Abstract
Comparative genomic studies have repeatedly shown that new protein-coding genes can emerge de novo from noncoding DNA. Still unknown is how and when the structures of encoded de novo proteins emerge and evolve. Combining biochemical, genetic and evolutionary analyses, we elucidate the function and structure of goddard, a gene which appears to have evolved de novo at least 50 million years ago within the Drosophila genus. Previous studies found that goddard is required for male fertility. Here, we show that Goddard protein localizes to elongating sperm axonemes and that in its absence, elongated spermatids fail to undergo individualization. Combining modelling, NMR and circular dichroism (CD) data, we show that Goddard protein contains a large central α-helix, but is otherwise partially disordered. We find similar results for Goddard's orthologs from divergent fly species and their reconstructed ancestral sequences. Accordingly, Goddard's structure appears to have been maintained with only minor changes over millions of years.
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Affiliation(s)
- Andreas Lange
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany
| | - Prajal H Patel
- Department of Biology, College of the Holy Cross, Worcester, MA, USA
| | - Brennen Heames
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany
| | - Adam M Damry
- Research School of Chemistry, ANU College of Science, Canberra, Australia
| | - Thorsten Saenger
- Department of Pediatric Kidney, Liver and Metabolic Diseases, Hannover Medical School, Hannover, Germany
| | - Colin J Jackson
- Research School of Chemistry, ANU College of Science, Canberra, Australia
| | | | - Erich Bornberg-Bauer
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany.
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Affinity-based proteomics reveals novel binding partners for Rab46 in endothelial cells. Sci Rep 2021; 11:4054. [PMID: 33603063 PMCID: PMC7893075 DOI: 10.1038/s41598-021-83560-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 01/27/2021] [Indexed: 12/22/2022] Open
Abstract
Rab46 is a novel Ca2+-sensing Rab GTPase shown to have important functions in endothelial and immune cells. The presence of functional Ca2+-binding, coiled-coil and Rab domains suggest that Rab46 will be important for coupling rapid responses to signalling in many cell types. The molecular mechanisms underlying Rab46 function are currently unknown. Here we provide the first resource for studying Rab46 interacting proteins. Using liquid chromatography tandem mass spectrometry (LC–MS/MS) to identify affinity purified proteins that bind to constitutively active GFP-Rab46 or inactive GFP-Rab46 expressed in endothelial cells, we have revealed 922 peptides that interact with either the GTP-bound Rab46 or GDP-bound Rab46. To identify proteins that could be potential Rab46 effectors we performed further comparative analyses between nucleotide-locked Rab46 proteins and identified 29 candidate effector proteins. Importantly, through biochemical and imaging approaches we have validated two potential effector proteins; dynein and the Na2+/ K+ ATPase subunit alpha 1 (ATP1α1). Hence, our use of affinity purification and LC–MS/MS to identify Rab46 neighbouring proteins provides a valuable resource for detecting Rab46 effector proteins and analysing Rab46 functions.
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Hatmal MM, Alshaer W, Al-Hatamleh MAI, Hatmal M, Smadi O, Taha MO, Oweida AJ, Boer JC, Mohamud R, Plebanski M. Comprehensive Structural and Molecular Comparison of Spike Proteins of SARS-CoV-2, SARS-CoV and MERS-CoV, and Their Interactions with ACE2. Cells 2020; 9:E2638. [PMID: 33302501 PMCID: PMC7763676 DOI: 10.3390/cells9122638] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 12/01/2020] [Accepted: 12/04/2020] [Indexed: 01/03/2023] Open
Abstract
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has recently emerged in China and caused a disease called coronavirus disease 2019 (COVID-19). The virus quickly spread around the world, causing a sustained global outbreak. Although SARS-CoV-2, and other coronaviruses, SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV) are highly similar genetically and at the protein production level, there are significant differences between them. Research has shown that the structural spike (S) protein plays an important role in the evolution and transmission of SARS-CoV-2. So far, studies have shown that various genes encoding primarily for elements of S protein undergo frequent mutation. We have performed an in-depth review of the literature covering the structural and mutational aspects of S protein in the context of SARS-CoV-2, and compared them with those of SARS-CoV and MERS-CoV. Our analytical approach consisted in an initial genome and transcriptome analysis, followed by primary, secondary and tertiary protein structure analysis. Additionally, we investigated the potential effects of these differences on the S protein binding and interactions to angiotensin-converting enzyme 2 (ACE2), and we established, after extensive analysis of previous research articles, that SARS-CoV-2 and SARS-CoV use different ends/regions in S protein receptor-binding motif (RBM) and different types of interactions for their chief binding with ACE2. These differences may have significant implications on pathogenesis, entry and ability to infect intermediate hosts for these coronaviruses. This review comprehensively addresses in detail the variations in S protein, its receptor-binding characteristics and detailed structural interactions, the process of cleavage involved in priming, as well as other differences between coronaviruses.
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Affiliation(s)
- Ma’mon M. Hatmal
- Department of Medical Laboratory Sciences, Faculty of Applied Health Sciences, The Hashemite University, Zarqa 13133, Jordan
| | - Walhan Alshaer
- Cell Therapy Center (CTC), The University of Jordan, Amman 11942, Jordan
| | - Mohammad A. I. Al-Hatamleh
- Department of Immunology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan 16150, Malaysia; (M.A.I.A.-H.); (R.M.)
| | | | - Othman Smadi
- Department of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan;
| | - Mutasem O. Taha
- Drug Design and Discovery Unit, Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman 11942, Jordan;
| | - Ayman J. Oweida
- Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada;
| | - Jennifer C. Boer
- Translational Immunology and Nanotechnology Unit, School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, Australia; (J.C.B.); (M.P.)
| | - Rohimah Mohamud
- Department of Immunology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan 16150, Malaysia; (M.A.I.A.-H.); (R.M.)
- Hospital Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan 16150, Malaysia
| | - Magdalena Plebanski
- Translational Immunology and Nanotechnology Unit, School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, Australia; (J.C.B.); (M.P.)
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Lim VT, Hahn DF, Tresadern G, Bayly CI, Mobley DL. Benchmark assessment of molecular geometries and energies from small molecule force fields. F1000Res 2020; 9:Chem Inf Sci-1390. [PMID: 33604023 PMCID: PMC7863993 DOI: 10.12688/f1000research.27141.1] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/18/2020] [Indexed: 12/22/2022] Open
Abstract
Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.
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Affiliation(s)
- Victoria T. Lim
- Department of Chemistry, University of California, Irvine, CA, 92697, USA
| | - David F. Hahn
- Computational Chemistry, Janssen Research & Development, Beerse, B-2340, Belgium
| | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Beerse, B-2340, Belgium
| | | | - David L. Mobley
- Department of Chemistry, University of California, Irvine, CA, 92697, USA
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA
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56
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Zhang L, Ma H, Qian W, Li H. Sequence-based protein structure optimization using enhanced simulated annealing algorithm on a coarse-grained model. J Mol Model 2020; 26:250. [PMID: 32833195 DOI: 10.1007/s00894-020-04490-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 07/30/2020] [Indexed: 12/28/2022]
Abstract
The understanding of protein structure is vital to determine biological function. We presented an enhanced simulated annealing (ESA) algorithm to investigate protein three-dimensional (3D) structure on a coarse-grained model. Inside the algorithm, we adjusted exploration equations to achieve good search intensity. To that end, our algorithm used (i) a multivariable disturbance operator for diversification of solution, (ii) a sign function to improve randomness of solution, and (iii) taking remainder operation performed on floating-point number to tackle out-of-range solution. By monitoring energy value throughout the simulation, the energy-optimal state can be found. The ESA algorithm was tested on artificial and real protein sequences with different lengths. The results show that our algorithm outperforms conventional simulated annealing algorithm and can compete with the reported algorithms before. Especially, our algorithm can obtain folding conformations with specific structural features. Further analysis shows that simulating trajectory of seeking the lowest energy can exhibit thermodynamic behavior of protein folding. Graphical Abstract.
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Affiliation(s)
- Lizhong Zhang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.,College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China
| | - He Ma
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China. .,Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang, 110169, China.
| | - Wei Qian
- Department of Electrical and Computer Engineering, College of Engineering, University of Texas, El Paso, TX, 79968, USA
| | - Haiyan Li
- College of Pharmaceutical and Bioengineering, Shenyang University of Chemical Technology, Shenyang, 110142, China
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57
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Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning. J Comput Biol 2020; 27:796-814. [DOI: 10.1089/cmb.2019.0193] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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58
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Mishra M, Agarwal S, Dixit A, Mishra VK, Kashaw V, Agrawal RK, Kashaw SK. Integrated computational investigation to develop molecular design of quinazoline scaffold as promising inhibitors of plasmodium lactate dehydrogenase. J Mol Struct 2020. [DOI: 10.1016/j.molstruc.2020.127808] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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59
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Ligand and structure based virtual screening of chemical databases to explore potent small molecule inhibitors against breast invasive carcinoma using recent computational technologies. J Mol Graph Model 2020; 98:107591. [PMID: 32234678 DOI: 10.1016/j.jmgm.2020.107591] [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: 12/03/2019] [Revised: 02/20/2020] [Accepted: 03/18/2020] [Indexed: 11/21/2022]
Abstract
Breast carcinoma is the most common invasive cancer to affect the women in the North America and the world. Cancer of breast is the number one cancer overall with estimated 1.5 lakh new cases during 2016. The success of the current endocrine therapies is often limited due to the development of resistance. Therefore, there is a need to develop new lead compounds for breast cancer treatment. As 70% of breast carcinoma is ER+, and it is well known previously that estrogen receptor alpha (ERα) is overexpressed in ER + cases, so in the current work we attempt to develop some novel potent analogues against ERα. To achieve this, we have adopted an integrative computational approach that involves multiple sequence alignment, virtual screening (ligand and structure based), molecular docking, fingerprint based clustering and molecular dynamics simulation. The approach envisaged vital information about the binding site residues, conserved sequence among different species, ligand and protein conformations, binding energy of compound to bind into the active site of the receptor. Molecular docking analysis revealed that some analogues exhibited significant binding towards ERα. The top docked complexes showing good docking scores, hydrogen bond and hydrophobic interactions were selected for molecular dynamics simulation studies. RMSD revealed that the systems were quite stable with RMSD value below 3 Å. The RMSF analysis calculated residue wise fluctuations and revealed that the residues are flexible enough to interact with the ligand. The residue at C-terminal showed more flexibility as compared to other residues. To confirm binding of these analogues, MMGBSA analysis was performed which revealed binding energy of the ligands. Further, per-residue decomposition energy analysis revealed that Glu353, Leu346, Leu387 and Arg394 contributed towards ligand binding. The results visibly indicated that MMGBSA can act as filter in virtual screening experiments and play a major role in facilitating drug discovery.
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60
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Agarwal S, Kashaw SK. Potential target identification for breast cancer and screening of small molecule inhibitors: A bioinformatics approach. J Biomol Struct Dyn 2020; 39:1975-1989. [PMID: 32186248 DOI: 10.1080/07391102.2020.1743757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
In the current study, we investigated the role of PAK1 (P21 (RAC1) Activated Kinase 1) gene in breast cancer and to this end, we performed differential gene expression analysis of PAK1 in breast cancer tissues compared to the normal adjacent tissue. We also studied its significance in protein-protein interaction (PPI) network, and analysed biological pathways, cellular processes, and role of PAK1 in different diseases. We found PAK1 to have significant role in breast cancer pathways such as integrin signaling, axonal guidance signaling, signaling by Rho family GTPases, ERK5 signaling. Additionally, it has been found as hub gene in PPI network, suggesting its possible regulatory role in breast carcinogenesis. Moreover, PAK1 had role in progression of various diseases as neoplasia, tumorigenesis, lymphatic neoplasia. Thereby, PAK1 can be used as a therapeutic target in breast cancer. Further, we put our efforts in identification of potential small molecules inhibitors against PAK1 by developing a composite virtual screening protocol involving molecular dynamics (MD) and molecular docking. The chemical library of compounds from NCI diversity sets, Pubchem and eMolecules were screened against PAK1 protein and hits which showed good binding affinity were considered for MD simulation study. Moreover, to assess binding of selected hits, MMGBSA (Molecular Mechanics-Generalized Born Surface Area) analysis was performed using AMBER (Assisted Model Building with Energy Refinement) package. MMGBSA calculations exhibited that the identified ligands showed good binding affinity with PAK1. HighlightsThe PAK1 has been found to be upregulated in breast cancer samples and is a potential oncogene playing role in different cellular functions and processes.The molecular docking studies revealed ligands showed good binding affinity towards PAK1 protein.The residues Glu345, Leu347, Thr406, Asp299, Asp393 and Gly350 were found to make H-bond interactions with small molecule inhibitors.The residues Ile276, Val284, Ala297, Tyr346, Leu396 and Asp407 were found to make hydrophobic interactions.The RMSD analysis confirmed stability of complexes throughout 40 ns production period.The MD simulations studies revealed the binding site flexibility, binding free energy of complexes and per-residue contribution in ligand binding.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shivangi Agarwal
- Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India
| | - Sushil K Kashaw
- Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India
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61
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Radan M, Ruzic D, Antonijevic M, Djikic T, Nikolic K. In silico identification of novel 5-HT 2A antagonists supported with ligand- and target-based drug design methodologies. J Biomol Struct Dyn 2020; 39:1819-1837. [PMID: 32141385 DOI: 10.1080/07391102.2020.1738961] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
A wide range of neuropsychological disorders is caused by serotonin 5-HT2A receptor (5-HT2AR) malfunction. Therefore, this receptor had been frequently used as target in CNS drug research. To design novel potent 5-HT2AR antagonists, we have combined ligand-based and target-based approaches. This study was performed on wide range of structurally diverse antagonists that were divided into three different clusters: clozapine, ziprasidone, and ChEMBL240876 derivatives. By performing the 50 ns long molecular dynamic simulations with each cluster representative in complex with 5-HT2A receptor, we have obtained virtually bioactive conformations of the ligands and three different antagonist-bound, inactive, conformations of the 5-HT2AR. These three 5-HT2AR conformations were further used for docking studies and generation of the bioactive conformations of the data set ligands in each cluster. Subsequently, selected conformers were used for 3D-Quantitative Structure Activity Relationship (3D-QSAR) modelling and pharmacophore analysis. The reliability and predictive power of the created model was assessed using an external test set compounds and showed reasonable external predictability. Statistically significant variables were used to define the most important structural features required for 5-HT2A antagonistic activity. Conclusions obtained from performed ligand-based (3D-QSAR) and target-based (molecular docking and molecular dynamics) methods were compiled and used as guidelines for rational drug design of novel 5-HT2AR antagonists.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Milica Radan
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Dusan Ruzic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Mirjana Antonijevic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Teodora Djikic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Katarina Nikolic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
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Zhang L, Ma H, Qian W, Li H. Protein structure optimization using improved simulated annealing algorithm on a three-dimensional AB off-lattice model. Comput Biol Chem 2020; 85:107237. [PMID: 32109854 DOI: 10.1016/j.compbiolchem.2020.107237] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 02/11/2020] [Accepted: 02/15/2020] [Indexed: 01/01/2023]
Abstract
This paper proposed an improved simulated annealing (ISA) algorithm for protein structure optimization based on a three-dimensional AB off-lattice model. In the algorithm, we provided a general formula used for producing initial solution, and designed a multivariable disturbance term, relating to the parameters of simulated annealing and a tuned constant, to generate neighborhood solution. To avoid missing optimal solution, storage operation was performed in searching process. We applied the algorithm to test artificial protein sequences from literature and constructed a benchmark dataset consisting of 10 real protein sequences from the Protein Data Bank (PDB). Otherwise, we generated Cα space-filling model to represent protein folding conformation. The results indicate our algorithm outperforms the five methods before in searching lower energies of artificial protein sequences. In the testing on real proteins, our method can achieve the energy conformations with Cα-RMSD less than 3.0 Å from the PDB structures. Moreover, Cα space-filling model may simulate dynamic change of protein folding conformation at atomic level.
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Affiliation(s)
- Lizhong Zhang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China
| | - He Ma
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China; Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang 110169, China.
| | - Wei Qian
- Department of Electrical and Computer Engineering, College of Engineering, University of Texas, El Paso TX 79968, USA
| | - Haiyan Li
- College of Pharmaceutical and Bioengineering, Shenyang University of Chemical Technology, Shenyang 110142, China
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63
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Wang Y, Zhou Y, Shi S, Lu G, Lin X, Xie C, Liu D, Yao D. A rational design for improving the pepsin resistance of cellulase E4 isolated from T. fusca based on the evaluation of the transition complex and molecular structure. Biochem Eng J 2020. [DOI: 10.1016/j.bej.2019.107417] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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64
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Structural bases that underline Trypanosoma cruzi calreticulin proinfective, antiangiogenic and antitumor properties. Immunobiology 2019; 225:151863. [PMID: 31732192 DOI: 10.1016/j.imbio.2019.10.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Accepted: 10/29/2019] [Indexed: 12/24/2022]
Abstract
Microbes have developed mechanisms to resist the host immune defenses and some elicit antitumor immune responses. About 6 million people are infected with Trypanosoma cruzi, the protozoan agent of Chagas' disease, the sixth neglected tropical disease worldwide. Eighty years ago, G. Roskin and N. Klyuyeva proposed that T. cruzi infection mediates an anti-cancer activity. This observation has been reproduced by several other laboratories, but no molecular basis has been proposed. We have shown that the highly pleiotropic chaperone calreticulin (TcCalr, formerly known as TcCRT), translocates from the parasite ER to the exterior, where it mediates infection. Similar to its human counterpart HuCALR (formerly known as HuCRT), TcCalr inhibits C1 in its capacity to initiate the classical pathway of complement activation. We have also proposed that TcCalr inhibits angiogenesis and it is a likely mediator of antitumor effects. We have generated several in silico structural TcCalr models to delimit a peptide (VC-TcCalr) at the TcCalr N-domain. Chemically synthesized VC-TcCalr did bind to C1q and was anti-angiogenic in Gallus gallus chorioallantoic membrane assays. These properties were associated with structural features, as determined in silico. VC-TcCalr, a strong dipole, interacts with charged proteins such as collagen-like tails and scavenger receptors. Comparatively, HuCALR has less polarity and spatial stability, probably due to at least substitutions of Gln for Gly, Arg for Lys, Arg for Asp and Ser for Arg that hinder protein-protein interactions. These differences can explain, at least in part, how TcCalr inhibits the complement activation pathway and has higher efficiency as an antiangiogenic and antitumor agent than HuCALR.
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Malliavin TE, Mucherino A, Lavor C, Liberti L. Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach. J Chem Inf Model 2019; 59:4486-4503. [PMID: 31442036 DOI: 10.1021/acs.jcim.9b00215] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The optimization approaches classically used during the determination of protein structure encounter various difficulties, especially when the size of the conformational space is large. Indeed, in such a case, algorithmic convergence criteria are more difficult to set up. Moreover, the size of the search space makes it difficult to achieve a complete exploration. The interval branch-and-prune (iBP) approach, based on the reformulation of the distance geometry problem (DGP) provides a theoretical frame for the generation of protein conformations, by systematically sampling the conformational space. When an appropriate subset of interatomic distances is known exactly, this worst-case exponential-time algorithm is provably complete and fixed-parameter tractable. These guarantees, however, immediately disappear as distance measurement errors are introduced. Here we propose an improvement of this approach: threading-augmented interval branch-and-prune (TAiBP), where the combinatorial explosion of the original iBP approach arising from its exponential complexity is alleviated by partitioning the input instances into consecutive peptide fragments and by using self-organizing maps (SOMs) to obtain clusters of similar solutions. A validation of the TAiBP approach is presented here on a set of proteins of various sizes and structures. The calculation inputs are a uniform covalent geometry extracted from force field covalent terms, the backbone dihedral angles with error intervals, and a few long-range distances. For most of the proteins smaller than 50 residues and interval widths of 20°, the TAiBP approach yielded solutions with RMSD values smaller than 3 Å with respect to the initial protein conformation. The efficiency of the TAiBP approach for proteins larger than 50 residues will require the use of nonuniform covalent geometry and may have benefits from the recent development of residue-specific force-fields.
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Affiliation(s)
- Thérèse E Malliavin
- Unité de Bioinformatique Structurale, UMR 3528, CNRS, and Departement de Bioinformatique, Biostatistique et Biologie Intégrative, USR 3756, CNRS , Institut Pasteur , 75015 Paris , France
| | | | - Carlile Lavor
- Applied Math Department , IMECC-University of Campinas , Campinas , SP 13083-970 , Brazil
| | - Leo Liberti
- LIX CNRS, Ecole Polytechnique , Institut Polytechnique de Paris , Route de Saclay , 91128 Palaiseau , France
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Wei Y, Zhang Z, She N, Chen X, Zhao Y, Zhang J. Atomistic insight into the inhibition mechanisms of suppressors of cytokine signaling on Janus kinase. Phys Chem Chem Phys 2019; 21:12905-12915. [PMID: 31157353 DOI: 10.1039/c9cp02257k] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Suppressors of cytokine signaling (SOCS) act as negative feedback regulators of the Janus kinase/signal transducer (JAK-STAT) signaling pathway by inhibiting the activity of JAK kinase. The kinase inhibitory region (KIR) of SOCS1 targets the substrate binding groove of JAK with high specificity, as demonstrated by significantly higher IC50 following the mutation of any of residue. To gain a greater understanding of the mechanisms of the inhibition of SOCS1 for JAK1, the binding mode, binding free energy decomposition, and desorption mechanism of JAK-SOCS1 complexes as well as a number of mutant systems were identified by extensive molecular dynamics (MD) simulations and the constant pulling velocity (PCV) method. Electrostatic interactions were identified for their contribution to protein-protein binding, which drove interactions between JAK1 and SOCS1. The polar residues Arg56, Arg59, and Asp105 of SOCS1 and Asp1042 and Asp1040 of JAK1 were key components in the binding, and electrostatic interactions of the side chains were prominent. The binding free energies of the six mutant proteins were lower when compared with those of the control proteins, and the side chain interactions were weakened. The residue Asp1040 played a crucial role in KIR close to the binding groove of JAK1. Moreover, salt bridges contributed significantly to JAK1 and SOCS1 binding and cleavage processes. The study presented herein provides a comprehensive understanding of the thermodynamic and dynamic processes of SOCS1 and JAK1 binding that will contribute meaningfully to the design of future studies related to peptide inhibitors based on SOCS1.
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Affiliation(s)
- Yaru Wei
- Henan Provincial Engineering Research Center of Green Anticorrosion Technology for Magnesium Alloy, College of Chemistry and Chemical Engineering, Henan University, Kaifeng 475004, People's Republic of China.
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67
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Safarizadeh H, Garkani-Nejad Z. Molecular docking, molecular dynamics simulations and QSAR studies on some of 2-arylethenylquinoline derivatives for inhibition of Alzheimer's amyloid-beta aggregation: Insight into mechanism of interactions and parameters for design of new inhibitors. J Mol Graph Model 2019; 87:129-143. [DOI: 10.1016/j.jmgm.2018.11.019] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Revised: 11/18/2018] [Accepted: 11/30/2018] [Indexed: 02/06/2023]
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68
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Safarizadeh H, Garkani-Nejad Z. Investigation of MI-2 analogues as MALT1 inhibitors to treat of diffuse large B-Cell lymphoma through combined molecular dynamics simulation, molecular docking and QSAR techniques and design of new inhibitors. J Mol Struct 2019. [DOI: 10.1016/j.molstruc.2018.12.022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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69
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Hanson J, Paliwal K, Litfin T, Yang Y, Zhou Y. Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks. Bioinformatics 2018; 35:2403-2410. [DOI: 10.1093/bioinformatics/bty1006] [Citation(s) in RCA: 115] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 11/02/2018] [Accepted: 12/06/2018] [Indexed: 11/14/2022] Open
Abstract
Abstract
Motivation
Sequence-based prediction of one dimensional structural properties of proteins has been a long-standing subproblem of protein structure prediction. Recently, prediction accuracy has been significantly improved due to the rapid expansion of protein sequence and structure libraries and advances in deep learning techniques, such as residual convolutional networks (ResNets) and Long-Short-Term Memory Cells in Bidirectional Recurrent Neural Networks (LSTM-BRNNs). Here we leverage an ensemble of LSTM-BRNN and ResNet models, together with predicted residue-residue contact maps, to continue the push towards the attainable limit of prediction for 3- and 8-state secondary structure, backbone angles (θ, τ, ϕ and ψ), half-sphere exposure, contact numbers and solvent accessible surface area (ASA).
Results
The new method, named SPOT-1D, achieves similar, high performance on a large validation set and test set (≈1000 proteins in each set), suggesting robust performance for unseen data. For the large test set, it achieves 87% and 77% in 3- and 8-state secondary structure prediction and 0.82 and 0.86 in correlation coefficients between predicted and measured ASA and contact numbers, respectively. Comparison to current state-of-the-art techniques reveals substantial improvement in secondary structure and backbone angle prediction. In particular, 44% of 40-residue fragment structures constructed from predicted backbone Cα-based θ and τ angles are less than 6 Å root-mean-squared-distance from their native conformations, nearly 20% better than the next best. The method is expected to be useful for advancing protein structure and function prediction.
Availability and implementation
SPOT-1D and its data is available at: http://sparks-lab.org/.
Supplementary information
Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jack Hanson
- Signal Processing Laboratory, Griffith University, Brisbane, QLD, Australia
| | - Kuldip Paliwal
- Signal Processing Laboratory, Griffith University, Brisbane, QLD, Australia
| | - Thomas Litfin
- School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia
| | - Yuedong Yang
- School of Data and Computer Science, Sun-Yat Sen University, Guangzhou, Guangdong, China
| | - Yaoqi Zhou
- School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia
- Institute for Glycomics, Griffith University, Gold Coast, QLD, Australia
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70
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Wang Y, Khan A, Chandra Kaushik A, Junaid M, Zhang X, Wei DQ. The systematic modeling studies and free energy calculations of the phenazine compounds as anti-tuberculosis agents. J Biomol Struct Dyn 2018; 37:4051-4069. [PMID: 30332914 DOI: 10.1080/07391102.2018.1537896] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Phenazine compounds have good activity against Mycobacterium tuberculosis (MTB). Based on the reported activities that were obtained in MTB H37Rv, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model was built to design novel compounds against MTB. A fivefold cross-validation method and external validation were used to analyze the accuracy of forecasting. The model has a cross-validation coefficient q2=0.7 and a non-cross-validation coefficient r2 = 0.903, indicating that the model has good predictive possibility. The design of anti-pneumococcus MTB compounds was guided by the obtained 3D-QSAR model, and several compounds with better activity were obtained. To test the activity of these compounds, molecular docking, molecular dynamics simulation, and post-simulation analysis of the already reported drug targets in MTB were carried out. Among the total 15 drug targets, only three targets (Rv2361c, Rv2965c, and Rv3048c) were selected based on the docking results. Initial results reported that these compounds possessed good inhibition activity for Rv2361c. The top nine complexes of Rv2361 ligands were only subjected to MD simulation which resulted in a stable dynamics of the structures and showed a residual fluctuation in inhibitors binding pocket. Free energy reported that overall, the derivatives hold strong energy against the protein target. Energetic contribution results showed that residues, Asp76, Arg80, Asn124, Arg127, Arg244, and Arg250, play a major role in total energy. Systems biology approach validates shortlisted drug effect on the entire system which might be useful to predict potential drug in wet lab as well. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Yueqi Wang
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
| | - Abbas Khan
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
| | - Aman Chandra Kaushik
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
| | - Muhammad Junaid
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
| | - Xuehong Zhang
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
| | - Dong-Qing Wei
- a State Key Laboratory of Microbial Metabolism & School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai , P. R. China
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71
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Shen ZL, Tian WD, Chen K, Ma YQ. Molecular dynamics simulation of G-actin interacting with PAMAM dendrimers. J Mol Graph Model 2018; 84:145-151. [DOI: 10.1016/j.jmgm.2018.06.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Revised: 05/13/2018] [Accepted: 06/12/2018] [Indexed: 11/15/2022]
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72
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Sieradzan AK, Golon Ł, Liwo A. Prediction of DNA and RNA structure with the NARES-2P force field and conformational space annealing. Phys Chem Chem Phys 2018; 20:19656-19663. [PMID: 30014063 DOI: 10.1039/c8cp03018a] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A physics-based method for the prediction of the structures of nucleic acids, which is based on the physics-based 2-bead NARES-2P model of polynucleotides and global-optimization Conformational Space Annealing (CSA) algorithm has been proposed. The target structure is sought as the global-energy-minimum structure, which ignores the entropy component of the free energy but spares expensive multicanonical simulations necessary to find the conformational ensemble with the lowest free energy. The CSA algorithm has been modified to optimize its performance when treating both single and multi-chain nucleic acids. It was shown that the method finds the native fold for simple RNA molecules and DNA duplexes and with limited distance restraints, which can easily be obtained from the secondary-structure-prediction servers, complex RNA folds can be treated with using moderate computer resources.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, 80-308 Gdańsk, Poland.
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73
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Agarwal S, Verma E, Kumar V, Lall N, Sau S, Iyer AK, Kashaw SK. An integrated computational approach of molecular dynamics simulations, receptor binding studies and pharmacophore mapping analysis in search of potent inhibitors against tuberculosis. J Mol Graph Model 2018; 83:17-32. [PMID: 29753941 DOI: 10.1016/j.jmgm.2018.04.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 04/26/2018] [Accepted: 04/27/2018] [Indexed: 12/15/2022]
Abstract
Tuberculosis is an infectious chronic disease caused by obligate pathogen Mycobacterium tuberculosis that affects millions of people worldwide. Although many first and second line drugs are available for its treatment, but their irrational use has adversely lead to the emerging cases of multiple drug resistant and extensively drug-resistant tuberculosis. Therefore, there is an intense need to develop novel potent analogues for its treatment. This has prompted us to develop potent analogues against TB. The Mycobacterium tuberculosis genome provides us with number of validated targets to combat against TB. Study of Mtb genome disclosed six epoxide hydrolases (A to F) which convert harmful epoxide into diols and act as a potential drug target for rational drug design. Our current strategy is to develop such analogues which inhibits epoxide hydrolase enzyme present in Mtb genome. To achieve this, we adopted an integrated computational approach involving QSAR, pharmacophore mapping, molecular docking and molecular dynamics simulation studies. The approach envisaged vital information about the role of molecular descriptors, essential pharmacophoric features and binding energy for compounds to bind into the active site of epoxide hydrolase. Molecular docking analysis revealed that analogues exhibited significant binding to Mtb epoxide hydrolase. Further, three docked complexes 2s, 37s and 15s with high, moderate and low docking scores respectively were selected for molecular dynamics simulation studies. RMSD analysis revealed that all complexes are stable with average RMSD below 2 Å throughout the 10 ns simulations. The B-factor analysis showed that the active site residues of epoxide hydrolase are flexible enough to interact with inhibitor. Moreover, to confirm the binding of these urea derivatives, MM-GBSA binding energy analysis were performed. The calculations showed that 37s has more binding affinity (ΔGtotal = -52.24 kcal/mol) towards epoxide hydrolase compared to 2s (ΔGtotal = -51.70 kcal/mol) and 15s (ΔGtotal = -49.97 kcal/mol). The structural features inferred in our study may provide the future directions to the scientists towards the discovery of new chemical entity exhibiting anti-TB property.
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Affiliation(s)
- Shivangi Agarwal
- Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India
| | - Ekta Verma
- Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India
| | - Vivek Kumar
- Department of Plant and Soil Sciences, University of Pretoria, South Africa
| | - Namrita Lall
- Department of Plant and Soil Sciences, University of Pretoria, South Africa
| | - Samaresh Sau
- Use-inspired Biomaterials & integrated Nano Delivery (U-BiND) Systems Laboratory, Department of Pharmaceutical Sciences, Wayne State University, Detroit, MI, USA
| | - Arun K Iyer
- Use-inspired Biomaterials & integrated Nano Delivery (U-BiND) Systems Laboratory, Department of Pharmaceutical Sciences, Wayne State University, Detroit, MI, USA; Molecular Imaging Program, Karmanos Cancer Institute, Detroit, MI, USA
| | - Sushil K Kashaw
- Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India.
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74
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Yang Y, Gao J, Wang J, Heffernan R, Hanson J, Paliwal K, Zhou Y. Sixty-five years of the long march in protein secondary structure prediction: the final stretch? Brief Bioinform 2018; 19:482-494. [PMID: 28040746 PMCID: PMC5952956 DOI: 10.1093/bib/bbw129] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 11/15/2016] [Indexed: 11/13/2022] Open
Abstract
Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82-84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88-90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction.
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Affiliation(s)
- Yuedong Yang
- Insitute for Glycomics and School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, QLD, Australia
| | - Jianzhao Gao
- School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China
| | - Jihua Wang
- Shandong Provincial Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou, China
| | - Rhys Heffernan
- Signal Processing Laboratory, Griffith University, Brisbane, Australia
| | - Jack Hanson
- Signal Processing Laboratory, Griffith University, Brisbane, Australia
| | - Kuldip Paliwal
- Signal Processing Laboratory, Griffith University, Brisbane, Australia
| | - Yaoqi Zhou
- Insitute for Glycomics and School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, QLD, Australia
- Shandong Provincial Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou, China
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75
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Patel JB, Chauhan JB. Computational analysis of non-synonymous single nucleotide polymorphism in the bovine cattle kappa-casein (CSN3) gene. Meta Gene 2018. [DOI: 10.1016/j.mgene.2017.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
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76
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Priya R, Sneha P, Rivera Madrid R, Doss CP, Singh P, Siva R. Molecular Modeling and Dynamic Simulation of Arabidopsis Thaliana
Carotenoid Cleavage Dioxygenase Gene: A Comparison with Bixa orellana
and Crocus Sativus. J Cell Biochem 2017; 118:2712-2721. [DOI: 10.1002/jcb.25919] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 01/30/2017] [Indexed: 01/18/2023]
Affiliation(s)
- R. Priya
- School of Bio Sciences and Technology; VIT University; Vellore 632014 Tamil Nadu India
| | - P. Sneha
- School of Bio Sciences and Technology; VIT University; Vellore 632014 Tamil Nadu India
| | - Renata Rivera Madrid
- Cenro de Investigacion Cientifica de Yucatan A.C. Calle 43 No. 130; Col. Chuburnade Hidalgo; Merida 97200 Yucatan Mexico
| | - C.George Priya Doss
- School of Bio Sciences and Technology; VIT University; Vellore 632014 Tamil Nadu India
| | - Pooja Singh
- Centre for Research in Biotechnology for Agriculture; University of Malaya; Kuala Lumpur 50603 Malaysia
| | - Ramamoorthy Siva
- School of Bio Sciences and Technology; VIT University; Vellore 632014 Tamil Nadu India
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77
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The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution. Biophys J 2017; 112:1350-1365. [PMID: 28402878 DOI: 10.1016/j.bpj.2017.02.029] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 02/16/2017] [Accepted: 02/22/2017] [Indexed: 02/05/2023] Open
Abstract
Homology modeling is a powerful tool for predicting a protein's structure. This approach is successful because proteins whose sequences are only 30% identical still adopt the same structure, while structure similarity rapidly deteriorates beyond the 30% threshold. By studying the divergence of protein structure as sequence evolves in real proteins and in evolutionary simulations, we show that this nonlinear sequence-structure relationship emerges as a result of selection for protein folding stability in divergent evolution. Fitness constraints prevent the emergence of unstable protein evolutionary intermediates, thereby enforcing evolutionary paths that preserve protein structure despite broad sequence divergence. However, on longer timescales, evolution is punctuated by rare events where the fitness barriers obstructing structure evolution are overcome and discovery of new structures occurs. We outline biophysical and evolutionary rationale for broad variation in protein family sizes, prevalence of compact structures among ancient proteins, and more rapid structure evolution of proteins with lower packing density.
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78
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Heffernan R, Yang Y, Paliwal K, Zhou Y. Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility. Bioinformatics 2017; 33:2842-2849. [DOI: 10.1093/bioinformatics/btx218] [Citation(s) in RCA: 234] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Accepted: 04/15/2017] [Indexed: 11/14/2022] Open
Affiliation(s)
- Rhys Heffernan
- Signal Processing Laboratory, Griffith University, Brisbane, QLD, Australia
| | - Yuedong Yang
- Institute for Glycomics and School of Information and Communication Technology, Griffith University, Southport, QLD, Australia
| | - Kuldip Paliwal
- Signal Processing Laboratory, Griffith University, Brisbane, QLD, Australia
| | - Yaoqi Zhou
- Institute for Glycomics and School of Information and Communication Technology, Griffith University, Southport, QLD, Australia
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79
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Sargsyan K, Grauffel C, Lim C. How Molecular Size Impacts RMSD Applications in Molecular Dynamics Simulations. J Chem Theory Comput 2017; 13:1518-1524. [PMID: 28267328 DOI: 10.1021/acs.jctc.7b00028] [Citation(s) in RCA: 221] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The root-mean-square deviation (RMSD) is a similarity measure widely used in analysis of macromolecular structures and dynamics. As increasingly larger macromolecular systems are being studied, dimensionality effects such as the "curse of dimensionality" (a diminishing ability to discriminate pairwise differences between conformations with increasing system size) may exist and significantly impact RMSD-based analyses. For such large bimolecular systems, whether the RMSD or other alternative similarity measures might suffer from this "curse" and lose the ability to discriminate different macromolecular structures had not been explicitly addressed. Here, we show such dimensionality effects for both weighted and nonweighted RMSD schemes. We also provide a mechanism for the emergence of the "curse of dimensionality" for RMSD from the law of large numbers by showing that the conformational distributions from which RMSDs are calculated become increasingly similar as the system size increases. Our findings suggest the use of weighted RMSD schemes for small proteins (less than 200 residues) and nonweighted RMSD for larger proteins when analyzing molecular dynamics trajectories.
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Affiliation(s)
- Karen Sargsyan
- Institute of Biomedical Sciences, Academia Sinica , Taipei 115, Taiwan
| | - Cédric Grauffel
- Institute of Biomedical Sciences, Academia Sinica , Taipei 115, Taiwan
| | - Carmay Lim
- Institute of Biomedical Sciences, Academia Sinica , Taipei 115, Taiwan.,Department of Chemistry, National Tsinghua University , Hsinchu 300, Taiwan
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80
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All-atom molecular dynamics simulations of lung surfactant protein B: Structural features of SP-B promote lipid reorganization. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2016; 1858:3082-3092. [DOI: 10.1016/j.bbamem.2016.09.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 08/30/2016] [Accepted: 09/20/2016] [Indexed: 01/07/2023]
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81
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Assessing the similarity of ligand binding conformations with the Contact Mode Score. Comput Biol Chem 2016; 64:403-413. [PMID: 27620381 DOI: 10.1016/j.compbiolchem.2016.08.007] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 08/17/2016] [Accepted: 08/25/2016] [Indexed: 11/22/2022]
Abstract
Structural and computational biologists often need to measure the similarity of ligand binding conformations. The commonly used root-mean-square deviation (RMSD) is not only ligand-size dependent, but also may fail to capture biologically meaningful binding features. To address these issues, we developed the Contact Mode Score (CMS), a new metric to assess the conformational similarity based on intermolecular protein-ligand contacts. The CMS is less dependent on the ligand size and has the ability to include flexible receptors. In order to effectively compare binding poses of non-identical ligands bound to different proteins, we further developed the eXtended Contact Mode Score (XCMS). We believe that CMS and XCMS provide a meaningful assessment of the similarity of ligand binding conformations. CMS and XCMS are freely available at http://brylinski.cct.lsu.edu/content/contact-mode-score and http://geaux-computational-bio.github.io/contact-mode-score/.
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82
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Engineering the thermostability of β-glucuronidase from Penicillium purpurogenum Li-3 by loop transplant. Appl Microbiol Biotechnol 2016; 100:9955-9966. [DOI: 10.1007/s00253-016-7630-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 04/18/2016] [Accepted: 05/11/2016] [Indexed: 12/21/2022]
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83
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Ghasemi F, Zomorodipour A, Karkhane AA, Khorramizadeh MR. In silico designing of hyper-glycosylated analogs for the human coagulation factor IX. J Mol Graph Model 2016; 68:39-47. [PMID: 27356208 DOI: 10.1016/j.jmgm.2016.05.011] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2015] [Revised: 05/24/2016] [Accepted: 05/25/2016] [Indexed: 11/17/2022]
Abstract
N-glycosylation is a process during which a glycan moiety attaches to the asparagine residue in the N-glycosylation consensus sequence (Asn-Xxx-Ser/Thr), where Xxx can be any amino acid except proline. Introduction of a new N-glycosylation site into a protein backbone leads to its hyper-glycosylation, and may improve the protein properties such as solubility, folding, stability, and secretion. Glyco-engineering is an approach to facilitate the hyper-glycosylation of recombinant proteins by application of the site-directed mutagenesis methods. In this regard, selection of a suitable location on the surface of a protein for introduction of a new N-glycosylation site is a main concern. In this work, a computational approach was conducted to select suitable location(s) for introducing new N-glycosylation sites into the human coagulation factor IX (hFIX). With this aim, the first 45 residues of mature hFIX were explored to find out suitable positions for introducing either Asn or Ser/Thr residues, to create new N-glycosylation site(s). Our exploration lead to detection of five potential positions, for hyper-glycosylation. For each suggested position, an analog was defined and subjected for N-glycosylation efficiency prediction. After generation of three-dimensional structures, by homology-based modeling, the five designed analogs were examined by molecular dynamic (MD) simulations, to predict their stability levels and probable structural distortions caused by amino acid substitutions, relative to the native counterpart. Three out of five suggested analogs, namely; E15T, K22N, and R37N, reached equilibration state with relatively constant Root Mean Square Deviation values. Additional analysis on the data obtained during MD simulations, lead us to conclude that, R37N is the only qualified analog with the most similar structure and dynamic behavior to that of the native counterpart, to be considered for further experimental investigations.
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Affiliation(s)
- Fahimeh Ghasemi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
| | - Alireza Zomorodipour
- Department of Molecular Medicine, Institute of Medical Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), P.O. Box: 14965/161, Tehran, Iran.
| | - Ali Asghar Karkhane
- Institute of Industrial and Environmental Biotechnology (IIEB), National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
| | - M Reza Khorramizadeh
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran; Biosensor Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Endocrinology and Metabolism Research Institute (EMRI), Tehran University of Medical Sciences, 5th Fl., Dr. Shariati Hospital, North Karegar Ave., Tehran 1411413137, Iran.
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84
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Yang K, Różycki B, Cui F, Shi C, Chen W, Li Y. Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations. PLoS One 2016; 11:e0156043. [PMID: 27227775 PMCID: PMC4881967 DOI: 10.1371/journal.pone.0156043] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 05/09/2016] [Indexed: 01/08/2023] Open
Abstract
Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.
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Affiliation(s)
- Kecheng Yang
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bartosz Różycki
- Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, 02–668, Warsaw, Poland
| | - Fengchao Cui
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- * E-mail: (FC); (YL)
| | - Ce Shi
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
| | - Wenduo Chen
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
| | - Yunqi Li
- Key Laboratory of Synthetic Rubber & Laboratory of Advanced Power Sources, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun, 130022, P. R. China
- * E-mail: (FC); (YL)
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85
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Kumar V, Sobhia ME. Molecular dynamics-based investigation of InhA substrate binding loop for diverse biological activity of direct InhA inhibitors. J Biomol Struct Dyn 2016; 34:2434-52. [DOI: 10.1080/07391102.2015.1118410] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Vivek Kumar
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar 160 062, Punjab, India
| | - M. Elizabeth Sobhia
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar 160 062, Punjab, India
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86
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Feng X, Tang H, Han B, Lv B, Li C. Enhancing the Thermostability of β-Glucuronidase by Rationally Redesigning the Catalytic Domain Based on Sequence Alignment Strategy. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.6b00535] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Xudong Feng
- School of Life Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China
| | - Heng Tang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China
| | - Beijia Han
- School of Life Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China
| | - Bo Lv
- School of Life Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China
| | - Chun Li
- School of Life Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China
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87
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Qiu Y, Wu X, Xie C, Hu Y, Liu D, Ma Y, Yao D. A rational design for improving the trypsin resistance of aflatoxin-detoxifizyme (ADTZ) based on molecular structure evaluation. Enzyme Microb Technol 2016; 86:84-92. [PMID: 26992797 DOI: 10.1016/j.enzmictec.2016.02.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Revised: 01/26/2016] [Accepted: 02/12/2016] [Indexed: 12/01/2022]
Abstract
The resistance of feed enzymes against proteases is crucial in livestock farming. In this study, the trypsin resistance of aflatoxin-detoxifizyme (ADTZ) is improved. ADTZ possesses 72 lys/arg residue sites, 45 of which are scattered on the outermost layers of the molecule (RSA≧25%). These 45 lys/arg sites could be target sites for trypsin hydrolysis. By considering shape-matching (including physical and secondary bond interactions) and the "induced fit-effect", we hypothesized that some of these lys/arg sites are vulnerable to trypsin. A protein-protein docking simulation method was used to avoid the massive computational requirements and to address the intricacy of selecting candidate sites, as candidate site selection is affected by space displacement. Optimal mutants (K244Q/K213C/K270T and R356E/K357T/R623C) were predicted by computational design with protein folding energy analysis and molecular dynamics simulations. A trypsin digestion assay was performed, and the mutants displayed much higher stability against trypsin hydrolysis compared to the native enzyme. Moreover, temperature- and pH-activity profiles revealed that the designed mutations did not affect the catalytic activity of the enzyme.
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Affiliation(s)
- Yuxin Qiu
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China
| | - Xiyang Wu
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China
| | - Chunfang Xie
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China; Department of Bioengineering, Jinan University, Guangzhou City, Guangdong Province 510632, China
| | - Yadong Hu
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China
| | - Daling Liu
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China; Department of Bioengineering, Jinan University, Guangzhou City, Guangdong Province 510632, China
| | - Yi Ma
- National Engineering Research Center of Genetic Medicine, Guangzhou City, Guangdong Province 510632, China
| | - Dongsheng Yao
- Institute of Microbial Biotechnology, Jinan University, Guangzhou City, Guangdong Province 510632, China; National Engineering Research Center of Genetic Medicine, Guangzhou City, Guangdong Province 510632, China.
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88
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Hoffmann J, Wrabl JO, Hilser VJ. The role of negative selection in protein evolution revealed through the energetics of the native state ensemble. Proteins 2016; 84:435-47. [PMID: 26800099 DOI: 10.1002/prot.24989] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 12/15/2015] [Accepted: 12/19/2015] [Indexed: 12/14/2022]
Abstract
Knowing the determinants of conformational specificity is essential for understanding protein structure, stability, and fold evolution. To address this issue, a novel statistical measure of energetic compatibility between sequence and structure was developed using an experimentally validated model of the energetics of the native state ensemble. This approach successfully matched sequences from a diverse subset of the human proteome to their respective folds. Unexpectedly, significant energetic compatibility between ostensibly unrelated sequences and structures was also observed. Interrogation of these matches revealed a general framework for understanding the origins of conformational specificity within a proteome: specificity is a complex function of both the ability of a sequence to adopt folds other than the native, and ability of a fold to accommodate sequences other than the native. The regional variation in energetic compatibility indicates that the compatibility is dominated by incompatibility of sequence for alternative fold segments, suggesting that evolution of protein sequences has involved substantial negative selection, with certain segments serving as "gatekeepers" that presumably prevent alternative structures. Beyond these global trends, a size dependence exists in the degree to which the energetic compatibility is determined from negative selection, with smaller proteins displaying more negative selection. This partially explains how short sequences can adopt unique folds, despite the higher probability in shorter proteins for small numbers of mutations to increase compatibility with other folds. In providing evolutionary ground rules for the thermodynamic relationship between sequence and fold, this framework imparts valuable insight for rational design of unique folds or fold switches.
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Affiliation(s)
- Jordan Hoffmann
- Department of Biology, Johns Hopkins University, Baltimore, Maryland, 21218.,T. C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland, 21218
| | - James O Wrabl
- Department of Biology, Johns Hopkins University, Baltimore, Maryland, 21218.,T. C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Vincent J Hilser
- Department of Biology, Johns Hopkins University, Baltimore, Maryland, 21218.,T. C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland, 21218
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89
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Kumar V, Sobhia ME. Molecular Dynamics Assisted Mechanistic Study of Isoniazid-Resistance against Mycobacterium tuberculosis InhA. PLoS One 2015; 10:e0144635. [PMID: 26658674 PMCID: PMC4682841 DOI: 10.1371/journal.pone.0144635] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 11/21/2015] [Indexed: 12/20/2022] Open
Abstract
Examination of InhA mutants I16T, I21V, I47T, S94A, and I95P showed that direct and water mediated H-bond interactions between NADH and binding site residues reduced drastically. It allowed conformational flexibility to NADH, particularly at the pyrophosphate region, leading to weakening of its binding at dinucleotide binding site. The highly scattered distribution of pyrophosphate dihedral angles and chi1 side chain dihedral angles of corresponding active site residues therein confirmed weak bonding between InhA and NADH. The average direct and water mediated bridged H-bond interactions between NADH and mutants were observed weaker as compared to wild type. Further, estimated NADH binding free energy in mutants supported the observed weakening of InhA-NADH interactions. Similarly, per residue contribution to NADH binding was also found little less as compared to corresponding residues in wild type. This investigation clearly depicted and supported the effect of mutations on NADH binding and can be accounted for isoniazid resistance as suggested by previous biochemical and mutagenic studies. Further, structural analysis of InhA provided the crucial points to enhance the NADH binding affinity towards InhA mutants in the presence of direct InhA inhibitors to combat isoniazid drug resistance. This combination could be a potential alternative for treatment of drug resistant tuberculosis.
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Affiliation(s)
- Vivek Kumar
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar- 160 062, Punjab, India
| | - M. Elizabeth Sobhia
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar- 160 062, Punjab, India
- * E-mail:
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90
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Dyrka W, Kurczyńska M, Konopka BM, Kotulska M. Fast assessment of structural models of ion channels based on their predicted current-voltage characteristics. Proteins 2015; 84:217-31. [PMID: 26650347 DOI: 10.1002/prot.24967] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Revised: 11/19/2015] [Accepted: 11/29/2015] [Indexed: 11/11/2022]
Abstract
Computational prediction of protein structures is a difficult task, which involves fast and accurate evaluation of candidate model structures. We propose to enhance single-model quality assessment with a functionality evaluation phase for proteins whose quantitative functional characteristics are known. In particular, this idea can be applied to evaluation of structural models of ion channels, whose main function - conducting ions - can be quantitatively measured with the patch-clamp technique providing the current-voltage characteristics. The study was performed on a set of KcsA channel models obtained from complete and incomplete contact maps. A fast continuous electrodiffusion model was used for calculating the current-voltage characteristics of structural models. We found that the computed charge selectivity and total current were sensitive to structural and electrostatic quality of models. In practical terms, we show that evaluating predicted conductance values is an appropriate method to eliminate models with an occluded pore or with multiple erroneously created pores. Moreover, filtering models on the basis of their predicted charge selectivity results in a substantial enrichment of the candidate set in highly accurate models. Tests on three other ion channels indicate that, in addition to being a proof of the concept, our function-oriented single-model quality assessment method can be directly applied to evaluation of structural models of some classes of protein channels. Finally, our work raises an important question whether a computational validation of functionality should be included in the evaluation process of structural models, whenever possible.
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Affiliation(s)
- Witold Dyrka
- Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, Wroclaw, 50-370, Poland
| | - Monika Kurczyńska
- Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, Wroclaw, 50-370, Poland
| | - Bogumił M Konopka
- Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, Wroclaw, 50-370, Poland
| | - Małgorzata Kotulska
- Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, Wroclaw, 50-370, Poland
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91
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Patel SM, Koringa PG, Reddy BB, Nathani NM, Joshi CG. In silico analysis of consequences of non-synonymous SNPs of Slc11a2 gene in Indian bovines. GENOMICS DATA 2015; 5:72-9. [PMID: 26484229 PMCID: PMC4583633 DOI: 10.1016/j.gdata.2015.05.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Revised: 05/21/2015] [Accepted: 05/21/2015] [Indexed: 01/20/2023]
Abstract
The aim of our study was to analyze the consequences of non-synonymous SNPs in Slc11a2 gene using bioinformatic tools. There is a current need of efficient bioinformatic tools for in-depth analysis of data generated by the next generation sequencing technologies. SNPs are known to play an imperative role in understanding the genetic basis of many genetic diseases. Slc11a2 is one of the major metal transporter families in mammals and plays a critical role in host defenses. In this study, we performed a comprehensive analysis of the impact of all non-synonymous SNPs in this gene using multiple tools like SIFT, PROVEAN, I-Mutant and PANTHER. Among the total 124 SNPs obtained from amplicon sequencing of Slc11a2 gene by Ion Torrent PGM involving 10 individuals of Gir cattle and Murrah buffalo each, we found 22 non-synonymous. Comparing the prediction of these 4 methods, 5 nsSNPs (G369R, Y374C, A377V, Q385H and N492S) were identified as deleterious. In addition, while tested out for polar interactions with other amino acids in the protein, from above 5, Y374C, Q385H and N492S showed a change in interaction pattern and further confirmed by an increase in total energy after energy minimizations in case of mutant protein compared to the native. 22 nsSNPs were predicted to decrease the stability of protein based on I-Mutant. From these SNPs, 5 was identified as deleterious by SIFT, PROVEAN, and PANTHER. Y374C, Q385H and N492S were found to be damaging.
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Key Words
- ATM, ataxia telangiectasia mutated
- BRAF, B-Raf
- CFTR, cystic fibrosis transmembrane conductance regulator
- GATK, Genome Analysis Tool Kit
- GalNAc-T1, N-acetylgalactosaminyltransferase 1
- HBB, hemoglobin beta
- HMM, Hidden Markov Model
- IGF1R, insulin-like growth factor 1 receptor
- Ion torrent PGM
- NCBI, National Center for Biotechnology Information
- Non-synonymous
- PANTHER
- PANTHER, Protein Analysis Through Evolutionary Relationships
- PROVEAN, Protein Variation Effect Analyzer
- PolyPhen, Polymorphism Phenotyping
- Protein
- RMSD, root-mean-square deviation
- SIFT
- SIFT, sorting intolerant from tolerant
- SNP, single nucleotide polymorphism
- Slc11a2, solute carrier family 11 member 2
- TMDs, transmembrane domains
- TYRP1, tyrosinase-related protein 1
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Affiliation(s)
- Shreya M Patel
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Prakash G Koringa
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Bhaskar B Reddy
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Neelam M Nathani
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Chaitanya G Joshi
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
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92
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Lee MS, Yu M, Kim KY, Park GH, Kwack K, Kim KP. Functional Validation of Rare Human Genetic Variants Involved in Homologous Recombination Using Saccharomyces cerevisiae. PLoS One 2015; 10:e0124152. [PMID: 25938495 PMCID: PMC4418691 DOI: 10.1371/journal.pone.0124152] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 03/10/2015] [Indexed: 12/02/2022] Open
Abstract
Systems for the repair of DNA double-strand breaks (DSBs) are necessary to maintain genome integrity and normal functionality of cells in all organisms. Homologous recombination (HR) plays an important role in repairing accidental and programmed DSBs in mitotic and meiotic cells, respectively. Failure to repair these DSBs causes genome instability and can induce tumorigenesis. Rad51 and Rad52 are two key proteins in homologous pairing and strand exchange during DSB-induced HR; both are highly conserved in eukaryotes. In this study, we analyzed pathogenic single nucleotide polymorphisms (SNPs) in human RAD51 and RAD52 using the Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant from Tolerant (SIFT) algorithms and observed the effect of mutations in highly conserved domains of RAD51 and RAD52 on DNA damage repair in a Saccharomyces cerevisiae-based system. We identified a number of rad51 and rad52 alleles that exhibited severe DNA repair defects. The functionally inactive SNPs were located near ATPase active site of Rad51 and the DNA binding domain of Rad52. The rad51-F317I, rad52-R52W, and rad52-G107C mutations conferred hypersensitivity to methyl methane sulfonate (MMS)-induced DNA damage and were defective in HR-mediated DSB repair. Our study provides a new approach for detecting functional and loss-of-function genetic polymorphisms and for identifying causal variants in human DNA repair genes that contribute to the initiation or progression of cancer.
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Affiliation(s)
- Min-Soo Lee
- Department of Life Science, Chung-Ang University, Seoul, Korea
| | - Mi Yu
- Department of Life Science, Chung-Ang University, Seoul, Korea
| | - Kyoung-Yeon Kim
- Department of Biomedical Science, CHA University, Seongnam, Korea
| | - Geun-Hee Park
- Department of Life Science, Chung-Ang University, Seoul, Korea
| | - KyuBum Kwack
- Department of Biomedical Science, CHA University, Seongnam, Korea
- * E-mail: (KPK); (KBK)
| | - Keun P. Kim
- Department of Life Science, Chung-Ang University, Seoul, Korea
- * E-mail: (KPK); (KBK)
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93
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Pitera JW. Expected distributions of root-mean-square positional deviations in proteins. J Phys Chem B 2014; 118:6526-30. [PMID: 24655018 DOI: 10.1021/jp412776d] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The atom positional root-mean-square deviation (RMSD) is a standard tool for comparing the similarity of two molecular structures. It is used to characterize the quality of biomolecular simulations, to cluster conformations, and as a reaction coordinate for conformational changes. This work presents an approximate analytic form for the expected distribution of RMSD values for a protein or polymer fluctuating about a stable native structure. The mean and maximum of the expected distribution are independent of chain length for long chains and linearly proportional to the average atom positional root-mean-square fluctuations (RMSF). To approximate the RMSD distribution for random-coil or unfolded ensembles, numerical distributions of RMSD were generated for ensembles of self-avoiding and non-self-avoiding random walks. In both cases, for all reference structures tested for chains more than three monomers long, the distributions have a maximum distant from the origin with a power-law dependence on chain length. The purely entropic nature of this result implies that care must be taken when interpreting stable high-RMSD regions of the free-energy landscape as "intermediates" or well-defined stable states.
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Affiliation(s)
- Jed W Pitera
- IBM Research - Almaden, 650 Harry Road, San Jose, California 95120, United States
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94
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Arabidopsis thaliana Tic110, involved in chloroplast protein translocation, contains at least fourteen highly divergent heat-like repeated motifs. Biologia (Bratisl) 2013. [DOI: 10.2478/s11756-013-0310-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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95
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Consequences of domain insertion on sequence-structure divergence in a superfold. Proc Natl Acad Sci U S A 2013; 110:E3381-7. [PMID: 23959887 DOI: 10.1073/pnas.1305519110] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Although the universe of protein structures is vast, these innumerable structures can be categorized into a finite number of folds. New functions commonly evolve by elaboration of existing scaffolds, for example, via domain insertions. Thus, understanding structural diversity of a protein fold evolving via domain insertions is a fundamental challenge. The haloalkanoic dehalogenase superfamily serves as an excellent model system wherein a variable cap domain accessorizes the ubiquitous Rossmann-fold core domain. Here, we determine the impact of the cap-domain insertion on the sequence and structure divergence of the core domain. Through quantitative analysis on a unique dataset of 154 core-domain-only and cap-domain-only structures, basic principles of their evolution have been uncovered. The relationship between sequence and structure divergence of the core domain is shown to be monotonic and independent of the corresponding type of domain insert, reflecting the robustness of the Rossmann fold to mutation. However, core domains with the same cap type share greater similarity at the sequence and structure levels, suggesting interplay between the cap and core domains. Notably, results reveal that the variance in structure maps to α-helices flanking the central β-sheet and not to the domain-domain interface. Collectively, these results hint at intramolecular coevolution where the fold diverges differentially in the context of an accessory domain, a feature that might also apply to other multidomain superfamilies.
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96
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Sequence and structure space model of protein divergence driven by point mutations. J Theor Biol 2013; 330:1-8. [DOI: 10.1016/j.jtbi.2013.03.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2012] [Revised: 03/07/2013] [Accepted: 03/18/2013] [Indexed: 12/11/2022]
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97
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Kolodny R, Kosloff M. From Protein Structure to Function via Computational Tools and Approaches. Isr J Chem 2013. [DOI: 10.1002/ijch.201200078] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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98
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Li Y, Hu F, Wang X, Cao H, Liu D, Yao D. A rational design for trypsin-resistant improvement of Armillariella tabescens β-mannanase MAN47 based on molecular structure evaluation. J Biotechnol 2013; 163:401-7. [DOI: 10.1016/j.jbiotec.2012.12.018] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2012] [Revised: 12/20/2012] [Accepted: 12/21/2012] [Indexed: 11/27/2022]
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99
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Shirvanyants D, Ding F, Tsao D, Ramachandran S, Dokholyan NV. Discrete molecular dynamics: an efficient and versatile simulation method for fine protein characterization. J Phys Chem B 2012; 116:8375-82. [PMID: 22280505 PMCID: PMC3406226 DOI: 10.1021/jp2114576] [Citation(s) in RCA: 166] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Until now it has been impractical to observe protein folding in silico for proteins larger than 50 residues. Limitations of both force field accuracy and computational efficiency make the folding problem very challenging. Here we employ discrete molecular dynamics (DMD) simulations with an all-atom force field to fold fast-folding proteins. We extend the DMD force field by introducing long-range electrostatic interactions to model salt-bridges and a sequence-dependent semiempirical potential accounting for natural tendencies of certain amino acid sequences to form specific secondary structures. We enhance the computational performance by parallelizing the DMD algorithm. Using a small number of commodity computers, we achieve sampling quality and folding accuracy comparable to the explicit-solvent simulations performed on high-end hardware. We demonstrate that DMD can be used to observe equilibrium folding of villin headpiece and WW domain, study two-state folding kinetics, and sample near-native states in ab initio folding of proteins of ∼100 residues.
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Affiliation(s)
- David Shirvanyants
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Feng Ding
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Douglas Tsao
- Department of Chemistry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Srinivas Ramachandran
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Nikolay V. Dokholyan
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
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100
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Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis P, Karaca E, Melquiond ASJ, Bonvin AMJJ. Clustering biomolecular complexes by residue contacts similarity. Proteins 2012; 80:1810-7. [PMID: 22489062 DOI: 10.1002/prot.24078] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2011] [Revised: 03/14/2012] [Accepted: 03/30/2012] [Indexed: 01/01/2023]
Abstract
Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions. Albeit widely used, these measures suffer from several theoretical and technical limitations (e.g., choice of regions for fitting) that impair their application in multicomponent systems (N > 2), large-scale studies (e.g., interactomes), and other time-critical scenarios. We present here a simple similarity measure for structural clustering based on atomic contacts--the fraction of common contacts--and compare it with the most used similarity measure of the protein docking community--interface backbone RMSD. We show that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein-protein and protein-DNA complexes. Furthermore, it allows easy clustering of similar conformations of multicomponent symmetrical assemblies in which chain permutations can occur. Simple contact-based metrics should be applicable to other structural biology clustering problems, in particular for time-critical or large-scale endeavors.
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Affiliation(s)
- João P G L M Rodrigues
- Bijvoet Center for Biomolecular Research, Faculty of Science, Utrecht University, 3584 CH Utrecht, The Netherlands
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