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arXiv 2019年

作者： Mei, Zhe Treado, John D. Grigas, Alex T. Levine, Zachary A. Regan, Lynne O'Hern, Corey S. Integrated Graduate Program in Physical & Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Department of Pathology Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Institute of Quantitative Biology Biochemistry and Biotechnology Center for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

There have been several studies suggesting that protein structures solved by NMR spectroscopy and x-ray crystallography show significant differences. To understand the origin of these differences, we assembled a database of high-quality protein structures solved by both methods. We also find significant differences between NMR and crystal structures|in the root-mean-square deviations of the Cα atomic positions, identities of core amino acids, backbone and sidechain dihedral angles, and packing fraction of core residues. In contrast to prior studies, we identify the physical basis for these differences by modelling protein cores as jammed packings of amino-acid-shaped particles. We find that we can tune the jammed packing fraction by varying the degree of thermalization used to generate the packings. For an athermal protocol, we find that the average jammed packing fraction is identical to that observed in the cores of protein structures solved by x-ray crystallography. In contrast, highly thermalized packing-generation protocols yield jammed packing fractions that are even higher than those observed in NMR structures. These results indicate that thermalized systems can pack more densely than athermal systems, which suggests a physical basis for the structural differences between protein structures solved by NMR and x-ray crystallography. Copyright © 2019, The Authors. All rights reserved.

关键词： X ray crystallography

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Using physical features of protein core packing to distinguish real proteins from decoys

arXiv

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arXiv 2020年

作者： Grigas, Alex T. Mei, Zhe Treado, John D. Levine, Zachary A. Regan, Lynne O'Hern, Corey S. Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Pathology Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Institute of Quantitative Biology Biochemistry and Biotechnology Centre for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

The ability to consistently distinguish real protein structures from computationally generated model decoys is not yet a solved problem. One route to distinguish real protein structures from decoys is to delineate the important physical features that specify a real protein. For example, it has long been appreciated that the hydrophobic cores of proteins contribute signifficantly to their stability. As a dataset of decoys to compare with real protein structures, we studied submissions to the bi-annual CASP competition (speciffically CASP11, 12, and 13), in which researchers attempt to predict the structure of a protein only knowing its amino acid sequence. Our analysis reveals that many of the submissions possess cores that do not recapitulate the features that define real proteins. In particular, the model structures appear more densely packed (because of energetically unfavorable atomic overlaps), contain too few residues in the core, and have improper distributions of hydrophobic residues throughout the structure. Based on these observations, we developed a deep learning method, which incorporates key physical features of protein cores, to predict how well a computational model recapitulates the real protein structure without knowledge of the structure of the target sequence. By identifying the important features of protein structure, our method is able to rank decoys from the CASP competitions equally well, if not better than, state-of-the-art methods that incorporate many additional features. Copyright © 2020, The Authors. All rights reserved.

关键词： Proteins

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Identifying topologically associating domains using differential kernels

arXiv

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arXiv 2023年

作者： Maisuradze, Luka King, Megan C. Surovtsev, Ivan V. Mochrie, Simon G.J. Shattuck, Mark D. O’Hern, Corey S. Department of Molecular Biophysics and Biochemistry Yale University New HavenCT United States Department of Cell Biology Yale School of Medicine New HavenCT United States Department of Physics Yale University New HavenCT United States Benjamin Levich Institute Physics Department The City College of New York New YorkNY United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT United States

Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional (3D) structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix Aij, where each element represents the average contact probability or number of contacts between chromatin loci i and j. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in Aij within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method to identify TADs, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that the new method consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. Thus, KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states. © 2023, CC BY.

关键词： Topology

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

arXiv

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arXiv 2023年

作者： Nawano, Aya Schroers, Jan Shattuck, Mark D. O’Hern, Corey S. Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Metallic glasses are frequently used as structural materials. Therefore, it is important to develop methods to predict their mechanical response as a function of the microstructure prior to loading. We develop a novel coarse-grained spring network model, which describes the mechanical response of metallic glasses using an equivalent series network of springs, which can break and re-form to mimic atomic rearrangements during deformation. To validate the spring network model, we perform numerical simulations of quasistatic, uniaxial tensile deformation of Lennard-Jones and embedded atom method (EAM) potentials for Cu50Zr50 metallic glasses in the absence of large-scale shear band formation. We consider samples prepared using a wide range of cooling rates and with different amounts of crystalline order. We show that both the Lennard-Jones and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters in the spring network model (ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ = 0 and at large strain, and strain at fracture where σ = 0), we can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses. For the computational studies of Cu50Zr50, we find that the yield strain distribution is shifted to larger strains for slowly cooled glasses compared to rapidly cooled glasses. In addition, the average number of new springs and their rate of formation decreases with decreasing cooling rate. These effects offset each other at large strains, causing the stress-strain curve to become independent of the sample preparation protocol in this regime. In future studies, we will extract the parameters that define the spring network model directly from atomic rearrangements that occur during uniaxial deformation. © 2023, CC BY-NC-ND.

关键词： Metallic glass

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Virtual Flavonoids Screening Identifies Potent Compounds Against Enterovirus A71 and Coxsackievirus A16

SSRN

引用

SSRN 2023年

作者： Sripattarphan, Amita Sanachai, Kamonpan Chavasiri, Warinthorn Wolschann, Peter Langer, Thierry Boonyasuppayakorn, Siwaporn Rungrotmongkol, Thanyada Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Department of Biochemistry Faculty of Science Khon Kaen University Khon Kaen40002 Thailand Center of Excellence in Natural Products Chemistry Department of Chemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Department of Pharmaceutical Chemistry Faculty of Life Sciences University of Vienna Althanstraße 14 ViennaA-1090 Austria Institute of Theoretical Chemistry University of Vienna Vienna1090 Austria Center of Excellence in Applied Medical Virology Department of Microbiology Faculty of Medicine Chulalongkorn University Bangkok10330 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok10330 Thailand

Worldwide outbreaks of hand, foot, and mouth disease (HFMD) are caused by enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16). Since no anti-HFMD drugs are currently available, it is interesting to study potential viral inhibitors. Rupintrivir is a rhinovirus 3C protease (3Cpro) inhibitor with apparent inhibitory activity against HFMD. This study constructs pharmacophore models of the EV-A71 and CV-A16 3Cpro complexed with rupintrivir using molecular dynamics (MD) simulations. Both models had similar pharmacophore features, including hydrogen bond donors and acceptors and hydrophobic interactions. These pharmacophore models were then used as a template to screen 39 flavonoid compounds as potential novel inhibitors. Diosmin, epigallocatechin gallate (EGCG), and RTH-011 showed high binding affinities for EV-A71 and CV-A16 3Cpro. They formed hydrogen bonds with important surrounding residues in both proteins, including H40, L127, T142, A144, T145, H161, I162, G163, and G164. In addition, their effective concentrations against rhabdomyosarcoma (RD) cell infection by EV-A71 and CV-A16 were determined. EGCG had the highest half maximal effective concentration (EC50) of 12.86 ± 1.30 µM for EV-A71 and 15.54 ± 1.50 µM for CV-A16, while diosmin had EC50 of 21.01±1.57 µM for EV-A71 and 30.68 ± 3.25 µM for CV-A16. Both compounds were non-toxic in RD cells, with 50% cytotoxic concentrations of >100 µM for EGCG and >500 µM for diosmin. In addition, MD simulation analysis showed that EGCG had a higher binding affinity than diosmin, supported by its significantly lower solvated binding free energies and greater numbers of contact atoms and key binding residues. Moreover, previous studies reported EGCG’s inhibitory effect on other viruses, such as severe acute respiratory syndrome coronavirus 2. Therefore, our findings suggest that EGCG can effectively inhibit the EV-A71 and CV-A16 3Cpro. © 2023, The Authors. All rights reserved.

关键词： Molecular dynamics

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Titania Nanosheets Generates Peroxynitrite for S-Nitrosylation and Enhanced p53 Function in Lung Cancer Cells

Research Square

引用

Research Square 2021年

作者： Soonnarong, Rapeepun Tungsukruthai, Sucharat Nutho, Bodee Rungrotmongkol, Thanyada Vinayanuwattikun, Chanida Maluangnont, Tosapol Chanvorachote, Pithi Interdisciplinary Program of Pharmacology Graduate School Chulalongkorn University Bangkok Thailand Cell-based Drug and Health Products Development Research Unit Chulalongkorn University Bangkok Thailand Departments of Pharmacology and Physiology Faculty of Pharmaceutical Sciences Bangkok Thailand Department of Pharmacology Faculty of Science Mahidol University Bangkok Thailand Biocatalyst and Environmental Biotechnology Reseach Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok Thailand Division of Medical Oncology Department of Medicine Chulalongkorn University Bangkok Thailand College of Materials Innovation and Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

Background: Metal oxide nanomaterials are increasingly being exploited in cancer therapy thanks to their unique properties, which can enhance the efficacy of current cancer therapies. However, the nanotoxicity and mechanism of Ti0.8O2 nanosheets for specific site-targeting strategies in NSCLC have not yet been investigated. Methods: The effects of Ti0.8O2 nanosheets on cytotoxicity in NSCLC cells and normal cells were examined. The apoptosis characteristics, including condensed and fragmented nuclei, as assessed by positive staining with annexin V. The cellular uptake of the nanosheets and the induction of stress fiber were assessed via transmission electron microscopy (TEM) and scanning electron microscopy (SEM) analyses, respectively. We also evaluated the expression of protein in death mechanism to identify the molecular mechanisms behind the toxicity of these cells. We investigated the relationship between S-nitrosylation and the increase in p53 stability by molecular dynamics. Results: Ti0.8O2 nanosheets caused cytotoxicity in several lung cancer cells, but not in normal cells. The nanosheets could enter lung cancer cells and exert an apoptosis induction. Results for protein analysis further indicated the activation of p53, increased Bax, decreased Bcl-2 and Mcl-1, and activation of caspase-3. The nanosheets also exhibited a substantial apoptosis effect in drug-resistant metastatic primary lung cancer cells, and it was found that the potency of the nanosheets was dramatically higher than that of cisplatin and etoposide. In terms of their mechanism of action, we found that the mode of apoptosis induction was through the generation of cellular ONOO− mediated the S-nitrosylation of p53 at C182. Molecular dynamics analysis further showed that the S-nitrosylation of one C182 stabilized the p53 dimer. Consequently, this nitrosylation of the protein led to an upregulation of p53 through its stabilization. Conclusions: Taking all the evidence together, we provided info

关键词： Molecular dynamics

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Void distributions reveal structural link between jammed packings and protein cores

arXiv

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arXiv 2018年

作者： Treado, John D. Mei, Zhe Regan, Lynne O'Hern, Corey S. Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Integrated Graduate Program in Physical & Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Molecular Biophysics & Biochemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Dense packing of hydrophobic residues in the cores of globular proteins determines their stability. Recently, we have shown that protein cores possess packing fraction φ ≈ 0.56, which is the same as dense, random packing of amino acid-shaped particles. In this article, we compare the structural properties of protein cores and jammed packings of amino acid-shaped particles in much greater depth by measuring their local and connected void regions. We find that the distributions of surface Voronoi cell volumes and local porosities obey similar statistics in both systems. We also measure the probability that accessible, connected void regions percolate as a function of the size of a spherical probe particle and show that both systems possess the same critical probe size. By measuring the critical exponent τ that characterizes the size distribution of connected void clusters at the onset of percolation, we show that void percolation in packings of amino acid-shaped particles and protein cores belong to the same universality class, which is different from that for void percolation in jammed sphere packings. We propose that the connected void regions of proteins are a defining feature of proteins and can be used to differentiate experimentally observed proteins from decoy structures that are generated using computational protein design software. This work emphasizes that jammed packings of amino acid-shaped particles can serve as structural and mechanical analogs of protein cores, and could therefore be useful in modeling the response of protein cores to cavity-expanding and -reducing mutations. Copyright © 2018, The Authors. All rights reserved.

关键词： Amino acids

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Evaluation of drug repositioning by molecular docking of pharmaceutical resources available in the Brazilian healthcare system against SARS-CoV-2

引用

Informatics in Medicine Unlocked 2021年 23卷 100539页

作者： Grahl, Matheus V.C. Alcará, Allan M. Perin, Ana Paula A. Moro, Carlo F. Pinto, Éderson S.M. Feltes, Bruno C. Ghilardi, Isadora M. Rodrigues, Felipe V.F. Dorn, Marcio da Costa, Jaderson C. Norberto de Souza, Osmar Ligabue-Braun, Rodrigo Brain Institute of Rio Grande do Sul (BraIns) Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Graduate Program in Medicine and Health Sciences Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Graduate Program in Medicine Pediatrics and Child Health Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Graduate Program in Cellular and Molecular Biology Center of Biotechnology Federal University of Rio Grande do Sul RS Brazil Laboratory of Structural Bioinformatics and Computational Biology Institute of Informatics Federal University of Rio Grande do Sul RS Brazil Laboratory of Immunobiology and Immunogenetics Institute of Biosciences Federal University of Rio Grande do Sul RS Brazil School of Technology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Department of Pharmacosciences and Graduate Program in Biosciences (PPGBio) Federal University of Health Sciences of Porto Alegre Porto Alegre Brazil

In 2020 SARS-CoV-2 reached pandemic status, reaching Brazil in mid-February. As of now, no specific drugs for treating the disease are available. In this work, the possibility of interaction between SARS-CoV-2 viral proteins (open and closed spike protein, isolate spike protein RBD, NSP 10, NSP 16, main protease, and RdRp polymerase) and multiple molecules is addressed through the repositioning of drugs available for the treatment of other diseases that are approved by the FDA and covered by SUS, the Brazilian Public Health System. Three different docking software were used, followed by a unification of the results by independent evaluation. Afterwards, the chemical interactions of the compounds with the targets were inspected via molecular dynamics and analyzed. The results point to a potential effectiveness of Penciclovir, Ribavirin, and Zanamivir, from a set of 48 potential candidates. They may also be multi-target drugs, showing high affinity with more than one viral protein. Further in vitro and in vivo validation is required to assess the suitability of repositioning the proposed drugs for COVID-19. © 2021 The Authors

关键词： COVID19 Drug repositioning Molecular docking SARS-CoV-2 SUS

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Communicationmachine Learning-Based QSAR and LB-PaCS-MD Guided Design of SARs-CoV-2 Main Protease Inhibitors

SSRN

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SSRN 2024年

作者： Toopradab, Borwornlak Xie, Wanting Duan, Lian Hengphasatporn, Kowit Harada, Ryuhei Sinsulpsiri, Silpsiri Shigeta, Yasuteru Shi, Liyi Maitarad, Phornphimon Rungrotmongkol, Thanyada Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok10330 Thailand Center of Excellence in Biocatalyst and Sustainable Biotechnology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Research Center of Nano Science and Technology Department of Chemistry College of Science Shanghai University Shanghai200444 China University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Graduate School of Pure and Applied Sciences University of Tsukuba 1-1-1 Tennodai Ibaraki305–8571 Japan Emerging Industries Institute Shanghai University Zhejiang Jiaxing314006 China

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an R2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design;with the potential to guide experimental synthesis and enzyme assay testing. © 2024, The Authors. All rights reserved.

关键词： Coronavirus

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Tessellated granular metamaterials with tunable elastic moduli

arXiv

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arXiv 2023年

作者： Pashine, Nidhi Wang, Dong Zhang, Jerry Patiballa, Sree Kalyan Witthaus, Sven Shattuck, Mark D. O’Hern, Corey S. Kramer-Bottiglio, Rebecca Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Benjamin Levich Institute Physics Department The City College of the City University of New York New YorkNY10031 United States

Most granular packings possess shear moduli (G) that increase with the applied external pressure, and bulk moduli (B) that increase or remain constant with pressure. This paper presents "tessellated" granular metamaterials for which both G and the ratio G/B decrease with increasing pressure. The granular metamaterials are made from flexible tessellations forming a ring of closed cells, each containing a small number of solid particles. For under-constrained tessellations, the dominant contributions to G and B are the particle-particle and particle-cell interactions. With specific particle configurations in the cells, we limit the number of possible particle rearrangements to achieve decreasing G as we increase the pressure difference between the inside and outside of the tessellation, leading to G/B 1 at large pressures. We further study tessellated granular metamaterials with cells containing a single particle and many particles to determine the variables that control the mechanical response of particle-filled tessellations as a function of pressure. © 2023, CC BY.

关键词： Metamaterials

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