1
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Guclu TF, Atilgan AR, Atilgan C. Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis. J Phys Chem B 2024; 128:7987-7996. [PMID: 39115184 DOI: 10.1021/acs.jpcb.4c04916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
Abstract
Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.
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Affiliation(s)
- Tandac F Guclu
- Faculty of Natural Sciences and Engineering, Sabanci University, Tuzla, Istanbul 34956, Turkey
| | - Ali Rana Atilgan
- Faculty of Natural Sciences and Engineering, Sabanci University, Tuzla, Istanbul 34956, Turkey
| | - Canan Atilgan
- Faculty of Natural Sciences and Engineering, Sabanci University, Tuzla, Istanbul 34956, Turkey
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2
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Zhang X, Xu J, Ming D. Analysis of Correlation Effects of Double Mutations in Enzymes: A Revised Residual-Contact Network Clique Model. Int J Mol Sci 2024; 25:9114. [PMID: 39201800 PMCID: PMC11354518 DOI: 10.3390/ijms25169114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 08/15/2024] [Accepted: 08/20/2024] [Indexed: 09/03/2024] Open
Abstract
The relationship between amino acid mutations and enzyme bioactivity is a significant challenge in modern bio-industrial applications. Despite many successful designs relying on complex correlations among mutations at different enzyme sites, the underlying mechanisms of these correlations still need to be explored. In this study, we introduced a revised version of the residual-contact network clique model to investigate the additive effect of double mutations based on the mutation occurrence topology, secondary structures, and physicochemical properties. The model was applied to a set of 182 double mutations reported in three extensively studied enzymes, and it successfully identified over 90% of additive double mutations and a majority of non-additive double mutations. The calculations revealed that the mutation additivity depends intensely on the studied mutation sites' topology and physicochemical properties. For example, double mutations on irregular secondary structure regions tend to be non-additive. Our method provides valuable tools for facilitating enzyme design and optimization. The code and relevant data are available at Github.
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Affiliation(s)
| | | | - Dengming Ming
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, 30 South Puzhu Road, Jiangbei New District, Nanjing 211816, China; (X.Z.); (J.X.)
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3
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Hayes RL, Cervantes LF, Abad Santos JC, Samadi A, Vilseck JZ, Brooks CL. How to Sample Dozens of Substitutions per Site with λ Dynamics. J Chem Theory Comput 2024; 20:6098-6110. [PMID: 38976796 PMCID: PMC11270746 DOI: 10.1021/acs.jctc.4c00514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/18/2024] [Accepted: 06/18/2024] [Indexed: 07/10/2024]
Abstract
Alchemical free energy methods are useful in computer-aided drug design and computational protein design because they provide rigorous statistical mechanics-based estimates of free energy differences from molecular dynamics simulations. λ dynamics is a free energy method with the ability to characterize combinatorial chemical spaces spanning thousands of related systems within a single simulation, which gives it a distinct advantage over other alchemical free energy methods that are mostly limited to pairwise comparisons. Recently developed methods have improved the scalability of λ dynamics to perturbations at many sites; however, the size of chemical space that can be explored at each individual site has previously been limited to fewer than ten substituents. As the number of substituents increases, the volume of alchemical space corresponding to nonphysical alchemical intermediates grows exponentially relative to the size corresponding to the physical states of interest. Beyond nine substituents, λ dynamics simulations become lost in an alchemical morass of intermediate states. In this work, we introduce new biasing potentials that circumvent excessive sampling of intermediate states by favoring sampling of physical end points relative to alchemical intermediates. Additionally, we present a more scalable adaptive landscape flattening algorithm for these larger alchemical spaces. Finally, we show that this potential enables more efficient sampling in both protein and drug design test systems with up to 24 substituents per site, enabling, for the first time, simultaneous simulation of all 20 amino acids.
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Affiliation(s)
- Ryan L. Hayes
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
- Department
of Pharmaceutical Sciences, University of
California Irvine, Irvine, California 92697, United States
| | - Luis F. Cervantes
- Department
of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Justin Cruz Abad Santos
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
| | - Amirmasoud Samadi
- Department
of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, California 92697, United States
| | - Jonah Z. Vilseck
- Department
of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, Indiana 46202, United States
- Center
for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Charles L. Brooks
- Department
of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
- Biophysics
Program, University of Michigan, Ann Arbor, Michigan 48109, United States
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4
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Hoya M, Matsunaga R, Nagatoishi S, Ide T, Kuroda D, Tsumoto K. Impact of single-residue mutations on protein thermal stability: The case of threonine 83 of BC2L-CN lectin. Int J Biol Macromol 2024; 272:132682. [PMID: 38815947 DOI: 10.1016/j.ijbiomac.2024.132682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 05/21/2024] [Accepted: 05/24/2024] [Indexed: 06/01/2024]
Abstract
The thermal stability of trimeric lectin BC2L-CN was investigated and found to be considerably altered when mutating residue 83, originally a threonine, located at the fucose-binding loop. Mutants were analyzed using differential scanning calorimetry and isothermal microcalorimetry. Although most mutations decreased the affinity of the protein for oligosaccharide H type 1, six mutations increased the melting temperature (Tm) by >5 °C; one mutation, T83P, increased the Tm value by 18.2 °C(T83P, Tm = 96.3 °C). In molecular dynamic simulations, the investigated thermostable mutants, T83P, T83A, and T83S, had decreased fluctuations in the loop containing residue 83. In the T83S mutation, the side-chain hydroxyl group of serine formed a hydrogen bond with a nearby residue, suggesting that the restricted movement of the side-chain resulted in fewer fluctuations and enhanced thermal stability. Residue 83 is located at the interface and near the upstream end of the equivalent loop in a different protomer; therefore, fluctuations by this residue likely propagate throughout the loop. Our study of the dramatic change in thermal stability by a single amino acid mutation provides useful insights into the rational design of protein structures, especially the structures of oligomeric proteins.
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Affiliation(s)
- Megumi Hoya
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Sagami Chemical Research Institute, 2743-1 Hayakawa, Ayase, Kanagawa 252-1193, Japan
| | - Ryo Matsunaga
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Satoru Nagatoishi
- Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Project Division of Advanced Biopharmaceutical Science, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
| | - Teruhiko Ide
- Tosoh Corporation, Hayakawa, 2743-1 Ayase, Kanagawa 252-1123, Japan
| | - Daisuke Kuroda
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Research Center for Drug and Vaccine Development, National Institute of Infectious Diseases, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan
| | - Kouhei Tsumoto
- Department of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; Project Division of Advanced Biopharmaceutical Science, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
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5
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Schreiber S, Gercke D, Lenz F, Jose J. Application of an alchemical free energy method for the prediction of thermostable DuraPETase variants. Appl Microbiol Biotechnol 2024; 108:305. [PMID: 38643427 PMCID: PMC11033240 DOI: 10.1007/s00253-024-13144-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/25/2024] [Accepted: 04/09/2024] [Indexed: 04/22/2024]
Abstract
Non-equilibrium (NEQ) alchemical free energy calculations are an emerging tool for accurately predicting changes in protein folding free energy resulting from amino acid mutations. In this study, this method in combination with the Rosetta ddg monomer tool was applied to predict more thermostable variants of the polyethylene terephthalate (PET) degrading enzyme DuraPETase. The Rosetta ddg monomer tool efficiently enriched promising mutations prior to more accurate prediction by NEQ alchemical free energy calculations. The relative change in folding free energy of 96 single amino acid mutations was calculated by NEQ alchemical free energy calculation. Experimental validation of ten of the highest scoring variants identified two mutations (DuraPETaseS61M and DuraPETaseS223Y) that increased the melting temperature (Tm) of the enzyme by up to 1 °C. The calculated relative change in folding free energy showed an excellent correlation with experimentally determined Tm resulting in a Pearson's correlation coefficient of r = - 0.84. Limitations in the prediction of strongly stabilizing mutations were, however, encountered and are discussed. Despite these challenges, this study demonstrates the practical applicability of NEQ alchemical free energy calculations in prospective enzyme engineering projects. KEY POINTS: • Rosetta ddg monomer enriches stabilizing mutations in a library of DuraPETase variants • NEQ free energy calculations accurately predict changes in Tm of DuraPETase • The DuraPETase variants S223Y, S42M, and S61M have increased Tm.
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Affiliation(s)
- Sebastian Schreiber
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - David Gercke
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - Florian Lenz
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - Joachim Jose
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany.
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6
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Zhang L, Zhou R, Liu D, Zhu M, Zhang G, Zhang L, Zhou SF, Jiang W. Multi-strategy orthogonal enhancement and analysis of aldo-keto reductase thermal stability. Int J Biol Macromol 2024; 264:130691. [PMID: 38458293 DOI: 10.1016/j.ijbiomac.2024.130691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 02/26/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
Given their outstanding efficiency and selectivity, enzymes are integral in various domains such as drug synthesis, the food industry, and environmental management. However, the inherent instability of natural enzymes limits their widespread industrial application. In this study, we underscore the efficacy of enhancing protein thermal stability through comprehensive protein design strategies, encompassing elements such as the free energy of protein folding, internal forces within proteins, and the overall structural design. We also demonstrate the efficiency and precision of combinatorial screening in the thermal stability design of aldo-keto reductase (AKR7-2-1). In our research, three single-point mutations and five combinatorial mutations were strategically introduced into AKR7-2-1, using multiple computational techniques. Notably, the E12I/S235I mutant showed a significant increase of 25.4 °C in its melting temperature (Tm). Furthermore, the optimal mutant, E12V/S235I, maintained 80 % of its activity while realizing a 16.8 °C elevation in Tm. Remarkably, its half-life at 50 °C was increased to twenty times that of the wild type. Structural analysis indicates that this enhanced thermal stability primarily arises from reduced oscillation in the loop region and increased internal hydrogen bonding. The promising results achieved with AKR7-2-1 demonstrate that our strategy could serve as a valuable reference for enhancing the thermal stability of other industrial enzymes.
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Affiliation(s)
- Lingzhi Zhang
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China
| | - Rui Zhou
- Shanghai Marine Diesel Engine Research Institute, Shanghai 201108, PR China
| | - Dekai Liu
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China
| | - Meinan Zhu
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China
| | - Guangya Zhang
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China
| | - Lijuan Zhang
- State Key Laboratory of Microbial Technology, Shandong University, No. 72 Binhai Road, Qingdao 266237, PR China
| | - Shu-Feng Zhou
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China.
| | - Wei Jiang
- College of Chemical Engineering, Huaqiao University, Xiamen 361021, Fujian Province, PR China.
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7
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Yamagishi M, Kuze Y, Kobayashi S, Nakashima M, Morishima S, Kawamata T, Makiyama J, Suzuki K, Seki M, Abe K, Imamura K, Watanabe E, Tsuchiya K, Yasumatsu I, Takayama G, Hizukuri Y, Ito K, Taira Y, Nannya Y, Tojo A, Watanabe T, Tsutsumi S, Suzuki Y, Uchimaru K. Mechanisms of action and resistance in histone methylation-targeted therapy. Nature 2024; 627:221-228. [PMID: 38383791 PMCID: PMC10917674 DOI: 10.1038/s41586-024-07103-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 01/23/2024] [Indexed: 02/23/2024]
Abstract
Epigenomes enable the rectification of disordered cancer gene expression, thereby providing new targets for pharmacological interventions. The clinical utility of targeting histone H3 lysine trimethylation (H3K27me3) as an epigenetic hallmark has been demonstrated1-7. However, in actual therapeutic settings, the mechanism by which H3K27me3-targeting therapies exert their effects and the response of tumour cells remain unclear. Here we show the potency and mechanisms of action and resistance of the EZH1-EZH2 dual inhibitor valemetostat in clinical trials of patients with adult T cell leukaemia/lymphoma. Administration of valemetostat reduced tumour size and demonstrated durable clinical response in aggressive lymphomas with multiple genetic mutations. Integrative single-cell analyses showed that valemetostat abolishes the highly condensed chromatin structure formed by the plastic H3K27me3 and neutralizes multiple gene loci, including tumour suppressor genes. Nevertheless, subsequent long-term treatment encounters the emergence of resistant clones with reconstructed aggregate chromatin that closely resemble the pre-dose state. Acquired mutations at the PRC2-compound interface result in the propagation of clones with increased H3K27me3 expression. In patients free of PRC2 mutations, TET2 mutation or elevated DNMT3A expression causes similar chromatin recondensation through de novo DNA methylation in the H3K27me3-associated regions. We identified subpopulations with distinct metabolic and gene translation characteristics implicated in primary susceptibility until the acquisition of the heritable (epi)mutations. Targeting epigenetic drivers and chromatin homeostasis may provide opportunities for further sustained epigenetic cancer therapies.
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Affiliation(s)
- Makoto Yamagishi
- Laboratory of Viral Oncology and Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
- Laboratory of Tumor Cell Biology, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
| | - Yuta Kuze
- Laboratory of Systems Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Seiichiro Kobayashi
- Division of Hematopoietic Disease Control, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Department of Hematology, Kanto Rosai Hospital, Kanagawa, Japan
| | - Makoto Nakashima
- Laboratory of Tumor Cell Biology, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Satoko Morishima
- Division of Endocrinology, Diabetes and Metabolism, Hematology and Rheumatology, Second Department of Internal Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Toyotaka Kawamata
- Department of Hematology/Oncology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Junya Makiyama
- Department of Hematology/Oncology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Department of Hematology, Sasebo City General Hospital, Nagasaki, Japan
| | - Kako Suzuki
- Laboratory of Viral Oncology and Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory of Tumor Cell Biology, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masahide Seki
- Laboratory of Systems Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Kazumi Abe
- Laboratory of Systems Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Kiyomi Imamura
- Laboratory of Systems Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Eri Watanabe
- IMSUT Clinical Flow Cytometry Laboratory, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Kazumi Tsuchiya
- IMSUT Clinical Flow Cytometry Laboratory, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Isao Yasumatsu
- Organic and Biomolecular Chemistry Department, Daiichi Sankyo RD Novare, Tokyo, Japan
| | | | | | - Kazumi Ito
- Translational Science I, Daiichi Sankyo, Tokyo, Japan
| | - Yukihiro Taira
- Laboratory of Viral Oncology and Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yasuhito Nannya
- Division of Hematopoietic Disease Control, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Department of Hematology/Oncology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Arinobu Tojo
- Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshiki Watanabe
- Department of Practical Management of Medical Information, Graduate School of Medicine, St Marianna University, Kanagawa, Japan
| | | | - Yutaka Suzuki
- Laboratory of Systems Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
| | - Kaoru Uchimaru
- Laboratory of Tumor Cell Biology, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
- Department of Hematology/Oncology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
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8
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Thakur A, Gizzio J, Levy RM. Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability. J Phys Chem B 2024; 128:1656-1667. [PMID: 38350894 PMCID: PMC10939730 DOI: 10.1021/acs.jpcb.3c08097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.
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Affiliation(s)
- Abhishek Thakur
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Joan Gizzio
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
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9
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Hayes RL, Nixon CF, Marqusee S, Brooks CL. Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design. Proc Natl Acad Sci U S A 2024; 121:e2312029121. [PMID: 38194446 PMCID: PMC10801872 DOI: 10.1073/pnas.2312029121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/22/2023] [Indexed: 01/11/2024] Open
Abstract
Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on E. coli RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions. The stabilities of 32,768 chimeras between these two sequences were computed using the MSλD framework. The most stable and least stable chimeras were predicted and tested along with several other sequences, revealing a designed chimera with approximately the same stability increase as AncCcons, but requiring only half the mutations. Comparing the computed stabilities with experiment for 12 sequences reveals a Pearson correlation of 0.86 and root mean squared error of 1.18 kcal/mol, an unprecedented level of accuracy well beyond less rigorous computational design methods. We then quantified selection pressure using a simple evolutionary model in which sequences are selected according to the Boltzmann factor of their stability. Selection temperatures from 110 to 168 K are estimated in three ways by comparing experimental and computational results to evolutionary models. These estimates indicate selection pressure is high, which has implications for evolutionary dynamics and for the accuracy required for design, and suggests accurate high-throughput computational methods like MSλD may enable more effective protein design.
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Affiliation(s)
- Ryan L. Hayes
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA92697
- Department of Chemistry, University of Michigan, Ann Arbor, MI48109
| | - Charlotte F. Nixon
- Department of Molecular and Cell Biology, University of California, Berkeley, CA94720
| | - Susan Marqusee
- Department of Molecular and Cell Biology, University of California, Berkeley, CA94720
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA94720
- Department of Chemistry, University of California, Berkeley, CA94720
| | - Charles L. Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, MI48109
- Biophysics Program, University of Michigan, Ann Arbor, MI48109
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10
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Ghaedizadeh S, Zeinali M, Dabirmanesh B, Rasekh B, Khajeh K, Banaei-Moghaddam AM. Rational design engineering of a more thermostable Sulfurihydrogenibium yellowstonense carbonic anhydrase for potential application in carbon dioxide capture technologies. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2024; 1872:140962. [PMID: 37716447 DOI: 10.1016/j.bbapap.2023.140962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/18/2023] [Accepted: 09/06/2023] [Indexed: 09/18/2023]
Abstract
Implementing hyperthermostable carbonic anhydrases into CO2 capture and storage technologies in order to increase the rate of CO2 absorption from the industrial flue gases is of great importance from technical and economical points of view. The present study employed a combination of in silico tools to further improve thermostability of a known thermostable carbonic anhydrase from Sulfurihydrogenibium yellowstonense. Experimental results showed that our rationally engineered K100G mutant not only retained the overall structure and catalytic efficiency but also showed a 3 °C increase in the melting temperature and a two-fold improvement in the enzyme half-life at 85 °C. Based on the molecular dynamics simulation results, rearrangement of salt bridges and hydrogen interactions network causes a reduction in local flexibility of the K100G variant. In conclusion, our study demonstrated that thermostability can be improved through imposing local structural rigidity by engineering a single-point mutation on the surface of the enzyme.
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Affiliation(s)
- Shima Ghaedizadeh
- Laboratory of Genomics and Epigenomics (LGE), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Majid Zeinali
- Microbiology and Biotechnology Research Group, Research Institute of Petroleum Industry (RIPI), Tehran, Iran.
| | - Bahareh Dabirmanesh
- Department of Biochemistry, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Behnam Rasekh
- Microbiology and Biotechnology Research Group, Research Institute of Petroleum Industry (RIPI), Tehran, Iran
| | - Khosrow Khajeh
- Department of Biochemistry, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Ali Mohammad Banaei-Moghaddam
- Laboratory of Genomics and Epigenomics (LGE), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
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11
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Annan A, Raiss N, Lemrabet S, Elomari N, Elmir EH, Filali-Maltouf A, Medraoui L, Oumzil H. Proposal of pharmacophore model for HIV reverse transcriptase inhibitors: Combined mutational effect analysis, molecular dynamics, molecular docking and pharmacophore modeling study. Int J Immunopathol Pharmacol 2024; 38:3946320241231465. [PMID: 38296818 PMCID: PMC10832406 DOI: 10.1177/03946320241231465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/13/2024] [Indexed: 02/02/2024] Open
Abstract
OBJECTIVES Antiretroviral therapy (ART) efficacy is jeopardized by the emergence of drug resistance mutations in HIV, compromising treatment effectiveness. This study aims to propose novel analogs of Effavirenz (EFV) as potential direct inhibitors of HIV reverse transcriptase, employing computer-aided drug design methodologies. METHODS Three key approaches were applied: a mutational profile study, molecular dynamics simulations, and pharmacophore development. The impact of mutations on the stability, flexibility, function, and affinity of target proteins, especially those associated with NRTI, was assessed. Molecular dynamics analysis identified G190E as a mutation significantly altering protein properties, potentially leading to therapeutic failure. Comparative analysis revealed that among six first-line antiretroviral drugs, EFV exhibited notably low affinity with viral reverse transcriptase, further reduced by the G190E mutation. Subsequently, a search for EFV-similar inhibitors yielded 12 promising molecules based on their affinity, forming the basis for generating a pharmacophore model. RESULTS Mutational analysis pinpointed G190E as a crucial mutation impacting protein properties, potentially undermining therapeutic efficacy. EFV demonstrated diminished affinity with viral reverse transcriptase, exacerbated by the G190E mutation. The search for EFV analogs identified 12 high-affinity molecules, culminating in a pharmacophore model elucidating key structural features crucial for potent inhibition. CONCLUSION This study underscores the significance of EFV analogs as potential inhibitors of HIV reverse transcriptase. The findings highlight the impact of mutations on drug efficacy, particularly the detrimental effect of G190E. The generated pharmacophore model serves as a pivotal reference for future drug development efforts targeting HIV, providing essential structural insights for the design of potent inhibitors based on EFV analogs identified in vitro.
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Affiliation(s)
- Azzeddine Annan
- Research Center of Plant and Microbial Biotechnologies, Biodiversity and Environment, Faculty of Sciences, Mohammed V University, Rabat, Morocco
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
| | - Noureddine Raiss
- Research Center of Plant and Microbial Biotechnologies, Biodiversity and Environment, Faculty of Sciences, Mohammed V University, Rabat, Morocco
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
| | - Sanae Lemrabet
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
| | - Nezha Elomari
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
| | - El Harti Elmir
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
| | - Abdelkarim Filali-Maltouf
- Research Center of Plant and Microbial Biotechnologies, Biodiversity and Environment, Faculty of Sciences, Mohammed V University, Rabat, Morocco
| | - Leila Medraoui
- Research Center of Plant and Microbial Biotechnologies, Biodiversity and Environment, Faculty of Sciences, Mohammed V University, Rabat, Morocco
| | - Hicham Oumzil
- Virology Department, National Reference Laboratory for HIV, Institute National of Hygiene, Rabat, Morocco
- Pedagogy and Research Unit of Microbiology, and Genomic Center of Human Pathologies, School of Medicine and Pharmacy, Mohamed V University, Rabat, Morocco
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12
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Papadourakis M, Sinenka H, Matricon P, Hénin J, Brannigan G, Pérez-Benito L, Pande V, van Vlijmen H, de Graaf C, Deflorian F, Tresadern G, Cecchini M, Cournia Z. Alchemical Free Energy Calculations on Membrane-Associated Proteins. J Chem Theory Comput 2023; 19:7437-7458. [PMID: 37902715 PMCID: PMC11017255 DOI: 10.1021/acs.jctc.3c00365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Indexed: 10/31/2023]
Abstract
Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.
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Affiliation(s)
- Michail Papadourakis
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Hryhory Sinenka
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Pierre Matricon
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Jérôme Hénin
- Laboratoire
de Biochimie Théorique UPR 9080, CNRS and Université Paris Cité, 75005 Paris, France
| | - Grace Brannigan
- Center
for Computational and Integrative Biology, Rutgers University−Camden, Camden, New Jersey 08103, United States of America
- Department
of Physics, Rutgers University−Camden, Camden, New Jersey 08102, United States
of America
| | - Laura Pérez-Benito
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Vineet Pande
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Herman van Vlijmen
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Chris de Graaf
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Francesca Deflorian
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Gary Tresadern
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Marco Cecchini
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
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13
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Gracia Carmona O, Oostenbrink C. Flexible Gaussian Accelerated Molecular Dynamics to Enhance Biological Sampling. J Chem Theory Comput 2023; 19:6521-6531. [PMID: 37649349 PMCID: PMC10536968 DOI: 10.1021/acs.jctc.3c00619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Indexed: 09/01/2023]
Abstract
Molecular dynamics simulations often struggle to obtain sufficient sampling to study complex molecular events due to high energy barriers separating the minima of interest. Multiple enhanced sampling techniques have been developed and improved over the years to tackle this issue. Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that works by adding a biasing potential, lifting the energy landscape up, and decreasing the height of its barriers. GaMD allows one to increase the sampling of events of interest without the need of a priori knowledge of the system or the relevant coordinates. All required acceleration parameters can be obtained from a previous search run. Upon its development, several improvements for the methodology have been proposed, among them selective GaMD in which the boosting potential is selectively applied to the region of interest. There are currently four selective GaMD methods that have shown promising results. However, all of these methods are constrained on the number, location, and scenarios in which this selective boosting potential can be applied to ligands, peptides, or protein-protein interactions. In this work, we showcase a GROMOS implementation of the GaMD methodology with a fully flexible selective GaMD approach that allows the user to define, in a straightforward way, multiple boosting potentials for as many regions as desired. We show and analyze the advantages of this flexible selective approach on two previously used test systems, the alanine dipeptide and the chignolin peptide, and extend these examples to study its applicability and potential to study conformational changes of glycans and glycosylated proteins.
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Affiliation(s)
- Oriol Gracia Carmona
- Institute
for Molecular Modeling and Simulation, Department of Material Sciences
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
| | - Chris Oostenbrink
- Institute
for Molecular Modeling and Simulation, Department of Material Sciences
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
- Christian
Doppler Laboratory for Molecular Informatics in the Biosciences, University of Natural Resources and Life Sciences, Vienna. Muthgasse 18, 1190 Vienna, Austria
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14
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Bauer J, Rajagopal N, Gupta P, Gupta P, Nixon AE, Kumar S. How can we discover developable antibody-based biotherapeutics? Front Mol Biosci 2023; 10:1221626. [PMID: 37609373 PMCID: PMC10441133 DOI: 10.3389/fmolb.2023.1221626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023] Open
Abstract
Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.
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Affiliation(s)
- Joschka Bauer
- Early Stage Pharmaceutical Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
| | - Nandhini Rajagopal
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Priyanka Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Pankaj Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Andrew E. Nixon
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Sandeep Kumar
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
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15
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Xue Z, Quan S. Understanding the Stabilization Mechanism of a Thermostable Mutant of Hygromycin B Phosphotransferase by Protein Sector-Guided Dynamic Analysis. ACS OMEGA 2023; 8:25739-25748. [PMID: 37521677 PMCID: PMC10372938 DOI: 10.1021/acsomega.3c00373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 06/12/2023] [Indexed: 08/01/2023]
Abstract
Point mutations can exert beneficial effects on proteins, including stabilization. The stabilizing effects of mutations are typically attributed to changes in free energy and residue interactions. However, these explanations lack detail and physical insights, which hinder the mechanistic study of protein stabilization and prevent accurate computational prediction of stabilizing mutations. Here, we investigate the physical mechanism underlying the enhanced thermostability of a Hygromycin B phosphotransferase mutant, Hph5. We find that the unpredictable mutation A118V induces rotation of F199, allowing it to establish an aromatic-aromatic interaction with W235. In contrast, the predictable mutation T246A acts through static hydrophobic interactions within the protein core. These discoveries were accelerated by a residue-coevolution-based theory, which links mutational effects to stability-associated local structures, providing valuable guidance for mechanistic exploration. The established workflow will benefit the development of accurate stability prediction programs and can be used to mine a protein stability database for undiscovered physical mechanisms.
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Affiliation(s)
- Zixiao Xue
- State
Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation
Center for Biomanufacturing (SCICB), East
China University of Science and Technology, Shanghai 200237, China
| | - Shu Quan
- State
Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation
Center for Biomanufacturing (SCICB), East
China University of Science and Technology, Shanghai 200237, China
- Shanghai
Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai 200237, China
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16
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Seong MS, Jang JA, Jeong YR, Kim YB, Kyaw YY, Kong HJ, Lee JH, Cheong J. Fibroblast Growth Factor 11 Inhibits Hepatitis B Virus Gene Expression Through FXRα Suppression. J Microbiol 2023; 61:693-702. [PMID: 37646922 PMCID: PMC10477102 DOI: 10.1007/s12275-023-00065-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 06/29/2023] [Accepted: 07/06/2023] [Indexed: 09/01/2023]
Abstract
Fibroblast growth factor 11 (FGF11) is a member of the intracellular FGF family, which shows different signal transmission compared with other FGF superfamily members. The molecular function of FGF11 is not clearly understood. In this study, we identified the inhibitory effect of FGF11 on hepatitis B virus (HBV) gene expression through transcriptional suppression. FGF11 decreased the mRNA and protein expression of HBV genes in liver cells. While the nuclear receptor FXRα1 increased HBV promoter transactivation, FGF11 decreased the FXRα-mediated gene induction of the HBV promoter by the FXRα agonist. Reduced endogenous levels of FXRα by siRNA and the dominant negative mutant protein (aa 1-187 without ligand binding domain) of FXRα expression indicated that HBV gene suppression by FGF11 is dependent on FXRα inhibition. In addition, FGF11 interacts with FXRα protein and reduces FXRα protein stability. These results indicate that FGF11 inhibits HBV replicative expression through the liver cell-specific transcription factor, FXRα, and suppresses HBV promoter activity. Our findings may contribute to the establishment of better regimens for the treatment of chronic HBV infections by including FGF11 to alter the bile acid mediated FXR pathway.
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Affiliation(s)
- Mi So Seong
- Department of Molecular Biology, Pusan National University, Busan, 46241, Republic of Korea
| | - Jeong Ah Jang
- Department of Molecular Biology, Pusan National University, Busan, 46241, Republic of Korea
| | - Ye Rim Jeong
- Department of Molecular Biology, Pusan National University, Busan, 46241, Republic of Korea
| | - Ye Bin Kim
- Department of Molecular Biology, Pusan National University, Busan, 46241, Republic of Korea
| | - Yi Yi Kyaw
- Advanced Molecular Research Centre, Department of Medical Research, Republic of Union of Myanmar, Yangon, 11191, Myanmar
| | - Hee Jeong Kong
- Biotechnology Research Division, National Institute of Fisheries Science, Busan, 46083, Republic of Korea
| | - Jung-Hyun Lee
- Marine Biotechnology Research Center, Korea Institute of Ocean Science and Technology, Busan, 49111, Republic of Korea
| | - JaeHun Cheong
- Department of Molecular Biology, Pusan National University, Busan, 46241, Republic of Korea.
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17
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Nobili G, Botticelli S, La Penna G, Morante S, Rossi G, Salina G. Probing protein stability: towards a computational atomistic, reliable, affordable, and improvable model. Front Mol Biosci 2023; 10:1122269. [PMID: 37325476 PMCID: PMC10267363 DOI: 10.3389/fmolb.2023.1122269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 05/16/2023] [Indexed: 06/17/2023] Open
Abstract
We present an improved application of a recently proposed computational method designed to evaluate the change of free energy as a function of the average value of a suitably chosen collective variable in proteins. The method is based on a full atomistic description of the protein and its environment. The goal is to understand how the protein melting temperature changes upon single-point mutations, because the sign of the temperature variation will allow us to discriminate stabilizing vs. destabilizing mutations in protein sequences. In this refined application the method is based on altruistic well-tempered metadynamics, a variant of multiple-walkers metadynamics. The resulting metastatistics is then modulated by the maximal constrained entropy principle. The latter turns out to be especially helpful in free-energy calculations as it is able to alleviate the severe limitations of metadynamics in properly sampling folded and unfolded configurations. In this work we apply the computational strategy outlined above in the case of the bovine pancreatic trypsin inhibitor, a well-studied small protein, which is a reference for computer simulations since decades. We compute the variation of the melting temperature characterizing the folding-unfolding process between the wild-type protein and two of its single-point mutations that are seen to have opposite effect on the free energy changes. The same approach is used for free energy difference calculations between a truncated form of frataxin and a set of five of its variants. Simulation data are compared to in vitro experiments. In all cases the sign of the change of melting temperature is reproduced, under the further approximation of using an empirical effective mean-field to average out protein-solvent interactions.
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Affiliation(s)
- Germano Nobili
- Dipartimento di Fisica, Universitá di Roma Tor Vergata, Roma, Italy
- INFN, Sezione di Roma Tor Vergata, Roma, Italy
| | - Simone Botticelli
- Dipartimento di Fisica, Universitá di Roma Tor Vergata, Roma, Italy
- INFN, Sezione di Roma Tor Vergata, Roma, Italy
| | - Giovanni La Penna
- CNR-Istituto di Chimica Dei Composti Organometallici, Firenze, Italy
- INFN, Sezione di Roma Tor Vergata, Roma, Italy
| | - Silvia Morante
- Dipartimento di Fisica, Universitá di Roma Tor Vergata, Roma, Italy
- INFN, Sezione di Roma Tor Vergata, Roma, Italy
- CNR-Istituto di Chimica Dei Composti Organometallici, Firenze, Italy
| | - Giancarlo Rossi
- Dipartimento di Fisica, Universitá di Roma Tor Vergata, Roma, Italy
- INFN, Sezione di Roma Tor Vergata, Roma, Italy
- Museo Storico della Fisica e Centro Studi e Ricerche E. Fermi, Roma, Italy
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18
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Wang Z, Zhou M, Cao N, Wang X. Site-directed modification of multifunctional lignocellulose-degrading enzymes of straw based on homologous modeling. World J Microbiol Biotechnol 2023; 39:214. [PMID: 37256388 DOI: 10.1007/s11274-023-03663-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/24/2023] [Indexed: 06/01/2023]
Abstract
Studying the straw lignocellulose strengthening mechanism during simultaneous degradation has important practical significance for improving resource utilization and reducing environmental pollution. In this paper, the degradation ability of four straw lignocellulose-degrading enzymes was evaluated by molecular docking and molecular dynamics. Using the significantly binds to straw lignocellulose-degrading enzyme as a template, a multifunctional lignocellulose-degrading enzyme 3CBH-1KS5-4XQD-1B85 was constructed based on amino acid recombination and homologous modeling. Five efficient degrading enzymes (3CBH-1, 3CBH-2, 3CBH-3, 3CBH-4, and 3CBH-5) were designed by site-directed mutagenesis of 3CBH-1KS5-4XQD-1B85 amino acid at position 346. Molecular dynamics showed that the degradation ability of 3CBH-1 was significant and it was 1.45 times higher than 3CBH-1KS5-4XQD-1B85. Moreover, the mechanism of enhanced degradability and the stability of the enzymes were explored. With the aid of Taguchi experiments, the suitable external environment for degrading straw was determined. In the presence of inhibitors (organic acids and phenolic compounds), the binding energy of 3CBH-1 (238.46 ± 30.96 kJ/mol) is 36.42% higher than that of 3CBH-1KS5-4XQD-1B85 (174.79 ± 20.35 kJ/mol) without external environmental stimulation. Based on homology modeling, this paper constructed a site-directed mutagenesis scheme of multifunctional enzymes, and the aim was to obtain multifunctional and efficient straw lignocellulose-degrading enzymes through protein engineering, which provided a feasible scheme for straw biodegradation.
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Affiliation(s)
- Zini Wang
- College of Plant Science, Jilin University, 5333 Xian Road, Changchun, 130062, China
| | - Mengying Zhou
- China Guangdong Nuclear Research Institute Limited Company, 1001 Shangbu Middle Road, Shenzhen, 518000, China
| | - Ning Cao
- College of Plant Science, Jilin University, 5333 Xian Road, Changchun, 130062, China
| | - Xiaoli Wang
- College of Plant Science, Jilin University, 5333 Xian Road, Changchun, 130062, China.
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19
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Chen W, Cui D, Jerome SV, Michino M, Lenselink EB, Huggins DJ, Beautrait A, Vendome J, Abel R, Friesner RA, Wang L. Enhancing Hit Discovery in Virtual Screening through Absolute Protein-Ligand Binding Free-Energy Calculations. J Chem Inf Model 2023; 63:3171-3185. [PMID: 37167486 DOI: 10.1021/acs.jcim.3c00013] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
In the hit identification stage of drug discovery, a diverse chemical space needs to be explored to identify initial hits. Contrary to empirical scoring functions, absolute protein-ligand binding free-energy perturbation (ABFEP) provides a theoretically more rigorous and accurate description of protein-ligand binding thermodynamics and could, in principle, greatly improve the hit rates in virtual screening. In this work, we describe an implementation of an accurate and reliable ABFEP method in FEP+. We validated the ABFEP method on eight congeneric compound series binding to eight protein receptors including both neutral and charged ligands. For ligands with net charges, the alchemical ion approach is adopted to avoid artifacts in electrostatic potential energy calculations. The calculated binding free energies correlate with experimental results with a weighted average of R2 = 0.55 for the entire dataset. We also observe an overall root-mean-square error (RMSE) of 1.1 kcal/mol after shifting the zero-point of the simulation data to match the average experimental values. Through ABFEP calculations using apo versus holo protein structures, we demonstrated that the protein conformational and protonation state changes between the apo and holo proteins are the main physical factors contributing to the protein reorganization free energy manifested by the overestimation of raw ABFEP calculated binding free energies using the holo structures of the proteins. Furthermore, we performed ABFEP calculations in three virtual screening applications for hit enrichment. ABFEP greatly improves the hit rates as compared to docking scores or other methods like metadynamics. The good performance of ABFEP in rank ordering compounds demonstrated in this work confirms it as a useful tool to improve the hit rates in virtual screening, thus facilitating hit discovery.
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Affiliation(s)
- Wei Chen
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Di Cui
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Steven V Jerome
- Schrödinger, Inc., 10201 Wateridge Circle, Suite 220, San Diego, California 92121, United States
| | - Mayako Michino
- Tri-Institutional Therapeutics Discovery Institute, 413 E. 69th Street, New York, New York 10065, United States
| | | | - David J Huggins
- Tri-Institutional Therapeutics Discovery Institute, 413 E. 69th Street, New York, New York 10065, United States
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, New York 10065, United States
| | - Alexandre Beautrait
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Jeremie Vendome
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Robert Abel
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Richard A Friesner
- Department of Chemistry, Columbia University, New York, New York 10027, United States
| | - Lingle Wang
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
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20
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David A, Sternberg MJE. Protein structure-based evaluation of missense variants: Resources, challenges and future directions. Curr Opin Struct Biol 2023; 80:102600. [PMID: 37126977 DOI: 10.1016/j.sbi.2023.102600] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 05/03/2023]
Abstract
We provide an overview of the methods that can be used for protein structure-based evaluation of missense variants. The algorithms can be broadly divided into those that calculate the difference in free energy (ΔΔG) between the wild type and variant structures and those that use structural features to predict the damaging effect of a variant without providing a ΔΔG. A wide range of machine learning approaches have been employed to develop those algorithms. We also discuss challenges and opportunities for variant interpretation in view of the recent breakthrough in three-dimensional structural modelling using deep learning.
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Affiliation(s)
- Alessia David
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK.
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK
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21
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Kasavajhala K, Simmerling C. Exploring the Transferability of Replica Exchange Structure Reservoirs to Accelerate Generation of Ensembles for Alternate Hamiltonians or Protein Mutations. J Chem Theory Comput 2023; 19:1931-1944. [PMID: 36861842 PMCID: PMC10658647 DOI: 10.1021/acs.jctc.3c00005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
Generating precise ensembles is commonly a prerequisite to understand the energetics of biological processes using Molecular Dynamics (MD) simulations. Previously, we have shown how unweighted reservoirs built from high temperature MD simulations can accelerate convergence of Boltzmann-weighted ensembles by at least 10× with the Reservoir Replica Exchange MD (RREMD) method. Therefore, in this work, we explore whether an unweighted structure reservoir generated with one Hamiltonian (solute force field plus solvent model) can be reused to quickly generate accurately weighted ensembles for Hamiltonians other than the one that was used to generate the reservoir. We also extended this methodology to rapidly estimate the effects of mutations on peptide stability by using a reservoir of diverse structures obtained from wild-type simulations. These results suggest that structures generated via fast methods such as coarse-grained models or structures predicted by Rosetta or deep learning approaches could be integrated into a reservoir to accelerate generation of ensembles using more accurate representations.
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Affiliation(s)
- Koushik Kasavajhala
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
| | - Carlos Simmerling
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
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22
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Lihan M, Lupyan D, Oehme D. Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations. Protein Sci 2023; 32:e4557. [PMID: 36573828 PMCID: PMC9878467 DOI: 10.1002/pro.4557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 12/28/2022]
Abstract
Improving protein thermostability has been a labor- and time-consuming process in industrial applications of protein engineering. Advances in computational approaches have facilitated the development of more efficient strategies to allow the prioritization of stabilizing mutants. Among these is FEP+, a free energy perturbation implementation that uses a thoroughly tested physics-based method to achieve unparalleled accuracy in predicting changes in protein thermostability. To gauge the applicability of FEP+ to situations where crystal structures are unavailable, here we have applied the FEP+ approach to homology models of 12 different proteins covering 316 mutations. By comparing predictions obtained with homology models to those obtained using crystal structures, we have identified that local rather than global sequence conservation between target and template sequence is a determining factor in the accuracy of predictions. By excluding mutation sites with low local sequence identity (<40%) to a template structure, we have obtained predictions with comparable performance to crystal structures (R2 of 0.67 and 0.63 and an RMSE of 1.20 and 1.16 kcal/mol for crystal structure and homology model predictions, respectively) for identifying stabilizing mutations when incorporating residue scanning into a cascade screening strategy. Additionally, we identify and discuss inherent limitations in sequence alignments and homology modeling protocols that translate into the poor FEP+ performance of a few select examples. Overall, our retrospective study provides detailed guidelines for the application of the FEP+ approach using homology models for protein thermostability predictions, which will greatly extend this approach to studies that were previously limited by structure availability.
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Affiliation(s)
- Muyun Lihan
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, and Center for Biophysics and Quantitative BiologyUniversity of Illinois Urbana‐ChampaignUrbanaIllinoisUSA
- Schrödinger Inc.CambridgeMassachusettsUSA
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23
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Haji-Allahverdipoor K, Jalali Javaran M, Rashidi Monfared S, Khadem-Erfan MB, Nikkhoo B, Bahrami Rad Z, Eslami H, Nasseri S. Insights Into The Effects of Amino Acid Substitutions on The Stability of Reteplase Structure: A Molecular Dynamics Simulation Study. IRANIAN JOURNAL OF BIOTECHNOLOGY 2023; 21:e3175. [PMID: 36811105 PMCID: PMC9938932 DOI: 10.30498/ijb.2022.308798.3175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 07/06/2022] [Indexed: 02/24/2023]
Abstract
Background Reteplase (recombinant plasminogen activator, r-PA) is a recombinant protein designed to imitate the endogenous tissue plasminogen activator and catalyze the plasmin production. It is known that the application of reteplase is limited by the complex production processes and protein's stability challenges. Computational redesign of proteins has gained momentum in recent years, particularly as a powerful tool for improving protein stability and consequently its production efficiency. Hence, in the current study, we implemented computational approaches to improve r-PA conformational stability, which fairly correlates with protein's resistance to proteolysis. Objectives The current study was developed in order to evaluate the effect of amino acid substitutions on the stability of reteplase structure using molecular dynamic simulations and computational predictions. Materials and Methods Several web servers designed for mutation analysis were utilized to select appropriate mutations. Additionally, the experimentally reported mutation, R103S, converting wild type r-PA into non-cleavable form, was also employed. Firstly, mutant collection, consisting of 15 structures, was constructed based on the combinations of four designated mutations. Then, 3D structures were generated using MODELLER. Finally, 17 independent 20-ns molecular dynamics (MD) simulations were conducted and different analysis were performed like root-mean-square deviation (RMSD), root-mean-square fluctuations (RMSF), secondary structure analysis, number of hydrogen bonds, principal components analysis (PCA), eigenvector projection, and density analysis. Results Predicted mutations successfully compensated the more flexible conformation caused by R103S substitution, so, improved conformational stability was analyzed from MD simulations. In particular, R103S/A286I/G322I indicated the best results and remarkably enhanced the protein stability. Conclusion The conformational stability conferred by these mutations will probably lead to more protection of r-PA in protease-rich environments in various recombinant systems and potentially enhance its production and expression level.
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Affiliation(s)
- Kaveh Haji-Allahverdipoor
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Mokhtar Jalali Javaran
- Department of Biotechnology, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Sajad Rashidi Monfared
- Department of Biotechnology, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Mohamad Bagher Khadem-Erfan
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Bahram Nikkhoo
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Zhila Bahrami Rad
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Habib Eslami
- Department of Pharmacology and Toxicology, School of Pharmacy, Hormozgan University of Medicinal sciences, Bandar Abbas, Iran
| | - Sherko Nasseri
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
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24
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Mansouri M, El Haddoumi G, Bendani H, Boumajdi N, Hakmi M, Abbou H, Bouricha EM, Elgharbaoui B, Kartti S, El Jaoudi R, Belyamani L, Kandoussi I, Ibrahimi A, El Hafidi N. In Silico Analyses of All STAT3 Missense Variants Leading to Explore Divergent AD-HIES Clinical Phenotypes. Evol Bioinform Online 2023; 19:11769343231169374. [PMID: 37123531 PMCID: PMC10134169 DOI: 10.1177/11769343231169374] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/20/2023] [Indexed: 05/02/2023] Open
Abstract
Autosomal dominant hyper-IgE syndrome (AD-HIES) is linked to dominant negative mutations of the STAT3 protein whose molecular basis for dysfunction is unclear and presenting with a variety of clinical manifestations with only supportive treatment. To establish the relationship between the impact of STAT3 mutations in different domains and the severity of the clinical manifestations, 105 STAT3 mutations were analyzed for their impact on protein stability, flexibility, function, and binding affinity using in Silico approaches. Our results showed that 73% of the studied mutations have an impact on the physicochemical properties of the protein, altering the stability, flexibility and function to varying degrees. In particular, mutations affecting the DNA binding domain (DBD) and the Src Homology 2 (SH2) have a significant impact on the protein structure and disrupt its interaction either with DNA or other STAT3 to form a heterodomain complex, leading to severe clinical phenotypes. Collectively, this study suggests that there is a close relationship between the domain involving the mutation, the degree of variation in the properties of the protein and the degree of loss of function ranging from partial loss to complete loss, explaining the variability of clinical manifestations between mild and severe.
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Affiliation(s)
- Mariam Mansouri
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Ghyzlane El Haddoumi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Houda Bendani
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Nasma Boumajdi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Mohammed Hakmi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Hanane Abbou
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
- Mohammed VI University of Health
Sciences (UM6SS), Casablanca, Morocco
| | - El Mehdi Bouricha
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Boutaina Elgharbaoui
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Souad Kartti
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Rachid El Jaoudi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
- Pharmacology and Toxicology Department,
Faculty of Medicine and Pharmacy, University Mohamed V, Rabat, Morocco
| | - Lahcen Belyamani
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
- Mohammed VI University of Health
Sciences (UM6SS), Casablanca, Morocco
- Emergency Department, Military Hospital
Mohammed V, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
| | - Ilham Kandoussi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
| | - Azeddine Ibrahimi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
- Mohammed VI University of Health
Sciences (UM6SS), Casablanca, Morocco
| | - Naima El Hafidi
- Biotechnology lab (MedBiotech),
Bioinova Research Center, Medical and Pharmacy School, Mohammed V University in
Rabat, Morocco
- Centre Mohammed VI of Research and
Innovation (CM6), Rabat, Morocco
- Division of Pediatric immunoallergology
and Infectious Diseases, Children University Hospital, Ibn Sina University Hospital,
Rabat, Morocco
- Pr. Naima El Hafidi, Biotechnology lab
(MedBiotech), Bioinova Research Center, Medical & Pharmacy School, Mohammed
V university in Rabat, Imp. Souissi, Rabat 10100, Morocco.
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25
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Gao Y, Wang B, Hu S, Zhu T, Zhang JZH. An efficient method to predict protein thermostability in alanine mutation. Phys Chem Chem Phys 2022; 24:29629-29639. [PMID: 36449314 DOI: 10.1039/d2cp04236c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The relationship between protein sequence and its thermodynamic stability is a critical aspect of computational protein design. In this work, we present a new theoretical method to calculate the free energy change (ΔΔG) resulting from a single-point amino acid mutation to alanine in a protein sequence. The method is derived based on physical interactions and is very efficient in estimating the free energy changes caused by a series of alanine mutations from just a single molecular dynamics (MD) trajectory. Numerical calculations are carried out on a total of 547 alanine mutations in 19 diverse proteins whose experimental results are available. The comparison between the experimental ΔΔGexp and the calculated values shows a generally good correlation with a correlation coefficient of 0.67. Both the advantages and limitations of this method are discussed. This method provides an efficient and valuable tool for protein design and engineering.
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Affiliation(s)
- Ya Gao
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Bo Wang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.
| | - Shiyu Hu
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Tong Zhu
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China. .,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - John Z H Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China. .,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.,Shenzhen Institute of Synthetic Biology, Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
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26
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Coskun D, Chen W, Clark AJ, Lu C, Harder ED, Wang L, Friesner RA, Miller EB. Reliable and Accurate Prediction of Single-Residue p Ka Values through Free Energy Perturbation Calculations. J Chem Theory Comput 2022; 18:7193-7204. [PMID: 36384001 DOI: 10.1021/acs.jctc.2c00954] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Accurate prediction of the pKa's of protein residues is crucial to many applications in biological simulation and drug discovery. Here, we present the use of free energy perturbation (FEP) calculations for the prediction of single-protein residue pKa values. We begin with an initial set of 191 residues with experimentally determined pKa values. To isolate sampling limitations from force field inaccuracies, we develop an algorithm to classify residues whose environments are significantly affected by crystal packing effects. We then report an approach to identify buried histidines that require significant sampling beyond what is achieved in typical FEP calculations. We therefore define a clean data set not requiring algorithms capable of predicting major conformational changes on which other pKa prediction methods can be tested. On this data set, we report an RMSE of 0.76 pKa units for 35 ASP residues, 0.51 pKa units for 44 GLU residues, and 0.67 pKa units for 76 HIS residues.
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Affiliation(s)
- Dilek Coskun
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Wei Chen
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Anthony J Clark
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Chao Lu
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Edward D Harder
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Lingle Wang
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
| | - Richard A Friesner
- Department of Chemistry, Columbia University, 3000 Broadway, MC 3110, New York, New York10036, United States
| | - Edward B Miller
- Schrödinger, Inc., 1540 Broadway, New York, New York10036, United States
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27
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Masson P, Lushchekina S. Conformational Stability and Denaturation Processes of Proteins Investigated by Electrophoresis under Extreme Conditions. Molecules 2022; 27:6861. [PMID: 36296453 PMCID: PMC9610776 DOI: 10.3390/molecules27206861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/17/2022] Open
Abstract
The functional structure of proteins results from marginally stable folded conformations. Reversible unfolding, irreversible denaturation, and deterioration can be caused by chemical and physical agents due to changes in the physicochemical conditions of pH, ionic strength, temperature, pressure, and electric field or due to the presence of a cosolvent that perturbs the delicate balance between stabilizing and destabilizing interactions and eventually induces chemical modifications. For most proteins, denaturation is a complex process involving transient intermediates in several reversible and eventually irreversible steps. Knowledge of protein stability and denaturation processes is mandatory for the development of enzymes as industrial catalysts, biopharmaceuticals, analytical and medical bioreagents, and safe industrial food. Electrophoresis techniques operating under extreme conditions are convenient tools for analyzing unfolding transitions, trapping transient intermediates, and gaining insight into the mechanisms of denaturation processes. Moreover, quantitative analysis of electrophoretic mobility transition curves allows the estimation of the conformational stability of proteins. These approaches include polyacrylamide gel electrophoresis and capillary zone electrophoresis under cold, heat, and hydrostatic pressure and in the presence of non-ionic denaturing agents or stabilizers such as polyols and heavy water. Lastly, after exposure to extremes of physical conditions, electrophoresis under standard conditions provides information on irreversible processes, slow conformational drifts, and slow renaturation processes. The impressive developments of enzyme technology with multiple applications in fine chemistry, biopharmaceutics, and nanomedicine prompted us to revisit the potentialities of these electrophoretic approaches. This feature review is illustrated with published and unpublished results obtained by the authors on cholinesterases and paraoxonase, two physiologically and toxicologically important enzymes.
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Affiliation(s)
- Patrick Masson
- Biochemical Neuropharmacology Laboratory, Kazan Federal University, Kremlievskaya Str. 18, 420111 Kazan, Russia
| | - Sofya Lushchekina
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygin Str. 4, 119334 Moscow, Russia
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28
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Yu Y, Wang Z, Wang L, Tian S, Hou T, Sun H. Predicting the mutation effects of protein–ligand interactions via end-point binding free energy calculations: strategies and analyses. J Cheminform 2022; 14:56. [PMID: 35987841 PMCID: PMC9392442 DOI: 10.1186/s13321-022-00639-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/08/2022] [Indexed: 12/04/2022] Open
Abstract
Protein mutations occur frequently in biological systems, which may impact, for example, the binding of drugs to their targets through impairing the critical H-bonds, changing the hydrophobic interactions, etc. Thus, accurately predicting the effects of mutations on biological systems is of great interests to various fields. Unfortunately, it is still unavailable to conduct large-scale wet-lab mutation experiments because of the unaffordable experimental time and financial costs. Alternatively, in silico computation can serve as a pioneer to guide the experiments. In fact, numerous pioneering works have been conducted from computationally cheaper machine-learning (ML) methods to the more expensive alchemical methods with the purpose to accurately predict the mutation effects. However, these methods usually either cannot result in a physically understandable model (ML-based methods) or work with huge computational resources (alchemical methods). Thus, compromised methods with good physical characteristics and high computational efficiency are expected. Therefore, here, we conducted a comprehensive investigation on the mutation issues of biological systems with the famous end-point binding free energy calculation methods represented by MM/GBSA and MM/PBSA. Different computational strategies considering different length of MD simulations, different value of dielectric constants and whether to incorporate entropy effects to the predicted total binding affinities were investigated to provide a more accurate way for predicting the energetic change upon protein mutations. Overall, our result shows that a relatively long MD simulation (e.g. 100 ns) benefits the prediction accuracy for both MM/GBSA and MM/PBSA (with the best Pearson correlation coefficient between the predicted ∆∆G and the experimental data of ~ 0.44 for a challenging dataset). Further analyses shows that systems involving large perturbations (e.g. multiple mutations and large number of atoms change in the mutation site) are much easier to be accurately predicted since the algorithm works more sensitively to the large change of the systems. Besides, system-specific investigation reveals that conformational adjustment is needed to refine the micro-environment of the manually mutated systems and thus lead one to understand why longer MD simulation is necessary to improve the predicting result. The proposed strategy is expected to be applied in large-scale mutation effects investigation with interpretation.
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29
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Novack D, Qian L, Acker G, Voelz VA, Baxter RHG. Oncogenic Mutations in the DNA-Binding Domain of FOXO1 that Disrupt Folding: Quantitative Insights from Experiments and Molecular Simulations. Biochemistry 2022; 61:1669-1682. [PMID: 35895105 DOI: 10.1021/acs.biochem.2c00224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
FOXO1, a member of the family of winged-helix motif Forkhead box (FOX) transcription factors, is the most abundantly expressed FOXO member in mature B cells. Sequencing of diffuse large B-cell lymphoma (DLBCL) tumors and cell lines identified specific mutations in the forkhead domain linked to loss of function. Differential scanning calorimetry and thermal shift assays were used to characterize how eight of these mutations affect the stability of the FOX domain. Mutations L183P and L183R were found to be particularly destabilizing. Electrophoresis mobility shift assays show these same mutations also disrupt FOXO1 binding to their canonical DNA sequences, suggesting that the loss of function is due to destabilization of the folded structure. Computational modeling of the effect of mutations on FOXO1 folding was performed using alchemical free energy perturbation (FEP), and a Markov model of the entire folding reaction was constructed from massively parallel molecular simulations, which predicts folding pathways involving the late folding of helix α3. Although FEP can qualitatively predict the destabilization from L183 mutations, we find that a simple hydrophobic transfer model, combined with estimates of unfolded-state solvent-accessible surface areas from molecular simulations, is able to more accurately predict changes in folding free energies due to mutations. These results suggest that the atomic detail provided by simulations is important for the accurate prediction of mutational effects on folding stability. Corresponding disease-associated mutations in other FOX family members support further experimental and computational studies of the folding mechanism of FOX domains.
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Affiliation(s)
- Dylan Novack
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Lei Qian
- Department of Medical Genetics & Molecular Biochemistry, Lewis Katz School of Medicine at Temple University, 3440 North Broad Street, Philadelphia, Pennsylvania 19140, United States
| | - Gwyneth Acker
- Department of Medical Genetics & Molecular Biochemistry, Lewis Katz School of Medicine at Temple University, 3440 North Broad Street, Philadelphia, Pennsylvania 19140, United States
| | - Vincent A Voelz
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Richard H G Baxter
- Department of Medical Genetics & Molecular Biochemistry, Lewis Katz School of Medicine at Temple University, 3440 North Broad Street, Philadelphia, Pennsylvania 19140, United States
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30
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Zhu F, Bourguet FA, Bennett WFD, Lau EY, Arrildt KT, Segelke BW, Zemla AT, Desautels TA, Faissol DM. Large-scale application of free energy perturbation calculations for antibody design. Sci Rep 2022; 12:12489. [PMID: 35864134 PMCID: PMC9302960 DOI: 10.1038/s41598-022-14443-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 06/07/2022] [Indexed: 01/02/2023] Open
Abstract
Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.
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Affiliation(s)
- Fangqiang Zhu
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA.
| | - Feliza A Bourguet
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - William F D Bennett
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Edmond Y Lau
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Kathryn T Arrildt
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Brent W Segelke
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Adam T Zemla
- Global Security Computing Division, Computing Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Thomas A Desautels
- Computational Engineering Division, Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, USA
| | - Daniel M Faissol
- Computational Engineering Division, Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, USA.
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31
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Sen N, Anishchenko I, Bordin N, Sillitoe I, Velankar S, Baker D, Orengo C. Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs. Brief Bioinform 2022; 23:bbac187. [PMID: 35641150 PMCID: PMC9294430 DOI: 10.1093/bib/bbac187] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 04/23/2022] [Accepted: 04/27/2022] [Indexed: 12/12/2022] Open
Abstract
Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.
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Affiliation(s)
- Neeladri Sen
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Ivan Anishchenko
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Nicola Bordin
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Christine Orengo
- Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
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Hayes RL, Vilseck JZ, Brooks CL. Addressing Intersite Coupling Unlocks Large Combinatorial Chemical Spaces for Alchemical Free Energy Methods. J Chem Theory Comput 2022; 18:2114-2123. [PMID: 35255214 PMCID: PMC9700482 DOI: 10.1021/acs.jctc.1c00948] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Alchemical free energy methods are playing a growing role in molecular design, both for computer-aided drug design of small molecules and for computational protein design. Multisite λ dynamics (MSλD) is a uniquely scalable alchemical free energy method that enables more efficient exploration of combinatorial alchemical spaces encountered in molecular design, but simulations have typically been limited to a few hundred ligands or sequences. Here, we focus on coupling between sites to enable scaling to larger alchemical spaces. We first discuss updates to the biasing potentials that facilitate MSλD sampling to include coupling terms and show that this can provide more thorough sampling of alchemical states. We then harness coupling between sites by developing a new free energy estimator based on the Potts models underlying direct coupling analysis, a method for predicting contacts from sequence coevolution, and find it yields more accurate free energies than previous estimators. The sampling requirements of the Potts model estimator scale with the square of the number of sites, a substantial improvement over the exponential scaling of the standard estimator. This opens up exploration of much larger alchemical spaces with MSλD for molecular design.
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Affiliation(s)
- Ryan L Hayes
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
- Biophysics Program, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Jonah Z Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Charles L Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
- Biophysics Program, University of Michigan, Ann Arbor, Michigan 48109, United States
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Markthaler D, Fleck M, Stankiewicz B, Hansen N. Exploring the Effect of Enhanced Sampling on Protein Stability Prediction. J Chem Theory Comput 2022; 18:2569-2583. [PMID: 35298174 DOI: 10.1021/acs.jctc.1c01012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Changes in protein stability due to side-chain mutations are evaluated by alchemical free-energy calculations based on classical molecular dynamics (MD) simulations in explicit solvent using the GROMOS force field. Three proteins of different complexity with a total number of 93 single-point mutations are analyzed, and the relative free-energy differences are discussed with respect to configurational sampling and (dis)agreement with experimental data. For the smallest protein studied, a 34-residue WW domain, the starting structure dependence of the alchemical free-energy changes, is discussed in detail. Deviations from previous simulations for the two other proteins are shown to result from insufficient sampling in the earlier studies. Hamiltonian replica exchange in combination with multiple starting structures and sufficient sampling time of more than 100 ns per intermediate alchemical state is required in some cases to reach convergence.
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Affiliation(s)
- Daniel Markthaler
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Maximilian Fleck
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Bartosz Stankiewicz
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Niels Hansen
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
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34
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Kumar GS, Sobhia ME, Ghosh K. Binding affinity analysis of quinolone and dione inhibitors with Mtb-DNA gyrase emphasising the crystal water molecular transfer energy to the protein–ligand association. MOLECULAR SIMULATION 2022. [DOI: 10.1080/08927022.2022.2042530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- G. Siva Kumar
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Punjab, India
| | - M. Elizabeth Sobhia
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Punjab, India
| | - Ketan Ghosh
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Punjab, India
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Accurate Prediction of Protein Thermodynamic Stability Changes upon Residue Mutation using Free Energy Perturbation. J Mol Biol 2021; 434:167375. [PMID: 34826524 DOI: 10.1016/j.jmb.2021.167375] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/05/2021] [Accepted: 11/17/2021] [Indexed: 01/17/2023]
Abstract
This work describes the application of a physics-based computational approach to predict the relative thermodynamic stability of protein variants, and evaluates the quantitative accuracy of those predictions compared to experimental data obtained from a diverse set of protein systems assayed at variable pH conditions. Physical stability is a key determinant of the clinical and commercial success of biological therapeutics, vaccines, diagnostics, enzymes and other protein-based products. Although experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins exist, they tend to be time consuming and costly, hence the need for accurate prediction methods. In contrast to many of the commonly available computational methods for stability prediction, the Free Energy Perturbation approach applied in this paper explicitly accounts for solvent effects and samples conformational dynamics using a rigorous molecular dynamics simulation process. On the entire validation dataset, consisting of 328 single point mutations spread across 14 distinct protein structures, our results show good overall correlation with experiment with an R2 of 0.65 and a low mean unsigned error of 0.95 kcal/mol. Application of the FEP approach in conjunction with experimental assessment techniques offers opportunities to lower the time and expense of product development and reduce the risk of costly late-stage failures.
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36
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Hayes RL, Buckner J, Brooks CL. BLaDE: A Basic Lambda Dynamics Engine for GPU-Accelerated Molecular Dynamics Free Energy Calculations. J Chem Theory Comput 2021; 17:6799-6807. [PMID: 34709046 DOI: 10.1021/acs.jctc.1c00833] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
There is an accelerating interest in practical applications of alchemical free energy methods to problems in protein design, constant pH simulations, and especially computer-aided drug design. In the present paper, we describe a basic lambda dynamics engine (BLaDE) that enables alchemical free energy simulations, including multisite λ dynamics (MSλD) simulations, on graphical processor units (GPUs). We find that BLaDE is 5 to 8 times faster than the current GPU implementation of MSλD-based free energy calculations in CHARMM. We also demonstrate that BLaDE running standard molecular dynamics attains a performance competitive with and sometimes exceeding that of the highly optimized OpenMM GPU code. BLaDE is available as a standalone program and through an API in CHARMM.
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Affiliation(s)
- Ryan L Hayes
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Joshua Buckner
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Charles L Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.,Biophysics Program, University of Michigan, Ann Arbor, Michigan 48109, United States
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37
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Fadason T, Farrow S, Gokuladhas S, Golovina E, Nyaga D, O'Sullivan JM, Schierding W. Assigning function to SNPs: Considerations when interpreting genetic variation. Semin Cell Dev Biol 2021; 121:135-142. [PMID: 34446357 DOI: 10.1016/j.semcdb.2021.08.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 08/12/2021] [Indexed: 12/26/2022]
Abstract
Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precision medicine. However, despite the apparent simplicity that is captured in the name SNP - 'single nucleotide' changes are not easy to functionally characterize. This complexity arises from multiple features of the genome including the fact that function is development and environment specific. As such, we are often fooled by our terminology and underlying assumptions that there is a single function for a SNP. Here we discuss some of what is known about SNPs, their functions and how we can go about characterizing them.
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Affiliation(s)
- Tayaza Fadason
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Sophie Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | | | - Evgeniia Golovina
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Denis Nyaga
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand; Garvan Institute of Medical Research, Sydney, New South Wales, Australia; MRC Lifecourse Epidemiology Unit, University of Southampton, United Kingdom.
| | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
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Boucher L, Somani S, Negron C, Ma W, Jacobs S, Chan W, Malia T, Obmolova G, Teplyakov A, Gilliland GL, Luo J. Surface salt bridges contribute to the extreme thermal stability of an FN3-like domain from a thermophilic bacterium. Proteins 2021; 90:270-281. [PMID: 34405904 DOI: 10.1002/prot.26218] [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] [Received: 07/25/2020] [Revised: 03/08/2021] [Accepted: 08/02/2021] [Indexed: 12/27/2022]
Abstract
This study uses differential scanning calorimetry, X-ray crystallography, and molecular dynamics simulations to investigate the structural basis for the high thermal stability (melting temperature 97.5°C) of a FN3-like protein domain from thermophilic bacteria Thermoanaerobacter tengcongensis (FN3tt). FN3tt adopts a typical FN3 fold with a three-stranded beta sheet packing against a four-stranded beta sheet. We identified three solvent exposed arginine residues (R23, R25, and R72), which stabilize the protein through salt bridge interactions with glutamic acid residues on adjacent strands. Alanine mutation of the three arginine residues reduced melting temperature by up to 22°C. Crystal structures of the wild type (WT) and a thermally destabilized (∆Tm -19.7°C) triple mutant (R23L/R25T/R72I) were found to be nearly identical, suggesting that the destabilization is due to interactions of the arginine residues. Molecular dynamics simulations showed that the salt bridge interactions in the WT were stable and provided a dynamical explanation for the cooperativity observed between R23 and R25 based on calorimetry measurements. In addition, folding free energy changes computed using free energy perturbation molecular dynamics simulations showed high correlation with melting temperature changes. This work is another example of surface salt bridges contributing to the enhanced thermal stability of thermophilic proteins. The molecular dynamics simulation methods employed in this study may be broadly useful for in silico surface charge engineering of proteins.
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Affiliation(s)
- Lauren Boucher
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Sandeep Somani
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | | | - Wenting Ma
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Steven Jacobs
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Winnie Chan
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Thomas Malia
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Galina Obmolova
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Alexey Teplyakov
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Gary L Gilliland
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Jinquan Luo
- Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
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39
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Tang Y, Zhao S, Peng Z, Li Z, Chen L, Gan P. Cu 2O nanoparticles anchored on carbon for the efficient removal of propofol from operating room wastewater via peroxymonosulfate activation: efficiency, mechanism, and pathway. RSC Adv 2021; 11:20983-20991. [PMID: 35479351 PMCID: PMC9034049 DOI: 10.1039/d1ra03049c] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/29/2021] [Indexed: 11/29/2022] Open
Abstract
Anesthetic drug wastage has increasingly become the main resource of operating room sewage, which poses a great risk to the safety of humans and other organisms. Propofol is the most widely used anesthetic drug in the world, and also occupies the largest proportion of the total anesthetic wastage in the operating room. In this work, a 2D Cu2O anchored carbon catalyst (Cu2O@NC) was prepared by the assembly-pyrolysis process and successfully applied to peroxymonosulfate (PMS) activation. We took propofol as a typical example and investigated the removal activity through heterostructure-enhanced advanced oxidation processes (AOPs). Through the degradation process, propofol can be removed from 20 ppm to ultralow levels within 5 min using the PMS/Cu2O@NC system. The degradation pathway of propofol was deduced through quantum chemical calculation and LC/GC-MS results. The final products were verified as CO2 and H2O. Moreover, sulfate radicals (SO4˙-) proved to be the dominant reactive oxidation species by radical scavenger experiments and ESR results. In addition, it has great universality for various pharmaceuticals such as tetracycline (TC), amoxicillin (AMX), cephalexin (CPX), and norfloxacin (NFX). Our work provided the possibility to treat operation room sewage in a rapid, high-efficiency, and feasible way.
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Affiliation(s)
- Yujie Tang
- Hunan Provincial Maternal and Child Health Care Hospital Changsha 410008 P. R. China
| | - Shiyin Zhao
- Faculty of Health Sciences, University of Macau Macau SAR 999078 P. R. China
| | - Zemin Peng
- Hunan Provincial Maternal and Child Health Care Hospital Changsha 410008 P. R. China
| | - Zhen Li
- Hunan Provincial Maternal and Child Health Care Hospital Changsha 410008 P. R. China
| | - Liang Chen
- Hunan Provincial Maternal and Child Health Care Hospital Changsha 410008 P. R. China
| | - Pei Gan
- Hunan Provincial Maternal and Child Health Care Hospital Changsha 410008 P. R. China
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40
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Hayes RL, Brooks CL. A strategy for proline and glycine mutations to proteins with alchemical free energy calculations. J Comput Chem 2021; 42:1088-1094. [PMID: 33844328 DOI: 10.1002/jcc.26525] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 11/07/2022]
Abstract
Computation of the thermodynamic consequences of protein mutations holds great promise in protein biophysics and design. Alchemical free energy methods can give improved estimates of mutational free energies, and are already widely used in calculations of relative and absolute binding free energies in small molecule design problems. In principle, alchemical methods can address any amino acid mutation with an appropriate alchemical pathway, but identifying a strategy that produces such a path for proline and glycine mutations is an ongoing challenge. Most current strategies perturb only side chain atoms, while proline and glycine mutations also alter the backbone parameters and backbone ring topology. Some strategies also perturb backbone parameters and enable glycine mutations. This work presents a strategy that enables both proline and glycine mutations and comprises two key elements: a dual backbone with restraints and scaling of bonded terms, facilitating backbone parameter changes, and a soft bond in the proline ring, enabling ring topology changes in proline mutations. These elements also have utility for core hopping and macrocycle studies in computer-aided drug design. This new strategy shows slight improvements over an alternative side chain perturbation strategy for a set T4 lysozyme mutations lacking proline and glycine, and yields good agreement with experiment for a set of T4 lysozyme proline and glycine mutations not previously studied. To our knowledge this is the first report comparing alchemical predictions of proline mutations with experiment. With this strategy in hand, alchemical methods now have access to the full palette of amino acid mutations.
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Affiliation(s)
- Ryan L Hayes
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan, USA
| | - Charles L Brooks
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan, USA.,Biophysics Program, University of Michigan, Ann Arbor, Michigan, USA
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41
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Enhanced plant-microbe remediation of PCBs in soil using enzyme modification technique combined with molecular docking and molecular dynamics. Biochem J 2021; 478:1921-1941. [PMID: 33900386 DOI: 10.1042/bcj20210104] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/21/2021] [Accepted: 04/26/2021] [Indexed: 11/17/2022]
Abstract
The study on the enhanced mechanisms of the enzymes involved in plant absorption, plant degradation, and microbial mineralization in the remediation of soils contaminated with polychlorinated biphenyls (PCBs) is of great significance for the application of plant-microbe combined remediation technique in PCB-contaminated soils. The present study first used a combination of molecular docking and molecular dynamics methods to calculate the effects of the plant absorption enzyme, plant degradation enzyme, and microbial mineralization enzyme on the PCBs in the soil environment. A multifunctional plant degradation enzyme was constructed with three functional roles of absorption, degradation, and mineralization using amino acid sequence recombination and site-directed mutagenesis to modify the template of plant degradation enzyme. Finally, using the Taguchi experimental design-assisted molecular dynamics simulation method, the suitable external environmental conditions of plant-microbe combined remediation of the PCB-contaminated soil were determined. In total, six multifunctional plant degradation enzymes were designed, which exhibited a significantly improved efficiency of PCB degradation. In comparison to the complex of plant absorption enzyme, plant degradation enzyme, and microorganism mineralization enzyme (6QIM-3GZX-1B85), the six multifunctional plant degradation enzymes exhibited significantly higher efficiency (2.10-2.38 times) in degrading the PCBs, with a maximum of 2.69 times under suitable external environmental conditions.
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42
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Wilson CJ, Chang M, Karttunen M, Choy WY. KEAP1 Cancer Mutants: A Large-Scale Molecular Dynamics Study of Protein Stability. Int J Mol Sci 2021; 22:5408. [PMID: 34065616 PMCID: PMC8161161 DOI: 10.3390/ijms22105408] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 05/11/2021] [Accepted: 05/13/2021] [Indexed: 12/30/2022] Open
Abstract
We have performed 280 μs of unbiased molecular dynamics (MD) simulations to investigate the effects of 12 different cancer mutations on Kelch-like ECH-associated protein 1 (KEAP1) (G333C, G350S, G364C, G379D, R413L, R415G, A427V, G430C, R470C, R470H, R470S and G476R), one of the frequently mutated proteins in lung cancer. The aim was to provide structural insight into the effects of these mutants, including a new class of ANCHOR (additionally NRF2-complexed hypomorph) mutant variants. Our work provides additional insight into the structural dynamics of mutants that could not be analyzed experimentally, painting a more complete picture of their mutagenic effects. Notably, blade-wise analysis of the Kelch domain points to stability as a possible target of cancer in KEAP1. Interestingly, structural analysis of the R470C ANCHOR mutant, the most prevalent missense mutation in KEAP1, revealed no significant change in structural stability or NRF2 binding site dynamics, possibly indicating an covalent modification as this mutant's mode of action.
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Affiliation(s)
- Carter J. Wilson
- Department of Biochemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5C1, Canada; (C.J.W.); (M.C.)
- Department of Applied Mathematics, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
| | - Megan Chang
- Department of Biochemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5C1, Canada; (C.J.W.); (M.C.)
| | - Mikko Karttunen
- Department of Applied Mathematics, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Chemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 3K7, Canada
- Centre for Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
| | - Wing-Yiu Choy
- Department of Biochemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5C1, Canada; (C.J.W.); (M.C.)
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Nikam R, Kulandaisamy A, Harini K, Sharma D, Gromiha MM. ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years. Nucleic Acids Res 2021; 49:D420-D424. [PMID: 33196841 PMCID: PMC7778892 DOI: 10.1093/nar/gkaa1035] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 10/14/2020] [Accepted: 10/26/2020] [Indexed: 11/12/2022] Open
Abstract
ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches. In addition, we provided a graphical interface for visualization of mutations at sequence and structure levels. ProThermDB is cross-linked with other relevant databases, PDB, UniProt, PubMed etc. It is freely available at https://web.iitm.ac.in/bioinfo2/prothermdb/index.html without any login requirements. It is implemented in Python, HTML and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Safari.
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Affiliation(s)
- Rahul Nikam
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - A Kulandaisamy
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - K Harini
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - Divya Sharma
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - M Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
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44
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Jespers W, Åqvist J, Gutiérrez-de-Terán H. Free Energy Calculations for Protein-Ligand Binding Prediction. Methods Mol Biol 2021; 2266:203-226. [PMID: 33759129 DOI: 10.1007/978-1-0716-1209-5_12] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Computational prediction of protein-ligand binding involves initial determination of the binding mode and subsequent evaluation of the strength of the protein-ligand interactions, which directly correlates with ligand binding affinities. As a consequence of increasing computer power, rigorous approaches to calculate protein-ligand binding affinities, such as free energy perturbation (FEP) methods, are becoming an essential part of the toolbox of computer-aided drug design. In this chapter, we provide a general overview of these methods and introduce the QFEP modules, which are open-source API workflows based on our molecular dynamics (MD) package Q. The module QligFEP allows estimation of relative binding affinities along ligand series, while QresFEP is a module to estimate binding affinity shifts caused by single-point mutations of the protein. We herein provide guidelines for the use of each of these modules based on data extracted from ligand-design projects. While these modules are stand-alone, the combined use of the two workflows in a drug-design project yields complementary perspectives of the ligand binding problem, providing two sides of the same coin. The selected case studies illustrate how to use QFEP to approach the two key questions associated with ligand binding prediction: identifying the most favorable binding mode from different alternatives and establishing structure-affinity relationships that allow the rational optimization of hit compounds.
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Affiliation(s)
- Willem Jespers
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Uppsala, Sweden
| | - Johan Åqvist
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Uppsala, Sweden
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Uppsala, Sweden.
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45
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Prakash SMU, Nazeer Y, Jayanthi S, Kabir MA. Computational insights into fluconazole resistance by the suspected mutations in lanosterol 14α-demethylase (Erg11p) of Candida albicans. MOLECULAR BIOLOGY RESEARCH COMMUNICATIONS 2020; 9:155-167. [PMID: 33344662 PMCID: PMC7731972 DOI: 10.22099/mbrc.2020.36298.1476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Mutations in the ergosterol biosynthesis gene 11 (ERG11) of Candida albicans have been frequently reported in fluconazole-resistant clinical isolates. Exploring the mutations and their effect could provide new insights into the underlying mechanism of fluconazole resistance. Erg11p_Threonine285Alanine (Erg11p_THR285ALA), Erg11p_Leucine321Phenylalanine (Erg11p_LEU321PHE) and Erg11p_Serine457Proline (Erg11p_SER457PRO) are three fluconazole-resistant suspected mutations reported in clinical isolates of C. albicans. Therefore, our study aims to investigate the role of these suspected mutations in fluconazole resistance using in-silico methods. Molecular dynamics simulation (MDS) analysis of apo-protein for 25ns (nanosecond) showed that suspected mutant proteins underwent slight conformational changes in the tertiary structure. Molecular docking with fluconazole followed by binding free energy analysis showed reduced non-bonded interactions with loss of heme interaction and the least binding affinity for Erg11p_SER457PRO mutation. MDS of suspected mutant proteins-fluconazole complexes for 50ns revealed that Erg11p_SER457PRO and Erg11p_LEU321PHE have clear differences in the interaction pattern and loss or reduced heme interaction compared to wild type Erg11p-fluconazole complex. MDS and binding free energy analysis of Erg11p_SER457PRO-fluconazole complex showed the least binding similar to verified mutation Erg11p_TYR447HIS-fluconazole complex. Taken together, our study concludes that suspected mutation Erg11p_THR285ALA may not have any role whereas Erg11p_LEU321PHE could have a moderate role. However, Erg11p_SER457PRO mutation has a strong possibility to play an active role in fluconazole resistance of C. albicans.
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Affiliation(s)
| | - Yasin Nazeer
- Regional Medical Research Centre, Indian Council of Medical Research (ICMR), Belagavi -590010, Karnataka, India
| | - Sivaraman Jayanthi
- Computational Drug Design Lab, School of BioSciences and Technology, Vellore Institute of Technology, Vellore-632014, Tamil Nadu, India
| | - Mohammad Anaul Kabir
- Molecular Genetics Laboratory, School of Biotechnology, National Institute of Technology Calicut, Calicut 673601, Kerala, India
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Wu R, Prabhu R, Ozkan A, Sitharam M. Rapid prediction of crucial hotspot interactions for icosahedral viral capsid self-assembly by energy landscape atlasing validated by mutagenesis. PLoS Comput Biol 2020; 16:e1008357. [PMID: 33079933 PMCID: PMC7598928 DOI: 10.1371/journal.pcbi.1008357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 10/30/2020] [Accepted: 09/22/2020] [Indexed: 02/07/2023] Open
Abstract
Icosahedral viruses are under a micrometer in diameter, their infectious genome encapsulated by a shell assembled by a multiscale process, starting from an integer multiple of 60 viral capsid or coat protein (VP) monomers. We predict and validate inter-atomic hotspot interactions between VP monomers that are important for the assembly of 3 types of icosahedral viral capsids: Adeno Associated Virus serotype 2 (AAV2) and Minute Virus of Mice (MVM), both T = 1 single stranded DNA viruses, and Bromo Mosaic Virus (BMV), a T = 3 single stranded RNA virus. Experimental validation is by in-vitro, site-directed mutagenesis data found in literature. We combine ab-initio predictions at two scales: at the interface-scale, we predict the importance (cruciality) of an interaction for successful subassembly across each interface between symmetry-related VP monomers; and at the capsid-scale, we predict the cruciality of an interface for successful capsid assembly. At the interface-scale, we measure cruciality by changes in the capsid free-energy landscape partition function when an interaction is removed. The partition function computation uses atlases of interface subassembly landscapes, rapidly generated by a novel geometric method and curated opensource software EASAL (efficient atlasing and search of assembly landscapes). At the capsid-scale, cruciality of an interface for successful assembly of the capsid is based on combinatorial entropy. Our study goes all the way from resource-light, multiscale computational predictions of crucial hotspot inter-atomic interactions to validation using data on site-directed mutagenesis' effect on capsid assembly. By reliably and rapidly narrowing down target interactions, (no more than 1.5 hours per interface on a laptop with Intel Core i5-2500K @ 3.2 Ghz CPU and 8GB of RAM) our predictions can inform and reduce time-consuming in-vitro and in-vivo experiments, or more computationally intensive in-silico analyses.
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Affiliation(s)
- Ruijin Wu
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Rahul Prabhu
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Aysegul Ozkan
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Meera Sitharam
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America
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Caldararu O, Mehra R, Blundell TL, Kepp KP. Systematic Investigation of the Data Set Dependency of Protein Stability Predictors. J Chem Inf Model 2020; 60:4772-4784. [DOI: 10.1021/acs.jcim.0c00591] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Octav Caldararu
- DTU Chemistry, Technical University of Denmark, Building 206, 2800 Kgs. Lyngby, Denmark
| | - Rukmankesh Mehra
- DTU Chemistry, Technical University of Denmark, Building 206, 2800 Kgs. Lyngby, Denmark
| | - Tom L. Blundell
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, United Kingdom
| | - Kasper P. Kepp
- DTU Chemistry, Technical University of Denmark, Building 206, 2800 Kgs. Lyngby, Denmark
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48
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Wang B, Qi Y, Gao Y, Zhang JZH. A method for efficient calculation of thermal stability of proteins upon point mutations. Phys Chem Chem Phys 2020; 22:8461-8466. [PMID: 32281996 DOI: 10.1039/d0cp00835d] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
A method for efficient prediction of the relative stability of a protein due to a single amino acid point mutation is presented. In this approach, we calculate the free energy change due to an arbitrary point mutation of a protein from a single MD trajectory of the wild type protein. The method is tested on 27 diverse protein systems with a total of 853 mutations and the calculated relative free energies show a generally good correlation with the experimental values (a correlation coefficient of 0.63). Comparison with the free energy perturbation (FEP) method and the recently developed machine learning methods on two different benchmark data sets shows that the current method is computationally efficient and also numerically reliable for predicting the changes in thermostability upon an arbitrary point mutation of a protein. A discussion is provided on how to further improve the accuracy of the method for the prediction of thermostability of proteins.
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Affiliation(s)
- Bo Wang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - Yifei Qi
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China and NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.
| | - Ya Gao
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China and School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
| | - John Z H Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China and NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China. and Department of Chemistry, New York University, NY, NY 10003, USA and Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
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49
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Zaucha J, Heinzinger M, Kulandaisamy A, Kataka E, Salvádor ÓL, Popov P, Rost B, Gromiha MM, Zhorov BS, Frishman D. Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins. Brief Bioinform 2020; 22:5872174. [PMID: 32672331 DOI: 10.1093/bib/bbaa132] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 05/26/2020] [Accepted: 05/28/2020] [Indexed: 12/18/2022] Open
Abstract
Membrane proteins are unique in that they interact with lipid bilayers, making them indispensable for transporting molecules and relaying signals between and across cells. Due to the significance of the protein's functions, mutations often have profound effects on the fitness of the host. This is apparent both from experimental studies, which implicated numerous missense variants in diseases, as well as from evolutionary signals that allow elucidating the physicochemical constraints that intermembrane and aqueous environments bring. In this review, we report on the current state of knowledge acquired on missense variants (referred to as to single amino acid variants) affecting membrane proteins as well as the insights that can be extrapolated from data already available. This includes an overview of the annotations for membrane protein variants that have been collated within databases dedicated to the topic, bioinformatics approaches that leverage evolutionary information in order to shed light on previously uncharacterized membrane protein structures or interaction interfaces, tools for predicting the effects of mutations tailored specifically towards the characteristics of membrane proteins as well as two clinically relevant case studies explaining the implications of mutated membrane proteins in cancer and cardiomyopathy.
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Affiliation(s)
- Jan Zaucha
- Department of Bioinformatics of the TUM School of Life Sciences Weihenstephan in Freising, Germany
| | - Michael Heinzinger
- Department of Informatics, Bioinformatics and Computational Biology of the TUM Faculty of Informatics in Garching, Germany
| | - A Kulandaisamy
- Department of Biotechnology of the IIT Bhupat and Jyoti Mehta School of BioSciences in Madras, India
| | - Evans Kataka
- Department of Bioinformatics of the TUM School of Life Sciences Weihenstephan in Freising, Germany
| | - Óscar Llorian Salvádor
- Department of Informatics, Bioinformatics and Computational Biology of the TUM Faculty of Informatics in Garching, Germany
| | - Petr Popov
- Center for Computational and Data-Intensive Science and Engineering of the Skolkovo Institute of Science and Technology in Moscow, Russia
| | - Burkhard Rost
- Department of Informatics, Bioinformatics and Computational Biology at the TUM Faculty of Informatics in Garching, Germany
| | | | - Boris S Zhorov
- Department of Biochemistry and Biomedical Sciences, McMaster University in Hamilton, Canada
| | - Dmitrij Frishman
- Department of Bioinformatics at the TUM School of Life Sciences Weihenstephan in Freising, Germany
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Kucukkal TG, Amin RU. Computational and structural studies of MeCP2 and associated mutants. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 2020. [DOI: 10.1142/s0219633620410011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Rett Syndrome is a rare genetic disorder exclusively seen in girls. Approximately 95% of RTT cases is caused by mutations in the MeCP2 gene which codes for Methyl-CpG-binding protein 2 (MeCP2). In this review, first, a brief introductory review of Rett Syndrome, MeCP2 protein structure and function, mutation types and frequencies, and phenotype–genotype relationships were provided. After that, the current knowledge on the wild-type and mutant MeCP2 protein structure and dynamics as well as its binding to DNA is reviewed. The review particularly focuses on computational (such as molecular dynamics) and experimental (such as electrophoretic mobility shift assays) studies on the MeCP2 binding to different types of DNA as well as the computational and experimental (such as circular dichroism) studies on the stability changes upon mutations. In the end, a brief opinion on future outlook for further computational studies is provided.
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Affiliation(s)
- Tugba G. Kucukkal
- Department of Science, Technology and Mathematics, Gallaudet University, 800 Florida Ave NE, Washington, DC 20002, USA
- Quest Student Research Institute, 14153 Robert Paris Ct Chantilly, VA 20151, USA
| | - Rijul U. Amin
- Quest Student Research Institute, 14153 Robert Paris Ct Chantilly, VA 20151, USA
- Department of Biological Sciences, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA 15260, USA
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