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Alalmaie A, Khashan R. Mechanistic Insight Into the Conformational Changes of Cas8 Upon Binding to Different PAM Sequences in the Transposon-Encoded Type I-F CRISPR-Cas System. Proteins 2024. [PMID: 39171866 DOI: 10.1002/prot.26730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 07/02/2024] [Indexed: 08/23/2024]
Abstract
The INTEGRATE system is a gene-editing approach that offers advantages over the widely used CRISPR-Cas9 system. It does not introduce double strand breaks in the target DNA but rather integrates the desired DNA sequence directly into it. The first step in the integration process is PAM recognition, which is critical to understanding and optimizing the system. Experimental testing revealed varying integration efficiencies of different PAM mutants, and computational simulations were carried out to gain mechanistic insight into the conformational changes of Cas8 during PAM recognition. Our results showed that the interaction between Arg246 and guanine at position (-1) of the target strand is critical for PAM recognition. We found that unfavorable interactions in the 5'-AC-3' PAM mutant disrupted this interaction and may be responsible for its 0% integration efficiency. Additionally, we discovered that PAM sequences not only initiate the integration process but also regulate it through an allosteric mechanism that connects the N-terminal domain and the helical bundle of Cas8. This allosteric regulation was present in all PAMs tested, even those with lower integration efficiencies, such as 5'-TC-3' and 5'-AC-3'. We identified the Cas8 residues that are involved in this regulation. Our findings provide valuable insights into PAM recognition mechanisms in the INTEGRATE system and can help improve the gene-editing technology.
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Affiliation(s)
- Amnah Alalmaie
- Department of Pharmaceutics, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
- Department of Pharmaceutical Sciences, Philadelphia College of Pharmacy, Saint Joseph University, Philadelphia, PA, USA
| | - Raed Khashan
- Division of Pharmaceutical Sciences, Collage of Pharmacy, Long Island University, Brooklyn, New York, USA
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2
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Rubina, Moin ST, Haider S. Identification of a Cryptic Pocket in Methionine Aminopeptidase-II Using Adaptive Bandit Molecular Dynamics Simulations and Markov State Models. ACS OMEGA 2024; 9:28534-28545. [PMID: 38973915 PMCID: PMC11223136 DOI: 10.1021/acsomega.4c02516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 07/09/2024]
Abstract
Methionine aminopeptidase-II (MetAP-II) is a metalloprotease, primarily responsible for the cotranslational removal of the N-terminal initiator methionine from the nascent polypeptide chain during protein synthesis. MetAP-II has been implicated in angiogenesis and endothelial cell proliferation and is therefore considered a validated target for cancer therapeutics. However, there is no effective drug available against MetAP-II. In this study, we employ Adaptive Bandit molecular dynamics simulations to investigate the structural dynamics of the apo and ligand-bound MetAP-II. Our results focus on the dynamic behavior of the disordered loop that is not resolved in most of the crystal structures. Further analysis of the conformational flexibility of the disordered loop reveals a hidden cryptic pocket that is predicted to be potentially druggable. The network analysis indicates that the disordered loop region has a direct signaling route to the active site. These findings highlight a new way to target MetAP-II by designing inhibitors for the allosteric site within this disordered loop region.
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Affiliation(s)
- Rubina
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
| | - Syed Tarique Moin
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
| | - Shozeb Haider
- UCL
School of Pharmacy, University College London, London WC1N 1AX, U.K.
- UCL
Centre for Advanced Research Computing, University College London, London WC1H 9RN, U.K.
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3
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Zhang G, Zhang C, Cai M, Luo C, Zhu F, Liang Z. FuncPhos-STR: An integrated deep neural network for functional phosphosite prediction based on AlphaFold protein structure and dynamics. Int J Biol Macromol 2024; 266:131180. [PMID: 38552697 DOI: 10.1016/j.ijbiomac.2024.131180] [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: 12/21/2023] [Revised: 03/19/2024] [Accepted: 03/26/2024] [Indexed: 04/01/2024]
Abstract
Phosphorylation modifications play important regulatory roles in most biological processes. However, the functional assignment for the vast majority of the identified phosphosites remains a major challenge. Here, we provide a deep learning framework named FuncPhos-STR as an online resource, for functional prediction and structural visualization of human proteome-level phosphosites. Based on our reported FuncPhos-SEQ framework, which was built by integrating phosphosite sequence evolution and protein-protein interaction (PPI) information, FuncPhos-STR was developed by further integrating the structural and dynamics information on AlphaFold protein structures. The characterized structural topology and dynamics features underlying functional phosphosites emphasized their molecular mechanism for regulating protein functions. By integrating the structural and dynamics, sequence evolutionary, and PPI network features from protein different dimensions, FuncPhos-STR has advantage over other reported models, with the best AUC value of 0.855. Using FuncPhos-STR, the phosphosites inside the pocket regions are accessible to higher functional scores, theoretically supporting their potential regulatory mechanism. Overall, FuncPhos-STR would accelerate the functional identification of huge unexplored phosphosites, and facilitate the elucidation of their allosteric regulation mechanisms. The web server of FuncPhos-STR is freely available at http://funcptm.jysw.suda.edu.cn/str.
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Affiliation(s)
- Guangyu Zhang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Cai Zhang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Mingyue Cai
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Cheng Luo
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Fei Zhu
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
| | - Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou 215123, China.
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4
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Vankadari N, Ghosal D. Structural Insights into SARS-CoV-2 Nonstructural Protein 1 Interaction with Human Cyclophilin and FKBP1 to Regulate Interferon Production. J Phys Chem Lett 2024; 15:919-924. [PMID: 38241259 DOI: 10.1021/acs.jpclett.3c02959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 coronavirus and the perpetual rise of new variants warrant investigation of the molecular and structural details of the infection process and modulation of the host defense by viral proteins. This Letter reports the combined experimental and computational approaches to provide key insights into the structural and functional basis of Nsp1's association with different cyclophilins and FKBPs in regulating COVID-19 infection. We demonstrated the real-time stability and functional dynamics of the Nsp1-CypA/FKBP1A complex and investigated the repurposing of potential inhibitors that could block these interactions. Overall, we provided insights into the inhibitory role Nsp1 in downstream interferon production, a key aspect for host defense that prevents the SARS-CoV-2 or related family of corona virus infection.
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Affiliation(s)
- Naveen Vankadari
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC 3000, Australia
- ARC Centre for Cryo-electron Microscopy of Membrane Proteins, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, VIC 3000, Australia
| | - Debnath Ghosal
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, VIC 3000, Australia
- ARC Centre for Cryo-electron Microscopy of Membrane Proteins, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, VIC 3000, Australia
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5
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López-Luis MA, Soriano-Pérez EE, Parada-Fabián JC, Torres J, Maldonado-Rodríguez R, Méndez-Tenorio A. A Proposal for a Consolidated Structural Model of the CagY Protein of Helicobacter pylori. Int J Mol Sci 2023; 24:16781. [PMID: 38069104 PMCID: PMC10706595 DOI: 10.3390/ijms242316781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 11/17/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
CagY is the largest and most complex protein from Helicobacter pylori's (Hp) type IV secretion system (T4SS), playing a critical role in the modulation of gastric inflammation and risk for gastric cancer. CagY spans from the inner to the outer membrane, forming a channel through which Hp molecules are injected into human gastric cells. Yet, a tridimensional structure has been reported for only short segments of the protein. This intricate protein was modeled using different approaches, including homology modeling, ab initio, and deep learning techniques. The challengingly long middle repeat region (MRR) was modeled using deep learning and optimized using equilibrium molecular dynamics. The previously modeled segments were assembled into a 1595 aa chain and a 14-chain CagY multimer structure was assembled by structural alignment. The final structure correlated with published structures and allowed to show how the multimer may form the T4SS channel through which CagA and other molecules are translocated to gastric cells. The model confirmed that MRR, the most polymorphic and complex region of CagY, presents numerous cysteine residues forming disulfide bonds that stabilize the protein and suggest this domain may function as a contractile region playing an essential role in the modulating activity of CagY on tissue inflammation.
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Affiliation(s)
- Mario Angel López-Luis
- Laboratorio de Biotecnología y Bioinformática Genómica, Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Campus Lázaro Cárdenas, Mexico City 11340, Mexico; (M.A.L.-L.); (E.E.S.-P.); (J.C.P.-F.); (R.M.-R.)
| | - Eva Elda Soriano-Pérez
- Laboratorio de Biotecnología y Bioinformática Genómica, Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Campus Lázaro Cárdenas, Mexico City 11340, Mexico; (M.A.L.-L.); (E.E.S.-P.); (J.C.P.-F.); (R.M.-R.)
| | - José Carlos Parada-Fabián
- Laboratorio de Biotecnología y Bioinformática Genómica, Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Campus Lázaro Cárdenas, Mexico City 11340, Mexico; (M.A.L.-L.); (E.E.S.-P.); (J.C.P.-F.); (R.M.-R.)
| | - Javier Torres
- Unidad de Investigación en Enfermedades Infecciosas, UMAE Pediatría, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico;
| | - Rogelio Maldonado-Rodríguez
- Laboratorio de Biotecnología y Bioinformática Genómica, Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Campus Lázaro Cárdenas, Mexico City 11340, Mexico; (M.A.L.-L.); (E.E.S.-P.); (J.C.P.-F.); (R.M.-R.)
| | - Alfonso Méndez-Tenorio
- Laboratorio de Biotecnología y Bioinformática Genómica, Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Campus Lázaro Cárdenas, Mexico City 11340, Mexico; (M.A.L.-L.); (E.E.S.-P.); (J.C.P.-F.); (R.M.-R.)
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6
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Krieger JM, Sorzano COS, Carazo JM. Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing. Int J Mol Sci 2023; 24:14245. [PMID: 37762547 PMCID: PMC10532346 DOI: 10.3390/ijms241814245] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/10/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.
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Affiliation(s)
- James M. Krieger
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
| | | | - Jose Maria Carazo
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
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7
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Talukder A, Rahman MM, Masum MHU. Biocomputational characterisation of MBO_200107 protein of Mycobacterium tuberculosis variant caprae: a molecular docking and simulation study. J Biomol Struct Dyn 2023; 41:7204-7223. [PMID: 36039775 DOI: 10.1080/07391102.2022.2118167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/23/2022] [Indexed: 10/14/2022]
Abstract
The principal objective of this study was to delineate the potentiality of the MBO_200107 protein from the Mycobacterium tuberculosis variant caprae in cancer research. It is a cytoplasmic protein, comprised of a 354-long amino acid chain, alkaline, had a molecular weight of 39089.37 Da, an isoelectric point of 9.62 and a grand average of hydropathicity of -0.345. One of the functional domains was predicted as Gammaglutamylcyclotransferase (GGCT). Among tertiary structures, the Modeller and Phyre2 model satisfied all the quality parameters, though they are truncated; contrarily, the I-TASSER model is full length and contains the sequence for the GGCT domain, though it did not meet all the quality parameters. It also has significant sequence similarities (47.5% by EMBOSS Water and 72.4% by EMBOSS Matcher) with a human GGCT, and the conserved sequences are confined to the GGCT domain of the MBO_200107. According to molecular docking analyses, the protein has a binding affinity of -4.8 kcal/mol by Autodock Vina and -56.465 kcal/mol by HPEPDOCK to the human glutathione (GSH), an essential metabolite for GGCT metabolism. The Molecular dynamic simulation of the docked complex showed the binding efficiency of the GSH to MBO_200107 with a minimal structural alteration. The in silico findings mentioned above revealed that the protein could be used as a supplementary tool in cancer research, such as designing vaccines or drugs where the role of GGCT has been implicated. Further, we recommend fully characterising the protein and conducting essential in vitro and in vivo experiments to determine its detailed usefulness.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Asma Talukder
- Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh
- Microbiology, Cancer and Bioinformatics Research Group, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Md Mijanur Rahman
- Microbiology, Cancer and Bioinformatics Research Group, Noakhali Science and Technology University, Noakhali, Bangladesh
- Department of Microbiology, Noakhali Science and Technology University, Noakhali, Bangladesh
- Menzies Health Institute Queensland, School of Pharmacy and Medical Sciences, Griffith University, Southport, Australia
| | - Md Habib Ullah Masum
- Microbiology, Cancer and Bioinformatics Research Group, Noakhali Science and Technology University, Noakhali, Bangladesh
- Department of Microbiology, Noakhali Science and Technology University, Noakhali, Bangladesh
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8
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Chakraborty C, Bhattacharya M, Saha A, Alshammari A, Alharbi M, Saikumar G, Pal S, Dhama K, Lee SS. Revealing the structural and molecular interaction landscape of the favipiravir-RTP and SARS-CoV-2 RdRp complex through integrative bioinformatics: Insights for developing potent drugs targeting SARS-CoV-2 and other viruses. J Infect Public Health 2023; 16:1048-1056. [PMID: 37196368 DOI: 10.1016/j.jiph.2023.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/04/2023] [Accepted: 05/08/2023] [Indexed: 05/19/2023] Open
Abstract
BACKGROUND The global research community has made considerable progress in therapeutic and vaccine research during the COVID-19 pandemic. Several therapeutics have been repurposed for the treatment of COVID-19. One such compound is, favipiravir, which was approved for the treatment of influenza viruses, including drug-resistant influenza. Despite the limited information on its molecular activity, clinical trials have attempted to determine the effectiveness of favipiravir in patients with mild to moderate COVID-19. Here, we report the structural and molecular interaction landscape of the macromolecular complex of favipiravir-RTP and SARS-CoV-2 RdRp with the RNA chain. METHODS Integrative bioinformatics was used to reveal the structural and molecular interaction landscapes of two macromolecular complexes retrieved from RCSB PDB. RESULTS We analyzed the interactive residues, H-bonds, and interaction interfaces to evaluate the structural and molecular interaction landscapes of the two macromolecular complexes. We found seven and six H-bonds in the first and second interaction landscapes, respectively. The maximum bond length is 3.79 Å. In the hydrophobic interactions, five residues (Asp618, Asp760, Thr687, Asp623, and Val557) were associated with the first complex and two residues (Lys73 and Tyr217) were associated with the second complex. The mobilities, collective motion, and B-factor of the two macromolecular complexes were analyzed. Finally, we developed different models, including trees, clusters, and heat maps of antiviral molecules, to evaluate the therapeutic status of favipiravir as an antiviral drug. CONCLUSIONS The results revealed the structural and molecular interaction landscape of the binding mode of favipiravir with the nsp7-nsp8-nsp12-RNA SARS-CoV-2 RdRp complex. Our findings can help future researchers in understanding the mechanism underlying viral action and guide the design of nucleotide analogs that mimic favipiravir and exhibit greater potency as antiviral drugs against SARS-CoV-2 and other infectious viruses. Thus, our work can help in preparing for future epidemics and pandemics.
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Affiliation(s)
- Chiranjib Chakraborty
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126, India.
| | - Manojit Bhattacharya
- Department of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore 756020, Odisha, India
| | - Abinit Saha
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126, India
| | - Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Post Box 2455, Riyadh 11451, Saudi Arabia
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Post Box 2455, Riyadh 11451, Saudi Arabia
| | - G Saikumar
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
| | - Soumen Pal
- School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
| | - Sang-Soo Lee
- Institute for Skeletal Aging & Orthopaedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon-si 24252, Gangwon-do, Republic of Korea
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9
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Vilardaga JP, Clark LJ, White AD, Sutkeviciute I, Lee JY, Bahar I. Molecular Mechanisms of PTH/PTHrP Class B GPCR Signaling and Pharmacological Implications. Endocr Rev 2023; 44:474-491. [PMID: 36503956 PMCID: PMC10461325 DOI: 10.1210/endrev/bnac032] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 11/14/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022]
Abstract
The classical paradigm of G protein-coupled receptor (GPCR) signaling via G proteins is grounded in a view that downstream responses are relatively transient and confined to the cell surface, but this notion has been revised in recent years following the identification of several receptors that engage in sustained signaling responses from subcellular compartments following internalization of the ligand-receptor complex. This phenomenon was initially discovered for the parathyroid hormone (PTH) type 1 receptor (PTH1R), a vital GPCR for maintaining normal calcium and phosphate levels in the body with the paradoxical ability to build or break down bone in response to PTH binding. The diverse biological processes regulated by this receptor are thought to depend on its capacity to mediate diverse modes of cyclic adenosine monophosphate (cAMP) signaling. These include transient signaling at the plasma membrane and sustained signaling from internalized PTH1R within early endosomes mediated by PTH. Here we discuss recent structural, cell signaling, and in vivo studies that unveil potential pharmacological outputs of the spatial versus temporal dimension of PTH1R signaling via cAMP. Notably, the combination of molecular dynamics simulations and elastic network model-based methods revealed how precise modulation of PTH signaling responses is achieved through structure-encoded allosteric coupling within the receptor and between the peptide hormone binding site and the G protein coupling interface. The implications of recent findings are now being explored for addressing key questions on how location bias in receptor signaling contributes to pharmacological functions, and how to drug a difficult target such as the PTH1R toward discovering nonpeptidic small molecule candidates for the treatment of metabolic bone and mineral diseases.
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Affiliation(s)
- Jean-Pierre Vilardaga
- Laboratory for GPCR Biology, Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Lisa J Clark
- Laboratory for GPCR Biology, Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Alex D White
- Laboratory for GPCR Biology, Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ieva Sutkeviciute
- Laboratory for GPCR Biology, Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ji Young Lee
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
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10
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Banerjee A, Bahar I. Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions. Int J Mol Sci 2023; 24:8450. [PMID: 37176156 PMCID: PMC10179678 DOI: 10.3390/ijms24098450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/01/2023] [Accepted: 05/06/2023] [Indexed: 05/15/2023] Open
Abstract
The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.
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Affiliation(s)
- Anupam Banerjee
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Ivet Bahar
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY 11794, USA
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11
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Taylor MK, Williams EP, Xue Y, Jenjaroenpun P, Wongsurawat T, Smith AP, Smith AM, Parvathareddy J, Kong Y, Vogel P, Cao X, Reichard W, Spruill-Harrell B, Samarasinghe AE, Nookaew I, Fitzpatrick EA, Smith MD, Aranha M, Smith JC, Jonsson CB. Dissecting Phenotype from Genotype with Clinical Isolates of SARS-CoV-2 First Wave Variants. Viruses 2023; 15:611. [PMID: 36992320 PMCID: PMC10059853 DOI: 10.3390/v15030611] [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: 01/12/2023] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 02/25/2023] Open
Abstract
The emergence and availability of closely related clinical isolates of SARS-CoV-2 offers a unique opportunity to identify novel nonsynonymous mutations that may impact phenotype. Global sequencing efforts show that SARS-CoV-2 variants have emerged and then been replaced since the beginning of the pandemic, yet we have limited information regarding the breadth of variant-specific host responses. Using primary cell cultures and the K18-hACE2 mouse, we investigated the replication, innate immune response, and pathology of closely related, clinical variants circulating during the first wave of the pandemic. Mathematical modeling of the lung viral replication of four clinical isolates showed a dichotomy between two B.1. isolates with significantly faster and slower infected cell clearance rates, respectively. While isolates induced several common immune host responses to infection, one B.1 isolate was unique in the promotion of eosinophil-associated proteins IL-5 and CCL11. Moreover, its mortality rate was significantly slower. Lung microscopic histopathology suggested further phenotypic divergence among the five isolates showing three distinct sets of phenotypes: (i) consolidation, alveolar hemorrhage, and inflammation, (ii) interstitial inflammation/septal thickening and peribronchiolar/perivascular lymphoid cells, and (iii) consolidation, alveolar involvement, and endothelial hypertrophy/margination. Together these findings show divergence in the phenotypic outcomes of these clinical isolates and reveal the potential importance of nonsynonymous mutations in nsp2 and ORF8.
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Affiliation(s)
- Mariah K. Taylor
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Evan P. Williams
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Yi Xue
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Piroon Jenjaroenpun
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Thidathip Wongsurawat
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Amanda P. Smith
- Department of Pediatrics, The University of Tennessee Health Science Center, Memphis, TN 38103, USA
| | - Amber M. Smith
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Department of Pediatrics, The University of Tennessee Health Science Center, Memphis, TN 38103, USA
- Institute for the Study of Host-Pathogen Systems, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Jyothi Parvathareddy
- Regional Biocontainment Laboratory, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Ying Kong
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Peter Vogel
- Veterinary Pathology Core Laboratory, St Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xueyuan Cao
- Department of Health Promotion and Disease Prevention, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Walter Reichard
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Briana Spruill-Harrell
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Amali E. Samarasinghe
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Department of Pediatrics, The University of Tennessee Health Science Center, Memphis, TN 38103, USA
| | - Intawat Nookaew
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Elizabeth A. Fitzpatrick
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Institute for the Study of Host-Pathogen Systems, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Micholas Dean Smith
- Center for Molecular Biophysics, University of Tennessee-Oak Ridge National Laboratory, Knoxville, TN 37996, USA
- Department of Biochemistry and Cellular and Molecular Biology, The University of Tennessee- Knoxville, Knoxville, TN 37996, USA
| | - Michelle Aranha
- Department of Biochemistry and Cellular and Molecular Biology, The University of Tennessee- Knoxville, Knoxville, TN 37996, USA
| | - Jeremy C. Smith
- Center for Molecular Biophysics, University of Tennessee-Oak Ridge National Laboratory, Knoxville, TN 37996, USA
- Department of Biochemistry and Cellular and Molecular Biology, The University of Tennessee- Knoxville, Knoxville, TN 37996, USA
| | - Colleen B. Jonsson
- Department of Microbiology, Immunology and Biochemistry, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Institute for the Study of Host-Pathogen Systems, University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Regional Biocontainment Laboratory, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
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12
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Banerjee A, Saha S, Tvedt NC, Yang LW, Bahar I. Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods. Curr Opin Struct Biol 2023; 78:102517. [PMID: 36587424 PMCID: PMC10038760 DOI: 10.1016/j.sbi.2022.102517] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/19/2022] [Accepted: 11/22/2022] [Indexed: 12/31/2022]
Abstract
Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.
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Affiliation(s)
- Anupam Banerjee
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Satyaki Saha
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Nathan C Tvedt
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA; Computational and Applied Mathematics and Statistics, The College of William and Mary, Williamsburg, VA 23185, USA
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, and PhD Program in Biomedical Artificial Intelligence, National Tsing Hua University, Hsinchu 300044, Taiwan; Physics Division, National Center for Theoretical Sciences, Taipei 106319, Taiwan
| | - Ivet Bahar
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA.
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13
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Insight into free energy and dynamic cross-correlations of residue for binding affinity of antibody and receptor binding domain SARS-CoV-2. Heliyon 2023; 9:e12667. [PMID: 36618128 PMCID: PMC9809146 DOI: 10.1016/j.heliyon.2022.e12667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 11/12/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023] Open
Abstract
SARS-CoV-2 virus continues to evolve and mutate causing most of the mutated variants resist to many of the therapeutic monoclonal antibodies (mAbs). Despite several mAbs retained neutralizing capability for Omicron BA.1 and BA.2, reduction in neutralization potency was reported. Hence, effort of searching for mAb that is broader in neutralization breadth without losing the neutralizing ability is continued. MW06 was reported with capability in neutralizing most of the variants of concern (VOC) and it binds to the conserved region (left flank) near epitope mAb sotrovimab (S309). In this study, binding affinity of mAb MW06 and its cocktail formulation with MW05 for receptor binding domain (RBD) SARS-CoV-2 virus was investigated under molecular dynamics simulations (MDs). Binding free energies computed by Molecular Mechanics Generalised Born Surface Area (MM-GBSA) algorithm predicted the binding affinity of MW06 for RBD BA.1 (-53 kcal/mol) as strong as RBD wildtype (-58 kcal/mol) while deterioration was observed for RBD BA.2 (-43 kcal/mol). Alike S309 and MW06, simulated cocktail mAb (MW05 and MW06)-RBD interactions suggested the neutralizing capability of the cocktail formulation for RBD BA.1 and BA.2 reduced. Meanwhile, residue pairs that favour the communication between the mAb and RBD have been identified by decomposing the free energy per pairwise residue basis. Apart from understanding the effects of mutation occurred in the RBD region on human angiotensin-converting enzyme 2 (hACE2) binding, impact of heavily mutated RBD on mAb-RBD interactions was investigated in this study as well. In addition to energetic profile obtained from MDs, plotting the dynamics cross-correlation map of the mAb-RBD complex under elastic network model (ENM) was aimed to understand the cross-correlations between residue fluctuations. It allows simple and rapid analysis on the motions or dynamics of the protein residues of mAbs and RBD in complex. Protein residues having correlated motions are normally part of the structural domains of the protein and their respective motions and protein function are related. Motion of mutated RBD residues and mAb residues was less correlated while their respective interactions energy computed to be higher. The combined techniques of MDs and ENM offered simplicity in understanding dynamics and energy contribution that explain binding affinity of mAb-RBD complexes.
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14
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Chakraborty C, Bhattacharya M, Chatterjee S, Sharma AR, Saha RP, Dhama K, Agoramoorthy G. Integrative Bioinformatics Approaches Indicate a Particular Pattern of Some SARS-CoV-2 and Non-SARS-CoV-2 Proteins. Vaccines (Basel) 2022; 11:vaccines11010038. [PMID: 36679883 PMCID: PMC9864461 DOI: 10.3390/vaccines11010038] [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: 11/08/2022] [Revised: 12/12/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
Pattern recognition plays a critical role in integrative bioinformatics to determine the structural patterns of proteins of viruses such as SARS-CoV-2. This study identifies the pattern of SARS-CoV-2 proteins to depict the structure-function relationships of the protein alphabets of SARS-CoV-2 and COVID-19. The assembly enumeration algorithm, Anisotropic Network Model, Gaussian Network Model, Markovian Stochastic Model, and image comparison protein-like alphabets were used. The distance score was the lowest with 22 for "I" and highest with 40 for "9". For post-processing and decision, two protein alphabets "C" (PDB ID: 6XC3) and "S" (PDB ID: 7OYG) were evaluated to understand the structural, functional, and evolutionary relationships, and we found uniqueness in the functionality of proteins. Here, models were constructed using "SARS-CoV-2 proteins" (12 numbers) and "non-SARS-CoV-2 proteins" (14 numbers) to create two words, "SARS-CoV-2" and "COVID-19". Similarly, we developed two slogans: "Vaccinate the world against COVID-19" and "Say no to SARS-CoV-2", which were made with the proteins structure. It might generate vaccine-related interest to broad reader categories. Finally, the evolutionary process appears to enhance the protein structure smoothly to provide suitable functionality shaped by natural selection.
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Affiliation(s)
- Chiranjib Chakraborty
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata 700126, West Bengal, India
- Correspondence:
| | - Manojit Bhattacharya
- Department of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore 756020, Odisha, India
| | - Srijan Chatterjee
- Institute for Skeletal Aging and Orthopaedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon-si 24252, Gangwon-do, Republic of Korea
| | - Ashish Ranjan Sharma
- Institute for Skeletal Aging and Orthopaedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon-si 24252, Gangwon-do, Republic of Korea
| | - Rudra P. Saha
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata 700126, West Bengal, India
| | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
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15
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Verkhivker GM, Agajanian S, Oztas D, Gupta G. Computational analysis of protein stability and allosteric interaction networks in distinct conformational forms of the SARS-CoV-2 spike D614G mutant: reconciling functional mechanisms through allosteric model of spike regulation. J Biomol Struct Dyn 2022; 40:9724-9741. [PMID: 34060425 DOI: 10.1080/07391102.2021.1933594] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By combining functional dynamics analysis and ensemble-based alanine scanning of the SARS-CoV-2 spike proteins we found that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. Our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of allosteric communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Gennady M Verkhivker
- Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, CA, USA.,Depatment of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, USA
| | - Steve Agajanian
- Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, CA, USA
| | - Deniz Oztas
- Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, CA, USA
| | - Grace Gupta
- Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, CA, USA
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16
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Pantaleão SQ, Camillo LDMB, Neves TC, Menezes IDG, Stangherlin LM, Batista HBDCR, Poole E, Nevels M, Philot EA, Scott AL, Carlan da Silva MC. Molecular modelling of the HCMV IL-10 protein isoforms and analysis of their interaction with the human IL-10 receptor. PLoS One 2022; 17:e0277953. [PMID: 36441804 PMCID: PMC9704672 DOI: 10.1371/journal.pone.0277953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 11/07/2022] [Indexed: 11/29/2022] Open
Abstract
The human cytomegalovirus (HCMV) UL111A gene encodes several homologs of the cellular interleukin 10 (cIL-10). Alternative splicing in the UL111A region produces two relatively well-characterized transcripts designated cmvIL-10 (isoform A) and LAcmvIL-10 (isoform B). The cmvIL-10 protein is the best characterized, both structurally and functionally, and has many immunosuppressive activities similar to cIL-10, while LAcmvIL-10 has more restricted biological activities. Alternative splicing also results in five less studied UL111A transcripts encoding additional proteins homologous to cIL-10 (isoforms C to G). These transcripts were identified during productive HCMV infection of MRC-5 cells with the high passage laboratory adapted AD169 strain, and the structure and properties of the corresponding proteins are largely unknown. Moreover, it is unclear whether these protein isoforms are able to bind the cellular IL-10 receptor and induce signalling. In the present study, we investigated the expression spectrum of UL111A transcripts in fully permissive MRC-5 cells and semi permissive U251 cells infected with the low passage HCMV strain TB40E. We identified a new spliced transcript (H) expressed during productive infection. Using computational methods, we carried out molecular modelling studies on the three-dimensional structures of the HCMV IL-10 proteins encoded by the transcripts detected in our work (cmvIL-10 (A), LAcmvIL-10 (B), E, F and H) and on their interaction with the human IL-10 receptor (IL-10R1). The modelling predicts clear differences between the isoform structures. Furthermore, the in silico simulations (molecular dynamics simulation and normal-mode analyses) allowed us to evaluate regions that contain potential receptor binding sites in each isoform. The analyses demonstrate that the complexes between the isoforms and IL-10R1 present different types of molecular interactions and consequently different affinities and stabilities. The knowledge about structure and expression of specific viral IL-10 isoforms has implications for understanding of their properties and role in HCMV immune evasion and pathogenesis.
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Affiliation(s)
| | | | - Tainan Cerqueira Neves
- Center for Natural and Humanities Sciences, Federal University of ABC, São Bernardo do Campo, Brazil
| | - Isabela de Godoy Menezes
- Center for Natural and Humanities Sciences, Federal University of ABC, São Bernardo do Campo, Brazil
| | - Lucas Matheus Stangherlin
- Center for Natural and Humanities Sciences, Federal University of ABC, São Bernardo do Campo, Brazil
| | | | - Emma Poole
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Michael Nevels
- School of Biology, University of St Andrews, St Andrews, United Kingdom
| | - Eric Alisson Philot
- Center for Mathematics, Computing and Cognition, Federal University of ABC, Santo André, Brazil
| | - Ana Ligia Scott
- Center for Mathematics, Computing and Cognition, Federal University of ABC, Santo André, Brazil
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17
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Leander M, Liu Z, Cui Q, Raman S. Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins. eLife 2022; 11:e79932. [PMID: 36226916 PMCID: PMC9662819 DOI: 10.7554/elife.79932] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 10/13/2022] [Indexed: 01/29/2023] Open
Abstract
A fundamental question in protein science is where allosteric hotspots - residues critical for allosteric signaling - are located, and what properties differentiate them. We carried out deep mutational scanning (DMS) of four homologous bacterial allosteric transcription factors (aTFs) to identify hotspots and built a machine learning model with this data to glean the structural and molecular properties of allosteric hotspots. We found hotspots to be distributed protein-wide rather than being restricted to 'pathways' linking allosteric and active sites as is commonly assumed. Despite structural homology, the location of hotspots was not superimposable across the aTFs. However, common signatures emerged when comparing hotspots coincident with long-range interactions, suggesting that the allosteric mechanism is conserved among the homologs despite differences in molecular details. Machine learning with our large DMS datasets revealed global structural and dynamic properties to be a strong predictor of whether a residue is a hotspot than local and physicochemical properties. Furthermore, a model trained on one protein can predict hotspots in a homolog. In summary, the overall allosteric mechanism is embedded in the structural fold of the aTF family, but the finer, molecular details are sequence-specific.
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Affiliation(s)
- Megan Leander
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Zhuang Liu
- Department of Physics, Boston UniversityBostonUnited States
| | - Qiang Cui
- Department of Physics, Boston UniversityBostonUnited States
- Department of Chemistry, Boston UniversityBostonUnited States
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
- Department of Bacteriology, University of Wisconsin-MadisonMadisonUnited States
- Department of Chemical and Biological Engineering, University of Wisconsin-MadisonMadisonUnited States
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18
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Bozelli JC, Yune J, Aulakh SS, Cao Z, Fernandes A, Seitova A, Tong Y, Schreier S, Epand RM. Human Diacylglycerol Kinase ε N-Terminal Segment Regulates the Phosphatidylinositol Cycle, Controlling the Rate but Not the Acyl Chain Composition of Its Lipid Intermediates. ACS Chem Biol 2022; 17:2495-2506. [PMID: 35767833 DOI: 10.1021/acschembio.2c00387] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Diacylglycerol kinase ε (DGKε), an enzyme of the phosphatidylinositol (PI) cycle, bears a highly conserved hydrophobic N-terminal segment, which was proposed to anchor the enzyme into the membrane. However, the importance of this segment to the DGKε function remains to be determined. To address this question, it is here reported an in silico and in vitro combined research strategy. Capitalizing on the AlphaFold 2.0 predicted structure of human DGKε, it is shown that its hydrophobic N-terminal segment anchors it into the membrane via a transmembrane α-helix. Coarse-grained based elastic network model studies showed that a conformational change in the hydrophobic N-terminal segment determines the proximity between the active site of DGKε and the membrane-water interface, likely regulating its kinase activity. In vitro studies with a purified DGKε construct lacking the hydrophobic N-terminal segment (His-SUMO*-Δ50-DGKε) corroborated the role of the N-terminus in regulating DGKε enzymatic properties. The comparison between the enzymatic properties of DGKε and His-SUMO*-Δ50-DGKε showed that the conserved N-terminal segment markedly inhibits the enzyme activity and its sensitivity to membrane intrinsic negative curvature, while also playing a role in the modulation of the enzyme by phosphatidylserine. On the other hand, this segment did not strongly affect its diacylglycerol acyl chain specificity, the modulation of the enzyme by membrane morphological changes, or the activation by phosphatidic acid-rich lipid domains. Hence, these results suggest that the conservation of the hydrophobic N-terminal segment of DGKε throughout evolution guaranteed not only membrane anchorage but also an efficient and elegant manner to regulate the rate of the PI cycle.
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Affiliation(s)
- José Carlos Bozelli
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
| | - Jenny Yune
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
| | - Sukhvershjit S Aulakh
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
| | - Zihao Cao
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
| | - Alexia Fernandes
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
| | - Alma Seitova
- Structural Genomics Consortium, University of Toronto, Toronto, ON N5G 1L7, Canada
| | - Yufeng Tong
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada
| | - Shirley Schreier
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo 05508-000, Brazil
| | - Richard M Epand
- Department of Biochemistry and Biomedical Sciences, McMaster University, Health Sciences Centre, Hamilton, ON L8S 3L8, Canada
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19
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Wingert B, Doruker P, Bahar I. Activation and Speciation Mechanisms in Class A GPCRs. J Mol Biol 2022; 434:167690. [PMID: 35728652 PMCID: PMC10129049 DOI: 10.1016/j.jmb.2022.167690] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 01/03/2023]
Abstract
Accurate development of allosteric modulators of GPCRs require a thorough assessment of their sequence, structure, and dynamics, toward gaining insights into their mechanisms of actions shared by family members, as well as dynamic features that distinguish subfamilies. Building on recent progress in the characterization of the signature dynamics of proteins, we analyzed here a dataset of 160 Class A GPCRs to determine their sequence similarities, structural landscape, and dynamic features across different species (human, bovine, mouse, squid, and rat), different activation states (active/inactive), and different subfamilies. The two dominant directions of variability across experimentally resolved structures, identified by principal component analysis of the dataset, shed light to cooperative mechanisms of activation, subfamily differentiation, and speciation of Class A GPCRs. The analysis reveals the functional significance of the conformational flexibilities of specific structural elements, including: the dominant role of the intracellular loop 3 (ICL3) together with the cytoplasmic ends of the adjoining helices TM5 and TM6 in enabling allosteric activation; the role of particular structural motifs at the extracellular loop 2 (ECL2) connecting TM4 and TM5 in binding ligands specific to different subfamilies; or even the differentiation of the N-terminal conformation across different species. Detailed analyses of the modes of motions accessible to the members of the dataset and their variations across members demonstrate how the active and inactive states of GPCRs obey distinct conformational dynamics. The collective fluctuations of the GPCRs are robustly defined in the active state, while the inactive conformers exhibit broad variance among members.
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Affiliation(s)
- Bentley Wingert
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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20
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Yu CC, Raj N, Chu JW. Edge weights in a protein elastic network reorganize collective motions and render long-range sensitivity responses. J Chem Phys 2022; 156:245105. [DOI: 10.1063/5.0095107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The effects of inter-residue interactions on protein collective motions are analyzed by comparing two elastic network models (ENM)—structural contact ENM (SC-ENM) and molecular dynamics (MD)-ENM—with the edge weights computed from an all-atom MD trajectory by structure-mechanics statistical learning. A theoretical framework is devised to decompose the eigenvalues of ENM Hessian into contributions from individual springs and to compute the sensitivities of positional fluctuations and covariances to spring constant variation. Our linear perturbation approach quantifies the response mechanisms as softness modulation and orientation shift. All contacts of C α positions in SC-ENM have an identical spring constant by fitting the profile of root-of-mean-squared-fluctuation calculated from an all-atom MD simulation, and the same trajectory data are also used to compute the specific spring constant of each contact as an MD-ENM edge weight. We illustrate that the soft-mode reorganization can be understood in terms of gaining weights along the structural contacts of low elastic strengths and loosing magnitude along those of high rigidities. With the diverse mechanical strengths encoded in protein dynamics, MD-ENM is found to have more pronounced long-range couplings and sensitivity responses with orientation shift identified as a key player in driving the specific residues to have high sensitivities. Furthermore, the responses of perturbing the springs of different residues are found to have asymmetry in the action–reaction relationship. In understanding the mutation effects on protein functional properties, such as long-range communications, our results point in the directions of collective motions as a major effector.
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Affiliation(s)
- Chieh Cheng Yu
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, 75 Bo-Ai Street, Hsinchu 30010, Taiwan
| | - Nixon Raj
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, 75 Bo-Ai Street, Hsinchu 30010, Taiwan
| | - Jhih-Wei Chu
- Institute of Bioinformatics and Systems Biology, Department of Biological Science and Technology, Institute of Molecular Medicine and Bioengineering, Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
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21
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Castillo F, Corbi-Verge C, Murciano-Calles J, Candel AM, Han Z, Iglesias-Bexiga M, Ruiz-Sanz J, Kim PM, Harty RN, Martinez JC, Luque I. Phage display identification of nanomolar ligands for human NEDD4-WW3: Energetic and dynamic implications for the development of broad-spectrum antivirals. Int J Biol Macromol 2022; 207:308-323. [PMID: 35257734 DOI: 10.1016/j.ijbiomac.2022.03.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 11/29/2022]
Abstract
The recognition of PPxY viral Late domains by the third WW domain of the human HECT-E3 ubiquitin ligase NEDD4 (NEDD4-WW3) is essential for the budding of many viruses. Blocking these interactions is a promising strategy to develop broad-spectrum antivirals. As all WW domains, NEDD4-WW3 is a challenging therapeutic target due to the low binding affinity of its natural interactions, its high conformational plasticity, and its complex thermodynamic behavior. In this work, we set out to investigate whether high affinity can be achieved for monovalent ligands binding to the isolated NEDD4-WW3 domain. We show that a competitive phage-display set-up allows for the identification of high-affinity peptides showing inhibitory activity of viral budding. A detailed biophysical study combining calorimetry, nuclear magnetic resonance, and molecular dynamic simulations reveals that the improvement in binding affinity does not arise from the establishment of new interactions with the domain, but is associated to conformational restrictions imposed by a novel C-terminal -LFP motif in the ligand, unprecedented in the PPxY interactome. These results, which highlight the complexity of WW domain interactions, provide valuable insight into the key elements for high binding affinity, of interest to guide virtual screening campaigns for the identification of novel therapeutics targeting NEDD4-WW3 interactions.
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Affiliation(s)
- Francisco Castillo
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Carles Corbi-Verge
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain; Donnelly Centre for Cellular and Biomolecular Research, Department of Molecular Genetics & Department of Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Javier Murciano-Calles
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Adela M Candel
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Ziying Han
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, 3800 Spruce St., Philadelphia, PA 19104, USA
| | - Manuel Iglesias-Bexiga
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Javier Ruiz-Sanz
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Philip M Kim
- Donnelly Centre for Cellular and Biomolecular Research, Department of Molecular Genetics & Department of Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Ronald N Harty
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, 3800 Spruce St., Philadelphia, PA 19104, USA
| | - Jose C Martinez
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain
| | - Irene Luque
- Department of Physical Chemistry, Institute of Biotechnology and Excelence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n 18071, Granada, Spain.
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22
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Elastic network modeling of cellular networks unveils sensor and effector genes that control information flow. PLoS Comput Biol 2022; 18:e1010181. [PMID: 35639793 PMCID: PMC9216591 DOI: 10.1371/journal.pcbi.1010181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 06/22/2022] [Accepted: 05/07/2022] [Indexed: 12/03/2022] Open
Abstract
The high-level organization of the cell is embedded in indirect relationships that connect distinct cellular processes. Existing computational approaches for detecting indirect relationships between genes typically consist of propagating abstract information through network representations of the cell. However, the selection of genes to serve as the source of propagation is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of the high-level organization of the cell by identifying the genes that propagate and receive information most effectively in the cell, and the indirect relationships between these genes. To this aim, we adapted a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic interaction profile similarity network. This network revealed a superior propensity for information propagation relative to simulated networks with similar topology. Perturbation-response scanning identified the major distributors and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters and contained genes with previously characterized involvement in signal transduction. We propose that indirect relationships between effector and sensor clusters represent major paths of information flow between distinct cellular processes. Genetic similarity networks for fission yeast and human displayed similarly strong propensities for information propagation and clusters of effector and sensor genes, suggesting that the global architecture enabling indirect relationships is evolutionarily conserved across species. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization and cooperativity in the cell.
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23
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Verkhivker GM, Agajanian S, Kassab R, Krishnan K. Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants. J Chem Inf Model 2022; 62:1956-1978. [PMID: 35377633 DOI: 10.1021/acs.jcim.2c00124] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.
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Affiliation(s)
- Gennady M Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States.,Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
| | - Steve Agajanian
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Ryan Kassab
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Keerthi Krishnan
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
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24
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Krieger JM, Sorzano COS, Carazo JM, Bahar I. Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0. Acta Crystallogr D Struct Biol 2022; 78:399-409. [PMID: 35362464 PMCID: PMC8972803 DOI: 10.1107/s2059798322001966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/18/2022] [Indexed: 11/24/2022] Open
Abstract
Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.
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Affiliation(s)
- James Michael Krieger
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Carlos Oscar S. Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Jose Maria Carazo
- Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Calle Darwin 3, 28049 Madrid, Spain
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213, USA
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25
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Zimmermann MT. Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research. Compr Physiol 2022; 12:3141-3166. [PMID: 35578963 DOI: 10.1002/cphy.c190047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.
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Affiliation(s)
- Michael T Zimmermann
- Bioinformatics Research and Development Laboratory, Genomic Sciences and Precision Medicine Center, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.,Clinical and Translational Sciences Institute, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.,Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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26
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Gaubitz C, Liu X, Pajak J, Stone NP, Hayes JA, Demo G, Kelch BA. Cryo-EM structures reveal high-resolution mechanism of a DNA polymerase sliding clamp loader. eLife 2022; 11:e74175. [PMID: 35179493 PMCID: PMC8893722 DOI: 10.7554/elife.74175] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 02/01/2022] [Indexed: 11/13/2022] Open
Abstract
Sliding clamps are ring-shaped protein complexes that are integral to the DNA replication machinery of all life. Sliding clamps are opened and installed onto DNA by clamp loader AAA+ ATPase complexes. However, how a clamp loader opens and closes the sliding clamp around DNA is still unknown. Here, we describe structures of the Saccharomyces cerevisiae clamp loader Replication Factor C (RFC) bound to its cognate sliding clamp Proliferating Cell Nuclear Antigen (PCNA) en route to successful loading. RFC first binds to PCNA in a dynamic, closed conformation that blocks both ATPase activity and DNA binding. RFC then opens the PCNA ring through a large-scale 'crab-claw' expansion of both RFC and PCNA that explains how RFC prefers initial binding of PCNA over DNA. Next, the open RFC:PCNA complex binds DNA and interrogates the primer-template junction using a surprising base-flipping mechanism. Our structures indicate that initial PCNA opening and subsequent closure around DNA do not require ATP hydrolysis, but are driven by binding energy. ATP hydrolysis, which is necessary for RFC release, is triggered by interactions with both PCNA and DNA, explaining RFC's switch-like ATPase activity. Our work reveals how a AAA+ machine undergoes dramatic conformational changes for achieving binding preference and substrate remodeling.
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Affiliation(s)
- Christl Gaubitz
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
| | - Xingchen Liu
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
| | - Joshua Pajak
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
| | - Nicholas P Stone
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
| | - Janelle A Hayes
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
| | - Gabriel Demo
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester MA & Central European Institute of Technology, Masaryk UniversityBrnoCzech Republic
| | - Brian A Kelch
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical SchoolWorcesterUnited States
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27
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Hot spots-making directed evolution easier. Biotechnol Adv 2022; 56:107926. [DOI: 10.1016/j.biotechadv.2022.107926] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/04/2022] [Accepted: 02/07/2022] [Indexed: 01/20/2023]
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28
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Bauer JA, Bauerová-Hlinková V. Extracting the Dynamic Motion of Proteins Using Normal Mode Analysis. Methods Mol Biol 2022; 2449:213-231. [PMID: 35507265 DOI: 10.1007/978-1-0716-2095-3_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Normal mode analysis (NMA) is a technique for describing the conformational states accessible to a protein in a minimum energy conformation. NMA gives results similar to those produced by principal components analysis of a molecular dynamics simulation, but with only a fraction of the computational effort. Here, we provide a brief overview of the theory and describe three methods for carrying out NMA, including the use of one of the on-line services, the use of off-line software for calculating the projection of the modes calculated from one conformation onto another, and an all-atom NMA calculated using GROMACS. For all three methods, we will use the E1·2Ca2+ form of the Ca2+-ATPase as a concrete example.
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Affiliation(s)
- Jacob A Bauer
- Institute of Molecular Biology, Slovak Academy of Sciences, Bratislava, Slovakia.
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29
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Structural Features of Cytochrome b5–Cytochrome b5 Reductase Complex Formation and Implications for the Intramolecular Dynamics of Cytochrome b5 Reductase. Int J Mol Sci 2021; 23:ijms23010118. [PMID: 35008543 PMCID: PMC8745658 DOI: 10.3390/ijms23010118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/10/2021] [Accepted: 12/21/2021] [Indexed: 12/15/2022] Open
Abstract
Membrane cytochrome b5 reductase is a pleiotropic oxidoreductase that uses primarily soluble reduced nicotinamide adenine dinucleotide (NADH) as an electron donor to reduce multiple biological acceptors localized in cellular membranes. Some of the biological acceptors of the reductase and coupled redox proteins might eventually transfer electrons to oxygen to form reactive oxygen species. Additionally, an inefficient electron transfer to redox acceptors can lead to electron uncoupling and superoxide anion formation by the reductase. Many efforts have been made to characterize the involved catalytic domains in the electron transfer from the reduced flavoprotein to its electron acceptors, such as cytochrome b5, through a detailed description of the flavin and NADH-binding sites. This information might help to understand better the processes and modifications involved in reactive oxygen formation by the cytochrome b5 reductase. Nevertheless, more than half a century since this enzyme was first purified, the one-electron transfer process toward potential electron acceptors of the reductase is still only partially understood. New advances in computational analysis of protein structures allow predicting the intramolecular protein dynamics, identifying potential functional sites, or evaluating the effects of microenvironment changes in protein structure and dynamics. We applied this approach to characterize further the roles of amino acid domains within cytochrome b5 reductase structure, part of the catalytic domain, and several sensors and structural domains involved in the interactions with cytochrome b5 and other electron acceptors. The computational analysis results allowed us to rationalize some of the available spectroscopic data regarding ligand-induced conformational changes leading to an increase in the flavin adenine dinucleotide (FAD) solvent-exposed surface, which has been previously correlated with the formation of complexes with electron acceptors.
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30
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Lv D, Pal P, Liu X, Jia Y, Thummuri D, Zhang P, Hu W, Pei J, Zhang Q, Zhou S, Khan S, Zhang X, Hua N, Yang Q, Arango S, Zhang W, Nayak D, Olsen SK, Weintraub ST, Hromas R, Konopleva M, Yuan Y, Zheng G, Zhou D. Development of a BCL-xL and BCL-2 dual degrader with improved anti-leukemic activity. Nat Commun 2021; 12:6896. [PMID: 34824248 PMCID: PMC8617031 DOI: 10.1038/s41467-021-27210-x] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 11/05/2021] [Indexed: 02/04/2023] Open
Abstract
PROteolysis-TArgeting Chimeras (PROTACs) have emerged as an innovative drug development platform. However, most PROTACs have been generated empirically because many determinants of PROTAC specificity and activity remain elusive. Through computational modelling of the entire NEDD8-VHL Cullin RING E3 ubiquitin ligase (CRLVHL)/PROTAC/BCL-xL/UbcH5B(E2)-Ub/RBX1 complex, we find that this complex can only ubiquitinate the lysines in a defined band region on BCL-xL. Using this approach to guide our development of a series of ABT263-derived and VHL-recruiting PROTACs, we generate a potent BCL-xL and BCL-2 (BCL-xL/2) dual degrader with significantly improved antitumor activity against BCL-xL/2-dependent leukemia cells. Our results provide experimental evidence that the accessibility of lysines on a target protein plays an important role in determining the selectivity and potency of a PROTAC in inducing protein degradation, which may serve as a conceptual framework to guide the future development of PROTACs.
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Affiliation(s)
- Dongwen Lv
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Pratik Pal
- grid.15276.370000 0004 1936 8091Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Xingui Liu
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Yannan Jia
- grid.240145.60000 0001 2291 4776Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX USA
| | - Dinesh Thummuri
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Peiyi Zhang
- grid.15276.370000 0004 1936 8091Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Wanyi Hu
- grid.15276.370000 0004 1936 8091Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Jing Pei
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Qi Zhang
- grid.240145.60000 0001 2291 4776Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX USA
| | - Shuo Zhou
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Sajid Khan
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Xuan Zhang
- grid.15276.370000 0004 1936 8091Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Nan Hua
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Qingping Yang
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Sebastian Arango
- grid.15276.370000 0004 1936 8091Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL USA
| | - Weizhou Zhang
- grid.15276.370000 0004 1936 8091Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL USA
| | - Digant Nayak
- grid.267309.90000 0001 0629 5880Department of Biochemistry & Structure Biology, Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Mays Cancer Center, the Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Shaun K. Olsen
- grid.267309.90000 0001 0629 5880Department of Biochemistry & Structure Biology, Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Mays Cancer Center, the Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Susan T. Weintraub
- grid.267309.90000 0001 0629 5880Department of Biochemistry & Structure Biology, Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Robert Hromas
- grid.267309.90000 0001 0629 5880Mays Cancer Center, the Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Marina Konopleva
- grid.240145.60000 0001 2291 4776Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX USA
| | - Yaxia Yuan
- Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
| | - Guangrong Zheng
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA.
| | - Daohong Zhou
- Department of Pharmacodynamics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
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31
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Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function. Comput Struct Biotechnol J 2021; 19:5309-5320. [PMID: 34765086 PMCID: PMC8554173 DOI: 10.1016/j.csbj.2021.09.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/02/2021] [Accepted: 09/05/2021] [Indexed: 11/23/2022] Open
Abstract
Statistical learning from protein dynamics unravels rigidities in interaction network. Backbone and side-chain mechanical couplings exhibit scale-free network properties. Graphical depiction of network rigidities captures sequence co-evolution patterns. Functional sites at secondary structure peripheries are mechanical hotspots. Our rigidity scores are compelling metrics for residue biological significance.
A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD.
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32
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Verkhivker GM, Agajanian S, Oztas DY, Gupta G. Allosteric Control of Structural Mimicry and Mutational Escape in the SARS-CoV-2 Spike Protein Complexes with the ACE2 Decoys and Miniprotein Inhibitors: A Network-Based Approach for Mutational Profiling of Binding and Signaling. J Chem Inf Model 2021; 61:5172-5191. [PMID: 34551245 DOI: 10.1021/acs.jcim.1c00766] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
We developed a computational framework for comprehensive and rapid mutational scanning of binding energetics and residue interaction networks in the SARS-CoV-2 spike protein complexes. Using this approach, we integrated atomistic simulations and conformational landscaping of the SARS-CoV-2 spike protein complexes with ensemble-based mutational screening and network modeling to characterize mechanisms of structure-functional mimicry and resilience toward mutational escape by the ACE2 protein decoy and de novo designed miniprotein inhibitors. A detailed analysis of structural plasticity of the SARS-CoV-2 spike proteins obtained from atomistic simulations of conformational landscapes and sequence-based profiling of the disorder propensities revealed the intrinsically flexible regions that harbor key functional sites targeted by circulating variants. The conservation of collective dynamics in the SARS-CoV-2 spike protein complexes showed that mutational escape positions are important for modulation of functional motions and that mutational changes in these sites can alter allosteric interaction networks. Through mutational profiling of binding and allosteric propensities in the SARS-CoV-2 spike protein complexes, we identified the key binding and regulatory hotspots that collectively determine functional response and resilience of miniproteins to mutational variants. The results suggest that binding affinities and allosteric signatures of the SARS-CoV-2 complexes can be determined by dynamic crosstalk between structurally stable regulatory centers and conformationally adaptable allosteric hotspots that collectively control the resilience toward mutational escape. This may underlie a mechanism in which moderate perturbations in the mutational escape positions can induce global allosteric changes and alter functional protein response by modulating signaling in the residue interaction networks.
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Affiliation(s)
- Gennady M Verkhivker
- Keck Center for Science and Engineering, Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, California 92866, United States.,Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
| | - Steve Agajanian
- Keck Center for Science and Engineering, Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, California 92866, United States
| | - Deniz Yasar Oztas
- Keck Center for Science and Engineering, Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, California 92866, United States
| | - Grace Gupta
- Keck Center for Science and Engineering, Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, California 92866, United States
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33
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Saih A, Bouqdayr M, Baba H, Hamdi S, Moussamih S, Bennani H, Saile R, Wakrim L, Kettani A. Computational Analysis of Missense Variants in the Human Transmembrane Protease Serine 2 ( TMPRSS2) and SARS-CoV-2. BIOMED RESEARCH INTERNATIONAL 2021; 2021:9982729. [PMID: 34692848 PMCID: PMC8531787 DOI: 10.1155/2021/9982729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/06/2021] [Accepted: 09/11/2021] [Indexed: 01/08/2023]
Abstract
The human transmembrane protease serine 2 (TMPRSS2) protein plays an important role in prostate cancer progression. It also facilitates viral entry into target cells by proteolytically cleaving and activating the S protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the current study, we used different available tools like SIFT, PolyPhen2.0, PROVEAN, SNAP2, PMut, MutPred2, I-Mutant Suite, MUpro, iStable, ConSurf, ModPred, SwissModel, PROCHECK, Verify3D, and TM-align to identify the most deleterious variants and to explore possible effects on the TMPRSS2 stability, structure, and function. The six missense variants tested were evaluated to have deleterious effects on the protein by SIFT, PolyPhen2.0, PROVEAN, SNAP2, and PMut. Additionally, V160M, G181R, R240C, P335L, G432A, and D435Y variants showed a decrease in stability by at least 2 servers; G181R, G432A, and D435Y are highly conserved and identified posttranslational modifications sites (PTMs) for proteolytic cleavage and ADP-ribosylation using ConSurf and ModPred servers. The 3D structure of TMPRSS2 native and mutants was generated using 7 meq as a template from the SwissModeller group, refined by ModRefiner, and validated using the Ramachandran plot. Hence, this paper can be advantageous to understand the association between these missense variants rs12329760, rs781089181, rs762108701, rs1185182900, rs570454392, and rs867186402 and susceptibility to SARS-CoV-2.
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Affiliation(s)
- Asmae Saih
- Virology Unit, Immunovirology Laboratory, Institut Pasteur du Maroc, 20360 Casablanca, Morocco
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
| | - Meryem Bouqdayr
- Virology Unit, Immunovirology Laboratory, Institut Pasteur du Maroc, 20360 Casablanca, Morocco
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
| | - Hanâ Baba
- Virology Unit, Immunovirology Laboratory, Institut Pasteur du Maroc, 20360 Casablanca, Morocco
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
| | - Salsabil Hamdi
- Environmental Health Laboratory, Institut Pasteur du Maroc, 20360 Casablanca, Morocco
| | - Samya Moussamih
- Immunology and Biodiversity Laboratory, Faculty of Sciences Ain Chock, Hassan II University of Casablanca, Morocco
| | - Houda Bennani
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
| | - Rachid Saile
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
| | - Lahcen Wakrim
- Virology Unit, Immunovirology Laboratory, Institut Pasteur du Maroc, 20360 Casablanca, Morocco
| | - Anass Kettani
- Laboratory of Biology and Health, URAC 34, Faculty of Sciences Ben M'Sik Hassan II University of Casablanca, Morocco
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34
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Verkhivker GM, Agajanian S, Oztas DY, Gupta G. Atomistic Simulations and In Silico Mutational Profiling of Protein Stability and Binding in the SARS-CoV-2 Spike Protein Complexes with Nanobodies: Molecular Determinants of Mutational Escape Mechanisms. ACS OMEGA 2021; 6:26354-26371. [PMID: 34660995 PMCID: PMC8515575 DOI: 10.1021/acsomega.1c03558] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/10/2021] [Indexed: 05/11/2023]
Abstract
Structure-functional studies have recently revealed a spectrum of diverse high-affinity nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this study, we combine atomistic simulations with the ensemble-based mutational profiling of binding for the SARS-CoV-2 S-RBD complexes with a wide range of nanobodies to identify dynamic and binding affinity fingerprints and characterize the energetic determinants of nanobody-escaping mutations. Using an in silico mutational profiling approach for probing the protein stability and binding, we examine dynamics and energetics of the SARS-CoV-2 complexes with single nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E + U, a biparatopic nanobody VHH VE, and a combination of the CC12.3 antibody and VHH V/W nanobodies. This study characterizes the binding energy hotspots in the SARS-CoV-2 protein and complexes with nanobodies providing a quantitative analysis of the effects of circulating variants and escaping mutations on binding that is consistent with a broad range of biochemical experiments. The results suggest that mutational escape may be controlled through structurally adaptable binding hotspots in the receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant binding epitope targeted by VHH U/V/W nanobodies. This study offers a plausible mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobodies can elicit the increased binding affinity response and yield resilience to common escape mutants.
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Affiliation(s)
- Gennady M. Verkhivker
- Keck
Center for Science and Engineering, Schmid College of Science and
Technology, Chapman University, One University Drive, Orange, California 92866, United States
- Department
of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
| | - Steve Agajanian
- Keck
Center for Science and Engineering, Schmid College of Science and
Technology, Chapman University, One University Drive, Orange, California 92866, United States
| | - Deniz Yasar Oztas
- Keck
Center for Science and Engineering, Schmid College of Science and
Technology, Chapman University, One University Drive, Orange, California 92866, United States
| | - Grace Gupta
- Keck
Center for Science and Engineering, Schmid College of Science and
Technology, Chapman University, One University Drive, Orange, California 92866, United States
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35
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Mersmann S, Strömich L, Song FJ, Wu N, Vianello F, Barahona M, Yaliraki S. ProteinLens: a web-based application for the analysis of allosteric signalling on atomistic graphs of biomolecules. Nucleic Acids Res 2021; 49:W551-W558. [PMID: 33978752 PMCID: PMC8661402 DOI: 10.1093/nar/gkab350] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/16/2021] [Accepted: 04/22/2021] [Indexed: 11/28/2022] Open
Abstract
The investigation of allosteric effects in biomolecular structures is of great current interest in diverse areas, from fundamental biological enquiry to drug discovery. Here we present ProteinLens, a user-friendly and interactive web application for the investigation of allosteric signalling based on atomistic graph-theoretical methods. Starting from the PDB file of a biomolecule (or a biomolecular complex) ProteinLens obtains an atomistic, energy-weighted graph description of the structure of the biomolecule, and subsequently provides a systematic analysis of allosteric signalling and communication across the structure using two computationally efficient methods: Markov Transients and bond-to-bond propensities. ProteinLens scores and ranks every bond and residue according to the speed and magnitude of the propagation of fluctuations emanating from any site of choice (e.g. the active site). The results are presented through statistical quantile scores visualised with interactive plots and adjustable 3D structure viewers, which can also be downloaded. ProteinLens thus allows the investigation of signalling in biomolecular structures of interest to aid the detection of allosteric sites and pathways. ProteinLens is implemented in Python/SQL and freely available to use at: www.proteinlens.io.
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Affiliation(s)
- Sophia F Mersmann
- Department of Mathematics, Imperial College London, Huxley Building, 180 Queen’s Gate, London SW7 2AZ, UK
| | - Léonie Strömich
- Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK
| | - Florian J Song
- Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK
| | - Nan Wu
- Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK
| | - Francesca Vianello
- Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK
| | - Mauricio Barahona
- Department of Mathematics, Imperial College London, Huxley Building, 180 Queen’s Gate, London SW7 2AZ, UK
| | - Sophia N Yaliraki
- Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK
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36
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Kong X, Xing E, Zhuang T, Li PK, Cheng X. Mechanistic Insights into the Allosteric Inhibition of Androgen Receptors by Binding Function 3 Antagonists from an Integrated Molecular Modeling Study. J Chem Inf Model 2021; 61:3477-3494. [PMID: 34165949 DOI: 10.1021/acs.jcim.1c00124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
An androgen receptor (AR) is an intensively studied treatment target for castration-resistant prostate cancer that is irresponsive to conventional antiandrogen therapeutics. Binding function 3 (BF3) inhibitors with alternative modes of action have emerged as a promising approach to overcoming antiandrogen resistance. However, how these BF3 inhibitors modulate AR function remains elusive, hindering the development of BF3-targeting agents. Here, we performed an integrated computational study to interrogate the binding mechanism of several known BF3 inhibitors with ARs. Our results show that the inhibitory effect of the BF3 antagonists arises from their allosteric modulation of the activation function (AF2) site, which alters the dynamic coupling between the BF3 and AF2 sites as well as the AF2-coactivator (SRC2-3) interaction. Moreover, the per-residue binding energy analyses reveal the "anchor" role of the linker connecting the phenyl ring and benzimidazole/indole in these BF3 inhibitors. Furthermore, the allosteric driver-interacting residues are found to include both "positive", e.g., Phe673 and Asn833, and "negative" ones, e.g., Phe826, and the differential interactions with these residues provide an explanation why stronger binding does not necessarily result in higher inhibitory activities. Finally, our allosteric communication pathway analyses delineate how the allosteric signals triggered by BF3 binding are propagated to the AF2 pocket through multiple short- and/or long-ranged transmission pathways. Collectively, our combined computational study provides a comprehensive structural mechanism underlying how the selected set of BF3 inhibitors modulate AR function, which will help guide future development of BF3 antagonists.
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Affiliation(s)
- Xiaotian Kong
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
| | - Enming Xing
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
| | - Tony Zhuang
- J. Willis Hurst Internal Medicine Program, Department of Medicine, Emory University, 100 Woodruff Circle, Atlanta, Georgia 30329, United States
| | - Pui-Kai Li
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
| | - Xiaolin Cheng
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
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37
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Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
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38
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Zhang Y, Zhang S, Xing J, Bahar I. Normal mode analysis of membrane protein dynamics using the vibrational subsystem analysis. J Chem Phys 2021; 154:195102. [PMID: 34240914 PMCID: PMC8131107 DOI: 10.1063/5.0046710] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 05/03/2021] [Indexed: 12/17/2022] Open
Abstract
The vibrational subsystem analysis is a useful approach that allows for evaluating the spectrum of modes of a given system by integrating out the degrees of freedom accessible to the environment. The approach could be utilized for exploring the collective dynamics of a membrane protein (system) coupled to the lipid bilayer (environment). However, the application to membrane proteins is limited due to high computational costs of modeling a sufficiently large membrane environment unbiased by end effects, which drastically increases the size of the investigated system. We derived a recursive formula for calculating the reduced Hessian of a membrane protein embedded in a lipid bilayer by decomposing the membrane into concentric cylindrical domains with the protein located at the center. The approach allows for the design of a time- and memory-efficient algorithm and a mathematical understanding of the convergence of the reduced Hessian with respect to increasing membrane sizes. The application to the archaeal aspartate transporter GltPh illustrates its utility and efficiency in capturing the transporter's elevator-like movement during its transition between outward-facing and inward-facing states.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Bldg., 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, USA
| | - She Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Bldg., 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, USA
| | | | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Bldg., 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, USA
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39
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Verkhivker GM, Agajanian S, Oztas DY, Gupta G. Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies: Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations. Biochemistry 2021; 60:1459-1484. [PMID: 33900725 PMCID: PMC8098775 DOI: 10.1021/acs.biochem.1c00139] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/12/2021] [Indexed: 12/11/2022]
Abstract
In this study, we used an integrative computational approach to examine molecular mechanisms and determine functional signatures underlying the role of functional residues in the SARS-CoV-2 spike protein that are targeted by novel mutational variants and antibody-escaping mutations. Atomistic simulations and functional dynamics analysis are combined with alanine scanning and mutational sensitivity profiling of the SARS-CoV-2 spike protein complexes with the ACE2 host receptor and the REGN-COV2 antibody cocktail(REG10987+REG10933). Using alanine scanning and mutational sensitivity analysis, we have shown that K417, E484, and N501 residues correspond to key interacting centers with a significant degree of structural and energetic plasticity that allow mutants in these positions to afford the improved binding affinity with ACE2. Through perturbation-based network modeling and community analysis of the SARS-CoV-2 spike protein complexes with ACE2, we demonstrate that E406, N439, K417, and N501 residues serve as effector centers of allosteric interactions and anchor major intermolecular communities that mediate long-range communication in the complexes. The results provide support to a model according to which mutational variants and antibody-escaping mutations constrained by the requirements for host receptor binding and preservation of stability may preferentially select structurally plastic and energetically adaptable allosteric centers to differentially modulate collective motions and allosteric interactions in the complexes with the ACE2 enzyme and REGN-COV2 antibody combination. This study suggests that the SARS-CoV-2 spike protein may function as a versatile and functionally adaptable allosteric machine that exploits the plasticity of allosteric regulatory centers to fine-tune response to antibody binding without compromising the activity of the spike protein.
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Affiliation(s)
- Gennady M. Verkhivker
- Keck Center for Science and Engineering, Schmid
College of Science and Technology, Chapman University, One
University Drive, Orange, California 92866, United States
- Depatment of Biomedical and Pharmaceutical Sciences,
Chapman University School of Pharmacy, Irvine, California
92618, United States
| | - Steve Agajanian
- Keck Center for Science and Engineering, Schmid
College of Science and Technology, Chapman University, One
University Drive, Orange, California 92866, United States
| | - Deniz Yazar Oztas
- Keck Center for Science and Engineering, Schmid
College of Science and Technology, Chapman University, One
University Drive, Orange, California 92866, United States
| | - Grace Gupta
- Keck Center for Science and Engineering, Schmid
College of Science and Technology, Chapman University, One
University Drive, Orange, California 92866, United States
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40
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Lam SD, Ashford P, Díaz-Sánchez S, Villar M, Gortázar C, de la Fuente J, Orengo C. Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE. Viruses 2021; 13:v13040708. [PMID: 33921873 PMCID: PMC8073597 DOI: 10.3390/v13040708] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 04/16/2021] [Accepted: 04/16/2021] [Indexed: 12/17/2022] Open
Abstract
Coronavirus-like organisms have been previously identified in Arthropod ectoparasites (such as ticks and unfed cat flea). Yet, the question regarding the possible role of these arthropods as SARS-CoV-2 passive/biological transmission vectors is still poorly explored. In this study, we performed in silico structural and binding energy calculations to assess the risks associated with possible ectoparasite transmission. We found sufficient similarity between ectoparasite ACE and human ACE2 protein sequences to build good quality 3D-models of the SARS-CoV-2 Spike:ACE complex to assess the impacts of ectoparasite mutations on complex stability. For several species (e.g., water flea, deer tick, body louse), our analyses showed no significant destabilisation of the SARS-CoV-2 Spike:ACE complex, suggesting these species would bind the viral Spike protein. Our structural analyses also provide structural rationale for interactions between the viral Spike and the ectoparasite ACE proteins. Although we do not have experimental evidence of infection in these ectoparasites, the predicted stability of the complex suggests this is possible, raising concerns of a possible role in passive transmission of the virus to their human hosts.
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Affiliation(s)
- Su Datt Lam
- Institute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, UK;
- Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
- Correspondence: (S.D.L.); (J.d.l.F.); (C.O.)
| | - Paul Ashford
- Institute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, UK;
| | - Sandra Díaz-Sánchez
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ronda de Toledo s/n, 13005 Ciudad Real, Spain; (S.D.-S.); (M.V.); (C.G.)
| | - Margarita Villar
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ronda de Toledo s/n, 13005 Ciudad Real, Spain; (S.D.-S.); (M.V.); (C.G.)
- Regional Centre for Biomedical Research (CRIB), Biochemistry Section, Faculty of Science and Chemical Technologies, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
| | - Christian Gortázar
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ronda de Toledo s/n, 13005 Ciudad Real, Spain; (S.D.-S.); (M.V.); (C.G.)
| | - José de la Fuente
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ronda de Toledo s/n, 13005 Ciudad Real, Spain; (S.D.-S.); (M.V.); (C.G.)
- Center for Veterinary Health Sciences, Department of Veterinary Pathobiology, Oklahoma State University, Stillwater, OK 74078, USA
- Correspondence: (S.D.L.); (J.d.l.F.); (C.O.)
| | - Christine Orengo
- Institute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, UK;
- Correspondence: (S.D.L.); (J.d.l.F.); (C.O.)
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41
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Kumar D T, Shaikh N, Kumar S U, Doss C GP, Zayed H. Structure-Based Virtual Screening to Identify Novel Potential Compound as an Alternative to Remdesivir to Overcome the RdRp Protein Mutations in SARS-CoV-2. Front Mol Biosci 2021; 8:645216. [PMID: 33898520 PMCID: PMC8062963 DOI: 10.3389/fmolb.2021.645216] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/11/2021] [Indexed: 01/18/2023] Open
Abstract
The number of confirmed COVID-19 cases is rapidly increasing with no direct treatment for the disease. Few repurposed drugs, such as Remdesivir, Chloroquine, Hydroxychloroquine, Lopinavir, and Ritonavir, are being tested against SARS-CoV-2. Remdesivir is the drug of choice for Ebola virus disease and has been authorized for emergency use. This drug acts against SARS-CoV-2 by inhibiting the RNA-dependent-RNA-polymerase (RdRp) of SARS-CoV-2. RdRp of viruses is prone to mutations that confer drug resistance. A recent study by Pachetti et al. in 2020 identified the P323L mutation in the RdRp protein of SARS-CoV-2. In this study, we aimed to determine the potency of lead compounds similar to Remdesivir, which can be used as an alternative when variants of SARS-CoV-2 develop resistance due to RdRp mutations. The initial screening yielded 704 compounds that were 90% similar to the control drug, Remdesivir. On further evaluation through drugability and antiviral inhibition percentage analyses, we shortlisted 32 and seven compounds, respectively. These seven compounds were further analyzed for their molecular interactions, which revealed that all seven compounds interacted with RdRp with higher affinity than Remdesivir under native conditions. However, three compounds failed to interact with the mutant protein with higher affinity than Remdesivir. Dynamic cross-correlation matrix (DCCM) and vector field collective motions analyses were performed to identify the precise movements of docked complexes' residues. Furthermore, the compound SCHEMBL20144212 showed a high affinity for native and mutant proteins and might provide an alternative against SARS-CoV-2 variants that might confer resistance to Remdesivir. Further validations by in vitro and in vivo studies are needed to confirm the efficacy of our lead compounds for their inhibition against SARS-CoV-2.
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Affiliation(s)
- Thirumal Kumar D
- Meenakshi Academy of Higher Education and Research, Chennai, India
| | - Nishaat Shaikh
- School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Udhaya Kumar S
- Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India
| | - George Priya Doss C
- School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Hatem Zayed
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar
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42
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Badaczewska-Dawid AE, Kolinski A, Kmiecik S. Protocols for Fast Simulations of Protein Structure Flexibility Using CABS-Flex and SURPASS. Methods Mol Biol 2021; 2165:337-353. [PMID: 32621235 DOI: 10.1007/978-1-0716-0708-4_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Conformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods since experimental characterization can be difficult. Depending on protein system size, computational tools may require large computational resources or significant simplifications in the modeled systems to speed up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling, and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.
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Affiliation(s)
- Aleksandra E Badaczewska-Dawid
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland.,Department of Chemistry, Iowa State University, Ames, IA, USA
| | - Andrzej Kolinski
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| | - Sebastian Kmiecik
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland.
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43
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Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
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44
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Kumar SU, Sankar S, Kumar DT, Younes S, Younes N, Siva R, Doss CGP, Zayed H. Molecular dynamics, residue network analysis, and cross-correlation matrix to characterize the deleterious missense mutations in GALE causing galactosemia III. Cell Biochem Biophys 2021; 79:201-219. [PMID: 33555556 DOI: 10.1007/s12013-020-00960-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2020] [Indexed: 01/17/2023]
Abstract
Epimerase-deficiency galactosemia (EDG) is caused by mutations in the UDP-galactose 4'-epimerase enzyme, encoded by gene GALE. Catalyzing the last reaction in the Leloir pathway, UDP-galactose-4-epimerase catalyzes the interconversion of UDP-galactose and UDP-glucose. This study aimed to use in-depth computational strategies to prioritize the pathogenic missense mutations in GALE protein and investigate the systemic behavior, conformational spaces, atomic motions, and cross-correlation matrix of the GALE protein. We searched four databases (dbSNP, ClinVar, UniProt, and HGMD) and major biological literature databases (PubMed, Science Direct, and Google Scholar), for missense mutations that are associated with EDG patients, our search yielded 190 missense mutations. We applied a systematic computational prediction pipeline, including pathogenicity, stability, biochemical, conservational, protein residue contacts, and structural analysis, to predict the pathogenicity of these mutations. We found three mutations (p.K161N, p.R239W, and p.G302D) with a severe phenotype in patients with EDG that correlated with our computational prediction analysis; thus, they were selected for further structural and simulation analyses to compute the flexibility and stability of the mutant GALE proteins. The three mutants were subjected to molecular dynamics simulation (MDS) with native protein for 200 ns using GROMACS. The MDS demonstrated that these mutations affected the beta-sheets and helical region that are responsible for the catalytic activity; subsequently, affects the stability and flexibility of the mutant proteins along with a decrease and more deviations in compactness when compared to that of a native. Also, three mutations created major variations in the combined atomic motions of the catalytic and C-terminal regions. The network analysis of the residues in the native and three mutant protein structures showed disturbed residue contacts occurred owing to the missense mutations. Our findings help to understand the structural behavior of a protein owing to mutation and are intended to serve as a platform for prioritizing mutations, which could be potential targets for drug discovery and development of targeted therapeutics.
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Affiliation(s)
- S Udhaya Kumar
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Srivarshini Sankar
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - D Thirumal Kumar
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Salma Younes
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar
| | - Nadin Younes
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar
| | - R Siva
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - C George Priya Doss
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
| | - Hatem Zayed
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar.
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45
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Verkhivker GM, Di Paola L. Dynamic Network Modeling of Allosteric Interactions and Communication Pathways in the SARS-CoV-2 Spike Trimer Mutants: Differential Modulation of Conformational Landscapes and Signal Transmission via Cascades of Regulatory Switches. J Phys Chem B 2021; 125:850-873. [PMID: 33448856 PMCID: PMC7839160 DOI: 10.1021/acs.jpcb.0c10637] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/08/2021] [Indexed: 12/13/2022]
Abstract
The rapidly growing body of structural and biochemical studies of the SARS-CoV-2 spike glycoprotein has revealed a variety of distinct functional states with radically different arrangements of the receptor-binding domain, highlighting a remarkable function-driven conformational plasticity and adaptability of the spike proteins. In this study, we examined molecular mechanisms underlying conformational and dynamic changes in the SARS-CoV-2 spike mutant trimers through the lens of dynamic analysis of allosteric interaction networks and atomistic modeling of signal transmission. Using an integrated approach that combined coarse-grained molecular simulations, protein stability analysis, and perturbation-based modeling of residue interaction networks, we examined how mutations in the regulatory regions of the SARS-CoV-2 spike protein can differentially affect dynamics and allosteric signaling in distinct functional states. The results of this study revealed key functional regions and regulatory centers that govern collective dynamics, allosteric interactions, and control signal transmission in the SARS-CoV-2 spike proteins. We found that the experimentally confirmed regulatory hotspots that dictate dynamic switching between conformational states of the SARS-CoV-2 spike protein correspond to the key hinge sites and global mediating centers of the allosteric interaction networks. The results of this study provide a novel insight into allosteric regulatory mechanisms of SARS-CoV-2 spike proteins showing that mutations at the key regulatory positions can differentially modulate distribution of states and determine topography of signal communication pathways operating through state-specific cascades of control switch points. This analysis provides a plausible strategy for allosteric probing of the conformational equilibrium and therapeutic intervention by targeting specific hotspots of allosteric interactions and communications in the SARS-CoV-2 spike proteins.
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Affiliation(s)
- Gennady M. Verkhivker
- Keck
Center for Science and Engineering, Schmid College of Science and
Technology, Chapman University, One University Drive, Orange, California 92866, United States
- Department
of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
| | - Luisa Di Paola
- Unit
of Chemical-Physics Fundamentals in Chemical Engineering, Department
of Engineering, Università Campus
Bio-Medico di Roma, via
Álvaro del Portillo 21, 00128 Rome, Italy
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46
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Planas-Iglesias J, Marques SM, Pinto GP, Musil M, Stourac J, Damborsky J, Bednar D. Computational design of enzymes for biotechnological applications. Biotechnol Adv 2021; 47:107696. [PMID: 33513434 DOI: 10.1016/j.biotechadv.2021.107696] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 01/12/2021] [Accepted: 01/13/2021] [Indexed: 12/14/2022]
Abstract
Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.
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Affiliation(s)
- Joan Planas-Iglesias
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Sérgio M Marques
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Gaspar P Pinto
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Milos Musil
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic; IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, 61266 Brno, Czech Republic
| | - Jan Stourac
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic.
| | - David Bednar
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno, Czech Republic.
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47
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Abstract
Allostery is a fundamental regulatory mechanism in the majority of biological processes of molecular machines. Allostery is well-known as a dynamic-driven process, and thus, the molecular mechanism of allosteric signal transmission needs to be established. Elastic network models (ENMs) provide efficient methods for investigating the intrinsic dynamics and allosteric communication pathways in proteins. In this chapter, two ENM methods including Gaussian network model (GNM) coupled with Markovian stochastic model, as well as the anisotropic network model (ANM), were introduced to identify allosteric effects in hemoglobins. Techniques on model parameters, scripting and calculation, analysis, and visualization are shown step by step.
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48
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Anthonymuthu TS, Tyurina YY, Sun WY, Mikulska-Ruminska K, Shrivastava IH, Tyurin VA, Cinemre FB, Dar HH, VanDemark AP, Holman TR, Sadovsky Y, Stockwell BR, He RR, Bahar I, Bayır H, Kagan VE. Resolving the paradox of ferroptotic cell death: Ferrostatin-1 binds to 15LOX/PEBP1 complex, suppresses generation of peroxidized ETE-PE, and protects against ferroptosis. Redox Biol 2021; 38:101744. [PMID: 33126055 PMCID: PMC7596334 DOI: 10.1016/j.redox.2020.101744] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 10/04/2020] [Accepted: 10/04/2020] [Indexed: 12/20/2022] Open
Abstract
Hydroperoxy-eicosatetraenoyl-phosphatidylethanolamine (HpETE-PE) is a ferroptotic cell death signal. HpETE-PE is produced by the 15-Lipoxygenase (15LOX)/Phosphatidylethanolamine Binding Protein-1 (PEBP1) complex or via an Fe-catalyzed non-enzymatic radical reaction. Ferrostatin-1 (Fer-1), a common ferroptosis inhibitor, is a lipophilic radical scavenger but a poor 15LOX inhibitor arguing against 15LOX having a role in ferroptosis. In the current work, we demonstrate that Fer-1 does not affect 15LOX alone, however, it effectively inhibits HpETE-PE production by the 15LOX/PEBP1 complex. Computational molecular modeling shows that Fer-1 binds to the 15LOX/PEBP1 complex at three sites and could disrupt the catalytically required allosteric motions of the 15LOX/PEBP1 complex. Using nine ferroptosis cell/tissue models, we show that HpETE-PE is produced by the 15LOX/PEBP1 complex and resolve the long-existing Fer-1 anti-ferroptotic paradox.
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Affiliation(s)
- Tamil S Anthonymuthu
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, PA, USA; Children's Neuroscience Institute, University of Pittsburgh, Pittsburgh, PA, USA; Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yulia Y Tyurina
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wan-Yang Sun
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA; Guangdong Engineering Research Center of Chinese Medicine & Disease Susceptibility, Jinan University, College of Pharmacy, Guangzhou, China
| | - Karolina Mikulska-Ruminska
- Department of Computational and System Biology, University of Pittsburgh, Pittsburgh, PA, USA; Institute of Physics, Faculty of Physics Astronomy and Informatics, Nicolaus Copernicus University in Toruń, Grudziadzka 5, 87-100 Torun, Poland
| | - Indira H Shrivastava
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Computational and System Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vladimir A Tyurin
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fatma B Cinemre
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA; Sakarya University School of Medicine, Sakarya, Turkey
| | - Haider H Dar
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew P VanDemark
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Theodore R Holman
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, CA, USA
| | - Yoel Sadovsky
- Magee-Womens Research Institute and Departments of OBGYN and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brent R Stockwell
- Department of Biological Sciences and Department of Chemistry, Columbia University, New York, NY, USA
| | - Rong-Rong He
- Guangdong Engineering Research Center of Chinese Medicine & Disease Susceptibility, Jinan University, College of Pharmacy, Guangzhou, China
| | - Ivet Bahar
- Department of Computational and System Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hülya Bayır
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, PA, USA; Children's Neuroscience Institute, University of Pittsburgh, Pittsburgh, PA, USA; Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Valerian E Kagan
- Children's Neuroscience Institute, University of Pittsburgh, Pittsburgh, PA, USA; Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA; Navigational Redox Lipidomics Group, Institute for Regenerative Medicine, IM Sechenov First Moscow State Medical University, Russian Federation.
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49
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Verkhivker GM. Molecular Simulations and Network Modeling Reveal an Allosteric Signaling in the SARS-CoV-2 Spike Proteins. J Proteome Res 2020; 19:4587-4608. [PMID: 33006900 PMCID: PMC7640983 DOI: 10.1021/acs.jproteome.0c00654] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Indexed: 12/13/2022]
Abstract
The development of computational strategies for the quantitative characterization of the functional mechanisms of SARS-CoV-2 spike proteins is of paramount importance in efforts to accelerate the discovery of novel therapeutic agents and vaccines combating the COVID-19 pandemic. Structural and biophysical studies have recently characterized the conformational landscapes of the SARS-CoV-2 spike glycoproteins in the prefusion form, revealing a spectrum of stable and more dynamic states. By employing molecular simulations and network modeling approaches, this study systematically examined functional dynamics and identified the regulatory centers of allosteric interactions for distinct functional states of the wild-type and mutant variants of the SARS-CoV-2 prefusion spike trimer. This study presents evidence that the SARS-CoV-2 spike protein can function as an allosteric regulatory engine that fluctuates between dynamically distinct functional states. Perturbation-based modeling of the interaction networks revealed a key role of the cross-talk between the effector hotspots in the receptor binding domain and the fusion peptide proximal region of the SARS-CoV-2 spike protein. The results have shown that the allosteric hotspots of the interaction networks in the SARS-CoV-2 spike protein can control the dynamic switching between functional conformational states that are associated with virus entry to the host receptor. This study offers a useful and novel perspective on the underlying mechanisms of the SARS-CoV-2 spike protein through the lens of allosteric signaling as a regulatory apparatus of virus transmission that could open up opportunities for targeted allosteric drug discovery against SARS-CoV-2 proteins and contribute to the rapid response to the current and potential future pandemic scenarios.
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Affiliation(s)
- Gennady M. Verkhivker
- Graduate
Program in Computational and Data Sciences, Keck Center for Science
and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, California 92866, United States
- Department
of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
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50
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Ponzoni L, Peñaherrera DA, Oltvai ZN, Bahar I. Rhapsody: predicting the pathogenicity of human missense variants. Bioinformatics 2020; 36:3084-3092. [PMID: 32101277 PMCID: PMC7214033 DOI: 10.1093/bioinformatics/btaa127] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 12/27/2019] [Accepted: 02/21/2020] [Indexed: 12/22/2022] Open
Abstract
MOTIVATION The biological effects of human missense variants have been studied experimentally for decades but predicting their effects in clinical molecular diagnostics remains challenging. Available computational tools are usually based on the analysis of sequence conservation and structural properties of the mutant protein. We recently introduced a new machine learning method that demonstrated for the first time the significance of protein dynamics in determining the pathogenicity of missense variants. RESULTS Here, we present a new interface (Rhapsody) that enables fully automated assessment of pathogenicity, incorporating both sequence coevolution data and structure- and dynamics-based features. Benchmarked against a dataset of about 20 000 annotated variants, the methodology is shown to outperform well-established and/or advanced prediction tools. We illustrate the utility of Rhapsody by in silico saturation mutagenesis studies of human H-Ras, phosphatase and tensin homolog and thiopurine S-methyltransferase. AVAILABILITY AND IMPLEMENTATION The new tool is available both as an online webserver at http://rhapsody.csb.pitt.edu and as an open-source Python package (GitHub repository: https://github.com/prody/rhapsody; PyPI package installation: pip install prody-rhapsody). Links to additional resources, tutorials and package documentation are provided in the 'Python package' section of the website. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Luca Ponzoni
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Daniel A Peñaherrera
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Zoltán N Oltvai
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.,Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA.,Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
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