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      Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein

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          Abstract

          High-risk strains of human papillomavirus (HPV) have been identified as the etiologic agent of some anogenital tract, head, and neck cancers. Although prophylactic HPV vaccines have been approved; it is still necessary a drug-based treatment against the infection and its oncogenic effects. The E6 oncoprotein is one of the most studied therapeutic targets of HPV, it has been identified as a key factor in cell immortalization and tumor progression in HPV-positive cells. E6 can promote the degradation of p53, a tumor suppressor protein, through the interaction with the cellular ubiquitin ligase E6AP. Therefore, preventing the formation of the E6-E6AP complex is one of the main strategies to inhibit the viability and proliferation of infected cells. Herein, we propose an in silico pipeline to identify small-molecule inhibitors of the E6-E6AP interaction. Virtual screening was carried out by predicting the ADME properties of the molecules and performing ensemble-based docking simulations to E6 protein followed by binding free energy estimation through MM/PB(GB)SA methods. Finally, the top-three compounds were selected, and their stability in the E6 docked complex and their effect in the inhibition of the E6-E6AP interaction was corroborated by molecular dynamics simulation. Therefore, this pipeline and the identified molecules represent a new starting point in the development of anti-HPV drugs.

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          Most cited references35

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          PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

          In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
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            MMPBSA.py: An Efficient Program for End-State Free Energy Calculations.

            MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.
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              The many roles of computation in drug discovery.

              An overview is given on the diverse uses of computational chemistry in drug discovery. Particular emphasis is placed on virtual screening, de novo design, evaluation of drug-likeness, and advanced methods for determining protein-ligand binding.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draft
                Role: Formal analysisRole: InvestigationRole: SupervisionRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 March 2019
                2019
                : 14
                : 3
                : e0213028
                Affiliations
                [1 ] Centro de Nanociencias y Nanotecnología, Universidad Nacional Autonoma de Mèxico, Ensenada, Baja California, México
                [2 ] Departamento de Ciencias Químicas, Facultad de Ciencias Exactas, Universidad Andres Bello, Sede Concepción, Chile
                [3 ] Departamento de Química Orgánica, Facultad de Ciencias Químicas, Universidad de Concepción, Concepción, Chile
                [4 ] Instituto de Química de Recursos Naturales, Universidad de Talca, Talca, Chile
                [5 ] Computer Science Department, CICESE Research Center, Ensenada, Mèxico
                Universita degli Studi di Torino, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-8497-2821
                Article
                PONE-D-18-30992
                10.1371/journal.pone.0213028
                6420176
                30875378
                adfb8e32-5531-4617-a67d-8907bb75fb98
                © 2019 Ricci-López et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 October 2018
                : 13 February 2019
                Page count
                Figures: 7, Tables: 3, Pages: 22
                Funding
                Funded by: CONACYT
                Award ID: 693115
                Award Recipient :
                Funded by: DGAPA-UNAM
                Award ID: Fellowship
                Award Recipient :
                Funded by: LANCAD
                Award ID: LANCAD-UNAM-DGTIC-286
                Award Recipient :
                Funded by: FONDECYT
                Award ID: 1160060
                Award Recipient :
                This work was supported by LANCAD-UNAM-DGTIC-286 grant at DGTIC- UNAM; FONDECYT 1160060 grant at Universidad Andres Bello (UNAB), Chile; CONACYT 693115 scholarship grant of JRL and DGAPA-UNAM fellowship of AVL. The funders had NO role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Physical Sciences
                Physics
                Thermodynamics
                Free Energy
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Medicine and Health Sciences
                Urology
                Genitourinary Infections
                Human Papillomavirus Infection
                Medicine and Health Sciences
                Infectious Diseases
                Sexually Transmitted Diseases
                Human Papillomavirus Infection
                Medicine and Health Sciences
                Infectious Diseases
                Viral Diseases
                Human Papillomavirus Infection
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Interactions
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Biology and life sciences
                Organisms
                Viruses
                DNA viruses
                Papillomaviruses
                HPV-16
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Viral Pathogens
                Papillomaviruses
                HPV-16
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
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                Papillomaviruses
                HPV-16
                Biology and Life Sciences
                Organisms
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                HPV-16
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Custom metadata
                All files are available from the PDB database ( https://www.rcsb.org/structure/4xr8) and ZINC15 public database ( https://zinc15.docking.org). Those interested can access the data in the same manner as the authors. The authors had no special access privileges. The supporting information is available from https://doi.org/10.6084/m9.figshare.7586417.v1.

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