ReviewInternational journal of molecular sciences2019
Methods for the Refinement of Protein Structure 3D Models.
Review in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- PROPTIMUS LIVE: local constrained α-carbon optimization of proteins.Nucleic acids research · 2026Article
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- Designing a multi-epitope vaccine against the midgut-specific fibrinogen-related protein 1(FREP1) of Anopheles stephensi to enhance protection against the malaria parasite: a step beyond traditional vaccine development approaches.Biotechnology letters · 2025Article
- Comprehensive immunoinformatics guided design and in silico assessment of a multi-epitope vaccine to elicit immunity against Mayaro virus.In silico pharmacology · 2025Article
- Computational exploration ofBiochemistry and biophysics reports · 2024Article
- In silico and experimental methods for designing a potent anticancer arazyme-herceptin fusion protein in HER2-positive breast cancer.Journal of molecular modeling · 2023Article
- In Silico Characterization ofACS omega · 2023Article
- Protein-Protein Interaction Studies Using Molecular Dynamics Simulation.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Bioinformatics evaluation of anticancer properties of GP63 protein-derived peptides on MMP2 protein of melanoma cancer.Journal of pathology informatics · 2023Article
- In Silico Structural and Functional Analyses of NLRP3 Inflammasomes to Provide Insights for Treating Neurodegenerative Diseases.BioMed research international · 2023Article
- Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Improvement of protein tertiary and quaternary structure predictions using the ReFOLD refinement method and the AlphaFold2 recycling process.Bioinformatics advances · 2023Article
- Immunoinformatics Approach to Design Novel Subunit Vaccine against the Epstein-Barr Virus.Microbiology spectrum · 2022Article
- Characterization and Evaluation of Cell-Penetrating Activity of Brevinin-2R: An Amphibian Skin Antimicrobial Peptide.Molecular biotechnology · 2022Article
- Development of multivalent vaccine targeting M segment of Crimean Congo Hemorrhagic Fever Virus (CCHFV) using immunoinformatic approaches.Saudi journal of biological sciences · 2022Article
- Review
- Computational insights into differential interaction of mammalian angiotensin-converting enzyme 2 with the SARS-CoV-2 spike receptor binding domain.Computers in biology and medicine · 2022Article
- Computational design and characterization of a multiepitope vaccine against carbapenemase-producingComputational and structural biotechnology journal · 2022Article
- Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement.Nature communications · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The refinement of predicted 3D protein models is crucial in bringing them closer towards experimental accuracy for further computational studies. Refinement approaches can be divided into two main stages: The sampling and scoring stages. Sampling strategies, such as the popular Molecular Dynamics (MD)-based protocols, aim to generate improved 3D models. However, generating 3D models that are closer to the native structure than the initial model remains challenging, as structural deviations from the native basin can be encountered due to force-field inaccuracies. Therefore, different restraint strategies have been applied in order to avoid deviations away from the native structure. For example, the accurate prediction of local errors and/or contacts in the initial models can be used to guide restraints. MD-based protocols, using physics-based force fields and smart restraints, have made significant progress towards a more consistent refinement of 3D models. The scoring stage, including energy functions and Model Quality Assessment Programs (MQAPs) are also used to discriminate near-native conformations from non-native conformations. Nevertheless, there are often very small differences among generated 3D models in refinement pipelines, which makes model discrimination and selection problematic. For this reason, the identification of the most native-like conformations remains a major challenge.
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