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Olechnovič K, Banciul R, Dapkūnas J, Venclovas Č. FTDMP: A Framework for Protein-Protein, Protein-DNA, and Protein-RNA Docking and Scoring. Proteins 2025. [PMID: 39748638 DOI: 10.1002/prot.26792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 11/27/2024] [Accepted: 12/18/2024] [Indexed: 01/04/2025]
Abstract
FTDMP is a software framework for biomolecular docking and scoring. It can perform docking of subunits containing one or more protein, DNA, or RNA chains, followed by subsequent scoring of the resulting models. FTDMP can also be used for the ranking of user-provided models of biomolecular complexes, generated by any structure prediction method. FTDMP evaluates models according to the consensus-based method VoroIF-jury, which combines individual scores derived from the Voronoi tessellation of biomolecular structures. In addition to the default scoring mode, FTDMP can easily adopt additional scores; thus, it may be used as a tool to assess newly developed scoring functions. FTDMP was evaluated during blind testing in recent CAPRI experiments and using protein-protein, protein-DNA, and protein-RNA docking benchmarks. It proved to be a useful tool for different research tasks, related to modeling biomolecular interactions. The software, cleaned docking benchmarks, and benchmarking results are available at https://bioinformatics.lt/software/ftdmp/.
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Affiliation(s)
- Kliment Olechnovič
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
- Université Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France
| | - Rita Banciul
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Justas Dapkūnas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Česlovas Venclovas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
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Dapkūnas J, Olechnovič K, Venclovas Č. Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction. Proteins 2021; 89:1834-1843. [PMID: 34176161 PMCID: PMC9292421 DOI: 10.1002/prot.26167] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 06/21/2021] [Accepted: 06/23/2021] [Indexed: 01/08/2023]
Abstract
The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template‐based modeling and free docking. Structural templates were identified using sensitive sequence‐based searches. If sequence‐based searches failed, we performed structure‐based template searches using selected CASP server models. In the absence of reliable templates we applied free docking starting from monomers generated by CASP servers. We evaluated and ranked models of protein complexes using an improved version of our protein structure quality assessment method, VoroMQA, taking into account both interaction interface and global structure scores. If reliable templates could be identified, generally accurate models of protein assemblies were generated with the exception of an antibody‐antigen interaction. The success of free docking mainly depended on the accuracy of initial subunit models and on the scoring of docking solutions. To put our overall results in perspective, we analyzed our performance in the context of other CASP groups. Although the subunits in our assembly models often were not of the top quality, these models had, overall, the best‐predicted intersubunit interfaces according to several accuracy measures. We attribute our relative success primarily to the emphasis on the interaction interface when modeling and scoring.
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Affiliation(s)
- Justas Dapkūnas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Kliment Olechnovič
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Česlovas Venclovas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
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Egbert M, Porter KA, Ghani U, Kotelnikov S, Nguyen T, Ashizawa R, Kozakov D, Vajda S. Conservation of binding properties in protein models. Comput Struct Biotechnol J 2021; 19:2549-2566. [PMID: 34025942 PMCID: PMC8114079 DOI: 10.1016/j.csbj.2021.04.048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/19/2021] [Accepted: 04/22/2021] [Indexed: 01/09/2023] Open
Abstract
We study the models submitted to round 12 of the Critical Assessment of protein Structure Prediction (CASP) experiment to assess how well the binding properties are conserved when the X-ray structures of the target proteins are replaced by their models. To explore small molecule binding we generate distributions of molecular probes - which are fragment-sized organic molecules of varying size, shape, and polarity - around the protein, and count the number of interactions between each residue and the probes, resulting in a vector of interactions we call a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model of the protein, is determined by calculating the correlation coefficient between the two vectors. The resulting correlation coefficients are shown to correlate with global measures of accuracy established in CASP, and the relationship yields an accuracy threshold that has to be reached for meaningful binding surface conservation. The clusters formed by the probe molecules reliably predict binding hot spots and ligand binding sites in both X-ray structures and reasonably accurate models of the target, but ensembles of models may be needed for assessing the availability of proper binding pockets. We explored ligand docking to the few targets that had bound ligands in the X-ray structure. More targets were available to assess the ability of the models to reproduce protein-protein interactions by docking both the X-ray structures and models to their interaction partners in complexes. It was shown that this application is more difficult than finding small ligand binding sites, and the success rates heavily depend on the local structure in the potential interface. In particular, predicted conformations of flexible loops are frequently incorrect in otherwise highly accurate models, and may prevent predicting correct protein-protein interactions.
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Affiliation(s)
- Megan Egbert
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States
| | - Kathryn A. Porter
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States
| | - Usman Ghani
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Thu Nguyen
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Ryota Ashizawa
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States
- Department of Chemistry, Boston University, Boston, MA 02215, United States
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Andreani J, Quignot C, Guerois R. Structural prediction of protein interactions and docking using conservation and coevolution. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2020. [DOI: 10.1002/wcms.1470] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Jessica Andreani
- Université Paris‐Saclay CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC) Gif‐sur‐Yvette France
| | - Chloé Quignot
- Université Paris‐Saclay CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC) Gif‐sur‐Yvette France
| | - Raphael Guerois
- Université Paris‐Saclay CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC) Gif‐sur‐Yvette France
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