PRODIGY: a web server for predicting the binding affinity of protein–protein complexes

Li, Xue; Rodrigues, João P. G. L. M.; Kastritis, Panagiotis L.; Bonvin, Alexandre M. J. J.; Vangone, Anna

doi:10.1093/bioinformatics/btw514

Cited by 904 publications

(843 citation statements)

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“…The docking was performed using the structures of T7L obtained from the previous step at different pH strengths and T7RNAP from our earlier work (Borkotoky S, Meena CK, Bhalerao GM, Murali A.: An in-silico glimpse into the pH dependent structural changes of T7 RNA polymerase: a protein with simplicity, Manuscript Submitted). The best-docked complexes were selected based on internal energy complex and binding energy from HADDOCK energies and binding affinities ΔG (kcal/mol) and dissociation constants K d (M) calculated from PRODIGY server [30]. This method uses a simple but robust descriptor of binding affinity based only on structural properties of a protein–protein complex (a combination of the number of contacts at the interface of a protein–protein complex and on properties of the non-interacting surface).…”

Section: Methodsmentioning

confidence: 99%

A computational assessment of pH-dependent differential interaction of T7 lysozyme with T7 RNA polymerase

Borkotoky

Murali

2017

BMC Struct Biol

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BackgroundT7 lysozyme (T7L), also known as N-acetylmuramoyl-L-alanine amidase, is a T7 bacteriophage gene product. It involves two functions: It can cut amide bonds in the bacterial cell wall and interacts with T7 RNA polymerase (T7RNAP) as a part of transcription inhibition. In this study, with the help of molecular dynamics (MD) calculations and computational interaction studies, we investigated the effect of varying pH conditions on conformational flexibilities of T7L and their influence on T7RNAP -T7L interactions.ResultsFrom the MD studies of the T7L at three different pH strengths viz. 5, neutral and 7.9 it was observed that T7L structure at pH 5 exhibited less stable nature with more residue level fluctuations, decrease of secondary structural elements and less compactness as compared to its counterparts: neutral pH and pH 7.9. The T-pad analysis of the MD trajectories identified local fluctuations in few residues that influenced the conformational differences in three pH strengths. From the docking of the minimum energy representative structures of T7L at different pH strengths (obtained from the free energy landscape analysis) with T7RNAP structures at same pH strengths, we saw strong interaction patterns at pH 7.9 and pH 5. The MD analysis of these complexes also confirmed the observations of docking study. From the combined in silico studies, it was observed that there are conformational changes in N-terminal and near helix 1 of T7L at different pH strengths, which are involved in the T7RNAP interaction, thereby varying the interaction pattern.ConclusionSince T7L has been used for developing novel therapeutics and T7RNAP one of the most biologically useful protein in both in-vitro and in vivo experiments, this in silico study of pH dependent conformational differences in T7L and the differential interaction with T7RNAP at different pH can provide a significant insight into the structural investigations on T7L and T7RNAP in varying pH environments.Electronic supplementary materialThe online version of this article (doi:10.1186/s12900-017-0077-9) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

A computational assessment of pH-dependent differential interaction of T7 lysozyme with T7 RNA polymerase

Borkotoky

Murali

2017

BMC Struct Biol

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“…When nine unique scoring functions developed for docking programs or web servers were tested on a benchmark of 81 protein complexes, correlations between scores and binding affinities were low or nonexistent ( r ranging from −0.18 to 0.32) . More recent studies utilizing supervised learning methods have increased correlations between predicted and experimental affinities, and there is still room for improvement . Prediction of changes in binding energy due to point mutations has seen greater success.…”

Section: Introductionmentioning

confidence: 99%

ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes

et al. 2017

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The ATLAS (Altered TCR Ligand Affinities and Structures) database (https://zlab.umassmed.edu/atlas/web/) is a manually curated repository containing the binding affinities for wild-type and mutant T cell receptors (TCRs) and their antigens, peptides presented by the major histocompatibility complex (pMHC). The database links experimentally measured binding affinities with the corresponding three dimensional (3D) structures for TCR-pMHC complexes. The user can browse and search affinities, structures, and experimental details for TCRs, peptides, and MHCs of interest. We expect this database to facilitate the development of next-generation protein design algorithms targeting TCR-pMHC interactions. ATLAS can be easily parsed using modeling software that builds protein structures for training and testing. As an example, we provide structural models for all mutant TCRs in ATLAS, built using the Rosetta program. Utilizing these structures, we report a correlation of 0.63 between experimentally measured changes in binding energies and our predicted changes.

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“…Modeled HCPs were docked with mAb using ClusPro 2.0 server and best docked pose as per ClusPro scoring was examined to study protein–protein interaction. Binding affinity of these complexes were calculated using PRODIGY server and the estimated Δ G and K D values for 10 HCP‐mAb complexes are shown in Figure a.…”

Section: Resultsmentioning

confidence: 99%

Understanding the mechanism of copurification of “difficult to remove” host cell proteins in rituximab biosimilar products

Singh

Mishra

Yadav

et al. 2019

Biotechnology Progress

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Host cell proteins (HCPs) are considered a critical quality attribute and are linked to safety and efficacy of biotherapeutic products. Researchers have identified 10 HCPs in Chinese hamster ovary (CHO) that exhibit common characteristics of product association, coelution, and age‐dependent expression and therefore are “difficult to remove” during downstream purification. These include cathepsin D, clusterin, galectin‐3‐binding protein, G‐protein coupled receptor 56, lipoprotein lipase, metalloproteinase inhibitor, nidogen‐1 secreted protein acidic and rich in cysteine (SPARC), sulfated glycoprotein, and insulin‐like growth factor‐2 RNA‐binding protein. While the levels of HCPs in the investigated biosimilars were within the acceptable range of <100 ppm, certain “difficult to remove” HCPs were found in the biosimilar samples. This article aims to elucidate the underlying interactions between these “difficult to remove” HCPs and the mAb product. Surface study of rituximab exhibited unstable discontinuous patches of residues on the protein surface that have high propensity to get buried and lower the solvent exposed area. The higher order structure and the receptor binding were not affected, except for one of the biosimilars, owing to extremely low‐HCP levels in its final drug product. Finally, based on the combined experimental and computational data from this study, a probable mechanism of retention for the 10 HCPs is proposed. The results presented here can guide downstream process design or avenues for protein engineering during product discovery to achieve more effective removal of the impurities.

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PRODIGY: a web server for predicting the binding affinity of protein–protein complexes

Abstract: PRODIGY is freely available at: http://milou.science.uu.nl/services/PRODIGY CONTACT: a.m.j.j.bonvin@uu.nl, a.vangone@uu.nl.

Cited by 904 publications

References 18 publications

A computational assessment of pH-dependent differential interaction of T7 lysozyme with T7 RNA polymerase

A computational assessment of pH-dependent differential interaction of T7 lysozyme with T7 RNA polymerase

ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes

Understanding the mechanism of copurification of “difficult to remove” host cell proteins in rituximab biosimilar products

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