SKEMPI 2.0: An updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation

Jankauskaite, Justina; Jiménez‐García, Brian; Dapkūnas, Justas; Fernández‐Recio, Juan; Moal, Iain H.

doi:10.1101/341735

Cited by 63 publications

(93 citation statements)

References 80 publications

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“…For the longitudinal mutant simulations, we obtained an attenuation factor on the order of 10 6 to 10 7 . This attenuation is consistent with the fact that the mutation adds bulky charged residues in place of smaller neutral ones and with the observation that the mutant cannot assemble MTs by itself (32), and it is plausible, given that single mutations are commonly observed to decrease binding affinity by 3 or more orders of magnitude (45). Even with attenuation factors that completely canceled the lateral interface contribution to binding affinity for the mutant tubulin that is present at <1% of the total, we were unable to recapitulate the decrease in growth rates observed experimentally in the presence of a small fraction of that mutant (SI Appendix, Fig.…”

Section: Analysis Of Mutant Tubulins With Perturbed Binding Interfacesupporting

confidence: 81%

Direct observation of individual tubulin dimers binding to growing microtubules

Mickolajczyk

Geyer

Kim

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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The biochemical basis of microtubule growth has remained elusive for over 30 years despite being fundamental for both cell division and associated chemotherapy strategies. Here, we combine interferometric scattering microscopy with recombinant tubulin to monitor individual tubulins binding to and dissociating from growing microtubule tips. We make direct, single-molecule measurements of tubulin association and dissociation rates. We detect two populations of transient dwell times and determine via binding-interface mutants that they are distinguished by the formation of one interprotofilament bond. Applying a computational model, we find that slow association kinetics with strong interactions along protofilaments best recapitulate our data and, furthermore, predicts plus-end tapering. Overall, we provide the most direct and complete experimental quantification of how microtubules grow to date.

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Section: Analysis Of Mutant Tubulins With Perturbed Binding Interfacesupporting

confidence: 81%

Direct observation of individual tubulin dimers binding to growing microtubules

Mickolajczyk

Geyer

Kim

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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show abstract

“…For the longitudinal mutant simulations, we obtained an attenuation factor on the order of 10 6 -10 7 . This attenuation is consistent with the observation that the double mutant cannot assemble MTs by itself (32), and is plausible given that single mutations are commonly observed to decrease binding affinity by three or more orders of magnitude (43). Even with attenuation factors that completely cancel the lateral interface contribution to binding affinity, we were unable to recapitulate the decrease in growth rates observed for that mutant (Fig S8).…”

Section: A Computational Kinetic Model Supports a Slow Tubulin On-ratsupporting

confidence: 88%

Direct observation of individual tubulin dimers binding to growing microtubules

Mickolajczyk¹,

Geyer²,

Kim³

et al. 2018

Preprint

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The biochemical basis of microtubule growth has remained elusive for over thirty years despite being fundamental for both cell division and associated chemotherapy strategies. Here, we combine interferometric scattering microscopy with recombinant tubulin to monitor individual tubulins binding to and dissociating from growing microtubule tips. We make the first direct, single-molecule measurements of tubulin on-and off-rates. We detect two populations of transient dwell times, and determine via binding-interface mutants that they are separated by the formation of inter-protofilament bonds. Applying a computational model, we find that slow association kinetics with strong interactions along protofilaments best recapitulate our data, and furthermore predict plus-end tapering. Overall, we provide the most direct and complete quantification of how microtubules grow to date. SIGNIFICANCEMicrotubule polymerization dynamics are fundamental to cell migration and cell division, where they are targets for chemotherapy drugs. Despite significant progress, the precise structural and biochemical events occurring at growing microtubule tips are not well defined, and better understanding is necessary for discriminating mechanisms of microtubule dynamics regulation in cells. Here, we visualize individual tubulin subunits reversibly and irreversibly interacting with dynamic microtubule tips, and thereby directly measure tubulin on-and off-rates. By analyzing plus-tip residence times of wild-type and mutant tubulin, we characterize the relative contributions of longitudinal (along protofilaments) and lateral (between protofilaments) bond energies to microtubule growth. This work provides insights into microtubule tip structure and potential modes of microtubule dynamics regulation.

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“…NetTree integrates the advantages of convolutional neural networks (CNN) and gradient-boosting trees (GBT), such that CNN is treated as an intermediate model that converts vectorized element-and site-specific persistent homology features into a higher-level abstract feature, and GBT uses the upstream features and other biochemistry features for prediction. The performance test of tenfold crossvalidation on the dataset (SKEMPI 2.0 [19]) carried out using gradient boosted regression trees (GBRTs). The errors with the SKEMPI2.0 dataset are 0.85 in terms of Pearson correlations coefficient (R p ) and 1.11 kcal/mol in terms of the root mean square error (RMSE) [36].…”

Section: Topology-based Machine Learning Prediction Of Protein-proteimentioning

confidence: 99%

Characterizing SARS-CoV-2 mutations in the United States

Wang

Chen

Gao

et al. 2020

Preprint

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been mutating since it was first sequenced in early January 2020. The genetic variants have developed into a few distinct clusters with different properties. Since the United States (US) has the highest number of viral infected patients globally, it is essential to understand the US SARS-CoV-2. Using genotyping, sequence-alignment, time-evolution, k-means clustering, protein-folding stability, algebraic topology, and network theory, we reveal that the US SARS-CoV-2 has four substrains and five top US SARS-CoV-2 mutations were first detected in China (2 cases), Singapore (2 cases), and the United Kingdom (1 case). The next three top US SARS-CoV-2 mutations were first detected in the US. These eight top mutations belong to two disconnected groups. The first group consisting of 5 concurrent mutations is prevailing, while the other group with three concurrent mutations gradually fades out. We identify that one of the top mutations, 27964C>T-(S24L) on ORF8, has an unusually strong gender dependence. Based on the analysis of all mutations on the spike protein, we further uncover that three of four US SASR-CoV-2 substrains become more infectious. Our study calls for effective viral control and containing strategies in the US.

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SKEMPI 2.0: An updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation

Cited by 63 publications

References 80 publications

Direct observation of individual tubulin dimers binding to growing microtubules

Direct observation of individual tubulin dimers binding to growing microtubules

Direct observation of individual tubulin dimers binding to growing microtubules

Characterizing SARS-CoV-2 mutations in the United States

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