Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
Search Results
Now showing 1 - 2 of 2
Book Part Toward Accurate in Silico Prediction of Antigen Binding Affinities for Antibody Engineering(Academic Press Inc., 2025) Uluçay, T.; Arslan, M.; Döşeme, H.; Kalyoncu, S.; Kale, S.In clinical applications and life sciences research, antibodies represent an important diagnostic and therapeutic potential thanks to their high target affinity, specificity, and broad developability. While the antigen affinity, one of the primary success assessors of an antibody, can be measured at reasonably high precision and reliability, the scalability of the measurements can be cumbersome and limited. This is troubling because the affinity must be monitored throughout all steps of the developability approaches such as affinity maturation and humanization of an antibody. In this context, in silico approaches present a lucrative opportunity at a fraction of the cost and time typically invested in a comparable wet lab undertaking. In addition to their high-throughput potential, in silico approaches can provide an invaluable side product, i.e., identifying the molecular driving forces behind affinity. Here, we investigated the performance of six different high-throughput servers in two settings common in antibody engineering applications: (i) de novo prediction of the experimental antibody-antigen binding constants, and (ii) the free energy change in binding due to single point mutations. We find that the accuracy of these tools can be significantly low in the two regimes relevant to antibody development: (i) prediction of high-affinity binding, and (ii) prediction of favorable mutations. These issues are intricately related to the training sets used in the underlying models of these tools where high-affinity complexes and favorable point mutations are typically underrepresented. We showed that biophysical characteristics of single point mutations, especially changes in bulkiness and hydrophobicity, increase the prediction error. We argue that while the prediction of mutational impact can be predicted within one kcal per mol using re-parameterized versions of the present in silico tools, the de novo prediction of the affinity likely requires revisiting the underlying physical models behind these tools. © 2025Conference Object Dynamic Recognition of the Nucleosome Core Particle by Select Chromatin Factors(Elsevier B.V., 2025) Döseme, H.; Uluçay, T.; Kale, S.The intricate interactions between the nucleosome core particle and chromatin-binding proteins control essential biological functions templated by DNA. The nucleosome is a symmetrical and disc-shaped nucleoprotein which binds several chromatin factors in a 2:1 stoichiometry. We report computational evidence for a DNA-sequence-driven emergence of asymmetry whereby the nucleosome binding affinities of the chromatin factors are altered on each side even though the protein factors bind chemically equivalent proteinous interfaces of the nucleosome. Furthermore, none of these proteins interact directly with the nucleosomal DNA. Using atomistic molecular dynamics simulations, we surveyed five chromatin factors that are known to bind the nucleosome in a 2:1 stoichiometry. In four factors, we found that the nucleosomal gyre that binds DNA strongly is also more preferred. These factors are Sir3, PRC1, RCC1, and SAGA-DUB. However, a fifth chromatin factor, 53BP1, prefers the gyre with the weaker DNA binding with higher affinity. We argue that this tunability in nucleosome affinity could be related to the function of the chromatin interactors as 53BP1 could prefer loose DNA gyres to execute its DNA repair function. © 2025 The Authors. Published by Elsevier B.V.