Antibody modeling assessment

Almagro, Juan C.; Beavers, Mary Pat; Hernandez-Guzman, Francisco; Maier, Johannes; Shaulsky, Jodi; Butenhof, Kenneth J.; Labute, Paul; Thorsteinson, Nels; Kelly, K.; Teplyakov, A.; Luo, Jinquan; Sweet, Raymond W.; Gilliland, Gary L.

doi:10.1002/prot.23130

Cited by 126 publications

(118 citation statements)

References 33 publications

Supporting

Mentioning

117

Contrasting

Order By: Relevance

“…The accuracy of homology modeling is highly dependent on the sequence similarity of the structural template(s) used, and for mAb variable domains, the framework modeling is generally successful (backbone RMSD < 1), as are the LC CDRs and HC CDRs 1 and 2. The CDR-H3 accuracy varies in homology modeling and this, 26,27 as well as sidechain conformational variation, can explain why the MD averaging improves experimental predictions. The conformational ensemble produced by LowModeMD likely smoothes out sensitivity in homology modeling, reducing error, especially when template quality is poor.…”

Section: Discussionmentioning

confidence: 99%

Homology modeling and structure-based design improve hydrophobic interaction chromatography behavior of integrin binding antibodies

Jetha

Thorsteinson²,

Jmeian

et al. 2018

mAbs

Self Cite

View full text Add to dashboard Cite

Monoclonal antibody (mAb) candidates from high-throughput screening or binding affinity optimization often contain mutations leading to liabilities for further development of the antibody, such as aggregation-prone regions and lack of solubility. In this work, we optimized a candidate integrin α11-binding mAb for developability using molecular modeling, rational design, and hydrophobic interaction chromatography (HIC). A homology model of the parental mAb Fv region was built, and this revealed hydrophobic patches on the surface of the complementarity-determining region loops. A series of 97 variants of the residues primarily responsible for the hydrophobic patches were expressed and their HIC retention times (RT) were measured. As intended, many of the computationally designed variants reduced the HIC RT compared to the parental mAb, and mutating residues that contributed most to hydrophobic patches had the greatest effect on HIC RT. A retrospective analysis was then performed where 3-dimentional protein property descriptors were evaluated for their ability to predict HIC RT using the current series of mAbs. The same descriptors were used to train a simple multi-parameter protein quantitative structure-property relationship model on this data, producing an improved correlation. We also extended this analysis to recently published HIC data for 137 clinical mAb candidates as well as 31 adnectin variants, and found that the surface area of hydrophobic patches averaged over a molecular dynamics sample consistently correlated to the experimental data across a diverse set of biotherapeutics.

show abstract

Section: Discussionmentioning

confidence: 99%

Homology modeling and structure-based design improve hydrophobic interaction chromatography behavior of integrin binding antibodies

Jetha

Thorsteinson²,

Jmeian

et al. 2018

mAbs

Self Cite

View full text Add to dashboard Cite

show abstract

“…Notably, this change is significantly lower than that of the other CDRs and is even smaller than the change in the FR and the constant domain (the baseline). It is not the shortest CDR, but it has the lowest number of contacts with the Ag (53), a low number of mutations during affinity maturation (55), and low structural diversity in different Abs (56). These observations may suggest that the conformational change that a CDR undergoes is related to its role in Ag binding.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Comparison of Free and Bound Antibodies Reveals Binding-Related Conformational Changes

Sela-Culang

Alon

Ofran

2012

The Journal of Immunology

106

View full text Add to dashboard Cite

To study structural changes that occur in Abs upon Ag binding, we systematically compared free and bound structures of all 141 crystal structures of the 49 Abs that were solved in these two forms. We found that many structural changes occur far from the Ag binding site. Some of them may constitute a mechanism for the recently suggested allosteric effects in Abs. Within the binding site itself, CDR-H3 is the only element that shows significant binding-related conformational changes; however, this occurs in only one third of the Abs. Beyond the binding site, Ag binding is associated with changes in the relative orientation of the H and L chains in both the variable and constant domains. An even larger change occurs in the elbow angle between the variable and the constant domains, and it is significantly larger for binding of big Ags than for binding of small ones. The most consistent and substantial conformational changes occur in a loop in the H chain constant domain. This loop is implicated in the interaction between the H and L chains, is often intrinsically disordered, and is involved in complement binding. Hence, we suggest that it may have a role in Ab function. These findings provide structural insight into the recently proposed allosteric effects in Abs.

show abstract

“…Moreover, these mispredicted cases in the CDR-H3 region are also located on very long loops (length given in brackets): M97 (11), M100b (13), M100h (16), M100i (19) and M100* (20). This suggested that the failure of the model in these cases was most likely due to uncertainty in the CDR-H3 modeling, 32,33 which would affect the features extracted from these structures.…”

Section: Resultsmentioning

confidence: 99%

“…This becomes especially important for long CDR-H3 loops, where even state-of-the art models still lack reliability. 32,33 It is also worth noting that predictive power is directly influenced by dataset size; therefore, the current model can be further improved (especially to minimize the number of false positives), with increased dataset size (specifically, liable Met) in the future. Some studies have shown that residues that fall outside of the traditionally defined CDRs can also be important to antigen binding, 37 which suggests that molecular assessment studies may need to be further extended to these residues.…”

Section: Discussionmentioning

confidence: 99%

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method

Sankar¹,

Hoi²,

Yuan

et al. 2018

mAbs

View full text Add to dashboard Cite

Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious diseases. Similar to any protein molecule, mAbs are susceptible to chemical modifications during the manufacturing process, long-term storage, and in vivo circulation that can impair their potency. One such modification is the oxidation of methionine residues. Chemical modifications that occur in the complementarity-determining regions (CDRs) of mAbs can lead to the abrogation of antigen binding and reduce the drug’s potency and efficacy. Thus, it is highly desirable to identify and eliminate any chemically unstable residues in the CDRs during the therapeutic antibody discovery process. To provide increased throughput over experimental methods, we extracted features from the mAbs’ sequences, structures, and dynamics, used random forests to identify important features and develop a quantitative and highly predictive in silico methionine oxidation model.

show abstract

Antibody modeling assessment

Cited by 126 publications

References 33 publications

Homology modeling and structure-based design improve hydrophobic interaction chromatography behavior of integrin binding antibodies

Homology modeling and structure-based design improve hydrophobic interaction chromatography behavior of integrin binding antibodies

A Systematic Comparison of Free and Bound Antibodies Reveals Binding-Related Conformational Changes

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method

Contact Info

Product

Resources

About