When clicking on the liabilities tab for a particular job you'll reach the listing of all liability predictions of an antibody:
This page shows liabilities for molecules that you selected in the previous views or all of them. It lists:
- identifier: Name of the molecule
- Chain: the chain name (usually heavy or light for sequence based predictions)
- Liability Name: the liability that has been predicted
- Motif: the sequence motif used to identify the liability
- Residue: the residue name & number
- Perc Exp: proportion of the residue that is solvent exposed
- Domain: which domain the liability is on (variable, constant)
- Location: Antibody region where this liability is found with the numbering scheme you selected
- Sec Structure: the secondary structure the residue is in
- Methods: list of methods used to identify a given hit
- Remarks: High risk remarks go here if detected by underlying method
- Germline Residue the residue in the closest germline on that position
- Germline Residue Neighbours the whole sequence motive around this residue in the closest germline sequence
In the same way you can use the actions menu of the page to add / hide columns, filter or highlight rows using particular criteria that you can customize.
You also can use Actions -> Report -> Save as to save a particular view of the report either for personal use, or if saved as public for all of your colleagues (if you are power user).
When clicking in the top right field, you can now also dynamically add or drop particular molecules from your set in this report. Simply check the ones you want or uncheck all to get them all.
Method description
Liabilities are identified using sequence motives associated with checking wether the residue / motive is sufficient exposed (>10% by default). This filter is followed for some with more precise methods that validate / invalidate the liability using further descriptors from the structural analysis or classify a liability as high-risk vs not.
The methods integrated that you can see in the interface are:
aggprone
Antibody aggregation prone motifs based on 38 motifs listed in the following article: X Wang, TK Das, SK Singh, S Kumar MAbs v.1(3); May-Jun 2009. There is no exposure requirement and no risk assessment is made.
exp_deamid
Finds Asn deamidation sites based on this motif: N-[DNPTGASC]. If a structural system is input, the root residue must exceed the exposure cutoff to be counted. No risk assessment is made.
yan_deamid
Finds Asn deamidation sites according to the decision tree in Figure 6 of Q Yan, et al; Structure based prediction of asparagine deamidation propensity in monoclonal Antibodies, mAbs, 10(6), 901–912, 2018. Requires a structural system. The method computes the required residue properties on the fly but can use pred-computed ensemble-averaged properties stored in MOE database as well. A high-risk assessment may be made.
exp_isoasp
Finds Asp isomerization sites based on this motif: D-[DCSAG]. If a structural system is input, the root residue must exceed the exposure cutoff to be counted. No risk assessment is made.
yan_isoasp
Finds Asp deamidation sites in an analogous matter to how Asn deamidation sites are classified by a decision tree (Figure 6) in Q Yan, et al. Structure based prediction of asparagine deamidation propensity in monoclonal Antibodies, mAbs, 10(6), 901–912, 2018. Assumes that the loop motifs are DG, DH or DS. Requires a structural system. The method computes the required residue properties on the fly but can use pred-computed ensemble-averaged properties stored in MOE database as well. A high-risk assessment may be made assuming stressed conditions.
exp_kglycation
Finds lysine residues in antibody CDRs. If a structural system is input, the root residue must exceed the exposure cutoff to be counted. No risk assessment is made.
exp_nglyc
Finds N-linked glycosylation motifs based on this motif: N-{P}-[ST]-{P}. If a structural system is input, the root residue must exceed the exposure cutoff to be counted. No risk assessment is made.
ccg_metox
Finds reactive methionine residues based on a simple decision tree developed in house (not published). Requires a structural system to be input. This method requires ensemble-average conformations to be pre- generated. Although it will run on a static structure, the classification will not be accurate as it makes use of the frac_met_s and met_water residue properties. A high-risk assessment is made if met_water > 4 and frac_met_s > 0.4.
exp_ox
Finds oxidation prone residues: M, C or W. If a structural system is input, the root residue must exceed the exposure cutoff to be counted. No risk assessment is made.
exp_pyro
Finds N-terminal E or Q sites. If a structural system is input, the residue must exceed the exposure cutoff to be counted. No risk assessment is made.
unpaircys
Flags unpaired cysteines. Note that there is an option to ignore unpaired cysteines that have S atoms within 5 Angstroms of each other. This option is there to prevent models that don’t have all Cys residues bonded correctly.