You can provide inputs to run_alphafold.py
in one of two ways:
- Single input file: Use the
--json_path
flag followed by the path to a single JSON file. - Multiple input files: Use the
--input_dir
flag followed by the path to a directory of JSON files.
AlphaFold 3 uses a custom JSON input format differing from the AlphaFold Server JSON input format. See below for more information.
The custom AlphaFold 3 format allows:
- Specifying protein, RNA, and DNA chains, including modified residues.
- Specifying custom multiple sequence alignment (MSA) for protein and RNA chains.
- Specifying custom structural templates for protein chains.
- Specifying ligands using Chemical Component Dictionary (CCD) codes.
- Specifying ligands using SMILES.
- Specifying ligands by defining them using the CCD mmCIF format and supplying them via the user-provided CCD.
- Specifying covalent bonds between entities.
- Specifying multiple random seeds.
The AlphaFold Server uses a separate JSON format from the one used here in the AlphaFold 3 codebase. In particular, the JSON format used in the AlphaFold 3 codebase offers more flexibility and control in defining custom ligands, branched glycans, and covalent bonds between entities.
We provide a converter in run_alphafold.py
which automatically detects the
input JSON format, denoted dialect
in the converter code. The converter
denotes the AlphaFoldServer JSON as alphafoldserver
, and the JSON format
defined here in the AlphaFold 3 codebase as alphafold3
. If the detected input
JSON format is alphafoldserver
, then the converter will translate that into
the JSON format alphafold3
.
The top-level of the alphafoldserver
JSON format is a list, allowing
specification of multiple inputs in a single JSON. In contrast, the alphafold3
JSON format requires exactly one input per JSON file. Specifying multiple inputs
in a single alphafoldserver
JSON is fully supported.
Note that the converter distinguishes between alphafoldserver
and alphafold3
JSON formats by checking if the top-level of the JSON is a list or not. In
particular, if you pass in a alphafoldserver
-style JSON without a top-level
list, then this is considered incorrect and run_alphafold.py
will raise an
error.
If the JSON in alphafoldserver
format specifies glycans, the converter will
raise an error. This is because translating glycans specified in the
alphafoldserver
format to the alphafold3
format is not currently supported.
The alphafoldserver
JSON format allows users to specify "modelSeeds": []
, in
which case a seed is chosen randomly for the user. On the other hand, the
alphafold3
format requires users to specify a seed.
The converter will choose a seed randomly if "modelSeeds": []
is set when
translating from alphafoldserver
JSON format to alphafold3
JSON format. If
seeds are specified in the alphafoldserver
JSON format, then those will be
preserved in the translation to the alphafold3
JSON format.
While AlphaFold Server treats ions and ligands as different entity types in the
JSON format, AlphaFold 3 treats ions as ligands. Therefore, to specify e.g. a
magnesium ion, one would specify it as an entity of type ligand
with
ccdCodes: ["MG"]
.
The alphafold3
JSON format requires the user to specify a unique identifier
(id
) for each entity. On the other hand, the alphafoldserver
does not allow
specification of an id
for each entity. Thus, the converter automatically
assigns one.
The converter iterates through the list provided in the sequences
field of the
alphafoldserver
JSON format, assigning an id
to each entity using the
following order ("reverse spreadsheet style"):
A, B, ..., Z, AA, BA, CA, ..., ZA, AB, BB, CB, ..., ZB, ...
For any entity with count > 1
, an id
is assigned arbitrarily to each "copy"
of the entity.
The top-level structure of the input JSON is:
{
"name": "Job name goes here",
"modelSeeds": [1, 2], # At least one seed required.
"sequences": [
{"protein": {...}},
{"rna": {...}},
{"dna": {...}},
{"ligand": {...}}
],
"bondedAtomPairs": [...], # Optional
"userCCD": "...", # Optional
"dialect": "alphafold3", # Required
"version": 2 # Required
}
The fields specify the following:
name: str
: The name of the job. A sanitised version of this name is used for naming the output files.modelSeeds: list[int]
: A list of integer random seeds. The pipeline and the model will be invoked with each of the seeds in the list. I.e. if you provide n random seeds, you will get n predicted structures, each with the respective random seed. You must provide at least one random seed.sequences: list[Protein | RNA | DNA | Ligand]
: A list of sequence dictionaries, each defining a molecular entity, see below.bondedAtomPairs: list[Bond]
: An optional list of covalently bonded atoms. These can link atoms within an entity, or across two entities. See more below.userCCD: str
: An optional string with user-provided chemical components dictionary. This is an expert mode for providing custom molecules when SMILES is not sufficient. This should also be used when you have a custom molecule that needs to be bonded with other entities - SMILES can't be used in such cases since it doesn't give the possibility of uniquely naming all atoms. It can also be used to provide a reference conformer for cases where RDKit fails to generate a conformer. See more below.dialect: str
: The dialect of the input JSON. This must be set toalphafold3
. See AlphaFold Server JSON Compatibility for more information.version: int
: The version of the input JSON. This must be set to 1 or 2. See AlphaFold Server JSON Compatibility and versions below for more information.
The top-level version
field (for the alphafold3
dialect) can be either 1
or 2
. The following features have been added in respective versions:
1
: the initial AlphaFold 3 input format.2
: added the option of specifying external MSA and templates using newly added fieldsunpairedMsaPath
,pairedMsaPath
, andmmcifPath
.
The sequences
section specifies the protein chains, RNA chains, DNA chains,
and ligands. Every entity in sequences
must have a unique ID. IDs don't have
to be sorted alphabetically.
Specifies a single protein chain.
{
"protein": {
"id": "A",
"sequence": "PVLSCGEWQL",
"modifications": [
{"ptmType": "HY3", "ptmPosition": 1},
{"ptmType": "P1L", "ptmPosition": 5}
],
"unpairedMsa": ..., # Mutually exclusive with unpairedMsaPath.
"unpairedMsaPath": ..., # Mutually exclusive with unpairedMsa.
"pairedMsa": ..., # Mutually exclusive with pairedMsaPath.
"pairedMsaPath": ..., # Mutually exclusive with pairedMsa.
"templates": [...]
}
}
The fields specify the following:
id: str | list[str]
: An uppercase letter or multiple letters specifying the unique IDs for each copy of this protein chain. The IDs are then also used in the output mmCIF file. Specifying a list of IDs (e.g.["A", "B", "C"]
) implies a homomeric chain with multiple copies.sequence: str
: The amino-acid sequence, specified as a string that uses the 1-letter standard amino acid codes.modifications: list[ProteinModification]
: An optional list of post-translational modifications. Each modification is specified using its CCD code and 1-based residue position. In the example above, we see that the first residue won't be a proline (P
) but insteadHY3
.unpairedMsa: str
: An optional multiple sequence alignment for this chain. This is specified using the A3M format (equivalent to the FASTA format, but also allows gaps denoted by the hyphen-
character). See more details below.unpairedMsaPath: str
: An optional path to a file that contains the multiple sequence alignment for this chain instead of providing it inline using theunpairedMsa
field. The path can be either absolute, or relative to the input JSON path. The file must be in the A3M format, and could be either plain text, or compressed using gzip, xz, or zstd.pairedMsa: str
: We recommend not using this optional field and using theunpairedMsa
for the purposes of pairing. See more details below.pairedMsaPath: str
: An optional path to a file that contains the multiple sequence alignment for this chain instead of providing it inline using thepairedMsa
field. The path can be either absolute, or relative to the input JSON path. The file must be in the A3M format, and could be either plain text, or compressed using gzip, xz, or zstd.templates: list[Template]
: An optional list of structural templates. See more details below.
Specifies a single RNA chain.
{
"rna": {
"id": "A",
"sequence": "AGCU",
"modifications": [
{"modificationType": "2MG", "basePosition": 1},
{"modificationType": "5MC", "basePosition": 4}
],
"unpairedMsa": ..., # Mutually exclusive with unpairedMsaPath.
"unpairedMsaPath": ... # Mutually exclusive with unpairedMsa.
}
}
The fields specify the following:
id: str | list[str]
: An uppercase letter or multiple letters specifying the unique IDs for each copy of this RNA chain. The IDs are then also used in the output mmCIF file. Specifying a list of IDs (e.g.["A", "B", "C"]
) implies a homomeric chain with multiple copies.sequence: str
: The RNA sequence, specified as a string using only the lettersA
,C
,G
,U
.modifications: list[RnaModification]
: An optional list of modifications. Each modification is specified using its CCD code and 1-based base position.unpairedMsa: str
: An optional multiple sequence alignment for this chain. This is specified using the A3M format. See more details below.unpairedMsaPath: str
: An optional path to a file that contains the multiple sequence alignment for this chain instead of providing it inline using theunpairedMsa
field. The path can be either absolute, or relative to the input JSON path. The file must be in the A3M format, and could be either plain text, or compressed using gzip, xz, or zstd.
Specifies a single DNA chain.
{
"dna": {
"id": "A",
"sequence": "GACCTCT",
"modifications": [
{"modificationType": "6OG", "basePosition": 1},
{"modificationType": "6MA", "basePosition": 2}
]
}
}
The fields specify the following:
id: str | list[str]
: An uppercase letter or multiple letters specifying the unique IDs for each copy of this DNA chain. The IDs are then also used in the output mmCIF file. Specifying a list of IDs (e.g.["A", "B", "C"]
) implies a homomeric chain with multiple copies.sequence: str
: The DNA sequence, specified as a string using only the lettersA
,C
,G
,T
.modifications: list[DnaModification]
: An optional list of modifications. Each modification is specified using its CCD code and 1-based base position.
Specifies a single ligand. Ligands can be specified using 3 different formats:
- CCD code(s). This is the easiest way to specify ligands. Supports specifying covalent bonds to other entities. CCD from 2022-09-28 is used. If multiple CCD codes are specified, you may want to specify a bond between these and/or a bond to some other entity. See the bonds section below.
- SMILES string. This enables specifying ligands that are not in CCD. If using SMILES, you cannot specify covalent bonds to other entities as these rely on specific atom names - see the next option for what to use for this case.
- User-provided CCD + custom ligand codes. This enables specifying ligands not in CCD, while also supporting specification of covalent bonds to other entities and backup reference coordinates for when RDKit fails to generate a conformer. This offers the most flexibility, but also requires careful attention to get all of the details right.
{
"ligand": {
"id": ["G", "H", "I"],
"ccdCodes": ["ATP"]
}
},
{
"ligand": {
"id": "J",
"ccdCodes": ["LIG-1337"]
}
},
{
"ligand": {
"id": "K",
"smiles": "CC(=O)OC1C[NH+]2CCC1CC2"
}
}
The fields specify the following:
id: str | list[str]
: An uppercase letter (or multiple letters) specifying the unique ID of this ligand. This ID is then also used in the output mmCIF file. Specifying a list of IDs (e.g.["A", "B", "C"]
) implies a ligand that has multiple copies.ccdCodes: list[str]
: An optional list of CCD codes. These could be either standard CCD codes, or custom codes pointing to the user-provided CCD.smiles: str
: An optional string defining the ligand using a SMILES string.
Each ligand may be specified using CCD codes or SMILES but not both, i.e. for a
given ligand, the ccdCodes
and smiles
fields are mutually exclusive.
Ions are treated as ligands, e.g. a magnesium ion would simply be a ligand with
ccdCodes: ["MG"]
.
Protein and RNA chains allow setting a custom Multiple Sequence Alignment (MSA). If not set, the data pipeline will automatically build MSAs for protein and RNA entities using Jackhmmer/Nhmmer search over genetic databases as described in the paper.
RNA unpairedMsa
can be either:
- Unset (or set explicitly to
null
). AlphaFold 3 won't build MSA for this RNA chain. - Set to an empty string (
""
). AlphaFold 3 won't build MSA and will run MSA-free for this RNA chain. - Set to a non-empty A3M string. AlphaFold 3 will use the provided MSA for this RNA chain.
For protein chains, the situation is slightly more complicated due to paired and unpaired MSA (see MSA Pairing below for more details).
The following combinations are valid for a given protein chain:
- Both
unpairedMsa
andpairedMsa
fields are unset (or explicitly set tonull
), AlphaFold 3 will build both MSAs automatically. This is the recommended option. - The
unpairedMsa
is set to to a non-empty A3M string,pairedMsa
set to an empty string (""
). AlphaFold 3 won't build MSA, will use theunpairedMsa
as is and runpairedMSA
-free. - The
pairedMsa
is set to to a non-empty A3M string,unpairedMsa
set to an empty string (""
). AlphaFold 3 won't build MSA, will use thepairedMsa
and rununpairedMSA
-free. This option is not recommended, see MSA Pairing below. - Both
unpairedMsa
andpairedMsa
fields are set to an empty string (""
). AlphaFold 3 will not build the MSA and the MSA input to the model will be just the query sequence (equivalent to running completely MSA-free). - Both
unpairedMsa
andpairedMsa
fields are set to a custom non-empty A3M string, AlphaFold 3 will use the provided MSA instead of building one as part of the data pipeline. This is considered an expert option.
Note that both unpairedMsa
and unpairedMsa
have to either be both set
(i.e. non-null
), or both unset (i.e. both null
, explicitly or implicitly).
Typically, when setting unpairedMsa
, you will set the pairedMsa
to an empty
string (""
). For example this will run the protein chain A with the given MSA,
but without any templates (template-free):
{
"protein": {
"id": "A",
"sequence": ...,
"unpairedMsa": "The A3M you want to run with",
"pairedMsa": "",
"templates": []
}
}
When setting your own MSA, you have to make sure that:
- The MSA is in the A3M format. This means adhering to the FASTA format while
also allowing lowercase characters denoting inserted residues and hyphens
(
-
) denoting gaps in sequences. - The first sequence is exactly equal to the query sequence.
- If all insertions are removed from MSA hits (i.e. all lowercase letters are removed), all sequences have exactly the same length as the query (they form an exact rectangular matrix).
MSA pairing matters only when folding multiple chains (multimers), since we need to find a way to concatenate MSAs for the individual chains along the sequence dimension. If done naively, by simply concatenating the individual MSA matrices along the sequence dimension and padding so that all MSAs have the same depth, one can end up with rows in the concatenated MSA that are formed by sequences from different organisms.
It may be desirable to ensure that across multiple chains, sequences in the MSA
that are from the same organism end up in the same MSA row. AlphaFold 3
internally achieves this by looking for the UniProt organism ID in the
pairedMsa
and pairing sequences based on this information.
We recommend users do the pairing manually or use the output of an appropriate
software and then provide the MSA using only the unpairedMsa
field. This
method gives exact control over the placement of each sequence in the MSA, as
opposed to relying on name-matching post-processing heuristics used for
pairedMsa
.
When setting unpairedMsa
manually, the pairedMsa
must be explicitly set to
an empty string (""
).
For instance, if there are two chains DEEP
and MIND
which we want to be
paired on organism A and C, we can achieve it as follows:
> query
DEEP
> match 1 (organism A)
D--P
> match 2 (organism B)
DD-P
> match 3 (organism C)
DD-P
> query
MIND
> match 1 (organism A)
M--D
> Empty hit to make sure pairing is achieved
----
> match 2 (organism C)
MIN-
The resulting MSA when chains are concatenated will then be:
> query
DEEPMIND
> match 1 + match 1
D--PM--D
> match 2 + padding
DD-P----
> match 3 + match 2
DD-PMIN-
Structural templates can be specified only for protein chains:
"templates": [
{
"mmcif": ..., # Mutually exclusive with mmcifPath.
"mmcifPath": ..., # Mutually exclusive with mmcif.
"queryIndices": [0, 1, 2, 4, 5, 6],
"templateIndices": [0, 1, 2, 3, 4, 8]
}
]
The fields specify the following:
mmcif: str
: A string containing the single chain protein structural template in the mmCIF format.mmcifPath: str
: An optional path to a file that contains the mmCIF with the structural template instead of providing it inline using themmcifPath
field. The path can be either absolute, or relative to the input JSON path. The file must be in the A3M format, and could be either plain text, or compressed using gzip, xz, or zstd.queryIndices: list[int]
: O-based indices in the query sequence, defining the mapping from query residues to template residues.templateIndices: list[int]
: O-based indices in the template sequence, defining the mapping from query residues to template residues.
A template is specified as an mmCIF string containing a single chain with the
structural template together with a 0-based mapping that maps query residue
indices to the template residue indices. The mapping is specified using two
lists of the same length. E.g. to express a mapping {0: 0, 1: 2, 2: 5, 3: 6}
,
you would specify the two indices lists as:
"queryIndices": [0, 1, 2, 3],
"templateIndices": [0, 2, 5, 6]
You can provide multiple structural templates. Note that if an mmCIF containing more than one chain is provided, you will get an error since it is not possible to determine which of the chains should be used as the template.
You can run template-free (but still run genetic search and build MSA) by
setting templates to []
and either explicitly setting both unpairedMsa
and
pairedMsa
to null
:
"protein": {
"id": "A",
"sequence": ...,
"pairedMsa": null,
"unpairedMsa": null,
"templates": []
}
Or you can simply fully omit them:
"protein": {
"id": "A",
"sequence": ...,
"templates": []
}
You can also run with pre-computed MSA, but let AlphaFold 3 search for
templates. This can be achieved by setting unpairedMsa
and pairedMsa
, but
keeping templates unset (or set to null
). The profile given as an input to
Hmmsearch when searching for templates will be built from the provided
unpairedMsa
:
"protein": {
"id": "A",
"sequence": ...,
"unpairedMsa": ...,
"pairedMsa": ...,
"templates": null
}
Or you can simply fully omit the templates
field thus setting it implicitly to
null
:
"protein": {
"id": "A",
"sequence": ...,
"unpairedMsa": ...,
"pairedMsa": ...,
}
To manually specify covalent bonds, use the bondedAtomPairs
field. This is
intended for modelling covalent ligands, and for defining multi-CCD ligands
(e.g. glycans). Defining covalent bonds between or within polymer entities is
not currently supported.
Bonds are specified as pairs of (source atom, destination atom), with each atom being uniquely addressed using 3 fields:
- Entity ID (
str
): this corresponds to theid
field for that entity. - Residue ID (
int
): this is 1-based residue index within the chain. For single-residue ligands, this is simply set to 1. - Atom name (
str
): this is the unique atom name within the given residue. The atom name for protein/RNA/DNA residues or CCD ligands can be looked up in the CCD for the given chemical component. This also explains why SMILES ligands don't support bonds: there is no atom name that could be used to define the bond. This shortcoming can be addressed by using the user-provided CCD format (see below).
The example below shows two bonds:
"bondedAtomPairs": [
[["A", 145, "SG"], ["L", 1, "C04"]],
[["J", 1, "O6"], ["J", 2, "C1"]]
]
The first bond is between chain A, residue 145, atom SG and chain L, residue 1, atom C04. This is a typical example for a covalent ligand. The second bond is between chain J, residue 1, atom O6 and chain J, residue 2, atom C1. This bond is within the same entity and is a typical example when defining a glycan.
All bonds are implicitly assumed to be covalent bonds. Other bond types are not supported.
Glycans are bound to a protein residue, and they are typically formed of multiple chemical components. To define a glycan, define a new ligand with all of the chemical components of the glycan. Then define a bond that links the glycan to the protein residue, and all bonds that are within the glycan between its individual chemical components.
For example, to define the following glycan composed of 4 components (CMP1, CMP2, CMP3, CMP4) bound to an asparagine in a protein chain A:
⋮
ALA CMP4
| |
ASN ―― CMP1 ―― CMP2
| |
ALA CMP3
⋮
You will need to specify:
- Protein chain A.
- Ligand chain B with the 4 components.
- Bonds ASN-CMP1, CMP1-CMP2, CMP2-CMP3, CMP2-CMP4.
There are two approaches to model a custom ligand not defined in the CCD. If the ligand is not bonded to other entities, it can be defined using a SMILES string. Otherwise, it is necessary to define that particular ligand using the CCD mmCIF format.
Once defined, this ligand needs to be assigned a name that doesn't clash with
existing CCD ligand names (e.g. LIG-1
). Avoid underscores (_
) in the name,
as it could cause issues in the mmCIF format.
The newly defined ligand can then be used as a standard CCD ligand using its custom name, and bonds can be linked to it using its named atom scheme.
The user-provided CCD must be passed in the userCCD
field (in the root of the
input JSON) as a string. Note that JSON doesn't allow newlines within strings,
so newline characters (\n
) must be used to delimit lines. Single rather than
double quotes should also be used around strings like the chemical formula.
The main pieces of information used are the atom names and elements, bonds, and
also the ideal coordinates (pdbx_model_Cartn_{x,y,z}_ideal
) which essentially
serve as a structural template for the ligand if RDKit fails to generate
conformers for that ligand.
The userCCD
can also be used to redefine standard chemical components in the
CCD. This can be useful if you need to redefine the ideal coordinates.
Below is an example userCCD
redefining component X7F, which serves to
illustrate the required sections. For readability purposes, newlines have not
been replaced by \n
.
data_MY-X7F
#
_chem_comp.id MY-X7F
_chem_comp.name '5,8-bis(oxidanyl)naphthalene-1,4-dione'
_chem_comp.type non-polymer
_chem_comp.formula 'C10 H6 O4'
_chem_comp.mon_nstd_parent_comp_id ?
_chem_comp.pdbx_synonyms ?
_chem_comp.formula_weight 190.152
#
loop_
_chem_comp_atom.comp_id
_chem_comp_atom.atom_id
_chem_comp_atom.alt_atom_id
_chem_comp_atom.type_symbol
_chem_comp_atom.charge
_chem_comp_atom.pdbx_align
_chem_comp_atom.pdbx_aromatic_flag
_chem_comp_atom.pdbx_leaving_atom_flag
_chem_comp_atom.pdbx_stereo_config
_chem_comp_atom.pdbx_backbone_atom_flag
_chem_comp_atom.pdbx_n_terminal_atom_flag
_chem_comp_atom.pdbx_c_terminal_atom_flag
_chem_comp_atom.model_Cartn_x
_chem_comp_atom.model_Cartn_y
_chem_comp_atom.model_Cartn_z
_chem_comp_atom.pdbx_model_Cartn_x_ideal
_chem_comp_atom.pdbx_model_Cartn_y_ideal
_chem_comp_atom.pdbx_model_Cartn_z_ideal
_chem_comp_atom.pdbx_component_atom_id
_chem_comp_atom.pdbx_component_comp_id
_chem_comp_atom.pdbx_ordinal
MY-X7F C02 C1 C 0 1 N N N N N N 48.727 17.090 17.537 -1.418 -1.260 0.018 C02 MY-X7F 1
MY-X7F C03 C2 C 0 1 N N N N N N 47.344 16.691 17.993 -0.665 -2.503 -0.247 C03 MY-X7F 2
MY-X7F C04 C3 C 0 1 N N N N N N 47.166 16.016 19.310 0.677 -2.501 -0.235 C04 MY-X7F 3
MY-X7F C05 C4 C 0 1 N N N N N N 48.363 15.728 20.184 1.421 -1.257 0.043 C05 MY-X7F 4
MY-X7F C06 C5 C 0 1 Y N N N N N 49.790 16.142 19.699 0.706 0.032 0.008 C06 MY-X7F 5
MY-X7F C07 C6 C 0 1 Y N N N N N 49.965 16.791 18.444 -0.706 0.030 -0.004 C07 MY-X7F 6
MY-X7F C08 C7 C 0 1 Y N N N N N 51.249 17.162 18.023 -1.397 1.240 -0.037 C08 MY-X7F 7
MY-X7F C10 C8 C 0 1 Y N N N N N 52.359 16.893 18.837 -0.685 2.443 -0.057 C10 MY-X7F 8
MY-X7F C11 C9 C 0 1 Y N N N N N 52.184 16.247 20.090 0.679 2.445 -0.045 C11 MY-X7F 9
MY-X7F C12 C10 C 0 1 Y N N N N N 50.899 15.876 20.515 1.394 1.243 -0.013 C12 MY-X7F 10
MY-X7F O01 O1 O 0 1 N N N N N N 48.876 17.630 16.492 -2.611 -1.301 0.247 O01 MY-X7F 11
MY-X7F O09 O2 O 0 1 N N N N N N 51.423 17.798 16.789 -2.752 1.249 -0.049 O09 MY-X7F 12
MY-X7F O13 O3 O 0 1 N N N N N N 50.710 15.236 21.750 2.750 1.257 -0.001 O13 MY-X7F 13
MY-X7F O14 O4 O 0 1 N N N N N N 48.229 15.189 21.234 2.609 -1.294 0.298 O14 MY-X7F 14
MY-X7F H1 H1 H 0 1 N N N N N N 46.487 16.894 17.367 -1.199 -3.419 -0.452 H1 MY-X7F 15
MY-X7F H2 H2 H 0 1 N N N N N N 46.178 15.732 19.640 1.216 -3.416 -0.429 H2 MY-X7F 16
MY-X7F H3 H3 H 0 1 N N N N N N 53.348 17.177 18.511 -1.221 3.381 -0.082 H3 MY-X7F 17
MY-X7F H4 H4 H 0 1 N N N N N N 53.040 16.041 20.716 1.212 3.384 -0.062 H4 MY-X7F 18
MY-X7F H5 H5 H 0 1 N N N N N N 50.579 17.904 16.365 -3.154 1.271 0.830 H5 MY-X7F 19
MY-X7F H6 H6 H 0 1 N N N N N N 49.785 15.059 21.877 3.151 1.241 -0.880 H6 MY-X7F 20
#
loop_
_chem_comp_bond.comp_id
_chem_comp_bond.atom_id_1
_chem_comp_bond.atom_id_2
_chem_comp_bond.value_order
_chem_comp_bond.pdbx_aromatic_flag
_chem_comp_bond.pdbx_stereo_config
_chem_comp_bond.pdbx_ordinal
MY-X7F O01 C02 DOUB N N 1
MY-X7F O09 C08 SING N N 2
MY-X7F C02 C03 SING N N 3
MY-X7F C02 C07 SING N N 4
MY-X7F C03 C04 DOUB N N 5
MY-X7F C08 C07 DOUB Y N 6
MY-X7F C08 C10 SING Y N 7
MY-X7F C07 C06 SING Y N 8
MY-X7F C10 C11 DOUB Y N 9
MY-X7F C04 C05 SING N N 10
MY-X7F C06 C05 SING N N 11
MY-X7F C06 C12 DOUB Y N 12
MY-X7F C11 C12 SING Y N 13
MY-X7F C05 O14 DOUB N N 14
MY-X7F C12 O13 SING N N 15
MY-X7F C03 H1 SING N N 16
MY-X7F C04 H2 SING N N 17
MY-X7F C10 H3 SING N N 18
MY-X7F C11 H4 SING N N 19
MY-X7F O09 H5 SING N N 20
MY-X7F O13 H6 SING N N 21
#
_pdbx_chem_comp_descriptor.type SMILES_CANONICAL
_pdbx_chem_comp_descriptor.descriptor 'Oc1ccc(O)c2C(=O)C=CC(=O)c12'
#
An example illustrating all the aspects of the input format is provided below. Note that AlphaFold 3 won't run this input out of the box as it abbreviates certain fields and the sequences are not biologically meaningful.
{
"name": "Hello fold",
"modelSeeds": [10, 42],
"sequences": [
{
"protein": {
"id": "A",
"sequence": "PVLSCGEWQL",
"modifications": [
{"ptmType": "HY3", "ptmPosition": 1},
{"ptmType": "P1L", "ptmPosition": 5}
],
"unpairedMsa": ...,
}
},
{
"protein": {
"id": "B",
"sequence": "RPACQLW",
"templates": [
{
"mmcif": ...,
"queryIndices": [0, 1, 2, 4, 5, 6],
"templateIndices": [0, 1, 2, 3, 4, 8]
}
]
}
},
{
"dna": {
"id": "C",
"sequence": "GACCTCT",
"modifications": [
{"modificationType": "6OG", "basePosition": 1},
{"modificationType": "6MA", "basePosition": 2}
]
}
},
{
"rna": {
"id": "E",
"sequence": "AGCU",
"modifications": [
{"modificationType": "2MG", "basePosition": 1},
{"modificationType": "5MC", "basePosition": 4}
],
"unpairedMsa": ...
}
},
{
"ligand": {
"id": ["F", "G", "H"],
"ccdCodes": ["ATP"]
}
},
{
"ligand": {
"id": "I",
"ccdCodes": ["NAG", "FUC"]
}
},
{
"ligand": {
"id": "Z",
"smiles": "CC(=O)OC1C[NH+]2CCC1CC2"
}
}
],
"bondedAtomPairs": [
[["A", 1, "CA"], ["B", 1, "CA"]],
[["A", 1, "CA"], ["G", 1, "CHA"]],
[["J", 1, "O6"], ["J", 2, "C1"]]
],
"userCCD": ...,
"dialect": "alphafold3",
"version": 2
}