rmrao

rmrao

rmrao

from typing import Tuple
import torch
import torch.nn.functional as F
import itertools
from timeit import default_timer as timer


class SoftmaxWeightedMean(torch.autograd.Function):

    @staticmethod

rmrao

from pymol import preset, cmd
from glob import glob
from os.path import sep, basename
from pathlib import Path


def bns(sel: str = "bb."):
    preset.ball_and_stick(selection=sel, mode=1)

rmrao

#!/bin/bash

count_nseqs() {
    file="$1"
    if [ -f "$file" ]; then
        if [[ "$file" == *.gz ]]; then
            count=$(zcat "$file" | grep -c "^>")
        else
            count=$(grep -c "^>" "$file")
        fi

rmrao

"""
To use these, open PyMOL separately and type:

    run <path/to/this_file.py>

Alternatively, place the above command in your ~/.pymolrc file.

"""

import math

rmrao

# ESMFold2 vs AlphaFold3 antibody/nanobody-antigen docking benchmark
# 106 targets (50 antibody + 56 nanobody), bound complexes from NooriFatima/AF3_AbNb_Benchmark
# (Hitawala & Gray 2024). PDB_short = crystal PDB + Fv-copy index.
PDB_short	protein_type	n_chains	folded_len
7q6c_0	antibody	3	601
7so5_0	antibody	3	970
7t17_0	antibody	3	625
7t7b_0	antibody	3	628
7tow_0	antibody	3	465
7tow_1	antibody	3	472