bio-structural-biology-modern-structure-prediction

Model Comparison

Model	Complexes	Ligands	Speed	Access
AlphaFold3	Yes	Yes	Slow	Server only (2025)
ESMFold	No	No	Fast	API or local
Chai-1	Yes	Yes	Moderate	Local or API
Boltz-1	Yes	Yes	Moderate	Local
ColabFold	No*	No	Moderate	Colab/local

*ColabFold can predict complexes with AlphaFold-Multimer.

ESMFold (Fastest Single-Chain)

Goal: Predict a protein's 3D structure from its amino acid sequence using the ESMFold language model, which requires no MSA and runs in seconds.

Approach: Submit the sequence to the ESMFold API (or run locally with the esm library), retrieve the predicted PDB coordinates, and assess per-residue confidence via pLDDT scores in the B-factor column.

Local ESMFold

import torch
import esm

def predict_esmfold_local(sequence, device='cuda'):
    '''Run ESMFold locally (requires ~16GB GPU memory)'''
    model = esm.pretrained.esmfold_v1()
    model = model.eval().to(device)

    with torch.no_grad():
        output = model.infer_pdb(sequence)
    return output