Contents

3. Biomolecular Property Prediction and Analysis Tools

BioMoDes: A Repository of Tools for Biomolecular Modeling and Design

This page of BioMoDes lists state-of-the-art and emerging tools for Biomolecular Property Prediction and Analysis.


3.1. Protein Function Prediction

2024 (Click to collapse/expand)
  • TransFew: A DL model for predicting protein function from sequence.
    Posted: March 14, 2024
    Preprint | Code (GitHub)

3.2. Protein Tm Prediction

2023
  • DeepTM: A model for predicting the melting temperature of thermophilic proteins from sequence.
    Published: Nov 04, 2023
    Paper | Code (GitHub) | Webserver

3.3. Prediction of Effect of Mutations

2024
  • CarbonDesign: A protein sequence design method that adapts the success ingredients of AF2. CarbonDesign utilizes Inverseformer, a network architecture adapted from AlphaFold’s Evoformer. Based on scTM score, sequence recovery rate, and BLOSUM score, CarbonDesign outperformed other published methods, including versions of ProteinMPNN and ESM-IF, on CAMEO and CASP15 test sets, as well as RFdiffusion-generated backbones. CarbonDesign is also capable of predicting the effects of mutations on protein function.
    Published: May 23, 2024
    Paper | Preprint | Code (GitHub) | Code (Code Ocean)

  • PreMode: A method for gene-specific mode-of-action prediction for missense variants.
    Posted: March 17, 2024
    Preprint | Code (GitHub)

  • Evo: A long-context foundation model that generalizes across the central dogma of biology: DNA, RNA, and proteins. Evo is a 7 billion parameter model trained to generate DNA sequences and is capable of prediction and generative tasks, from molecules to whole genomes.
    Posted: March 06, 2024
    Preprint | Code (GitHub) | Code (PyPI) | Blog | Playground | Colab Notebook

  • PRESCOTT: A model and webserver for predicting the effect of missense mutations, that rivals AlphaMissense. PRESCOTT is a predictor that combines ESCOTT, an epistatic and structural model of mutational effects, with allele frequencies information from the Genome Aggregation Database (gnomAD). PRESCOTT identifies protein regions most susceptible to mutations, scores individual point mutations, and categorizes mutations as benign, pathogenic, and uncertain. The PRESCOTT model was built on protein structural models, human genomic and exomic data, and huge protein sequences across species.
    Posted: Feb 06, 2024
    Preprint | Code (GitLab) | Webserver | Docker Image


3.4. Binding Site Prediction

2024
2023
  • AF2BIND: A model for predicting ligand-binding residues on a target protein. AF2BIND is a logistic regression model trained using AlphaFold2’s internal pairwise representation.
    Posted: Oct 18, 2023
    Preprint | Code (GitHub) | Colab Notebook | Home

3.5. Stability Prediction

2024
  • stab_ESM-IF: This approach leveraged ESM-IF, a generative model for protein sequence, to predict absolute protein stability.
    Posted: March 15, 2024
    Preprint | Code (GitHub) | Colab Notebook

3.6. Protein-protein/-peptide Interaction Prediction and Analysis

2024
  • PPIscreenML: A classifier that uses AF2 models to distinguish interacting protein pairs from non-interacting pairs.
    Posted: March 17, 2024
    Preprint | Code (GitHub)

  • MAGPIE: An interactive tool for visualization and analysis of interactions between a protein or ligand and its binding partners. Posted: March 04, 2024
    Preprint | Code (GitHub)

  • Tapioca: A pipeline for de novo prediction of dynamic protein–protein interactions.
    Published: Feb 15, 2024
    Paper | Code (GitHub) | Webserver

  • AlphaCRV: An AlphaFold-based pipeline for accurate identification of binder topologies by clustering, ranking and visualization of models. Posted: Feb 08, 2024
    Preprint | Code (GitHub)

  • ARCTIC-3D: An automated tool and webserver to mine and rationalize protein-protein interface information for a given protein. For a given protein, ARCTIC-3D retrieves existing interface information from the PDBe-graph database, and then applies hierarchical clustering on calculated similarity values of interfaces projected on the protein structure. Information generated by ARCTIC-3D can be used as input restraints to docking methods like HADDOCK, and similar to AlphaLink and ColabDock (both using experimental restraints), to drive protein complex modeling with results comparable to prediction by AF-Multimer.
    Published: Jan 06, 2024
    Paper | Code (GitHub) | Webserver

2023
  • FragFold: An AlphaFold2-based method for high-throughput prediction of peptide binding to protein targets. It’s a method that was employed for high-throughput computational discovery of inhibitory protein fragments.
    Posted: Dec 20, 2023
    Preprint | Code (GitHub)

3.7. Protein Structure Quality Assessment

2024
  • ModFOLD9: A webserver for estimating local and global quality of 3D protein models.
    Published: March 11, 2024
    Paper | Webserver

3.8. Enzyme Substrate and Km Prediction

2023
  • ProSmith: A multimodal network and webserver for predicting drug-target interaction/affinity, small-molecule enzyme substrate, and enzyme Km for target substrate.
    Posted: Oct 12, 2023
    Preprint | Code (GitHub) | Webserver

3.9. pKa Prediction

2024
  • PypKa: A tool and webserver for physics-based and ML-assisted protein pKa estimation and biomolecular structure preparation. PypKa prepares input structures compatible with CHARMM, AMBER and GROMOS ffs. Two additional, alternative methods are provided for pKa estimation, including PypKa, pKAI and pKAI+
    Published: April 15, 2024
    Paper | Code (GitHub) | Webserver

  • DeepKa: A tool and webserver for protein pKa prediction.
    Published: March 26, 2024
    Paper | Code (GitHub) | Webserver

3.10. Protein Solubility and Aggregation Prediction

2024
  • Aggrescan4D: A structure-based predictor of pH-dependent protein aggregation to facilitate protein solubility engineering. Aggrescan4D builds on its predecessor, Aggrescan3D.
    Published: May 13, 2024
    Paper | Webserver

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