Rafał Madaj

Applicability of AlphaFold2 in the modeling of dimeric, trimeric, and tetrameric coiled-coil domains

This paper evaluates AlphaFold2's ability to model coiled-coil domains, showing improved prediction of oligomeric states compared to previous methods.

AlphaFold2 captures the conformational landscape of the HAMP signaling domain

The paper uses AlphaFold2 to generate 5000 models of the HAMP domain, revealing its conformational variability and structural conservation across families.

Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann-fold proteins

This paper develops deep learning models to predict and design cofactor specificity in Rossmann-fold proteins, achieving nearly perfect accuracy in benchmark tests.

Target2DeNovoDrugPropMax : a novel programmatic tool incorporating deep learning and in silico methods for automated de novo drug design for any target of interest

A program to automate the discovery of drugs for West Nile and Dengue virus -- programmatic screening of over a billion compounds on PubChem, generation of drug leads and automated In Silico modelling

The paper presents a Python program that screens over a billion compounds from PubChem using machine learning to generate drug leads for Dengue and West Nile viruses, followed by automated In Silico modelling of their interactions with methyltransferase targets.

Automated identification of small drug molecules for Hepatitis C virus through a novel programmatic tool and extensive Molecular Dynamics studies of select drug candidates

The paper introduces a programmatic tool that automates drug discovery for Hepatitis C virus using machine learning and molecular dynamics simulations to identify potential drug candidates.