Using PyMOL as a platform for computational drug design
PyMOL, a cross‐platform molecular graphics tool, has been widely used for three‐
dimensional (3D) visualization of proteins, nucleic acids, small molecules, electron …
dimensional (3D) visualization of proteins, nucleic acids, small molecules, electron …
A review of methods available to estimate solvent-accessible surface areas of soluble proteins in the folded and unfolded states
S Ausaf Ali, M Imtaiyaz Hassan, A Islam… - Current Protein and …, 2014 - benthamdirect.com
Solvent accessible surface area (SASA) of proteins has always been considered as a
decisive factor in protein folding and stability studies. It is defined as the surface …
decisive factor in protein folding and stability studies. It is defined as the surface …
AlphaFill: enriching AlphaFold models with ligands and cofactors
Artificial intelligence-based protein structure prediction approaches have had a
transformative effect on biomolecular sciences. The predicted protein models in the …
transformative effect on biomolecular sciences. The predicted protein models in the …
Mega-scale experimental analysis of protein folding stability in biology and design
Advances in DNA sequencing and machine learning are providing insights into protein
sequences and structures on an enormous scale. However, the energetics driving folding …
sequences and structures on an enormous scale. However, the energetics driving folding …
Protein sequence analysis using the MPI bioinformatics toolkit
Abstract The MPI Bioinformatics Toolkit (https://toolkit. tuebingen. mpg. de) provides
interactive access to a wide range of the best‐performing bioinformatics tools and …
interactive access to a wide range of the best‐performing bioinformatics tools and …
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
In the field of artificial intelligence, a combination of scale in data and model capacity
enabled by unsupervised learning has led to major advances in representation learning and …
enabled by unsupervised learning has led to major advances in representation learning and …
Evaluating protein transfer learning with TAPE
Protein modeling is an increasingly popular area of machine learning research. Semi-
supervised learning has emerged as an important paradigm in protein modeling due to the …
supervised learning has emerged as an important paradigm in protein modeling due to the …
PremPS: Predicting the impact of missense mutations on protein stability
Y Chen, H Lu, N Zhang, Z Zhu, S Wang… - PLoS computational …, 2020 - journals.plos.org
Computational methods that predict protein stability changes induced by missense
mutations have made a lot of progress over the past decades. Most of the available methods …
mutations have made a lot of progress over the past decades. Most of the available methods …
PrankWeb: a web server for ligand binding site prediction and visualization
PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method
for ligand binding site prediction. P2Rank is a template-free machine learning method based …
for ligand binding site prediction. P2Rank is a template-free machine learning method based …
Highly flexible ligand docking: Benchmarking of the DockThor program on the LEADS-PEP protein–peptide data set
Protein–peptide interactions play a crucial role in many cellular and biological functions,
which justify the increasing interest in the development of peptide-based drugs. However …
which justify the increasing interest in the development of peptide-based drugs. However …