AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …

The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …

By focusing on essential features, while averaging over less important details, coarse-
grained (CG) models provide significant computational and conceptual advantages with …

The “protein folding problem” consists of three closely related puzzles:(a) What is the folding
code?(b) What is the folding mechanism?(c) Can we predict the native structure of a protein …

Lattice protein folding models are a cornerstone of computational biophysics. Although
these models are a coarse grained representation, they provide useful insight into the …

The molecular details involved in the folding, dynamics, organization, and interaction of
proteins with other molecules are often difficult to assess by experimental techniques …

Electrostatics plays a fundamental role in virtually all processes involving biomolecules in
solution. The Poisson–Boltzmann equation constitutes one of the most fundamental …

The difficulty of simulating quantum systems, well known to quantum chemists, prompted the
idea of quantum computation. One can avoid the steep scaling associated with the exact …

Recognition and binding of specific sites on DNA by proteins is central for many cellular
functions such as transcription, replication, and recombination. In the process of recognition …

In this paper, the fundamental concepts and equations necessary for performing small angle
X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS …