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Related papers: Predicting biomolecular binding kinetics: A review

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Rebinding kinetics of molecular ligands plays a critical role in biomachinery, from regulatory networks to protein transcription, and is also a key factor for designing drugs and high-precision biosensors.In this study, we investigate…

Biological Physics · Physics 2018-07-12 Aykut Erbas , Monica Olvera de la Cruz , John F. Marko

A quantitative understanding of how cells interact with their extracellular matrix via molecular bonds is fundamental for many important processes in cell biology and engineering. In these interactions, the deformability of cells and matrix…

Biological Physics · Physics 2022-07-13 Qiangzeng Huang , Jizeng Wang

Kinetic rate constants fundamentally characterize the dynamics of the chemical interaction of macromolecules, and thus their study sets a major direction in experimental biochemistry. The estimation of such constants is often challenging,…

Quantitative Methods · Quantitative Biology 2017-08-04 József Vass , Sergey N. Krylov

We present a time-independent quantum formalism to describe the dynamics of molecules with permanent electric dipole moments in a two-dimensional confined geometry such as a one-dimensional optical lattice, in the presence of an electric…

Atomic Physics · Physics 2011-01-17 Goulven Quéméner , John L. Bohn

Approximate molecular calculations via standard Kohn-Sham Density Functional Theory are exactly reproduced by performing self-consistent calculations on isolated fragments via Partition Density Functional Theory [Phys. Rev. A 82, 024501…

Other Condensed Matter · Physics 2016-11-25 Jonathan Nafziger , Qin Wu , Adam Wasserman

The discerning behavior of living systems relies on accurate interactions selected from the lot of molecular collisions occurring in the cell. To ensure the reliability of interactions, binding partners are classically envisioned as finely…

Molecular Networks · Quantitative Biology 2016-09-28 Denis Michel , Benjamin Boutin , Philippe Ruelle

Compartmentalised biochemical reactions are a ubiquitous building block of biological systems. The interplay between chemical and compartmental dynamics can drive rich and complex dynamical behaviors that are difficult to analyse…

Molecular Networks · Quantitative Biology 2023-06-16 Tommaso Bianucci , Christoph Zechner

Recent advancements in protein docking site prediction have highlighted the limitations of traditional rigid docking algorithms, like PIPER, which often neglect critical stochastic elements such as solvent-induced fluctuations. These…

Quantitative Methods · Quantitative Biology 2024-12-02 Nanjie Chen , Dongliang Yu , Dmitri Beglov , Mark Kon , Julio Enrique Castrillon-Candas

Current experimental and theoretical studies on the effect of intermolecular interactions on molecular conduction appear to be in conflict with each other. In particular, some experimental results, e.g., the observation of 2-dimensional…

Mesoscale and Nanoscale Physics · Physics 2007-07-23 A. Landau , L. Kronik , A. Nitzan

The adhesion of biomembranes is mediated by the binding of membrane-anchored receptor and ligand proteins. The proteins can only bind if the separation between apposing membranes is sufficiently close to the length of the protein complexes,…

Subcellular Processes · Quantitative Biology 2019-11-22 Thomas R. Weikl , Jinglei Hu , Batuhan Kav , Bartosz Rozycki

Dynamic bonding is an essential feature of many soft materials. Molecular simulations have proven to be a powerful tool for modeling bonding kinetics and thermodynamics in these materials, providing insights into their properties that…

Soft Condensed Matter · Physics 2026-05-26 Tyla R. Holoman , B. P. Prajwal , Glen M. Hocky , Thomas M. Truskett

We present a novel machine learning approach to understanding conformation dynamics of biomolecules. The approach combines kernel-based techniques that are popular in the machine learning community with transfer operator theory for…

Computational Physics · Physics 2019-01-24 Stefan Klus , Andreas Bittracher , Ingmar Schuster , Christof Schütte

Using a simple hydrophobic/polar protein model, we perform a Monte Carlo study of the thermodynamics and kinetics of binding to a target structure for two closely related sequences, one of which has a unique folded state while the other is…

Biomolecules · Quantitative Biology 2009-11-10 Nitin Gupta , Anders Irbäck

We propose a computational method to quantitatively evaluate the systematic uncertainties that arise from undetectable sources in biological measurements using live-cell imaging techniques. We then demonstrate this method in measuring…

Quantitative Methods · Quantitative Biology 2019-07-09 Masaki Watabe , Satya N. V. Arjunan , Wei Xiang Chew , Kazunari Kaizu , Koichi Takahashi

Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein-ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein-ligand binding mode is essential.…

Biomolecules · Quantitative Biology 2023-12-20 Jintao Zhu , Zhonghui Gu , Jianfeng Pei , Luhua Lai

The time evolution of the formation probability of native bonds has been studied for designed sequences which fold fast into the native conformation. From this analysis a clear hierarchy of bonds emerge a) local, fast forming highly stable…

Condensed Matter · Physics 2009-10-31 G. Tiana , R. A. Broglia

Molecular dynamics (MD) simulations and computer-aided drug design (CADD) have advanced substantially over the past two decades, thanks to continuous computer hardware and software improvements. Given these advancements, MD simulations are…

Quantitative Methods · Quantitative Biology 2023-11-29 Mayar Ahmed , Alex M. Maldonado , Jacob D. Durrant

We investigate diffusion-limited reactions between a diffusing particle and a target site on a semiflexible polymer, a key factor determining the kinetics of DNA-protein binding and polymerization of cytoskeletal filaments. Our theory…

Soft Condensed Matter · Physics 2010-12-08 Yann von Hansen , Roland R. Netz , Michael Hinczewski

Most machine learning models for materials science rely on descriptors based on materials compositions and structures, even though the chemical bond has been proven to be a valuable concept for predicting materials properties. Over the…

As an example of topic where biology and physics meet, we present the issue of protein folding and stability, and the development of thermodynamics-based bioinformatics tools that predict the stability and thermal resistance of proteins and…

Biomolecules · Quantitative Biology 2016-03-15 Fabrizio Pucci , Marianne Rooman
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