A. Kolomeisky

Differences in Relevant Physicochemical Properties Correlate with Synergistic Activity of Antimicrobial Peptides

This paper develops a theoretical framework to link physicochemical properties of antimicrobial peptides with their synergistic activity, finding that less similar peptides exhibit greater synergy due to complementary antibacterial actions.

Dynamics of Single-Base Editing: Theoretical Analysis

This study theoretically analyzes the dynamics of single-base editing, showing that target and bystander products can be temporarily separated, suggesting dynamic selectivity improves precision.

Assembly of Synaptic Protein-DNA Complexes: Critical Role of Non-Specific Interactions

The paper investigates the stability of SfiI-DNA complexes using single-molecule fluorescence and develops a theoretical model to explain the role of non-specific DNA interactions in synaptic protein-DNA complex assembly.

Theoretical understanding of evolutionary dynamics on inhomogeneous networks

The paper investigates the microscopic mechanisms of mutation fixation on inhomogeneous networks, focusing on star networks, and explains fixation probabilities and times using physics-inspired free-energy landscape arguments.

Predicting Antimicrobial Activity for Untested Peptide-Based Drugs Using Collaborative Filtering and Link Prediction

This paper predicts antimicrobial activity of untested peptide-based drugs using collaborative filtering and link prediction to identify effective AMP-AMP and AMP-antibiotic combinations.

Sequence Dependent Internucleosomal Interactions Dominate Array Assembly

This study investigates how DNA sequence and internucleosomal interactions influence nucleosome array compaction using Atomic Force Microscopy and develops a theoretical model to explain the results.

DLPacker: Deep Learning for Prediction of Amino Acid Side Chain Conformations in Proteins

The paper introduces a deep learning method for predicting amino acid side chain conformations, showing significant improvements over existing physics-based methods.

Single-Cell Stochastic Modeling of the Action of Antimicrobial Peptides on Bacteria

This study develops a stochastic model to analyze how antimicrobial peptides neutralize bacteria, showing that both entry and inhibition processes are critical for their effectiveness.

Trade-Offs between Speed, Accuracy, and Dissipation in tRNAIle Aminoacylation

This study uses a stochastic model to analyze how tRNAIle aminoacylation balances speed, accuracy, and energy dissipation in E. coli, revealing an economic proofreading strategy that optimizes performance under tolerable error rates.

Kinetic control of stationary flux ratios for a wide range of biochemical processes

The paper demonstrates that steady-state flux ratios in biochemical processes are invariant to energy perturbations and controlled by kinetic factors rather than thermodynamic ones.

Mesoscopic Liquid Clusters Represent a Distinct Condensate of Mutant p53

This study investigates the phase behavior of mutant p53, showing it forms mesoscopic liquid clusters that facilitate amyloid fibril nucleation and revealing that structural destabilization drives condensation.

Mechanism of genome interrogation: How CRISPR RNA-guided Cas9 proteins locate specific targets on DNA

This paper develops a theoretical model to explain how CRISPR RNA-guided Cas9 proteins locate and cleave specific DNA targets, incorporating physical-chemical processes and experimental testable predictions.