Davit A. Potoyan

This study identifies the cytoplasmic coupling domains of TRPV1 as the temperature-responsive region using simulations and analysis of contact networks.

This paper introduces a structure-aware generative framework that integrates geometric encoding and coevolutionary constraints to map, cluster, and design protein sequences, improving homology detection and structure-guided sequence generation.

This paper introduces ALSEBO, a Bayesian optimization method for protein design that efficiently finds optimal sequences with few evaluations by leveraging coevolutionary statistics.

This study shows multi-component biomolecular condensates suppress amyloid formation by sequestering proteins, limiting their availability for fibril formation.

This study identifies molecular rules governing the formation of multiphase protein-RNA condensates and demonstrates how sequence and composition can program their architecture.

This study designs synthetic biomolecular condensates that control microtubule assembly through tunable material properties and interfacial rheology.

This study introduces FD-MD simulations to show that condensate interfaces enhance amyloid nucleation through β-motifs and molecular flux, leading to different growth morphologies and aging trajectories.

This study shows that sequence-dependent chain rigidity in coarse-grained models accurately reproduces viscoelastic properties of biomolecular condensates and reveals universal correlations between rigidity and elasticity.

This study shows how charge patterns in the H3 tail affect nucleosome condensate formation and dynamics through phase separation mechanisms.

This study uses molecular simulations to investigate how temperature and magnesium ions influence RNA phase separation, revealing sequence-specific stability and ion-dependent behavior.

This paper analyzes sequence-dynamics relationships in subtilisin-like serine proteases to understand thermal adaptation mechanisms, revealing structural features that contribute to thermophilic and psychrophilic stability.

This study uses deep learning and coevolutionary analysis to explore how sequence variation and structural dynamics influence thermal adaptation in cytosolic malate dehydrogenase.

This paper uses an energy landscape framework to analyze how low-complexity protein sequences encode material properties of biomolecular condensates, showing periodic motifs promote elasticity and random sequences promote viscosity.

This study investigates the microscopic origins of flow activation energy in biomolecular condensates using simulations, revealing its connection to sticker-sticker pair lifetimes and sequence patterns.

This study uses atomistic simulations to analyze how different amino acids interact with RNA fragments, revealing how these interactions influence protein-RNA phase separation.

This study shows how 3D genome architecture influences transcription factor movement and reduces time spent commuting between binding sites.

BIAPSS provides a web platform for analyzing sequence-dependent properties of proteins involved in liquid-liquid phase separation, offering tools for both individual and global sequence analysis.