77 citations · 142 across the 10 of their papers we have counts for
11 papers
Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction
Thomas Egg, Harry Winston Sullivan, Maya M. Martirossyan +8
Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models are a promising approach for…
The Role of Concentration in Determining NaCl Nucleation Mechanism: A Story of Pathways Coexistence
Porhouy Minh, Sapna Sarupria
Deciphering the microscopic details of crystal nucleation remains a key open problem in chemical physics. For aqueous sodium chloride (NaCl), the extent to which nucleation involve…
Path Sampling for Rare Events Boosted by Machine Learning
Porhouy Minh, Sapna Sarupria
The study by Jung et al. (Jung H, Covino R, Arjun A, et al., Nat Comput Sci. 3:334-345 (2023)) introduced Artificial Intelligence for Molecular Mechanism Discovery (AIMMD), a novel…
Thermodynamic Basis of Sugar-Dependent Polymer Stabilization: Informing Biologic Formulation Design
Praveen Muralikrishnan, Jonathan W. P. Zajac, Caryn L. Heldt +2
The stabilization of macromolecules is fundamental to developing biological formulations, such as vaccines and protein therapeutics. In this study, we employ coarse grained polymer…
Crystal Nucleation Kinetics and Mechanism: Influence of Interaction Potential
Porhouy Minh, Steven W. Hall, Ryan S. DeFever +1
Modulating liquid-to-solid transitions and the resulting crystalline structure for tailored properties is much desired. Colloidal systems are exemplary to this end, but the fundame…
Impact of Co-Excipient Selection on Hydrophobic Polymer Folding: Insights for Optimal Formulation Design
Jonathan W. P. Zajac, Praveen Muralikrishnan, Caryn L. Heldt +2
The stabilization of liquid biological products is a complex task that depends on the chemical composition of both the active ingredient and any excipients in solution. Frequently,…
LeaPP: Learning Pathways to Polymorphs through machine learning analysis of atomic trajectories
Steven W. Hall, Porhouy Minh, Sapna Sarupria
Understanding the mechanisms underlying crystal formation is crucial. For most systems, crystallization typically goes through a nucleation process that involves dynamics that happ…
Flipping Out: Role of Arginine in Hydrophobic Interactions and Biological Formulation Design
Jonathan W. P. Zajac, Praveen Muralikrishnan, Idris Tohidian +4
Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we…
Practical guide to replica exchange transition interface sampling and forward flux sampling
Steven W. Hall, Grisell Díaz Leines, Sapna Sarupria +1
Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of so-called rare events that are characterized by transitions between metastable state…
Contour forward flux sampling: Sampling rare events along multiple collective variables
Ryan S. DeFever, Sapna Sarupria
Many rare event transitions involve multiple collective variables (CVs) and the most appropriate combination of CVs is generally unknown a priori. We thus introduce a new method, c…
Suppression of Sub-surface Freezing in Free-Standing Thin Films of a Coarse-grained Model of Water
Amir Haji-Akbari, Ryan S. DeFever, Sapna Sarupria +1
Freezing in the vicinity of water-vapor interfaces is of considerable interest to a wide range of disciplines, most notably the atmospheric sciences. In this work, we use molecular…