How Robust Is the Ligand Binding Transition State?

For many drug targets, it has been shown that the kinetics of drug binding (e.g., on rate and off rate) is more predictive of drug efficacy than thermodynamic quantities alone.

Flexible Topology: A Dynamic Model of a Continuous Chemical Space.

Ligand design problems involve searching chemical space for a molecule with a set of desired properties. As chemical space is discrete, this search must be conducted in a pointwise manner, separately investigating one molecule at a time, which can be inefficient. We propose a method called "Flexible Topology", where a ligand is composed of a set of shapeshifting "ghost" atoms, whose atomic identities and connectivity can dynamically change over the course of a simulation.

Support Vector Regression-Based Monte Carlo Simulation of Flexible Water Clusters.

Molecular simulations based on classical force fields are computationally efficient but lack accuracy due to the empirical formulation of non-bonded interactions. Quantum mechanical (QM) methods, albeit accurate, have inhibitory computational costs for large molecules and clusters. Hence, to overcome the bottleneck, machine learning (ML)-based methods have been employed in the recent years.

Machine learning prediction of interaction energies in rigid water clusters.

Classical force fields form a computationally efficient avenue for calculating the energetics of large systems. However, due to the constraints of the underlying analytical form, it is sometimes not accurate enough. Quantum mechanical (QM) methods, although accurate, are computationally prohibitive for large systems.

An interaction energy driven biased sampling technique: A faster route to ionization spectra in condensed phase.

We introduce a computationally efficient approach for calculating spectroscopic properties, such as ionization energies (IEs) in the condensed phase. Discrete quantum mechanical/molecular mechanical (QM/MM) approaches for spectroscopic properties in a dynamic system, such as aqueous solution, need a large sample space to obtain converged estimates, especially for the cases where particle (electron) number is not conserved, such as IEs or electron affinities (EAs). We devise a biased sampling technique based on an approximate estimate of interaction energy between the solute and solvent, that accelerates the convergence and therefore, reduces the computational cost significantly.

Electrostatic Origin of the Red Solvatochromic Shift of DFHBDI in RNA Spinach.

Interactions with the environment tune the spectral properties of biological chromophores, e.g., fluorescent proteins.

Effect of Solvation on Electron Detachment and Excitation Energies of a Green Fluorescent Protein Chromophore Variant.

Hybrid quantum mechanics/molecular mechanics (QM/MM) is applied to the fluorinated green fluorescent protein (GFP) chromophore (DFHBDI) in its deprotonated form to understand the solvatochromic shifts in its vertical detachment energy (VDE) and vertical excitation energy (VEE). This variant of the GFP chromophore becomes fluorescent in an RNA environment and has a wide range of applications in biomedical and biochemical fields. From microsolvation studies, we benchmark (with respect to full QM) the accuracy of our QM/MM calculations with effective fragment potential (EFP) as the MM method of choice.