Examining experimentally the "millions" of available chemical compounds with drug-like properties is a formidable task. Researchers analyze drug databases computationally, filter them based on structure, chemical characteristics, and affinities towards target proteins, and then test the final, high-affinity molecules in the laboratory. Existing scoring systems find it difficult to account for entropy and desolvation effects, despite improvements in processing power. Even though computational approaches for incorporating protein flexibility in scoring are challenging and under development, they remain a potential option for protein-ligand binding affinity estimation. Quantitative agreement between computational and experimental estimates will result from the application of a binding affinity framework based on physics and employing unique free energy calculation methodologies. A method for estimating binding affinities that takes into account the conformational dynamics of both proteins and ligands and employs improved sampling methods within a unified framework could expedite the process of locating new drug-like molecules with accurate target binding affinities in enormous databases.

In this study, we investigate in a comparative manner how a specific peptide known as the Pd4 and its two known variants may form nanoparticles both in an isolated state and when attached to the green fluorescent protein (GFPuv). More importantly, we introduce a novel computational approach to predict the trend of the size and activity of the peptide-directed nanoparticles by estimating the binding affinity of the peptide to a single ion.

I used molecular dynamics (MD) simulations to explore the differential behavior of the isolated and GFP-fused peptides and their mutants.

This work paves the way for a computational framework for engineering more efficient pH-sensing mechanosensitive channels.

Understanding the chemical basis of an engineered mechanosensitive channel's spontaneous activation. The orientation-based strategy used to generate and optimize an open model of modified MscL in this research is a promising tool for creating unknown protein states and exploring ion channel activation mechanisms. This study aids research into pH-triggered drug delivery liposomes (DDL), which use MscL as a nanovalve.

Research article:
Elucidating the molecular basis of spontaneous activation in an engineered mechanosensitive channel

YidC is a membrane protein that facilitates the insertion of newly synthesized proteins into lipid membranes. Through YidC, proteins are inserted into the lipid bilayer via the SecYEG-dependent complex. Additionally, YidC functions as a chaperone in protein folding processes. Several studies have provided evidence of its independent insertion mechanism.

The interaction of peptides with membrane lipids is significant in the biological processes. Short peptides are an excellent alternative to the immune response antibodies, and they play a very crucial role in binding, insertion, and folding of membrane proteins. The characterization of solvent dependent conformational ensemble of the peptides is required for a molecular-level understanding of the thermodynamic hydrophobicity scale. To characterize the solvent-peptide interactions, we have developed a computational procedure that allows us to accurately model the peptides in both aqueous and organic solvent conditions and determine their properties at a thermodynamic level. This study evaluates the peptide conformational dynamics at different temperatures using molecular dynamics (MD) in the explicit solvent of water and octanol to estimate the transfer free energies accurately and to predict the partition coefficients. We have used a series of equilibrium MD simulations, and alchemical free energy calculations to measure the transfer free energies within various approximations. This study sheds light on the efficiency and accuracy of several different computational strategies for the study of transfer free energies.

Conference Poster:
Developing Efficient Transfer Free Energy Calculation Methods For Hydrophobicity Predictions

The proposed research project aims to study the conformational dynamics of the complete trimeric influenza HA ectodomain for the first time at an atomic level. In particular, we will study the confor- mational changes of HA that are triggered by protonation of a highly-conserved histidine residue in the HA2 hinge region. This will be followed by an investigation of the conformational transitions of HA2 upon the full exposure to solvents due to removal of HA

Conference Poster:
Molecular Dynamics Investigation of The Ph-Dependent Influenza Hemagglutinin Conformational Changes

The proposed research project aims to study understanding how coronavirus spike glycoproteins undergo conformational changes to bind to host ACE2 receptors is key to the development of coronavirus vaccines and therapeutics, which requires a dynamic rather than a static picture to provide a reliable structure-based drug design framework. The virus that causes COVID-19, SARS-CoV-2, is more stable and slower changing than the previous form that caused the SARS outbreak in 2003, according to new computational simulations of the behavior of SARS-CoV-1 and SARS-CoV-2 spike proteins before fusion with human cell receptors.

Conference Poster:
Characterizing The Roles Of Chemomechanical Couplings In The Differential Behavior Of Sars-cov-1 And Sars-cov-2 Spike Glycoproteins