Sagar D. Khare

HaloMPNN: retraining ProteinMPNN on halophilic proteomes for salt-tolerant enzyme design

This paper retrained ProteinMPNN on halophilic proteomes to design salt-tolerant enzymes, showing HaloMPNN shifts protein properties toward halophilic traits.

Protein tertiary packing is nearly achiral

This paper investigates how chirality propagates through protein tertiary structure and introduces a geometric descriptor to quantify it, finding that tertiary packing is nearly achiral.

Combinatorial Protein Language Model-Guided Engineering of TEV Protease for Enhanced Stability and Production

This study uses three protein language models to engineer TEV protease variants with improved stability and production, showing high efficiency with fewer designs.

Graph attention with structural features improves the generalizability of identifying functional sequences at a protein interface

The paper improves prediction of functional protein interface sequences by integrating structural and sequence features using a graph attention model, achieving better generalization across diverse variants.

Constrained Diffusion for Protein Design with Hard Structural Constraints

This paper introduces a constrained diffusion framework for protein design that enforces strict structural constraints while maintaining structural diversity, achieving state-of-the-art results on motif scaffolding and pocket design tasks.

Framework for Martini-based Coarse-grained Model of Enzymes: Model Development and Experimental Validation

The paper develops and validates coarse-grained models of enzymes using a top-down approach, showing agreement between simulated and experimental structural measures.

Synergistic Multi-Pronged Interactions Mediate the Effective Inhibition of Alpha-Synuclein Aggregation by the Chaperone HtrA1

This paper shows how HtrA1* inhibits alpha-synuclein aggregation through synergistic interactions with its PDZ and Protease domains.

Prediction and Design of Protease Enzyme Specificity Using a Structure-Aware Graph Convolutional Network

This paper introduces PGCN, a structure-aware graph convolutional network for predicting protease specificity and designing proteases, showing accurate predictions and successful experimental validation.

A comprehensive survey of coronaviral main protease active site diversity in 3D: Identifying and analyzing drug discovery targets in search of broad specificity inhibitors for the next coronavirus pandemic

The paper analyzes the diversity of coronaviral main protease active sites to identify potential broad-spectrum inhibitors for future pandemics.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

The paper presents a framework for ensuring reproducibility in bio-macromolecular modeling through automated benchmarks and a test server, demonstrating its utility for Rosetta and other tools.

Computational Structure Prediction Provides a Plausible Mechanism for Electron Transfer by the Outer Membrane Protein Cyc2 from Acidithiobacillus ferrooxidans

The paper presents a computational model of the Cyc2 protein from Acidithiobacillus ferrooxidans, proposing a mechanism for ferrous iron electron transfer.

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic

The paper analyzes 3D structural changes in SARS-CoV-2 proteins during the first six months of the pandemic, showing amino acid substitutions primarily affect surfaces and boundary layers.

Mathematical models of protease-based enzymatic biosensors

This paper develops mathematical models of fast protease-based biosensors capable of Boolean logic computation using reaction conditions as tuning parameters.

Biophysical determinants of mutational robustness in a viral molecular fitness landscape

The paper maps the sequence-energetics-function relationship of the HCV NS3/4A protease, revealing mutational robustness and clustering of cleavable/uncleavable motifs.