J. B. Siegel

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

This paper fine-tunes a protein language model on a large dataset to predict protein folding stability, showing reasonable performance on small domains but limitations in generalizing to larger scaffolds.

Computationally Driven Design of Novel BACE-1 Inhibitors for Alzheimer's Disease

This study designs new BACE-1 inhibitors using computational modeling, showing improved docking scores compared to Verubecestat for Alzheimer's disease treatment.

Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: V311D, F248N, Y166H, Y166K, M221K

The paper adds functional data for five β-glucosidase B mutants to a database and evaluates their thermal stability and kinetic parameters.

Environmental impacts of cultured meat: A cradle-to-gate life cycle assessment

This study conducts a life cycle assessment of near-term cultured meat production, finding its environmental impact could be much higher than median beef production if using refined growth media.

Computationally Designed Carbonic Anhydrase Inhibitors Derived from Sulfonamides for Treatment of Glaucoma

This paper designs two novel carbonic anhydrase II inhibitors derived from sulfonamides for glaucoma treatment, showing improved docking scores compared to existing drugs.

Design of Novel Selective Serotonin Reuptake Inhibitors Using Computational Modeling Studies

This study uses computational modeling to design two novel SSRIs with higher binding affinity to hSERT than existing drugs and identifies Macaca fascicularis as a suitable preclinical model.

Computationally Guided Design of Two Novel Soluble Epoxide Hydrolase Inhibitors

This study designs two novel soluble epoxide hydrolase inhibitors using computational methods to improve binding affinity and reduce inhibitory concentration.

Computationally Guided Design of Novel Angiotensin Converting Enzyme Inhibitors

The paper designs two novel ACE inhibitors with improved properties using computational methods and identifies suitable animal models for preclinical testing.

Computational Design of Two New Vitamin K Epoxide Reductase Inhibitors

This study designs two new VKOR inhibitors using computational methods, predicting improved ADMET and binding properties over existing drugs.

Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: L171M, H178M, M221L, E406W, N160E, F415M

The paper introduces six mutants of β-glucosidase B and adds their catalytic activity and thermal stability data to the Design2Data database.

Design to Data for mutants of β-Glucosidase B from Paenibacillus polymyxa: I45K, A357S, I20A, I20V, and I20E

The paper characterizes the kinetic and thermal properties of five β-glucosidase B mutants and contributes to a growing dataset of enzyme mutation effects.

Computational design of two new soluble epoxide hydrolase (sEH) inhibitors

This study computationally designs two new soluble epoxide hydrolase (sEH) inhibitors with improved pharmacokinetic properties and docking scores compared to t-TUCB.

Techno-economic assessment of animal cell-based meat

This study assesses the economic viability of animal cell-based meat using a model based on cellular metabolism and engineering conventions, identifying key cost factors and technical requirements for profitability.

Computationally Guided Design of Novel Selective Serotonin Reuptake Inhibitors

This study designs two novel SSRIs with better docking scores than paroxetine using computational methods and identifies mice as a suitable preclinical model.

Computationally Guided Design of BCR-ABL Tyrosine Kinase Inhibitors

The paper designs two new BCR-ABL tyrosine kinase inhibitors with predicted improved binding affinity over imatinib for advanced chronic myeloid leukemia treatment.

Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: Q22T, W123R, F155G, Y169M, W438D, V401A

The paper quantifies thermal stability and catalytic efficiency of six β-glucosidase B mutants and adds the data to a dataset to improve Rosetta algorithms for protein engineering.

Evaluating molecular modeling tools for thermal stability using an independently generated dataset

The paper evaluates five computational tools for predicting thermal stability and soluble protein production in enzyme mutants using an expanded dataset of 51 β-glucosidase mutants.

Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: M319C, T431I, and K337D

The paper introduces three new mutants of β-glucosidase B to expand a dataset for training computational enzyme design algorithms and exploring structure-function relationships.

Computationally Guided Design of Dipeptidyl Peptidase-4 Inhibitors

This study designs two new DPP-4 inhibitors using computational methods, showing improved docking scores compared to anagliptin.