@article{qi_pfaendtner_2024, title={High-Throughput Computational Screening of Solid-Binding Peptides}, volume={3}, ISSN={["1549-9626"]}, DOI={10.1021/acs.jctc.3c01286}, abstractNote={Inspired by biomineralization, a naturally occurring, protein-facilitated process, solid-binding peptides (SBPs) have gained much attention for their potential to fabricate various shaped nanocrystals and hierarchical nanostructures. The advantage of SBPs over other traditionally used synthetic polymers or short ligands is their tunable interaction with the solid material surface via carefully programmed sequence and being solution-dependent simultaneously. However, designing a sequence with targeted binding affinity or selectivity often involves intensive processes such as phage display, and only a limited number of sequences can be identified. Other computational efforts have also been introduced, but the validation process remains prohibitively expensive once a suitable sequence has been identified. In this paper, we present a new model to rapidly estimate the binding free energy of any given sequence to a solid surface. We show how the overall binding of a polypeptide can be estimated from the free energy contribution of each residue based on the statistics of the thermodynamically stable structure ensemble. We validated our model using five silica-binding peptides of different binding affinities and lengths and showed that the model is accurate and robust across a wider range of chemistries and binding strengths. The computational cost of this method can be as low as 3% of the commonly used enhanced sampling scheme for similar studies and has a great potential to be used in high-throughput algorithms to obtain larger training data sets for machine learning SBP screening.}, journal={JOURNAL OF CHEMICAL THEORY AND COMPUTATION}, author={Qi, Xin and Pfaendtner, Jim}, year={2024}, month={Mar} }
 @article{torkelson_naser_qi_li_yang_pushpavanam_chen_baneyx_pfaendtner_2024, title={Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications}, volume={36}, ISSN={["1520-5002"]}, DOI={10.1021/acs.chemmater.3c02216}, abstractNote={Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. This computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.}, number={2}, journal={CHEMISTRY OF MATERIALS}, author={Torkelson, Kaylyn and Naser, Nada Y. and Qi, Xin and Li, Zhiliang and Yang, Wenchao and Pushpavanam, Karthik and Chen, Chun-Long and Baneyx, Francois and Pfaendtner, Jim}, year={2024}, month={Jan}, pages={786–794} }
 @article{zorman_phillips_shi_zhang_de yoreo_pfaendtner_2024, title={Thermodynamic Analysis of Silk Fibroin-Graphite Hybrid Materials and Their Morphology}, volume={2}, ISSN={["1520-5207"]}, DOI={10.1021/acs.jpcb.3c08147}, abstractNote={Silk fibroin (SF) is a β-sheet-rich protein that is responsible for the remarkable tensile strength of silk. In addition to its mechanical properties, SF is biocompatible and biodegradable, making it an attractive candidate for use in biotic/abiotic hybrid materials. A pairing of particular interest is the use of SF with graphene-based nanomaterials (GBNs). The properties of this interface drive the formation of well-ordered nanostructures and can improve the electronic properties of the resulting hybrid. It was previously demonstrated that SF can form lamellar nanostructures in the presence of graphite; however, the equilibrium morphology and associated driving interactions are not fully understood. In this study, we characterize these interactions between SF and SF lamellar with graphite using molecular dynamics (MD) simulations and umbrella sampling (US). We find that SF lamellar nanostructures have strong orientational and spatial preferences on graphite that are driven by the hydrophobic effect, destabilizing solvent–protein interactions and stabilizing protein–protein and protein–graphite interactions. Finally, we show how careful consideration of these underlying interactions can be applied to rationally modify the nanostructure morphology.}, journal={JOURNAL OF PHYSICAL CHEMISTRY B}, author={Zorman, Marlo and Phillips, Christian and Shi, Chenyang and Zhang, Shuai and De Yoreo, James and Pfaendtner, Jim}, year={2024}, month={Feb} }
 @article{intan_pfaendtner_2023, title={Role of Surface Features on the Initial Dissolution of CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> Perovskite in Liquid Water: An Ab Initio Molecular Dynamics Study}, volume={17}, ISSN={["1936-086X"]}, DOI={10.1021/acsnano.3c04601}, abstractNote={The degradation of CH3NH3PbI3 (MAPbI3) hybrid organic inorganic perovskite (HOIP) by water has been the major issue hampering its use in commercial perovskites solar cells (PSCs), as MAPbI3 HOIP has been known to easily degrade in the presence of water. Even though there have been numerous studies investigating this phenomenon, there is still no consensus on the mechanisms of the initial stages of dissolution. Here, we attempt to consolidate differing mechanistic interpretations previously reported in the literature through the use of the first-principles constrained ab initio molecular dynamics (AIMD) to study both the energetics and mechanisms that accompany the degradation of MAPbI3 HOIP in liquid water. By comparing the dissolution free energy barrier between surface species of different surficial types, we find that the dominant dissolution mechanisms of surface species vary widely based on the specific surface features. The high sensitivity of the dissolution mechanism to surface features has contributed to the many dissolution mechanisms proposed in the literature. In contrast, the dissolution free energy barriers are mainly determined by the dissolving species rather than the type of surfaces, and the type of surfaces the ions are dissolving from is inconsequential toward the dissolution free energy barrier. However, the presence of surface defects such as vacancy sites is found to significantly lower the dissolution free energy barriers. Based on the estimated dissolution free energy barriers, we propose that the dissolution of MAPbI3 HOIP in liquid water originates from surface defect sites that propagate laterally along the surface layer of the MAPbI3 HOIP crystal.}, number={22}, journal={ACS NANO}, author={Intan, Nadia N. and Pfaendtner, Jim}, year={2023}, month={Nov}, pages={22371–22387} }
 @article{summers_kraft_alamdari_pfaendtner_kaar_2020, title={Enhanced Activity and Stability of Acidothermus cellulolyticus Endoglucanase 1 in Ionic Liquids via Engineering Active Site Residues and Non-Native Disulfide Bridges}, volume={8}, url={http://dx.doi.org/10.1021/acssuschemeng.0c03242}, DOI={10.1021/acssuschemeng.0c03242}, abstractNote={We report the rational mutagenesis and engineering of endoglucanase 1 (E1) from Acidothermus cellulolyticus, an industrially relevant cellulase, for improved biomass conversion in ionic liquids. Th...}, number={30}, journal={ACS Sustainable Chemistry & Engineering}, publisher={American Chemical Society (ACS)}, author={Summers, Samantha and Kraft, Casey and Alamdari, Sarah and Pfaendtner, Jim and Kaar, Joel L.}, year={2020}, month={Aug}, pages={11299–11307} }
 @article{beckner_mao_pfaendtner_2018, title={Statistical models are able to predict ionic liquid viscosity across a wide range of chemical functionalities and experimental conditions}, volume={3}, url={http://dx.doi.org/10.1039/c7me00094d}, DOI={10.1039/c7me00094d}, abstractNote={Herein we present a method of developing predictive models of viscosity for ionic liquids (ILs) using publicly available data in the ILThermo database and the open-source software toolkits PyChem, RDKit, and SciKit-Learn.}, number={1}, journal={Molecular Systems Design & Engineering}, publisher={Royal Society of Chemistry (RSC)}, author={Beckner, Wesley and Mao, Coco M. and Pfaendtner, Jim}, year={2018}, pages={253–263} }
 @article{tung_pfaendtner_2016, title={Kinetics and mechanism of ionic-liquid induced protein unfolding: application to the model protein HP35}, volume={1}, url={http://dx.doi.org/10.1039/c6me00047a}, DOI={10.1039/c6me00047a}, abstractNote={We demonstrate an approach to quantify protein unfolding times using molecular simulation in a greatly accelerated manner compared to standard MD simulations, showing up to 400 fold speed increases.}, number={4}, journal={Molecular Systems Design & Engineering}, publisher={Royal Society of Chemistry (RSC)}, author={Tung, Hsin-Ju and Pfaendtner, Jim}, year={2016}, pages={382–390} }