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1. Protein structure prediction in the era of AI: Challenges and limitations when applying to in silico force spectroscopy

   https://doi.org/10.3389/fbinf.2022.983306  

   Gomes, Priscila S.; Gomes, Diego E.; Bernardi, Rafael C. (October 2022, Frontiers in Bioinformatics)

   Mechanoactive proteins are essential for a myriad of physiological and pathological processes. Guided by the advances in single-molecule force spectroscopy (SMFS), we have reached a molecular-level understanding of how mechanoactive proteins sense and respond to mechanical forces. However, even SMFS has its limitations, including the lack of detailed structural information during force-loading experiments. That is where molecular dynamics (MD) methods shine, bringing atomistic details with femtosecond time-resolution. However, MD heavily relies on the availability of high-resolution structural data, which is not available for most proteins. For instance, the Protein Data Bank currently has 192K structures deposited, against 231M protein sequences available on Uniprot. But many are betting that this gap might become much smaller soon. Over the past year, the AI-based AlphaFold created a buzz on the structural biology field by being able to predict near-native protein folds from their sequences. For some, AlphaFold is causing the merge of structural biology with bioinformatics. Here, using an in silico SMFS approach pioneered by our group, we investigate how reliable AlphaFold structure predictions are to investigate mechanical properties of Staphylococcus bacteria adhesins proteins. Our results show that AlphaFold produce extremally reliable protein folds, but in many cases is unable to predict high-resolution protein complexes accurately. Nonetheless, the results show that AlphaFold can revolutionize the investigation of these proteins, particularly by allowing high-throughput scanning of protein structures. Meanwhile, we show that the AlphaFold results need to be validated and should not be employed blindly, with the risk of obtaining an erroneous protein mechanism. 

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2. Allosteric regulatory control in dihydrofolate reductase is revealed by dynamic asymmetry

   https://doi.org/10.1002/pro.4700  

   Kazan, I. Can; Mills, Jeremy H.; Ozkan, S. Banu (July 2023, Protein Science)

   Abstract We investigated the relationship between mutations and dynamics inEscherichia colidihydrofolate reductase (DHFR) using computational methods. Our study focused on the M20 and FG loops, which are known to be functionally important and affected by mutations distal to the loops. We used molecular dynamics simulations and developed position‐specific metrics, including the dynamic flexibility index (DFI) and dynamic coupling index (DCI), to analyze the dynamics of wild‐type DHFR and compared our results with existing deep mutational scanning data. Our analysis showed a statistically significant association between DFI and mutational tolerance of the DHFR positions, indicating that DFI can predict functionally beneficial or detrimental substitutions. We also applied an asymmetric version of our DCI metric (DCI_asym) to DHFR and found that certain distal residues control the dynamics of the M20 and FG loops, whereas others are controlled by them. Residues that are suggested to control the M20 and FG loops by our DCI_asymmetric are evolutionarily nonconserved; mutations at these sites can enhance enzyme activity. On the other hand, residues controlled by the loops are mostly deleterious to function when mutated and are also evolutionary conserved. Our results suggest that dynamics‐based metrics can identify residues that explain the relationship between mutation and protein function or can be targeted to rationally engineer enzymes with enhanced activity. 

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3. Advancing the Mechanosensitivity of Atropisomeric Diarylethene Mechanophores Through a Lever-Arm Effect

   https://doi.org/10.26434/chemrxiv-2024-smxcc-v2  

   Zhang, Cijun; Kouznetsova, Tatiana B; Zhu, Boyu; Sweeney, Liam; Lancer, Max; Gitsov, Ivan; Craig, Stephen L; Hu, Xiaoran (November 2024, Cambridge University Press)

   Understanding structure-mechanical activity relationships (SMARs) in polymer mechanochemistry is essential for the rational design of mechanophores with desired properties, yet SMARs in noncovalent mechanical transformations remain relatively underexplored. In this study, we designed a subset of diarylethene mechanophores based on a lever-arm hypothesis and systematically investigated their mechanical activity toward a noncovalent-yet-chemical conversion of atro-pisomer stereochemistry. Results from DFT calculations, single-molecule force spectroscopy (SMFS) measurements, and ultrasonication experiments collectively support the lever-arm hypothesis and confirm the exceptional sensitivity of chemo-mechanical coupling in these atropisomers. Notably, the transition force for the diarylethene M3 featuring extended 5-phenylbenzo[b]thiophene aryl groups is determined to be 131 pN ± 4 pN by SMFS. This value is lower than typically recorded for other mechanically induced chemical processes, highlighting its exceptional sensitivity to low-magnitude forces. This work contributes a fundamental understanding of chemo-mechanical coupling in atropisomeric configurational mechanophores and paves the way for designing highly sensitive mechanochemical processes that could facilitate the study of nanoscale mechanical behaviors across scientific disciplines. 

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4. Mechanical Stability of a Small, Highly-Luminescent Engineered Protein NanoLuc

   https://doi.org/10.3390/ijms22010055  

   Ding, Yue; Apostolidou, Dimitra; Marszalek, Piotr (January 2021, International Journal of Molecular Sciences)

   null (Ed.)

   NanoLuc is a bioluminescent protein recently engineered for applications in molecular imaging and cellular reporter assays. Compared to other bioluminescent proteins used for these applications, like Firefly Luciferase and Renilla Luciferase, it is ~150 times brighter, more thermally stable, and smaller. Yet, no information is known with regards to its mechanical properties, which could introduce a new set of applications for this unique protein, such as a novel biomaterial or as a substrate for protein activity/refolding assays. Here, we generated a synthetic NanoLuc derivative protein that consists of three connected NanoLuc proteins flanked by two human titin I91 domains on each side and present our mechanical studies at the single molecule level by performing Single Molecule Force Spectroscopy (SMFS) measurements. Our results show each NanoLuc repeat in the derivative behaves as a single domain protein, with a single unfolding event occurring on average when approximately 72 pN is applied to the protein. Additionally, we performed cyclic measurements, where the forces applied to a single protein were cyclically raised then lowered to allow the protein the opportunity to refold: we observed the protein was able to refold to its correct structure after mechanical denaturation only 16.9% of the time, while another 26.9% of the time there was evidence of protein misfolding to a potentially non-functional conformation. These results show that NanoLuc is a mechanically moderately weak protein that is unable to robustly refold itself correctly when stretch-denatured, which makes it an attractive model for future protein folding and misfolding studies. 

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5. The Parallel Reversible Pebbling Game: Analyzing the Post-quantum Security of iMHFs

   Blocki, Jeremiah; Holman, Blake; Lee, Seunghoon (December 2022, Theory of Cryptography Conference (TCC 2022))

   Kiltz, E. (Ed.)

   The classical (parallel) black pebbling game is a useful abstraction which allows us to analyze the resources (space, space-time, cumulative space) necessary to evaluate a function f with a static data-dependency graph G. Of particular interest in the field of cryptography are data-independent memory-hard functions fG,H which are defined by a directed acyclic graph (DAG) G and a cryptographic hash function H. The pebbling complexity of the graph G characterizes the amortized cost of evaluating fG,H multiple times as well as the total cost to run a brute-force preimage attack over a fixed domain X, i.e., given y∈{0,1}∗ find x∈X such that fG,H(x)=y. While a classical attacker will need to evaluate the function fG,H at least m=|X| times a quantum attacker running Grover’s algorithm only requires O(m−−√) blackbox calls to a quantum circuit CG,H evaluating the function fG,H. Thus, to analyze the cost of a quantum attack it is crucial to understand the space-time cost (equivalently width times depth) of the quantum circuit CG,H. We first observe that a legal black pebbling strategy for the graph G does not necessarily imply the existence of a quantum circuit with comparable complexity—in contrast to the classical setting where any efficient pebbling strategy for G corresponds to an algorithm with comparable complexity for evaluating fG,H. Motivated by this observation we introduce a new parallel reversible pebbling game which captures additional restrictions imposed by the No-Deletion Theorem in Quantum Computing. We apply our new reversible pebbling game to analyze the reversible space-time complexity of several important graphs: Line Graphs, Argon2i-A, Argon2i-B, and DRSample. Specifically, (1) we show that a line graph of size N has reversible space-time complexity at most O(N^{1+2/√logN}). (2) We show that any (e, d)-reducible DAG has reversible space-time complexity at most O(Ne+dN2^d). In particular, this implies that the reversible space-time complexity of Argon2i-A and Argon2i-B are at most O(N^2 loglogN/√logN) and O(N^2/(log N)^{1/3}), respectively. (3) We show that the reversible space-time complexity of DRSample is at most O((N^2loglog N)/log N). We also study the cumulative pebbling cost of reversible pebblings extending a (non-reversible) pebbling attack of Alwen and Blocki on depth-reducible graphs. 

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