Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering

Molecular mechanisms for stabilizing biologics in the solid state

Protein drugs exhibit challenges of biophysical and biochemical instability due to their structural complexity and rich dynamics. Solid-state biologics aim to enhance stability by increasing molecular rigidity within the formulation matrix, representing a primary category of drug products alongside sterile liquid formulations. Understanding the molecular mechanisms behind the stabilization and destabilization of protein drugs, influenced by formulation composition and drying processes, provides scientific rationale for drug product design. This review aims to elaborate on the two primary models of water-to-sugar substitution and matrix vitrification, respectively, via thermodynamic and kinetic stabilization. It offers an up-to-date review of experimental investigations into these hypotheses, specifically elucidating protein structure and protein-excipient interactions at the molecular level, molecular dynamics across a broad range of motion regimes, and microscopic attributes such as protein-sugar and protein-salt miscibility and microenvironmental acidity, in relevant liquid, frozen, and solid states, using advanced biophysical techniques for solid-state analysis. Moreover, we discuss how these mechanistic understandings facilitate the investigation and prediction of critical stability behaviors and enables the design of solid biological drug products.

Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches

Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.

Semi-rational design of nitroarene dioxygenase for catalytic ability toward 2,4-dichloronitrobenzene

Rieske non-heme dioxygenase family enzymes play an important role in the aerobic biodegradation of nitroaromatic pollutants, but no active dioxygenases are available in nature for initial reactions in the degradation of many refractory pollutants like 2,4-dichloronitrobenzene (24DCNB). Here, we report the engineering of hotspots in 2,3-dichloronitrobenzene dioxygenase from Diaphorobacter sp. strain JS3051, achieved through molecular dynamic simulation analysis and site-directed mutagenesis, with the aim of enhancing its catalytic activity toward 24DCNB. The computationally predicted activity scores were largely consistent with the detected activities in wet experiments. Among them, the two most beneficial mutations (E204M and M248I) were obtained, and the combined mutant reached up to a 62-fold increase in activity toward 24DCNB, generating a single product, 3,5-dichlorocatechol, which is a naturally occurring compound. In silico analysis confirmed that residue 204 affected the substrate preference for meta-substituted nitroarenes, while residue 248 may influence substrate preference by interaction with residue 295. Overall, this study provides a framework for manipulating nitroarene dioxygenases using computational methods to address various nitroarene contamination problems.IMPORTANCEAs a result of human activities, various nitroaromatic pollutants continue to enter the biosphere with poor degradability, and dioxygenation is an important kickoff step to remove toxic nitro-groups and convert them into degradable products. The biodegradation of many nitroarenes has been reported over the decades; however, many others still lack corresponding enzymes to initiate their degradation. Although rieske non-heme dioxygenase family enzymes play extraordinarily important roles in the aerobic biodegradation of various nitroaromatic pollutants, prediction of their substrate specificity is difficult. This work greatly improved the catalytic activity of dioxygenase against 2,4-dichloronitrobenzene by computer-aided semi-rational design, paving a new way for the evolution strategy of nitroarene dioxygenase. This study highlights the potential for using enzyme structure-function information with computational pre-screening methods to rapidly tailor the catalytic functions of enzymes toward poorly biodegradable contaminants.

Temporal Resolution of Activity-Related Solvation Dynamics in the TIM Barrel Enzyme Murine Adenosine Deaminase

Murine adenosine deaminase (mADA) is a prototypic system for studying the thermal activation of active site chemistry within the TIM barrel family of enzyme reactions. Previous temperature-dependent hydrogen deuterium exchange studies under various conditions have identified interconnected thermal networks for heat transfer from opposing protein-solvent interfaces to active site residues in mADA. One of these interfaces contains a solvent exposed helix-loop-helix moiety that presents the hydrophobic face of its long α-helix to the backside of bound substrate. Herein we pursue the time and temperature dependence of solvation dynamics at the surface of mADA, for comparison to established kinetic parameters that represent active site chemistry. We first created a modified protein devoid of native tryptophans with close to native kinetic behavior. Single site-specific tryptophan mutants were back inserted into each of the four positions where native tryptophans reside. Measurements of nanosecond fluorescence relaxation lifetimes and Stokes shift decays, that reflect time dependent environmental reoroganization around the photo-excited state of Trp*, display minimal temperature dependences. These regions serve as controls for the behavior of a new single tryptophan inserted into a solvent exposed region near the helix-loop-helix moiety located behind the bound substrate, Lys54Trp. This installed Trp displays a significantly elevated value for Ea ( k Stokes shift ) ; further, when Phe61 within the long helix positioned behind bound substrate is replaced by a series of aliphatic hydrophobic side chains, the trends in Ea ( k Stokes shift ) mirror the earlier reported impact of the same series of function-altering hydrophobic side chains on the activation energy of catalysis, Ea ( k cat ) .The reported experimental findings implicate a solvent initiated and rapid (>ns) protein restructuring that contributes to the enthalpic activation barrier to catalysis in mADA.

Human Kir2.1 Potassium Channel: Protocols for Cryo-EM Data Processing and Molecular Dynamics Simulations

Kir channels are potassium (K+) channels responsible for the mechanism of inward rectification, which plays a fundamental role in maintaining the resting membrane potential. There are seven Kir subfamilies, and their opening and closing mechanism is regulated by different regulatory factors. Genetically inherited defects in Kir channels are responsible for several rare human diseases, and for most of them, there are currently no effective therapeutic treatments. High-resolution structural information is not available for several members within the Kir subfamilies. Recently, our group achieved a significant breakthrough by utilizing cryo-EM single-particle analysis to elucidate the first structure of the human Kir2.1 channel. We present here the data processing protocol of the cryo-EM data of the human Kir2.1 channel, which is applicable to the structural determination of other ion channels by cryo-EM single-particle analysis. We also introduce a protocol designed to assess the structural heterogeneity within the cryo-EM data, allowing for the identification of other possible protein structure conformations present in the collected data. Moreover, we present a protocol for conducting all-atom molecular dynamics (MD) simulations for K+ channels, which can be incorporated into various membrane models to simulate different environments. We also propose some methods for analyzing the MD simulations, with a particular emphasis on assessing the local mobility of protein residues.

The Impact of Nε-Acryloyllysine Piperazides on the Conformational Dynamics of Transglutaminase 2

In addition to the classic functions of proteins, such as acting as a biocatalyst or binding partner, the conformational states of proteins and their remodeling upon stimulation need to be considered. A prominent example of a protein that undergoes comprehensive conformational remodeling is transglutaminase 2 (TGase 2), the distinct conformational states of which are closely related to particular functions. Its involvement in various pathophysiological processes, including fibrosis and cancer, motivates the development of theranostic agents, particularly based on inhibitors that are directed toward the transamidase activity. In this context, the ability of such inhibitors to control the conformational dynamics of TGase 2 emerges as an important parameter, and methods to assess this property are in great demand. Herein, we describe the application of the switchSENSE^® principle to detect conformational changes caused by three irreversibly binding N^ε-acryloyllysine piperazides, which are suitable radiotracer candidates of TGase 2. The switchSENSE^® technique is based on DNA levers actuated by alternating electric fields. These levers are immobilized on gold electrodes with one end, and at the other end of the lever, the TGase 2 is covalently bound. A novel computational method is introduced for describing the resulting lever motion to quantify the extent of stimulated conformational TGase 2 changes. Moreover, as a complementary biophysical method, native polyacrylamide gel electrophoresis was performed under similar conditions to validate the results. Both methods prove the occurrence of an irreversible shift in the conformational equilibrium of TGase 2, caused by the binding of the three studied N^ε-acryloyllysine piperazides.

Engineering and Design of Programmable Genome Editors

Programmable genome editors are enzymes that can be targeted to a specific location in the genome for making site-specific alterations or deletions. The engineering, design, and development of sequence-specific editors has resulted in a dramatic increase in the precision of editing for nucleotide sequences. These editors can target specific locations in a genome, in vivo. The genome editors are being deployed for the development of genetically modified organisms for agriculture and industry, and for gene therapy of inherited human genetic disorders, cancer, and immunotherapy. Experimental and computational studies of structure, binding, activity, dynamics, and folding, reviewed here, have provided valuable insights that have the potential for increasing the functional efficiency of these gene/genome editors. Biochemical and biophysical studies of the specificities of natural and engineered genome editors reveal that increased binding affinity can be detrimental because of the increase of off-target effects and that the engineering and design of genome editors with higher specificity may require modulation and control of the conformational dynamics.

Functionalization of a symmetric protein scaffold: Redundant folding nuclei and alternative oligomeric folding pathways

Successful de novo protein design ideally targets specific folding kinetics, stability thermodynamics, and biochemical functionality, and the simultaneous achievement of all these criteria in a single step design is challenging. Protein design is potentially simplified by separating the problem into two steps: (a) an initial design of a protein "scaffold" having appropriate folding kinetics and stability thermodynamics, followed by (b) appropriate functional mutation-possibly involving insertion of a peptide functional "cassette." This stepwise approach can also separate the orthogonal effects of the "stability/function" and "foldability/function" tradeoffs commonly observed in protein design. If the scaffold is a protein architecture having an exact rotational symmetry, then there is the potential for redundant folding nuclei and multiple equivalent sites of functionalization; thereby enabling broader functional adaptation. We describe such a "scaffold" and functional "cassette" design strategy applied to a β-trefoil threefold symmetric architecture and a heparin ligand functionality. The results support the availability of redundant folding nuclei within this symmetric architecture, and also identify a minimal peptide cassette conferring heparin affinity. The results also identify an energy barrier of destabilization that switches the protein folding pathway from monomeric to trimeric, thereby identifying another potential advantage of symmetric protein architecture in de novo design.

Biorecognition Engineering Technologies for Cancer Diagnosis: A Systematic Literature Review of Non-Conventional and Plausible Sensor Development Methods

Cancer is the second cause of mortality worldwide. Early diagnosis of this multifactorial disease is challenging, especially in populations with limited access to healthcare services. A vast repertoire of cancer biomarkers has been studied to facilitate early diagnosis; particularly, the use of antibodies against these biomarkers has been of interest to detect them through biorecognition. However, there are certain limitations to this approach. Emerging biorecognition engineering technologies are alternative methods to generate molecules and molecule-based scaffolds with similar properties to those presented by antibodies. Molecularly imprinted polymers, recombinant antibodies, and antibody mimetic molecules are three novel technologies commonly used in scientific studies. This review aimed to present the fundamentals of these technologies and address questions about how they are implemented for cancer detection in recent scientific studies. A systematic analysis of the scientific peer-reviewed literature regarding the use of these technologies on cancer detection was carried out starting from the year 2000 up to 2021 to answer these questions. In total, 131 scientific articles indexed in the Web of Science from the last three years were included in this analysis. The results showed that antibody mimetic molecules technology was the biorecognition technology with the highest number of reports. The most studied cancer types were: multiple, breast, leukemia, colorectal, and lung. Electrochemical and optical detection methods were the most frequently used. Finally, the most analyzed biomarkers and cancer entities in the studies were carcinoembryonic antigen, MCF-7 cells, and exosomes. These technologies are emerging tools with adequate performance for developing biosensors useful in cancer detection, which can be used to improve cancer diagnosis in developing countries.

Integrating dynamics into enzyme engineering

Enzyme engineering has become a widely adopted practice in research labs and industry. In parallel, the past decades have seen tremendous strides in characterizing the dynamics of proteins, using a growing array of methodologies. Importantly, links have been established between the dynamics of proteins and their function. Characterizing the dynamics of an enzyme prior to, and following, its engineering is beginning to inform on the potential of 'dynamic engineering', i.e. the rational modification of protein dynamics to alter enzyme function. Here we examine the state of knowledge at the intersection of enzyme engineering and protein dynamics, describe current challenges and highlight pioneering work in the nascent area of dynamic engineering.

In Silico Evaluation of Enzymatic Tunnels in the Biotransformation of α-Tocopherol Esters

Motivation: α-Tocopherol is a molecule obtained primarily from plant sources that are important for the pharmaceutical and cosmetics industry. However, this component has some limitations such as sensitivity to oxygen, presence of light, and high temperatures. For this molecule to become more widely used, it is important to carry out a structural modification so that there is better stability and thus it can carry out its activities. To carry out this structural modification, some modifications are carried out, including the application of biotransformation using enzymes as biocatalysts. Thus, the application of a computational tool that helps in understanding the transport mechanisms of molecules in the tunnels present in the enzymatic structures is of fundamental importance because it promotes a computational screening facilitating bench applications.

Objective: The aim of this work was to perform a computational analysis of the biotransformation of α-tocopherol into tocopherol esters, observing the tunnels present in the enzymatic structures as well as the energies which correspond to the transport of molecules.

Method: To carry out this work, 9 lipases from different organisms were selected; their structures were analyzed by identifying the tunnels (quantity, conformation, and possibility of transport) and later the calculations of substrate transport for the biotransformation reaction in the identified tunnels were carried out. Additionally, the transport of the product obtained in the reaction through the tunnels was also carried out.

Results: In this work, the quantity of existing tunnels in the morphological conformational characteristics in the lipases was verified. Thus, the enzymes with fewer tunnels were RML (3 tunnels), LBC and RNL (4 tunnels), PBLL (5 tunnels), CALB (6 tunnels), HLG (7 tunnels), and LCR and LTL (8 tunnels) and followed by the enzyme LPP with the largest number of tunnels (39 tunnels). However, the enzyme that was most likely to transport substrates in terms of α-tocopherol biotransformation (in relation to the E_max and E_a energies of ligands and products) was CALB, as it obtains conformational and transport characteristics of molecules with a particularity. The most conditions of transport analysis were α-tocopherol tunnel 3 (E_max: −4.6 kcal/mol; E_a: 1.1 kcal/mol), vinyl acetate tunnel 1 (E_max: −2.4 kcal/mol; E_a: 0.1 kcal/mol), and tocopherol acetate tunnel 2 (E_max: −3.7 kcal/mol; E_a: 2 kcal/mol).

Computer-aided understanding and engineering of enzymatic selectivity

Enzymes offering chemo-, regio-, and stereoselectivity enable the asymmetric synthesis of high-value chiral molecules. Unfortunately, the drawback that naturally occurring enzymes are often inefficient or have undesired selectivity toward non-native substrates hinders the broadening of biocatalytic applications. To match the demands of specific selectivity in asymmetric synthesis, biochemists have implemented various computer-aided strategies in understanding and engineering enzymatic selectivity, diversifying the available repository of artificial enzymes. Here, given that the entire asymmetric catalytic cycle, involving precise interactions within the active pocket and substrate transport in the enzyme channel, could affect the enzymatic efficiency and selectivity, we presented a comprehensive overview of the computer-aided workflow for enzymatic selectivity. This review includes a mechanistic understanding of enzymatic selectivity based on quantum mechanical calculations, rational design of enzymatic selectivity guided by enzyme-substrate interactions, and enzymatic selectivity regulation via enzyme channel engineering. Finally, we discussed the computational paradigm for designing enzyme selectivity in silico to facilitate the advancement of asymmetric biosynthesis.

Computational Enzyme Engineering Pipelines for Optimized Production of Renewable Chemicals

To enable a sustainable supply of chemicals, novel biotechnological solutions are required that replace the reliance on fossil resources. One potential solution is to utilize tailored biosynthetic modules for the metabolic conversion of CO₂ or organic waste to chemicals and fuel by microorganisms. Currently, it is challenging to commercialize biotechnological processes for renewable chemical biomanufacturing because of a lack of highly active and specific biocatalysts. As experimental methods to engineer biocatalysts are time- and cost-intensive, it is important to establish efficient and reliable computational tools that can speed up the identification or optimization of selective, highly active, and stable enzyme variants for utilization in the biotechnological industry. Here, we review and suggest combinations of effective state-of-the-art software and online tools available for computational enzyme engineering pipelines to optimize metabolic pathways for the biosynthesis of renewable chemicals. Using examples relevant for biotechnology, we explain the underlying principles of enzyme engineering and design and illuminate future directions for automated optimization of biocatalysts for the assembly of synthetic metabolic pathways.

Recent advances in user-friendly computational tools to engineer protein function

Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.

Exploring the Cold-Adaptation Mechanism of Serine Hydroxymethyltransferase by Comparative Molecular Dynamics Simulations

Cold-adapted enzymes feature a lower thermostability and higher catalytic activity compared to their warm-active homologues, which are considered as a consequence of increased flexibility of their molecular structures. The complexity of the (thermo)stability-flexibility-activity relationship makes it difficult to define the strategies and formulate a general theory for enzyme cold adaptation. Here, the psychrophilic serine hydroxymethyltransferase (pSHMT) from Psychromonas ingrahamii and its mesophilic counterpart, mSHMT from Escherichia coli, were subjected to μs-scale multiple-replica molecular dynamics (MD) simulations to explore the cold-adaptation mechanism of the dimeric SHMT. The comparative analyses of MD trajectories reveal that pSHMT exhibits larger structural fluctuations and inter-monomer positional movements, a higher global flexibility, and considerably enhanced local flexibility involving the surface loops and active sites. The largest-amplitude motion mode of pSHMT describes the trends of inter-monomer dissociation and enlargement of the active-site cavity, whereas that of mSHMT characterizes the opposite trends. Based on the comparison of the calculated structural parameters and constructed free energy landscapes (FELs) between the two enzymes, we discuss in-depth the physicochemical principles underlying the stability-flexibility-activity relationships and conclude that (i) pSHMT adopts the global-flexibility mechanism to adapt to the cold environment and, (ii) optimizing the protein-solvent interactions and loosening the inter-monomer association are the main strategies for pSHMT to enhance its flexibility.

Alpha-Carbonic Anhydrases from Hydrothermal Vent Sources as Potential Carbon Dioxide Sequestration Agents: In Silico Sequence, Structure and Dynamics Analyses

With the increase in CO2 emissions worldwide and its dire effects, there is a need to reduce CO2 concentrations in the atmosphere. Alpha-carbonic anhydrases (α-CAs) have been identified as suitable sequestration agents. This study reports the sequence and structural analysis of 15 α-CAs from bacteria, originating from hydrothermal vent systems. Structural analysis of the multimers enabled the identification of hotspot and interface residues. Molecular dynamics simulations of the homo-multimers were performed at 300 K, 363 K, 393 K and 423 K to unearth potentially thermostable α-CAs. Average betweenness centrality (BC) calculations confirmed the relevance of some hotspot and interface residues. The key residues responsible for dimer thermostability were identified by comparing fluctuating interfaces with stable ones, and were part of conserved motifs. Crucial long-lived hydrogen bond networks were observed around residues with high BC values. Dynamic cross correlation fortified the relevance of oligomerization of these proteins, thus the importance of simulating them in their multimeric forms. A consensus of the simulation analyses used in this study suggested high thermostability for the α-CA from Nitratiruptor tergarcus. Overall, our novel findings enhance the potential of biotechnology applications through the discovery of alternative thermostable CO2 sequestration agents and their potential protein design.