Rotamer Dynamics: Analysis of Rotamers in Molecular Dynamics Simulations of Proteins

The State-of-the-Art Overview to Application of Deep Learning in Accurate Protein Design and Structure Prediction

In recent years, there has been a notable increase in the scientific community's interest in rational protein design. The prospect of designing an amino acid sequence that can reliably fold into a desired three-dimensional structure and exhibit the intended function is captivating. However, a major challenge in this endeavor lies in accurately predicting the resulting protein structure. The exponential growth of protein databases has fueled the advancement of the field, while newly developed algorithms have pushed the boundaries of what was previously achievable in structure prediction. In particular, using deep learning methods instead of brute force approaches has emerged as a faster and more accurate strategy. These deep-learning techniques leverage the vast amount of data available in protein databases to extract meaningful patterns and predict protein structures with improved precision. In this article, we explore the recent developments in the field of protein structure prediction. We delve into the newly developed methods that leverage deep learning approaches, highlighting their significance and potential for advancing our understanding of protein design.

Identification of small molecular inhibitors of SIRT3 by computational and biochemical approaches a potential target of breast cancer

Sirtuin 3 (SIRT3) belongs to the Sirtuin protein family, which consists of NAD+-dependent lysine deacylase, involved in the regulation of various cellular activities. Dysregulation of SIRT3 activity has been linked to several types of cancer, including breast cancer. Because of its ability to stimulate adaptive metabolic pathways, it can aid in the survival and proliferation of breast cancer cells. Finding new chemical compounds targeted towards SIRT3 was the primary goal of the current investigation. Virtual screening of ~ 800 compounds using molecular docking techniques yielded 8 active hits with favorable binding affinities and poses. Docking studies verified that the final eight compounds formed stable contacts with the catalytic domain of SIRT3. Those compounds have good pharmacokinetic/dynamic properties and gastrointestinal absorption. Based on excellent pharmacokinetic and pharmacodynamic properties, two compounds (MI-44 and MI-217) were subjected to MD simulation. Upon drug interaction, molecular dynamics simulations demonstrate mild alterations in the structure of proteins and stability. Binding free energy calculations revealed that compounds MI-44 (- 45.61 ± 0.064 kcal/mol) and MI-217 (- 41.65 ± 0.089 kcal/mol) showed the maximum energy, suggesting an intense preference for the SIRT3 catalytic site for attachment. The in-vitro MTT assay on breast cancer cell line (MDA-MB-231) and an apoptotic assay for these potential compounds (MI-44/MI-217) was also performed, with flow cytometry to determine the compound's ability to cause apoptosis in breast cancer cells. The percentage of apoptotic cells (including early and late apoptotic cells) increased from 1.94% in control to 79.37% for MI-44 and 85.37% for MI-217 at 15 μM. Apoptotic cell death was effectively induced by these two compounds in a flow cytometry assay indicating them as a good inhibitor of human SIRT3. Based on our findings, MI-44 and MI-217 merit additional investigation as possible breast cancer therapeutics.

Identification of new pharmacophore against SARS-CoV-2 spike protein by multi-fold computational and biochemical techniques

COVID-19 appeared as a highly contagious disease after its outbreak in December 2019 by the virus, named SARS-CoV-2. The threat, which originated in Wuhan, China, swiftly became an international emergency. Among different genomic products, spike protein of virus plays a crucial role in the initiation of the infection by binding to the human lung cells, therefore, SARS-CoV-2's spike protein is a promising therapeutic target. Using a combination of a structure-based virtual screening and biochemical assay, this study seeks possible therapeutic candidates that specifically target the viral spike protein. A database of ~ 850 naturally derived compounds was screened against SARS-CoV-2 spike protein to find natural inhibitors. Using virtual screening and inhibitory experiments, we identified acetyl 11-keto-boswellic acid (AKBA) as a promising molecule for spike protein, which encouraged us to scan the rest of AKBA derivatives in our in-house database via 2D-similarity searching. Later 19 compounds with > 85% similarity with AKBA were selected and docked with receptor binding domain (RBD) of spike protein. Those hits declared significant interactions at the RBD interface, best possess and excellent drug-likeness and pharmacokinetics properties with high gastrointestinal absorption (GIA) without toxicity and allergenicity. Our in-silico observations were eventually validated by in vitro bioassay, interestingly, 10 compounds (A3, A4, C3, C6A, C6B, C6C, C6E, C6H, C6I, and C6J) displayed significant inhibitory ability with good percent inhibition (range: > 72-90). The compounds C3 (90.00%), C6E (91.00%), C6C (87.20%), and C6D (86.23%) demonstrated excellent anti-SARS CoV-2 spike protein activities. The docking interaction of high percent inhibition of inhibitor compounds C3 and C6E was confirmed by MD Simulation. In the molecular dynamics simulation, we observed the stable dynamics of spike protein inhibitor complexes and the influence of inhibitor binding on the protein's conformational arrangements. The binding free energy ΔGTOTAL of C3 (-38.0 ± 0.08 kcal/mol) and C6E (-41.98 ± 0.08 kcal/mol) respectively indicate a strong binding affinity to Spike protein active pocket. These findings demonstrate that these molecules particularly inhibit the function of spike protein and, therefore have the potential to be evaluated as drug candidates against SARS-CoV-2.

Sirtuin 1 inhibition: a promising avenue to suppress cancer progression through small inhibitors design

SIRT1 is a protein associated with vital cell functions such as gene regulation, metabolism, ageing, and cellular energy restoration. Its association with the tumor suppressor protein p53 is essential for controlling the growth of cells, apoptosis, and response to DNA damage. By raising p53 acetylation, encouraging apoptosis, and reducing cell proliferation, inhibiting SIRT1's catalytic domain, which interacts with p53, shows potential as a cancer treatment. The aim of the study is to find compounds that could inhibit SIRT1 and thus lower the proliferation of cancer cells. Employing molecular docking techniques, a virtual screening of ∼900 compounds (isolated from medicinal plants and derivatives) gave us 13 active compounds with good binding affinity. Additional evaluation of pharmacokinetic and pharmacodynamic properties led to the selection of eight compounds with desirable properties. Docking analysis confirmed stable interactions between the final eight compounds (C1-C8) and the SIRT1 catalytic domain. Molecular dynamics simulations show overall stability and moderate changes in protein structure upon compound binding. The compactness of the protein indicated the protein's tight packing upon the inhibitors binding. Binding free energy calculations revealed that compounds C2 (-49.96 ± 0.073 kcal/mol and C1 (-44.79 ± 0.077 kcal/mol) exhibited the highest energy, indicating strong binding affinity to the SIRT1 catalytic domain. These compounds, along with C8, C5, C6, C3, C4 and C7, showed promising potential as SIRT1 inhibitors. Based on their ability to reduce SIRT1 activity and increase apoptosis, the eight chemicals discovered in this work may be useful in treating cancer.Communicated by Ramaswamy H. Sarma.

Solvent Accessibility Promotes Rotamer Errors during Protein Modeling with Major Side-Chain Prediction Programs

Side-chain rotamer prediction is one of the most critical late stages in protein 3D structure building. Highly advanced and specialized algorithms (e.g., FASPR, RASP, SCWRL4, and SCWRL4v) optimize this process by use of rotamer libraries, combinatorial searches, and scoring functions. We seek to identify the sources of key rotamer errors as a basis for correcting and improving the accuracy of protein modeling going forward. In order to evaluate the aforementioned programs, we process 2496 high-quality single-chained all-atom filtered 30% homology protein 3D structures and use discretized rotamer analysis to compare original with calculated structures. Among 513,024 filtered residue records, increased amino acid residue-dependent rotamer errors─associated in particular with polar and charged amino acid residues (ARG, LYS, and GLN)─clearly correlate with increased amino acid residue solvent accessibility and an increased residue tendency toward the adoption of non-canonical off rotamers which modeling programs struggle to predict accurately. Understanding the impact of solvent accessibility now appears key to improved side-chain prediction accuracies.

Modeling the role of charged residues in thermophilic proteins by rotamer and dynamic cross correlation analysis

Discerning the determinants of protein thermostability is very important both from the theoretical and applied perspective. Different lines of evidence seem to indicate that a dynamical network of salt bridges/charged residues plays a fundamental role in the thermostability of enzymes. In this work, we applied measures of dynamic variance, like the Gini coefficients, Kullback-Leibler (KL) divergence and dynamic cross correlation (DCC) coefficients to compare the behavior of 3 pairs of homologous proteins from the thermophilic bacterium Thermus thermophilus and mesophilic Escherichia coli. Molecular dynamic (MD) simulations of these proteins were performed at 303 K and 363 K. In the characterization of their side chain rotamer distributions, the corresponding Gini coefficients and KL-divergence both revealed significant correlations with temperature. Similarly, a DCC analysis revealed a higher trend to de-correlate the movement of charged residues at higher temperatures in the thermophilic proteins, when compared with their mesophilic homologues. These results highlight the importance of dynamic electrostatic network interactions for the thermostability of enzymes.

In silico investigation of uncoupling protein function in avian genomes

Introduction

The uncoupling proteins (UCPs) are involved in lipid metabolism and belong to a family of mitochondrial anionic transporters. In poultry, only one UCP homologue has been identified and experimentally shown to be associated with growth, feed conversion ratio, and abdominal fat according to its predominant expression in bird muscles. In endotherm birds, cell metabolic efficiency can be tuned by the rate of mitochondrial coupling. Thus, avUCP may be a key contributor to controlling metabolic rate during particular environmental changes.

Methods

This study aimed to perform a set of in-silico investigations primarily focused on the structural, biological, and biomimetic functions of avUCP. Thereby, using in silico genome analyses among 8 avian species (chicken, turkey, swallow, manakin, sparrow, wagtail, pigeon, and mallard) and a series of bioinformatic approaches, we provide phylogenetic inference and comparative genomics of avUCPs and investigate whether sequence variation can alter coding sequence characteristics, the protein structure, and its biological features. Complementarily, a combination of literature mining and prediction approaches was also applied to predict the gene networks of avUCP to identify genes, pathways, and biological crosstalk associated with avUCP function.

Results

The results showed the evolutionary alteration of UCP proteins in different avian species. Uncoupling proteins in avian species are highly conserved trans membrane proteins as seen by sequence alignment, physio-chemical parameters, and predicted protein structures. Taken together, avUCP has the potential to be considered a functional marker for the identification of cell metabolic state, thermogenesis, and oxidative stress caused by cold, heat, fasting, transfer, and other chemical stimuli stresses in birds. It can also be deduced that avUCP, in migrant or domestic birds, may increase heat stress resistance by reducing fatty acid transport/b-oxidation and thermoregulation alongside antioxidant defense mechanisms. The predicted gene network for avUCP highlighted a cluster of 21 genes involved in response to stress and 28 genes related to lipid metabolism and the proton buffering system. Finally, among 11 enriched pathways, crosstalk of 5 signaling pathways including MAPK, adipocytokine, mTOR, insulin, ErbB, and GnRH was predicted, indicating a possible combination of positive or negative feedback among pathways to regulate avUCP functions.

Discussion

Genetic selection for fast-growing commercial poultry has unintentionally increased susceptibility to many kinds of oxidative stress, and so avUCP could be considered as a potential candidate gene for balancing energy expenditure and reactive oxygen species production, especially in breeding programs. In conclusion, avUCP can be introduced as a pleiotropic gene that requires the contribution of regulatory genes, hormones, pathways, and genetic crosstalk to allow its finely-tuned function.

Thin-Plate Superstructures of the Immunogenic 33-mer Gliadin Peptide

Gluten related-disorders have a prevalence of 1-5 % worldwide triggered by the ingestion of gluten proteins in wheat, rye, barley, and some oats. In wheat gluten, the most studied protein is gliadin, whose immunodominant 33-mer amino acid fragment remains after digestive proteolysis and accumulates in the gut mucosa. Here, we report the formation of 33-mer thin-plate superstructures using intrinsic tyrosine (Tyr) steady-state fluorescence anisotropy and cryo-TEM in combination with water tension measurements. Furthermore, we showed that fluorescence decay measurements of 33-mer intrinsic fluorophore Tyr provided information on the early stages of the formation of the thin-plate structures. Finally, conformational analysis of Tyr residues using minimalist models by molecular dynamic simulations (MD) demonstrated that changes in Tyr rotamer states depend on the oligomerization stage. Our findings further advance the understanding of the formation of the 33-mer gliadin peptide superstructures and their relation to health and disease.

Exploiting Sequence-Dependent Rotamer Information in Global Optimization of Proteins

Rotamers, namely amino acid side chain conformations common to many different peptides, can be compiled into libraries. These rotamer libraries are used in protein modeling, where the limited conformational space occupied by amino acid side chains is exploited. Here, we construct a sequence-dependent rotamer library from simulations of all possible tripeptides, which provides rotameric states dependent on adjacent amino acids. We observe significant sensitivity of rotamer populations to sequence and find that the library is successful in locating side chain conformations present in crystal structures. The library is designed for applications with basin-hopping global optimization, where we use it to propose moves in conformational space. The addition of rotamer moves significantly increases the efficiency of protein structure prediction within this framework, and we determine parameters to optimize efficiency.

Methyl Viologens of Bis-(4'-Pyridylethynyl)Arenes - Structures, Photophysical and Electrochemical Studies, and their Potential Application in Biology

A series of bis‐(4’‐pyridylethynyl)arenes (arene=benzene, tetrafluorobenzene, and anthracene) were synthesized and their bis‐N‐methylpyridinium compounds were investigated as a class of π‐extended methyl viologens. Their structures were determined by single crystal X‐ray diffraction, and their photophysical and electrochemical properties (cyclic voltammetry), as well as their interactions with DNA/RNA were investigated. The dications showed bathochromic shifts in emission compared to the neutral compounds. The neutral compounds showed very small Stokes shifts, which are a little larger for the dications. All of the compounds showed very short fluorescence lifetimes (<4 ns). The neutral compound with an anthracene core has a quantum yield of almost unity. With stronger acceptors, the analogous bis‐N‐methylpyridinium compound showed a larger two‐photon absorption cross‐section than its neutral precursor. All of the dicationic compounds interact with DNA/RNA; while the compounds with benzene and tetrafluorobenzene cores bind in the grooves, the one with an anthracene core intercalates as a consequence of its large, condensed aromatic linker moiety, and it aggregates within the polynucleotide when in excess over DNA/RNA. Moreover, all cationic compounds showed highly specific CD spectra upon binding to ds‐DNA/RNA, attributed to the rare case of forcing the planar, achiral molecule into a chiral rotamer, and negligible toxicity toward human cell lines at ≤10 μM concentrations. The anthracene‐analogue exhibited intracellular accumulation within lysosomes, preventing its interaction with cellular DNA/RNA. However, cytotoxicity was evident at 1 μM concentration upon exposure to light, due to singlet oxygen generation within cells. These multi‐faceted features, in combination with its two‐photon absorption properties, suggest it to be a promising lead compound for development of novel light‐activated theranostic agents.

Successes and challenges in multiscale modelling of artificial metalloenzymes: the case study of POP-Rh2 cyclopropanase

Molecular modelling applications in metalloenzyme design are still scarce due to a series of challenges. On top of that, the simulations of metal-mediated binding and the identification of catalytic competent geometries require both large conformational exploration and simulation of fine electronic properties. Here, we demonstrate how the incorporation of new tools in multiscale strategies, namely substrate diffusion exploration, allows taking a step further. As a showcase, the enantioselective profiles of the most outstanding variants of an artificial Rh₂-based cyclopropanase (GSH, HFF and RFY) developed by Lewis and co-workers (Nat. Commun., 2015, 6, 7789 and Nat. Chem., 2018, 10, 318-324) have been rationalized. DFT calculations on the free-cofactor-mediated process identify the carbene insertion and the cyclopropanoid formation as crucial events, the latter being the enantiodetermining step, which displays up to 8 competitive orientations easily altered by the protein environment. The key intermediates of the reaction were docked into the protein scaffold showing that some mutated residues have direct interaction with the cofactor and/or the co-substrate. These interactions take the form of a direct coordination of Rh in GSH and HFF and a strong hydrophobic patch with the carbene moiety in RFY. Posterior molecular dynamics sustain that the cofactor induces global re-arrangements of the protein. Finally, massive exploration of substrate diffusion, based on the GPathFinder approach, defines this event as the origin of the enantioselectivity in GSH and RFY. For HFF, fine molecular dockings suggest that it is likely related to local interactions upon diffusion. This work shows how modelling of long-range mutations on the catalytic profiles of metalloenzymes may be unavoidable and software simulating substrate diffusion should be applied.

A rotamer relay information system in the epidermal growth factor receptor-drug complexes reveals clues to new paradigm in protein conformational change

Cancer cells can escape the effects of chemotherapy through mutations and upregulation of a tyrosine kinase protein called the epidermal growth factor receptor (EGFR). In the past two decades, four generations of tyrosine kinase inhibitors targeting EGFR have been developed. Using comparative structure analysis of 116 EGFR-drug complex crystal structures, cluster analysis produces two clans of 73 and 43 structures, respectively. The first clan of 73 structures is larger and is comprised mostly of the C-helix-IN conformation while the second clan of 43 structures correlates with the C-helix-OUT conformation. A deep rotamer analysis identifies 43 residues (18%) of the total of 237 residues spanning the kinase structures under investigation with significant rotamer variations between the C-helix-IN and C-helix-OUT clans. The locations of these rotamer variations take on the appearance of side chain conformational relays extending out from points of EGFR mutation to different regions of the EGFR kinase. Accordingly, we propose that key EGFR mutations act singly or together to induce drug resistant conformational changes in EGFR that are communicated via these side chain conformational relays. Accordingly, these side chain conformational relays appear to play a significant role in the development of tumour resistance. This phenomenon also suggests a new paradigm in protein conformational change that is mediated by supportive relays of rotamers on the protein surface, rather than through conventional backbone movements.

Mechanisms of Viscous Media Effects on Elementary Steps of Bacterial Bioluminescent Reaction

Enzymes activity in a cell is determined by many factors, among which viscosity of the microenvironment plays a significant role. Various cosolvents can imitate intracellular conditions in vitro, allowing to reduce a combination of different regulatory effects. The aim of the study was to analyze the media viscosity effects on the rate constants of the separate stages of the bacterial bioluminescent reaction. Non-steady-state reaction kinetics in glycerol and sucrose solutions was measured by stopped-flow technique and analyzed with a mathematical model developed in accordance with the sequence of reaction stages. Molecular dynamics methods were applied to reveal the effects of cosolvents on luciferase structure. We observed both in glycerol and in sucrose media that the stages of luciferase binding with flavin and aldehyde, in contrast to oxygen, are diffusion-limited. Moreover, unlike glycerol, sucrose solutions enhanced the rate of an electronically excited intermediate formation. The MD simulations showed that, in comparison with sucrose, glycerol molecules could penetrate the active-site gorge, but sucrose solutions caused a conformational change of functionally important αGlu175 of luciferase. Therefore, both cosolvents induce diffusion limitation of substrates binding. However, in sucrose media, increasing enzyme catalytic constant neutralizes viscosity effects. The activating effect of sucrose can be attributed to its exclusion from the catalytic gorge of luciferase and promotion of the formation of the active site structure favorable for the catalysis.

Dynamic cross correlation analysis of Thermus thermophilus alkaline phosphatase and determinants of thermostability

BACKGROUND

Understanding the determinants of protein thermostability is very important both from the theoretical and applied perspective. One emerging view in thermostable enzymes seems to indicate that a salt bridge/charged residue network plays a fundamental role in their thermostability.

METHODS

The structure of alkaline phosphatase (AP) from Thermus thermophilus HB8 was solved by X-ray crystallography at 2.1 Å resolution. The obtained structure was further analyzed by molecular dynamics studies at different temperatures (303 K, 333 K and 363 K) and compared to homologous proteins from the cold-adapted organisms Shewanella sp. and Vibrio strain G15-21. To analyze differences in measures of dynamic variation, several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis were used. Using hierarchical clustering, the obtained results were combined to determine residues showing high degree dynamical variations due to temperature jumps. Furthermore, dynamic cross correlation (DCC) analysis was carried out to characterize networks of charged residues.

RESULTS

Top clustered residues showed a higher propensity for thermostabilizing mutations, indicating evolutionary pressure acting on thermophilic organisms. The description of rotamer distributions by Gini coefficients and Kullback-Leibler (KL) divergence both revealed significant correlations with temperature. DCC analysis revealed a significant trend to de-correlation of the movement of charged residues at higher temperatures.

SIGNIFICANCE

The de-correlation of charged residues detected in Thermus thermophilus AP, highlights the importance of dynamic electrostatic network interactions for the thermostability of this enzyme.

Toward structure-based drug design against the epidermal growth factor receptor (EGFR)

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Structural variations in EGFR should not be ignored in structure-based drug design.

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Main variations involve inward and outward folding of C-helix in the kinase N-lobe.

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Origins of variations are mutations and drug R-groups but not the drug core.

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Comparative modeling, fitting and clustering are imperative steps in EGFR drug design.

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Alternatively, volume and shape of binding site can be used to filter ligands against structures.

Most of the available crystal structures of epidermal growth factor receptor (EGFR) kinase domain, bound to drug inhibitors, originated from ligand-based drug design studies. Here, we used variations in 110 crystal structures to assemble eight distinct families highlighting the C-helix orientation in the N-lobe of the EGFR kinase domain. The families shared similar mutational profiles and similarity in the ligand R-groups (chemical composition, geometry, and charge) facing the C-helix, mutation sites, and DFG domain. For structure-based drug design, we recommend a systematic decision-making process for choice of template, guided by appropriate pairwise fitting and clustering before the molecular docking step. Alternatively, the binding site shape/volume can be used to filter and select the compound libraries.

Crystal structure of Thermus thermophilus methylenetetrahydrofolate dehydrogenase and determinants of thermostability

The elucidation of mechanisms behind the thermostability of proteins is extremely important both from the theoretical and applied perspective. Here we report the crystal structure of methylenetetrahydrofolate dehydrogenase (MTHFD) from Thermus thermophilus HB8, a thermophilic model organism. Molecular dynamics trajectory analysis of this protein at different temperatures (303 K, 333 K and 363 K) was compared with homologous proteins from the less temperature resistant organism Thermoplasma acidophilum and the mesophilic organism Acinetobacter baumannii using several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis. These methods enabled the determination of important residues for the thermostability of this enzyme. The description of rotamer distributions by Gini coefficients and Kullback–Leibler (KL) divergence both revealed significant correlations with temperature. The emerging view seems to indicate that a static salt bridge/charged residue network plays a fundamental role in the temperature resistance of Thermus thermophilus MTHFD by enhancing both electrostatic interactions and entropic energy dispersion. Furthermore, this analysis uncovered a relationship between residue mutations and evolutionary pressure acting on thermophilic organisms and thus could be of use for the design of future thermostable enzymes.

Voltage vs. Ligand I: Structural basis of the intrinsic flexibility of S3 segment and its significance in ion channel activation

We systematically predict the internal flexibility of the S3 segment, one of the most mobile elements in the voltage-sensor domain. By analyzing the primary amino acid sequences of V-sensor containing proteins, including Hv1, TPC channels and the voltage-sensing phosphatases, we established correlations between the local flexibility and modes of activation for different members of the VGIC superfamily. Taking advantage of the structural information available, we also assessed structural aspects to understand the role played by the flexibility of S3 during the gating of the pore. We found that S3 flexibility is mainly determined by two specific regions: (1) a short NxxD motif in the N-half portion of the helix (S3a), and (2) a short sequence at the beginning of the so-called paddle motif where the segment has a kink that, in some cases, divide S3 into two distinct helices (S3a and S3b). A good correlation between the flexibility of S3 and the reported sensitivity to temperature and mechanical stretch was found. Thus, if the channel exhibits high sensitivity to heat or membrane stretch, local S3 flexibility is low. On the other hand, high flexibility of S3 is preferentially associated to channels showing poor heat and mechanical sensitivities. In contrast, we did not find any apparent correlation between S3 flexibility and voltage or ligand dependence. Overall, our results provide valuable insights into the dynamics of channel-gating and its modulation.