Protein stability, flexibility and function

Temperature sensitivity of bat antibodies links metabolic state of bats with antigen-recognition diversity

The bat immune system features multiple unique properties such as dampened inflammatory responses and increased tissue protection, explaining their long lifespan and tolerance to viral infections. Here, we demonstrated that body temperature fluctuations corresponding to different physiological states in bats exert a large impact on their antibody repertoires. At elevated temperatures typical for flight, IgG from the bat species Myotis myotis and Nyctalus noctula show elevated antigen binding strength and diversity, recognizing both pathogen-derived antigens and autoantigens. The opposite is observed at temperatures reflecting inactive physiological states. IgG antibodies of human and other mammals, or antibodies of birds do not appear to behave in a similar way. Importantly, diversification of bat antibody specificities results in preferential recognition of damaged endothelial and epithelial cells, indicating an anti-inflammatory function. The temperature-sensitivity of bat antibodies is mediated by the variable regions of immunoglobulin molecules. Additionally, we uncover specific molecular features of bat IgG, such as low thermodynamic stability and implication of hydrophobic interactions in antigen binding as well as high prevalence of polyreactivity. Overall, our results extend the understanding of bat tolerance to disease and inflammation and highlight the link between metabolism and immunity.

Rheostatic contributions to protein stability can obscure a position's functional role

Rheostat positions, which can be substituted with various amino acids to tune protein function across a range of outcomes, are a developing area for advancing personalized medicine and bioengineering. Current methods cannot accurately predict which proteins contain rheostat positions or their substitution outcomes. To compare the prevalence of rheostat positions in homologs, we previously investigated their occurrence in two pyruvate kinase (PYK) isozymes. Human liver PYK contained numerous rheostat positions that tuned the apparent affinity for the substrate phosphoenolpyruvate (Kapp-PEP) across a wide range. In contrast, no functional rheostat positions were identified in Zymomonas mobilis PYK (ZmPYK). Further, the set of ZmPYK substitutions included an unusually large number that lacked measurable activity. We hypothesized that the inactive substitution variants had reduced protein stability, precluding detection of Kapp-PEP tuning. Using modified buffers, robust enzymatic activity was obtained for 19 previously-inactive ZmPYK substitution variants at three positions. Surprisingly, both previously-inactive and previously-active substitution variants all had Kapp-PEP values close to wild-type. Thus, none of the three positions were functional rheostat positions, and, unlike human liver PYK, ZmPYK's Kapp-PEP remained poorly tunable by single substitutions. To directly assess effects on stability, we performed thermal denaturation experiments for all ZmPYK substitution variants. Many diminished stability, two enhanced stability, and the three positions showed different thermal sensitivity to substitution, with one position acting as a "stability rheostat." The differences between the two PYK homologs raises interesting questions about the underlying mechanism(s) that permit functional tuning by single substitutions in some proteins but not in others.

Evaluating the Therapeutic Potential of Curcumin and Synthetic Derivatives: A Computational Approach to Anti-Obesity Treatments

Natural compounds such as curcumin, a polyphenolic compound derived from the rhizome of turmeric, have gathered remarkable scientific interest due to their diverse metabolic benefits including anti-obesity potential. However, curcumin faces challenges stemming from its unfavorable pharmacokinetic profile. To address this issue, synthetic curcumin derivatives aimed at enhancing the biological efficacy of curcumin have previously been developed. In silico modelling techniques have gained significant recognition in screening synthetic compounds as drug candidates. Therefore, the primary objective of this study was to assess the pharmacokinetic and pharmacodynamic characteristics of three synthetic derivatives of curcumin. This evaluation was conducted in comparison to curcumin, with a specific emphasis on examining their impact on adipogenesis, inflammation, and lipid metabolism as potential therapeutic targets of obesity mechanisms. In this study, predictive toxicity screening confirmed the safety of curcumin, with the curcumin derivatives demonstrating a safe profile based on their LD50 values. The synthetic curcumin derivative 1A8 exhibited inactivity across all selected toxicity endpoints. Furthermore, these compounds were deemed viable candidate drugs as they adhered to Lipinski's rules and exhibited favorable metabolic profiles. Molecular docking studies revealed that both curcumin and its synthetic derivatives exhibited favorable binding scores, whilst molecular dynamic simulations showed stable binding with peroxisome proliferator-activated receptor gamma (PPARγ), csyclooxygenase-2 (COX2), and fatty acid synthase (FAS) proteins. The binding free energy calculations indicated that curcumin displayed potential as a strong regulator of PPARγ (-60.2 ± 0.4 kcal/mol) and FAS (-37.9 ± 0.3 kcal/mol), whereas 1A8 demonstrated robust binding affinity with COX2 (-64.9 ± 0.2 kcal/mol). In conclusion, the results from this study suggest that the three synthetic curcumin derivatives have similar molecular interactions to curcumin with selected biological targets. However, in vitro and in vivo experimental studies are recommended to validate these findings.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Improving the thermostability and modulating the inulin profile of inulosucrase through rational glycine-to-proline substitution

The flexibility of protein structure plays a crucial role in enzyme stability and catalysis. Among the amino acids, glycine is particularly important in conferring flexibility to proteins. In this study, the effects of flexible glycine residues in Lactobacillus reuteri 121 inulosucrase (LrInu) on stability and inulin profile were investigated through glycine-to-proline substitutions. Molecular dynamics (MD) simulations were employed to discover the flexible glycine residues, and eight glycine residues, including Gly217, Gly298, Gly330, Gly416, Gly450, Gly624, Gly627, Gly629, were selected for site-directed mutagenesis. The results demonstrated significant changes in both thermostability and inulin profiles of the variants. Particularly, the G624P and G627P variants showed reduced production of long-chain oligosaccharides compared to the WT. This can be ascribed to the increased rigidity of the active site, which is crucial for the induction-fit mechanism. Overall, this study provides valuable insights into the role of flexible glycine residues in the activity, stability, and inulin synthesis of LrInu.

Normal mode analysis and comparative study of intrinsic dynamics of alcohol oxidase enzymes from GMC protein family

Glucose-Methanol-Choline (GMC) family enzymes are very important in catalyzing the oxidation of a wide range of structurally diverse substrates. Enzymes that constitute the GMC family, share a common tertiary fold but < 25% sequence identity. Cofactor FAD, FAD binding signature motif, and similar structural scaffold of the active site are common features of oxidoreductase enzymes of the GMC family. Protein functionality mainly depends on protein three-dimensional structures and dynamics. In this study, we used the normal mode analysis method to search the intrinsic dynamics of GMC family enzymes. We have explored the dynamical behavior of enzymes with unique substrate catabolism and active site characteristics from different classes of the GMC family. Analysis of individual enzymes and comparative ensemble analysis of enzymes from different classes has shown conserved dynamic motion at FAD binding sites. The present study revealed that GMC enzymes share a strong dynamic similarity (Bhattacharyya coefficient >90% and root mean squared inner product >52%) despite low sequence identity across the GMC family enzymes. The study predicts that local deformation energy between atoms of the enzyme may be responsible for the catalysis of different substrates. This study may help that intrinsic dynamics can be used to make meaningful classifications of proteins or enzymes from different organisms.Communicated by Ramaswamy H. Sarma.

Halting aberrant DNA methylation via in silico Identification of potent inhibitors of DNMT3B enzyme: Atomistic insights

To date, Cancer remains a global threat due to its impact on growing life expectancy. With the many efforts and methods of combating the disease, complete success remains a challenge owing to several limitations including cancer cells developing resistance through mutations, off-target effect of some cancer drugs resulting in toxicities, among many others. Aberrant DNA methylation is understood to be the primary reason for improper gene silence, which can result in neoplastic transformation, carcinogenesis, and tumour progression. DNA methyltransferase B (DNMT3B) enzyme is considered a potential target for the treatment of several cancers due to its important role in DNA methylation. However, only a few DNMT3B inhibitors have been reported to date. Herein, in silico molecular recognition techniques such as Molecular docking, Pharmacophore-based virtual screen and MD simulation were employed to identify potential inhibitors of DNMT3B that can halt aberrancy in DNA methylation. Findings initially identified 878 hit compounds based on a designed pharmacophore model from the reference compound Hypericin. Molecular docking was used to rank the hits by testing their efficiency when bound to the target enzyme and the top three (3) selected. All three (3) of the top hits showed excellent pharmacokinetic properties but two (2) (Zinc33330198 and Zinc77235130) were identified to be non-toxic. Molecular dynamic simulation of the final two hits showed good stability, flexibility, and structural rigidity of the compounds on DNMT3B. Finally, thermodynamic energy estimations show both compounds had favourable free energies comprising - 26.04 kcal/mol for Zinc77235130 and - 15.73 kcal/mol for Zinc33330198. Amongst the final two hits, Zinc77235130 showed consistency in favourable results across all the tested parameters and was thus selected as the lead compound for further experimental validation. The identification of this lead compound will form important basis for the inhibition of aberrant DNA methylation in cancer therapy.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Model of ligand-triggered information transmission in G-protein coupled receptor complexes

We present a model for the effects of ligands on information transmission in G-Protein Coupled Receptor (GPCR) complexes. The model is built ab initio entirely on principles of statistical mechanics and tenets of information transmission theory and was validated in part using agonist-induced effector activity and signaling bias for the angiotensin- and adrenergic-mediated signaling pathways, with in vitro observations of phosphorylation sites on the C tail of the GPCR complex, and single-cell information-transmission experiments. The model extends traditional kinetic models that form the basis for many existing models of GPCR signaling. It is based on maximizing the rates of entropy production and information transmission through the GPCR complex. The model predicts that (1) phosphatase-catalyzed reactions, as opposed to kinase-catalyzed reactions, on the C-tail and internal loops of the GPCR are responsible for controlling the signaling activity, (2) signaling favors the statistical balance of the number of switches in the ON state and the number in the OFF state, and (3) biased-signaling response depends discontinuously on ligand concentration.

New insights into the effect of mutations on affibody-Fc interaction, a molecular dynamics simulation approach

Staphylococcal protein A (SpA) domain B (the basis of affibody) has been widely used in affinity chromatography and found therapeutic applications against inflammatory diseases through targeting the Fc part of immunoglobulin G (IgG). We have performed extensive molecular dynamics simulation of 41 SpA mutants and compared their dynamics and conformations to wild type. The simulations revealed the molecular details of structural and dynamics changes that occurred due to introducing point mutations and helped to explain the SPR results. It was observed in some variants a point mutation caused extensive structural changes far from the mutation site, while an effect of some other mutations was limited to the site of the mutated residue. Also, the pattern of hydrogen bond networks and hydrophobic core arrangements were investigated. We figured out mutations that occurred at positions 128, 136, 150 and 153, affected two hydrophobic cores at the interface as well as mutations introduced at positions 129 and 154 interrupted two hydrogen bond networks of the interface, SPR data showed all of these mutations reduced binding affinity significantly. Overall, by scanning the SpA-Fc interface through the large numbers of introduced mutations, the new insights have been gained which would help to design high- affinity ligands of IgG.

Identification of potential candidate vaccines against Mycobacterium ulcerans based on the major facilitator superfamily transporter protein

Buruli ulcer is a neglected tropical disease that is characterized by non-fatal lesion development. The causative agent is Mycobacterium ulcerans (M. ulcerans). There are no known vectors or transmission methods, preventing the development of control methods. There are effective diagnostic techniques and treatment routines; however, several socioeconomic factors may limit patients' abilities to receive these treatments. The Bacillus Calmette-Guérin vaccine developed against tuberculosis has shown limited efficacy, and no conventionally designed vaccines have passed clinical trials. This study aimed to generate a multi-epitope vaccine against M. ulcerans from the major facilitator superfamily transporter protein using an immunoinformatics approach. Twelve M. ulcerans genome assemblies were analyzed, resulting in the identification of 11 CD8+ and 7 CD4+ T-cell epitopes and 2 B-cell epitopes. These conserved epitopes were computationally predicted to be antigenic, immunogenic, non-allergenic, and non-toxic. The CD4+ T-cell epitopes were capable of inducing interferon-gamma and interleukin-4. They successfully bound to their respective human leukocyte antigens alleles in in silico docking studies. The expected global population coverage of the T-cell epitopes and their restricted human leukocyte antigens alleles was 99.90%. The population coverage of endemic regions ranged from 99.99% (Papua New Guinea) to 21.81% (Liberia). Two vaccine constructs were generated using the Toll-like receptors 2 and 4 agonists, LprG and RpfE, respectively. Both constructs were antigenic, non-allergenic, non-toxic, thermostable, basic, and hydrophilic. The DNA sequences of the vaccine constructs underwent optimization and were successfully in-silico cloned with the pET-28a(+) plasmid. The vaccine constructs were successfully docked to their respective toll-like receptors. Molecular dynamics simulations were carried out to analyze the binding interactions within the complex. The generated binding energies indicate the stability of both complexes. The constructs generated in this study display severable favorable properties, with construct one displaying a greater range of favorable properties. However, further analysis and laboratory validation are required.

Rational design of a novel multi-epitope peptide-based vaccine against Onchocerca volvulus using transmembrane proteins

Almost a decade ago, it was recognized that the global elimination of onchocerciasis by 2030 will not be feasible without, at least, an effective prophylactic and/or therapeutic vaccine to complement chemotherapy and vector control strategies. Recent advances in computational immunology (immunoinformatics) have seen the design of novel multi-epitope onchocerciasis vaccine candidates which are however yet to be evaluated in clinical settings. Still, continued research to increase the pool of vaccine candidates, and therefore the chance of success in a clinical trial remains imperative. Here, we designed a multi-epitope vaccine candidate by assembling peptides from 14 O. volvulus (Ov) proteins using an immunoinformatics approach. An initial 126 Ov proteins, retrieved from the Wormbase database, and at least 90% similar to orthologs in related nematode species of economic importance, were screened for localization, presence of transmembrane domain, and antigenicity using different web servers. From the 14 proteins retained after the screening, 26 MHC-1 and MHC-II (T-cell) epitopes, and linear B-lymphocytes epitopes were predicted and merged using suitable linkers. The Mycobacterium tuberculosis Resuscitation-promoting factor E (RPFE_MYCTU), which is an agonist of TLR4, was then added to the N-terminal of the vaccine candidate as a built-in adjuvant. Immune simulation analyses predicted strong B-cell and IFN-γ based immune responses which are necessary for protection against O. volvulus infection. Protein-protein docking and molecular dynamic simulation predicted stable interactions between the 3D structure of the vaccine candidate and human TLR4. These results show that the designed vaccine candidate has the potential to stimulate both humoral and cellular immune responses and should therefore be subject to further laboratory investigation.

Microsecond MD Simulations of the Plexin-B1 RBD: N-H Probability Density as Descriptor of Structural Dynamics, Dimerization-Related Conformational Entropy, and Transient Dimer Asymmetry

Amide-bond equilibrium probability density, P_eq = exp(-u) (u, local potential), and associated conformational entropy, S_k = -∫P_eq (ln P_eq) dΩ ─ln ∫dΩ, are derived for the Rho GTPase binding domain of Plexin-B1 (RBD) as monomer and dimer from 1 μs MD simulations. The objective is to elucidate the effect of dimerization on the dynamic structure of the RBD. Dispersed (peaked) P_eq functions indicate "flexibility" ("rigidity"; the respective concepts are used below in this context). The L1 and L3 loops are throughout highly flexible, the L2 loop and the secondary structure elements are generally rigid, and the L4 loop is flexible in the monomer and rigid in the dimer. Overall, many residues are more flexible in the dimer. These features, and their implications, are discussed. Unexpectedly, we find that monomer unit 1 of the dimer (in short, d1) is unusually flexible, whereas monomer unit 2 (in short, d2) is as rigid as the RBD monomer. This is revealed due to their engagement in slow-to-intermediate conformational exchange detected previously by ¹⁵N relaxation experiments. Such motions occur with rates on the order of 10³-10⁴ s^-1; hence, they cannot be completely sampled over the course of 1 μs simulation. However, the extent to which rigid d2 is affected is small enough to enable physically relevant analysis. The entropy difference between d2 and the monomer yields an entropic contribution of -7 ± 0.7 kJ/mol to the free energy of RBD dimerization. In previous work aimed at similar objectives we used 50-100 ns MD simulations. Those results and the present result differ considerably. In summary, bond-vector P_eq functions derived directly from long MD simulations are useful descriptors of protein structural dynamics and provide accurate conformational entropy. Within the scope of slow conformational exchange, they can be useful, even in the presence of incomplete sampling.

Molecular Insights into the Role of Pathogenic nsSNPs in GRIN2B Gene Provoking Neurodevelopmental Disorders

The GluN2B subunit of N-methyl-D-aspartate receptors plays an important role in the physiology of different neurodevelopmental diseases. Genetic variations in the GluN2B coding gene (GRIN2B) have consistently been linked to West syndrome, intellectual impairment with focal epilepsy, developmental delay, macrocephaly, corticogenesis, brain plasticity, as well as infantile spasms and Lennox–Gastaut syndrome. It is unknown, however, how GRIN2B genetic variation impacts protein function. We determined the cumulative pathogenic impact of GRIN2B variations on healthy participants using a computational approach. We looked at all of the known mutations and calculated the impact of single nucleotide polymorphisms on GRIN2B, which encodes the GluN2B protein. The pathogenic effect, functional impact, conservation analysis, post-translation alterations, their driving residues, and dynamic behaviors of deleterious nsSNPs on protein models were then examined. Four polymorphisms were identified as phylogenetically conserved PTM drivers and were related to structural and functional impact: rs869312669 (p.Thr685Pro), rs387906636 (p.Arg682Cys), rs672601377 (p.Asn615Ile), and rs1131691702 (p.Ser526Pro). The combined impact of protein function is accounted for by the calculated stability, compactness, and total globularity score. GluN2B hydrogen occupancy was positively associated with protein stability, and solvent-accessible surface area was positively related to globularity. Furthermore, there was a link between GluN2B protein folding, movement, and function, indicating that both putative high and low local movements were linked to protein function. Multiple GRIN2B genetic variations are linked to gene expression, phylogenetic conservation, PTMs, and protein instability behavior in neurodevelopmental diseases. These findings suggest the relevance of GRIN2B genetic variations in neurodevelopmental problems.

Rethinking the MtInhA tertiary and quaternary structure flexibility: a molecular dynamics view

Flexibility and function are related properties in the study of protein dynamics. Flexibility reflects in the conformational potential of proteins and thus in their functionalities. The presence of interactions between protein-ligands and protein-protein complexes, substrates, and environmental changes can alter protein plasticity, acting from the rearrangement of the side chains of amino acids to the folding/unfolding of large structural motifs. To evaluate the effects of the flexibility in protein systems, we defined the enzyme 2-trans-enoyl-ACP (CoA) reductase from Mycobacterium tuberculosis, or MtInhA, as our target system. MtInhA is biologically active as a tetramer in solution; however, computational studies commonly use the monomer justifying the independence of its active sites due to their distances. However, differences in flexibility between tertiary and quaternary structures could present impact on the size of the active site, influencing the drug discovery process. In this study, we investigated the influence of flexibility restrictions in A- and B-loops of the MtInhA in order to suggest a monomeric structure that describes the conformational behavior of the tetrameric system. Overall, we observed that simulations where restrictions were applied to the A- and B-loops present a more similar behavior to the native structure when compared to unrestricted simulations. Therefore, our work presents a monomeric model of MtInhA, which has conformational characteristics of the biologically active structure. Thus, the data obtained in this work can be applied to the MtInhA system for the generation of more reliable flexible models for molecular docking experiments, and also for the performance of longer simulations by molecular dynamics and with a lower computational cost.

Polar Substitutions on the Surface of a Lipase Substantially Improve Tolerance in Organic Solvents

Biocatalysis in organic solvents (OSs) enables more efficient routes to the synthesis of various valuable chemicals. However, OSs often reduce enzymatic activity, which limits the use of enzymes in OSs. Herein, we report a comprehensive understanding of interactions between surface polar substitutions and DMSO by integrating molecular dynamics (MD) simulations of 45 variants from Bacillus subtilis lipase A (BSLA) and substitution landscape into a "BSLA-SSM" library. By systematically analyzing 39 structural-, solvation-, and interaction energy-based observables, we discovered that hydration shell maintenance, DMSO reduction, and decreased local flexibility simultaneously govern the stability of polar variants in OS. Moreover, the fingerprints of 1631 polar-related variants in three OSs demonstrated that substituting aromatic to polar amino acid(s) hold great potential to highly improve OSs resistance. Hence, surface polar engineering is a powerful strategy to generate OS-tolerant lipases and other enzymes, thereby adapting the catalyst to the desired reaction and process with OSs.

Impact of compound mutations I1171N + F1174I and I1171N + L1198H on the structure of ALK in NSCLC pathogenesis: atomistic insights

Anaplastic lymphoma kinase (ALK) fusion genes are found in 3%-5% of non-small cell lung cancers (NSCLCs). NSCLC is the most common type of lung cancer, accounting for 84% of all lung cancer diagnoses. Available treatment options for ALK-positive NSCLCs involve the use of ALK tyrosine kinase inhibitors (ALK-TKIs) which have shown to be effective with a high response rate. Nonetheless, the emergence of multiple compound mutations such as I1171N + F1174I or I1171N + L1198H has been reported to cause resistance to all approved ALK-TKIs. However, the underlying molecular mechanisms surrounding the impact of these compound mutants remain poorly understood. Hence, we performed molecular dynamics simulations to characterize the structural effects and functional implications of these compound mutations. Findings revealed a destabilizing effect on ALK by mutants as compared to the wild-type ALK structure. Also, further insights revealed a lower root-mean-squared fluctuation, radius of gyration, and solvent-accessible surface area values of I1171N + F1174I and I1171N + L1198H ALK compound mutations suggesting that the mutants have a more compact structure and a smaller surface area than the wild-type protein. The mutants also distorted the activation loop residues (Tyr1278, Tyr1282, and Tyr1283) in the ALK structure, which further identify them as possible disruptors of phosphorylation. In contrast to wild conformation, the mutant conformations exhibited a reduced node degree in their residue interaction networks. Collectively, our findings provide deeper insights into the deleterious effects of I1171N + F1174I and I1171N + L1198H ALK compound mutations, which may contribute to NSCLC pathogenesis.Communicated by Ramaswamy H. Sarma.

A lesson for the maestro of the replication fork: Targeting the protein-binding interface of proliferating cell nuclear antigen for anticancer therapy

The proliferating cell nuclear antigen (PCNA) has emerged as a promising candidate for the development of novel cancer therapeutics. PCNA is a nononcogenic mediator of DNA replication that regulates a diverse range of cellular functions and pathways through a comprehensive list of protein-protein interactions. The hydrophobic binding pocket on PCNA offers an opportunity for the development of inhibitors to target various types of cancers and modulate protein-protein interactions. In the present study, we explored the binding modes and affinity of molecule I1 (standard molecule) with the previously suggested dimer interface pocket and the hydrophobic pocket present on the frontal side of the PCNA monomer. We also identified potential lead molecules from the library of in-house synthesized 3-methylenisoindolin-1-one based molecules to inhibit the protein-protein interactions of PCNA. Our results were based on robust computational methods, including molecular docking, conventional, steered, and umbrella sampling molecular dynamics simulations. Our results suggested that the standard inhibitor I1 interacts with the hydrophobic pocket of PCNA with a higher affinity than the previously suggested binding site. Also, the proposed molecules showed better or comparable binding free energies as calculated by the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach and further validated by enhanced umbrella sampling simulations. In vitro and in vivo methods could test the computationally suggested molecules for advancement in the drug discovery pipeline.

Monitoring protein unfolding transitions by NMR-spectroscopy

NMR-spectroscopy has certain unique advantages for recording unfolding transitions of proteins compared e.g. to optical methods. It enables per-residue monitoring and separate detection of the folded and unfolded state as well as possible equilibrium intermediates. This allows a detailed view on the state and cooperativity of folding of the protein of interest and the correct interpretation of subsequent experiments. Here we summarize in detail practical and theoretical aspects of such experiments. Certain pitfalls can be avoided, and meaningful simplification can be made during the analysis. Especially a good understanding of the NMR exchange regime and relaxation properties of the system of interest is beneficial. We show by a global analysis of signals of the folded and unfolded state of GB1 how accurate values of unfolding can be extracted and what limits different NMR detection and unfolding methods. E.g. commonly used exchangeable amides can lead to a systematic under determination of the thermodynamic protein stability. We give several perspectives of how to deal with more complex proteins and how the knowledge about protein stability at residue resolution helps to understand protein properties under crowding conditions, during phase separation and under high pressure.

Phenolic compounds as α-glucosidase inhibitors: a docking and molecular dynamics simulation study

Phenolic compounds possess significant biological activity. Several pieces of research emphasize the medicinal importance of phenolic compounds, including diabetes. The present study investigated the α-glucosidase inhibitory activity of phenolic compounds reported from several plants. The phenolic compounds reported in different literature were collected. Molecular docking was carried out using AutoDock Vina. Various physicochemical properties such as size, LogP, molecular complexity, hydrogen bonding properties of phenolic compounds were correlated with the binding affinities. Furthermore, MD simulation was carried out to study the structural stability of the docking complexes. A total of 155 phenolic compounds were reported from different plants. Amentoflavone showed the strongest binding affinity with α-glucosidase, much more potent than reference acarbose. The binding energy showed a good correlation with the molecular complexity, hydrogen bond donor and acceptor property and heavy atom counts of the compounds. The polarity of the surface area also showed a positive correlation with the binding affinity of the compounds. The best docking phenolic compound, amentoflavone, showed stable binding affinity and conformation during the simulation period compared to apoprotein and acarbose-docking complex. The top ten phenolic compounds, including amentoflavone, showed considerable drug-likeness properties with fewer toxicity effects. The study suggests that the amentoflavone could be a potential therapeutic drug as an α-glucosidase inhibitor and help control postprandial hyperglycemia.Communicated by Ramaswamy H. Sarma.

Conjugated Dienones from Differently Substituted Cinnamaldehyde as Highly Potent Monoamine Oxidase-B Inhibitors: Synthesis, Biochemistry, and Computational Chemistry

Fifteen multiconjugated dienones (MK1-MK15) were synthesized and evaluated to determine their inhibitory activities against monoamine oxidases (MAOs) A and B. All derivatives were found to be potent and highly selective MAO-B inhibitors. Compound MK6, with an IC₅₀ value of 2.82 nM, most effectively inhibited MAO-B, like MK12 (IC₅₀ = 3.22 nM), followed by MK5, MK13, and MK14 (IC₅₀ = 4.02, 4.24, and 4.89 nM, respectively). The selectivity index values of MK6 and MK12 for MAO-B over MAO-A were 7361.5 and 1780.5, respectively. Compounds MK6 and MK12 were competitive reversible inhibitors of MAO-B, with K _i values of 1.10 ± 0.20 and 3.0 ± 0.27 nM, respectively. Cytotoxic studies showed that MK5, MK6, MK12, and MK14 exhibited low toxicities on Vero cells, with IC₅₀ values of 218.4, 149.1, 99.96, and 162.3 μg/mL, respectively, which were much higher than those for their effective nanomolar-level concentrations. Also, MK5, MK6, MK12, and MK14 decreased cell damage in H₂O₂-induced cells via a significant scavenging effect of reactive oxygen species. Molecular modeling was performed to rationalize the potential inhibitory activities of MK5, MK6, MK12, and MK14 toward MAO-B and their possible binding mechanisms, showing high-affinity binding pocket interactions and conformation perturbations of the compounds with MAO-B, which were interpreted as the conformational dynamics of MAO-B. This study concluded that all the compounds tested were more potent MAO-B inhibitors than the reference drugs, and leading compounds could be further explored for their effectiveness in various kinds of neurodegenerative disorders.

The molecular docking and molecular dynamics study of flavonol synthase and flavonoid 3'-monooxygenase enzymes involved for the enrichment of kaempferol

Kaempferol is a natural flavonol that shows many pharmacological properties including anti-inflammatory, antioxidant, anticancer, antidiabetic activities etc. It has been reported in many vegetables, fruits, herbs and medicinal plants. The enzyme flavonol synthase (FLS, EC 1.14.20.6) catalyses the conversion of dihydroflavonols to flavonols. Whereas flavonoid 3'-monooxygenase (F3'H, EC 1.14.14.82) catalyses the hydroxylation of dihydroflavonol, and flavonol. FLS is involved in the synthesis of the kaempferol whereas F3'H causes degradation of kaempferol. The present study aimed to analyse the binding affinity, stability and activating activity of enzyme FLS as well as inhibitory activity of enzyme F3'H involved in the enrichment of the kaempferol using the in-silico approaches. Computational study for physico-chemical properties, conserved domain identification, 3-D structure prediction and its validation, conservation analysis, molecular docking followed by molecular dynamics analysis of FLS and F3'H, protein-activator (FLS-LIG Complex) and protein-inhibitor (F3'H-LIG Complex) complexes have been performed. Other structural analyses like root mean square fluctuation (RMSF), root mean square deviation (RMSD), surface area solvent accessibility (SASA), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA), Poisson-Boltzmann analysis (MM_PBSA) and the dynamic cross correlation map (DCCM) analysis to explore the structural, functional and thermodynamic stability of the proteins and the complexes were also studied. The molecular docking result showed that FLS binds strongly with the activator ascorbate (CID _54670067) while F3'H binds with the inhibitor ketoconazole (CID_456201). The most powerful inhibitor (ketoconazole for F3'H) and activator (ascorbate for FLS) is determined by computing the thermodynamic binding free energy through MM_PBSA analysis. The current work provides wide-ranging structural and functional information about FLS and F3'H enzymes showing detailed molecular mechanism of kaempferol biosynthesis and its degradation and hence kaempferol enrichment. Finding of the present work opens up new possibilities for future research towards enrichment of kaempferol by using activator (ascorbate) for FLS and inhibitor (ketoconazole) for F3'H as well as for its large-scale production using in vitro approaches.Communicated by Ramaswamy H. Sarma.

Structure, Dynamics and Stability of the Globular Domain of Human Linker Histone H1.0 and the Role of Positive Charges

Linker histone H1 (H1) is an abundant chromatin‐binding protein that acts as an epigenetic regulator binding to nucleosomes and altering chromatin structures and dynamics. Nonetheless, the mechanistic details of its function remain poorly understood. Recent work suggest that the number and position of charged side chains on the globular domain (GD) of H1 influence chromatin structure and hence gene repression. Here, we solved the solution structure of the unbound GD of human H1.0, revealing that the structure is almost completely unperturbed by complex formation, except for a loop connecting two antiparallel β‐strands. We further quantified the role of the many positive charges of the GD for its structure and conformational stability through the analysis of 11 charge variants. We find that modulating the number of charges has little effect on the structure, but the stability is affected, resulting in a difference in melting temperature of 26 K between GD of net charge +5 versus +13. This result suggests that the large number of positive charges on H1‐GDs have evolved for function rather than structure and high stability. The stabilization of the GD upon binding to DNA can thus be expected to have a pronounced electrostatic component, a contribution that is amenable to modulation by posttranslational modifications, especially acetylation and phosphorylation.

PDB Code(s): 6hq1;

Switchable Zinc(II)-Responsive Globular β-Sheet Peptide

The natural function of many proteins depends on their ability to switch their conformation driven by environmental changes. In this work, we present a small, monomeric β-sheet peptide that switches between a molten globule and a folded state through Zn(II) binding. The solvent-exposed hydrophobic core on the β-sheet surface was substituted by a His₃-site, whereas the internal hydrophobic core was left intact. Zn(II) is specifically recognized by the peptide relative to other divalent metal ions, binds in the lower micromolar range, and can be removed and re-added without denaturation of the peptide. In addition, the peptide is fully pH-switchable, has a pK_a of about 6, and survives several cycles of acidification and neutralization. In-depth structural characterization of the switch was achieved by concerted application of circular dichroism (CD) and multinuclear NMR spectroscopy. Thus, this study represents a viable approach toward a globular β-sheet Zn(II) mini-receptor prototype.

Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias B_M . The models were externally validated on three test data sets probing different pathologies and for internal consistency (symmetry and neutrality). Model structure and performance substantially depended on training data and even fitting method. We developed two final models: SimBa-IB for typical natural mutations and SimBa-SYM for situations where stabilizing and destabilizing mutations occur to a similar extent. SimBa-SYM, despite is simplicity, is essentially non-biased (vs. the S^sym data set) while still performing well for all data sets (R ~ 0.46-0.54, MAE = 1.16-1.24 kcal/mol). The simple models provide advantage in terms of interpretability, use and future improvement, and are freely available on GitHub.

Identification of molecular basis that underlie enzymatic specificity of AzoRo from Rhodococcus opacus 1CP: A potential NADH:quinone oxidoreductase

Azo dyes are important to various industries such as textile industries. However, these dyes are known to comprise toxic, mutagenic, and carcinogenic representatives. Several approaches have already been employed to mitigate the problem such as the use of enzymes. Azoreductases have been well-studied in its capability to reduce azo dyes. AzoRo from Rhodococcus opacus 1CP has been found to be accepting only methyl red as a substrate, surmising that the enzyme may have a narrow active site. To determine the active site configuration of AzoRo at atomic level and identify the key residues involved in substrate binding and enzyme specificity, we have determined the crystal structure of holo-AzoRo and employed a rational design approach to generate AzoRo variants. The results reported here show that AzoRo has a different configuration of the active site when compared with other bacterial NAD(P)H azoreductases, having other key residues playing a role in the substrate binding and restricting the enzyme activity towards different azo dyes. Moreover, it was observed that AzoRo has only about 50% coupling yield to methyl red and p-benzoquinone - giving rise to the possibility that NADH oxidation still occurs even during catalysis. Results also showed that AzoRo is more active and more efficient towards quinones (about four times higher than methyl red).

Double Mutant of Chymotrypsin Inhibitor 2 Stabilized through Increased Conformational Entropy

The conformational heterogeneity of a folded protein can affect not only its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here, we have examined whether changed native-state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side chains with molecular dynamics simulations to quantify the native-state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: a reduction in conformational dynamics (and entropy estimated from this) of the native state of the L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native-state entropy might be needed to improve the predictions of the effect of mutations on protein stability.

Machine learning & deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry

Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) have substantial implications in virtual screening, peptide synthesis, drug ADMET screening and biomarker discovery. These strategies can increase the positive outcomes in the drug discovery process without false-positive rates and can be achieved in a cost-effective way with a minimum duration of time by high-quality data acquisition. This review substantially discusses the recent updates in AI tools as cheminformatics application in medicinal chemistry for the data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry while improving small-molecule bioactivities and properties.

Structural Distinctive 26SK, a Ribosome-Inactivating Protein from Jatropha curcas and Its Biological Activities

Ribosome-inactivating proteins (RIPs) are a group of proteins exhibiting N-glycosidase activity leading to an inactivation of protein synthesis. Thirteen predicted Jatropha curcas RIP sequences could be grouped into RIP types 1 or 2. The expression of the RIP genes was detected in seed kernels, seed coats, and leaves. The full-length cDNA of two RIP genes (26SK and 34.7(A)SK) were cloned and studied. The 34.7(A)SK protein was successfully expressed in the host cells while it was difficult to produce even only a small amount of the 26SK protein. Therefore, the crude proteins were used from E. coli expressing 26SK and 34.7(A)SK constructs and they showed RIP activity. Only the cell lysate from 26SK could inhibit the growth of E. coli. In addition, the crude protein extracted from 26SK expressing cells displayed the effect on the growth of MDA-MB-231, a human breast cancer cell line. Based on in silico analysis, all 13 J. curcas RIPs contained RNA and ribosomal P2 stalk protein binding sites; however, the C-terminal region of the P2 stalk binding site was lacking in the 26SK structure. In addition, an amphipathic distribution between positive and negative potential was observed only in the 26SK protein, similar to that found in the anti-microbial peptide. These findings suggested that this 26SK protein structure might have contributed to its toxicity, suggesting potential uses against pathogenic bacteria in the future.

Hydrogen gas as a central on-off functional switch of reversible metabolic arrest - New perspectives for biotechnological applications

Metabolism is the sum of all chemical reactions that sustain life. There is an ongoing effort to control metabolic rate, which correlates with the maximum lifespan potential and constitutes one of the oldest scientific questions. Herein, we report on the complete reversible arrest of cellular metabolism and cell growth in a series of organisms, from microalgae to yeast upon exposure to a 100 % hydrogen atmosphere. We also report a tolerance of the microalgae under these conditions against extreme stress conditions, like high salt concentrations. The addition of oxygen or air almost completely restores the metabolic rate and cell growth. Molecular dynamics simulations are employed to decipher this phenomenon at atomic scale. Various proteins, including photosynthetic and respiratory complexes (LHCII, cytochrome c5) are probed in the interaction with hydrogen. Exposure to hydrogen, as opposed to oxygen, decreases the fluctuations of protein residues indicating thermostability. According to the above mechanism, an absolute hydrogen atmosphere can preserve biological products (e.g. fruits) for a long time without consuming any energy. By combining biological, chemical and computational methods, in this research we provide the basis for future innovative studies and advances in the field of biotechnology.

Protein analysis and stability: Overcoming trial-and-error by grouping according to physicochemical properties

Today proteins are possibly the most important class of substances. Yet new tasks for proteins are still often solved by trial-and-error approaches. However, in some areas these euphemistically called "screening approaches" are not suitable. E.g. stability tests just take too long and therefore require a more strategic, target-orientated concept. This concept is available by grouping proteins according to their physicochemical properties and then pulling out the right drawer for new tasks. These properties include size, then charge and hydrophobicity as well as their patchinesses, and the degree of order. In addition, solubility, the content of (free) enthalpy, aromatic-amino-acid- and α/β-frequency as well as helix capping, and corresponding patchiness, the number of specific motifs and domains as well as the typical concentration range can be helpful to discriminate between different groups of proteins. Analyzing correlations will reduce the necessary amount of parameters and additional ones, which may be still undiscovered at the present time, can be identified looking at protein subgroups with similar physicochemical properties which still behave heterogeneously. Step-by-step the methodology will be improved. Possibly protein stability will be the driver of this process, but all other areas such as production, purification and analytics including sample pre-treatment and the choice of appropriate separation conditions for e.g. chromatography and electrophoresis will profit from a rational strategy.

Three Simple Properties Explain Protein Stability Change upon Mutation

Accurate prediction of protein stability upon mutation enables rational engineering of new proteins and insights into protein evolution and monogenetic diseases caused by single-point amino acid substitutions. Many tools have been developed to this aim, ranging from energy-based models to machine-learning methods that use large amounts of experimental data. However, as the methods become more complex, the interpretation of the chemistry underlying the protein stability effects becomes obscure. It is thus of interest to identify the simplest prediction model that retains complete amino acid specific interpretation; for a given number of input descriptors, we expect such a model to be almost universal. In this study, we identify such a limiting model, SimBa, a simple multilinear regression model trained on a substitution-type-balanced experimental data set. The model accounts only for the solvent accessibility of the site, volume difference, and polarity difference caused by mutation. Our results show that this very simple and directly applicable model performs comparably to other much more complex, widely used protein stability prediction methods. This suggests that a hard limit of ∼1 kcal/mol numerical accuracy and an R ∼ 0.5 trend accuracy exists and that new features, such as account of unfolded states, water colocalization, and amino acid correlations, are required to improve accuracy to, e.g., 1/2 kcal/mol.

Salting-in and salting-out effects of short amphiphilic molecules: a balance between specific ion effects and hydrophobicity

Salting-in or salting-out tendencies depend on a balance between headgroup-specific ion effects and the hydrophobicity of the tail.

Himalayan bioactive molecules as potential entry inhibitors for the human immunodeficiency virus

The human immunodeficiency virus interacts with the cluster of differentiation 4 receptors and one of the two chemokine receptors (CCR5 and CXCR4) to gain entry in human cells. Both the co-receptors are essential for viral entry, replication, and are considered critical targets for antiviral drugs. In this study, bioactive molecules from different Himalayan plants were screened considering their potential to bind with the CCR5 and CXCR4 co-receptors. We utilized computational and thermodynamic parameters to validate the binding of the selected biomolecules to the active site of the co-receptors. The molecules Butyl 2-ethylhexyl phthalate and Dactylorhin-A showed a higher binding affinity with CCR5 co-receptor than the standard antagonist Maraviroc. Moreover, Pseudohypericin, Amarogentin, and Dactylorhin-E exhibited stronger interactions with CXCR4 than the co-crystallized inhibitor Isothiourea-1 t. Hence, we suggest that these molecules could be developed as potential inhibitors of the CCR5 and CXCR4 co-receptors. However, this require further in-vitro and in-vivo validation.

Schistosomal Sulfotransferase Interaction with Oxamniquine Involves Hybrid Mechanism of Induced-fit and Conformational Selection

Background:

Sulfotransferase family comprises key enzymes involved in drug metabolism. Oxamniquine is a pro-drug converted into its active form by schistosomal sulfotransferase. The conformational dynamics of side-chain amino acid residues at the binding site of schistosomal sulfotransferase towards activation of oxamniquine has not received attention.

Objective:

The study investigated the conformational dynamics of binding site residues in free and oxamniquine bound schistosomal sulfotransferase systems and their contribution to the mechanism of oxamniquine activation by schistosomal sulfotransferase using molecular dynamics simulations and binding energy calculations.

Methods:

Schistosomal sulfotransferase was obtained from Protein Data Bank and both the free and oxamniquine bound forms were subjected to molecular dynamics simulations using GROMACS-4.5.5 after modeling it’s missing amino acid residues with SWISS-MODEL. Amino acid residues at its binding site for oxamniquine was determined and used for Principal Component Analysis and calculations of side-chain dihedrals. In addition, binding energy of the oxamniquine bound system was calculated using g_MMPBSA.

Results:

The results showed that binding site amino acid residues in free and oxamniquine bound sulfotransferase sampled different conformational space involving several rotameric states. Importantly, Phe45, Ile145 and Leu241 generated newly induced conformations, whereas Phe41 exhibited shift in equilibrium of its conformational distribution. In addition, the result showed binding energy of -130.091 ± 8.800 KJ/mol and Phe45 contributed -9.8576 KJ/mol.

Conclusion:

The results showed that schistosomal sulfotransferase binds oxamniquine by relying on hybrid mechanism of induced fit and conformational selection models. The findings offer new insight into sulfotransferase engineering and design of new drugs that target sulfotransferase.

Conformational behavior of coat protein in plants and association with coat protein-mediated resistance against TMV

Tobacco mosaic virus (TMV) coat protein (CP) self assembles in viral RNA deprived transgenic plants to form aggregates based on the physical conditions of the environment. Transgenic plants in which these aggregates are developed show resistance toward infection by TMV referred to as CP-MR. This phenomenon has been extensively used to protect transgenic plants against viral diseases. The mutants T42W and E50Q CP confer enhanced CP-MR as compared to the WT CP. The aggregates, when examined, show the presence of helical discs in the case of WT CP; on the other hand, mutants show the presence of highly stable non-helical long rods. These aggregates interfere with the accumulation of MP as well as with the disassembly of TMV in plant cells. Here, we explored an atomic level insight to the process of CP-MR through MD simulations. The subunit-subunit interactions were assessed with the help of MM-PBSA calculations. Moreover, classification of secondary structure elements of the protein also provided unambiguous information about the conformational changes occurring in the two chains, which indicated toward increased flexibility of the mutant protein and seconded the other results of simulations. Our finding indicates the essential structural changes caused by the mutation in CP subunits, which are critically responsible for CP-MR and provides an in silico insight into the effects of these transitions over CP-MR. These results could further be utilized to design TMV-CP-based small peptides that would be able to provide appropriate protection against TMV infection.

MODELLING OF 3D-STRUCTURES OF THE RARE MELANOCORTIN-1-RECEPTOR MUTATIONS ASSOCIATED TO MELANISM IN THE BANANAQUIT

Melanism in plumage color is often associated to the single nucleotide polymorphism of the melanocortin-1-receptor (MC1R). Despite the striking association between the substitution of a Glutamic-acid by for a Lysine at position 92 on the MC1R protein and a completely black plumage, an in-depth understanding of the effect of missense mutations on the conformational change and behavior of the MC1R in the lipid bilayer caused by the absence of a crystal structure is lacking. We examine the structural basis for receptor activation using DNA sequences from the GenBank to perform in silicoprotein homology-based modeling. Our tridimensional model shows that the Alanine for a 179-Threoninesubstitution is a structural complement of the charge-reversing effect associated to the substitution of a Glutamic-acid by for a Lysine at position 92 on the MC1R. We proposed the possibility of gradual evolution in stability and electrostatic properties of the MC1R by the sequential accumulation of these two rare substitutions. These two rare substitutions further perturb physical-chemical properties that may be necessary folding requirements of the constitutively active MC1R forms without altering of ligand binding affinity. The computational coarse-grained molecular dynamics of the MC1R binding affinities to the melanocyte-stimulating hormone predicted the disparity in ligand binding amongalleles. We speculate that the disparity in structural constraints and ligand binding among the alleles within heterozygous individuals may contribute as a mechanism to the plumage color variation in the Coereba flaveola.

Computational analysis of androgen receptor (AR) variants to decipher the relationship between protein stability and related-diseases

Although more than 1,000 androgen receptor (AR) mutations have been identified and these mutants are pathologically important, few theoretical studies have investigated the role of AR protein folding stability in disease and its relationship with the phenotype of the patients. Here, we extracted AR variant data from four databases: ARDB, HGMD, Cosmic, and 1,000 genome. 905 androgen insensitivity syndrome (AIS)-associated loss-of-function mutants and 168 prostate cancer-associated gain-of-function mutants in AR were found. We analyzed the effect of single-residue variation on the folding stability of AR by FoldX and guanidine hydrochloride denaturation experiment, and found that genetic disease-associated mutations tend to have a significantly greater effect on protein stability than gene polymorphisms. Moreover, AR mutants in complete androgen insensitivity syndrome (CAIS) tend to have a greater effect on protein stability than in partial androgen insensitive syndrome (PAIS). This study, by linking disease phenotypes to changes in AR stability, demonstrates the importance of protein stability in the pathogenesis of hereditary disease.

Snapshot of the evolution and mutation patterns of SARS-CoV-2

The COVID-19 pandemic is the most important public health threat in recent history. Here we study how its causal agent, SARS-CoV-2, has diversified genetically since its first emergence in December 2019. We have created a pipeline combining both phylogenetic and structural analysis to identify possible human-adaptation related mutations in a data set consisting of 4,894 SARS-CoV-2 complete genome sequences. Although the phylogenetic diversity of SARS-CoV-2 is low, the whole genome phylogenetic tree can be divided into five clusters/clades based on the tree topology and clustering of specific mutations, but its branches exhibit low genetic distance and bootstrap support values. We also identified 11 residues that are high-frequency substitutions, with four of them currently showing some signal for potential positive selection. These fast-evolving sites are in the non-structural proteins nsp2, nsp5 (3CL-protease), nsp6, nsp12 (polymerase) and nsp13 (helicase), in accessory proteins (ORF3a, ORF8) and in the structural proteins N and S. Temporal and spatial analysis of these potentially adaptive mutations revealed that the incidence of some of these sites was declining after having reached an (often local) peak, whereas the frequency of other sites is continually increasing and now exhibit a worldwide distribution. Structural analysis revealed that the mutations are located on the surface of the proteins that modulate biochemical properties. We speculate that this improves binding to cellular proteins and hence represents fine-tuning of adaptation to human cells. Our study has implications for the design of biochemical and clinical experiments to assess whether important properties of SARS-CoV-2 have changed during the epidemic.

Structure based design of inhibitory peptides targeting ornithine decarboxylase dimeric interface and in vitro validation in human retinoblastoma Y79 cells

Polyamine synthesis in human cells is initiated by catalytic action of Ornithine decarboxylase (ODC) on Ornithine. Elevated levels of polyamines are manifested proliferating cancer cells and are found to promote tumour cell adhesion. Di-flouro methyl orninthine is a known inhibitor of ODC, however its usage is limited due its low affinity quick clearance and incompetent cellular uptake, thus posing a need for potential inhibitors. Currently, peptides are substituting drugs, as these are highly selective, specific and potent. Hence, in this study, the interacting interfaces of native homodimeric form of ODC and its heterodimer with Antizyme were probed to design inhibitory peptides targeting ODC. The designed peptides were validated for structural fitness by extensive molecular dynamics simulations and Circular dichroism studies. Finally, these peptides were validated in Y79 retinoblastoma cells for impact on ODC activity, cytotoxicity cell cycle and cell adhesion. On collective analysis, Peptide3 (Pep 3) and Peptide4 (Pep 4) were found to be potentially targeting ODC, as these peptides showed significant decrease in intracellular polyamine levels, cell adhesion and cell cycle perturbation in Y79 cells. Thus, Pep 3 and Pep 4 shall be favourably considered as therapeutic agents for targeting ODC mediated proliferation in retinoblastoma.Communicated by Ramaswamy H. Sarma.

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.

Rational drug repurposing for cancer by inclusion of the unbiased molecular dynamics simulation in the structure-based virtual screening approach: Challenges and breakthroughs

Managing cancer is now one of the biggest concerns of health organizations. Many strategies have been developed in drug discovery pipelines to help rectify this problem and two of the best ones are drug repurposing and computational methods. The combination of these approaches can have immense impact on the course of drug discovery. In silico drug repurposing can significantly reduce the time, the cost and the effort of drug development. Computational methods such as structure-based drug design (SBDD) and virtual screening can predict the potentials of small molecule binders, such as drugs, for having favorable effect on a particular molecular target. However, the demand for accuracy and efficiency of SBDD requires more sophisticated and complicated approaches such as unbiased molecular dynamics (UMD) simulation that has been recently introduced. As a complementary strategy, the knowledge acquired from UMD simulations can increase the chance of finding the right candidates and the pipeline of its administration is introduced and discussed in this review. An elaboration of this pipeline is also made by detailing an example, the binding and unbinding pathways of dasatinib-c-Src kinase complex, which shows that how influential this method can be in rational drug repurposing in cancer treatment.