Repurposing and computational design of PARP inhibitors as SARS-CoV-2 inhibitors

Coronavirus disease 2019 (COVID-19) is a recent pandemic that caused serious global emergency. To identify new and effective therapeutics, we employed a drug repurposing approach. The poly (ADP ribose) polymerase inhibitors were used for this purpose and were repurposed against the main protease (Mpro) target of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). The results from these studies were used to design compounds using the 'Grow Scaffold' modules available on Discovery Studio v2018. The three designed compounds, olaparib 1826 and olaparib 1885, and rucaparib 184 demonstrated better CDOCKER docking scores for Mpro than their parent compounds. Moreover, the compounds adhered to Lipinski's rule of five and demonstrated a synthetic accessibility score of 3.55, 3.63, and 4.30 for olaparib 1826, olaparib 1885, and rucaparib 184, respectively. The short-range Coulombic and Lennard-Jones potentials also support the potential binding of the modified compounds to Mpro. Therefore, we propose these three compounds as novel SARS-CoV-2 inhibitors.

In silico analysis of substitution mutations in the β-globin gene in Turkish population of β-thalassemia

Beta-thalassemia is a genetic blood disorder represented by anomalies in hemoglobin's beta chain production. Most hemoglobin defects are a result of mutations of the structural β-globin gene. Many diseases, including β-thalassemia, benefit from computational studies that aid researchers in investigating the association of genotype and phenotype. In this study, the alanine substitution mutations of the β-globin protein sub-units in the Turkish population (Hb Ankara, Hb Siirt and Hb Izmir) and the effects of those mutations on the β-globin protein structure and performance are examined using molecular dynamics simulation. While Hb Ankara variant showed a non-conservative mutation, Hb Siirt and Hb Izmir showed a semi-conservative mutation. RMSF values of Hb Siirt, between residues 95 and 99, were higher than wild-type and the other mutant proteins. The residues of Hb Ankara showed lower fluctuation compared to the other structures. The mean ROG values were 1.47 nm, 1.46 nm, 1.49 nm and 1.48 and the average number of the hydrogen bonds were 92, 100, 99, and 89 for Hb Ankara, Hb Siirt and Hb Izmir, respectively. Moreover, a significant increase in overall motion in Hb Siirt was observed based on PCA analysis. Hb Siirt substitution mutation might cause an effect in β-globin proteins which could impact the protein function. This indicates a major role on beta globin subunit's stability for alanine on 27th position. However, Hb Ankara and Hb Izmir variants may act as a silent mutation, since these two mutations did not show a large change in the dynamics of the protein.Communicated by Ramaswamy H. Sarma.

Translocating Peptides of Biomedical Interest Obtained from the Spike (S) Glycoprotein of the SARS-CoV-2

At the beginning of 2020, the pandemic caused by the SARS-CoV-2 virus led to the fast sequencing of its genome to facilitate molecular engineering strategies to control the pathogen’s spread. The spike (S) glycoprotein has been identified as the leading therapeutic agent due to its role in localizing the ACE2 receptor in the host’s pulmonary cell membrane, binding, and eventually infecting the cells. Due to the difficulty of delivering bioactive molecules to the intracellular space, we hypothesized that the S protein could serve as a source of membrane translocating peptides. AHB-1, AHB-2, and AHB-3 peptides were identified and analyzed on a membrane model of DPPC (dipalmitoylphosphatidylcholine) using molecular dynamics (MD) simulations. An umbrella sampling approach was used to quantify the energy barrier necessary to cross the boundary (13.2 to 34.9 kcal/mol), and a flat-bottom pulling helped to gain a deeper understanding of the membrane’s permeation dynamics. Our studies revealed that the novel peptide AHB-1 exhibited comparable penetration potential of already known potent cell-penetrating peptides (CPPs) such as TP2, Buforin II, and Frenatin 2.3s. Results were confirmed by in vitro analysis of the peptides conjugated to chitosan nanoparticles, demonstrating its ability to reach the cytosol and escape endosomes, while maintaining high biocompatibility levels according to standardized assays.

Computational analysis of deleterious single nucleotide polymorphisms in catechol O-Methyltransferase conferring risk to post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is one of the prevalent neurological disorder which is drawing increased attention over the past few decades. Major risk factors for PTSD can be categorized into environmental and genetic factors. Among the genetic risk factors, polymorphisms in the catechol-O-methyltransferase (COMT) gene is known to be associated with the risk for PTSD. In the present study, we analysed the impact of deleterious single nucleotide polymorphisms (SNPs) in the COMT gene conferring risk to PTSD using computational based approaches followed by molecular dynamic simulations. The data on COMT gene associated with PTSD were collected from several databases including Online Mendelian Inheritance in Man (OMIM) search. Datasets related to SNP were downloaded from the dbSNP database. To study the structural and dynamic effects of COMT wild type and mutant forms, we performed molecular dynamics simulations (MD simulations) at a time scale of 300 ns. Results from screening the SNPs using the computational tools SIFT and Polyphen-2 demonstrated that the SNP rs4680 (V158M) in COMT has a deleterious effect with phenotype in PTSD. Results from the MD simulations showed that there is some major fluctuations in the structural features including root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuation (RMSF) and secondary structural elements including α-helices, sheets and turns between wild-type (WT) and mutant forms of COMT protein. In conclusion, our study provides novel insights into the deleterious effects and impact of V158M mutation on COMT protein structure which plays a key role in PTSD.

How Quickly Do Proteins Fold and Unfold, and What Structural Parameters Correlate with These Values?

The correlations between the logarithm of the unfolding rate of 108 proteins and their structural parameters were calculated. We showed that there is a good correlation between the logarithm of folding and unfolding rates (0.79) and protein stability and unfolding rate (0.79). Thus, the faster the protein folds, the faster it unfolds. Folding and unfolding rates are higher for the proteins with two-state kinetics, in comparison with the proteins with multi-state kinetics. At the same time, two-state bacterial proteins folds and unfolds two orders of magnitude faster than two-state eukaryotic proteins, and multi-state bacterial proteins folds and unfolds slower than multi-state eukaryotic proteins. Despite the fact that the folding rates of thermophilic and mesophilic proteins are close, the unfolding rates of thermophilic proteins is about two orders of magnitude lower than for mesophilic proteins. The correlation between unfolding rate and stability of thermophilic proteins is high (0.90). We also found that the unfolding rate correlates with such structural parameters as: size of the protein, radius of the cross-section, logarithm of absolute contact order, and radius of gyration. This information will be useful for engineering and designing new proteins with desired properties.

Establishing knowledge on the sequence arrangement pattern of nucleated protein folding

The heat-tolerance mechanisms of (hyper)thermophilic proteins provide a unique opportunity to investigate the unsolved protein folding problem. In an attempt to determine whether the interval between residues in sequence might play a role in determining thermostability, we constructed a sequence interval-dependent value function to calculate the residue pair frequency. Additionally, we identified a new sequence arrangement pattern, where like-charged residues tend to be adjacently assembled, while unlike-charged residues are distributed over longer intervals, using statistical analysis of a large sequence database. This finding indicated that increasing the intervals between unlike-charged residues can increase protein thermostability, with the arrangement patterns of these charged residues serving as thermodynamically favorable nucleation points for protein folding. Additionally, we identified that the residue pairs K-E, R-E, L-V and V-V involving long sequence intervals play important roles involving increased protein thermostability. This work demonstrated a novel approach for considering sequence intervals as keys to understanding protein folding. Our findings of novel relationships between residue arrangement and protein thermostability can be used in industry and academia to aid the design of thermostable proteins.

Analysis of molecular structures and mechanisms for toxins derived from venomous animals

As predominant component in the venom of many dangerous animal species, toxins have been thoroughly investigated for drug design or as pharmacologic tools. The present study demonstrated the use of size and hydrophobicity of amino acid residues for the purposes of quantifying the valuable sequence-structure relationship and performing further analysis of interactional mechanisms in secondary structure elements (SSEs) for toxin native conformations. First, we showed that the presence of large and hydrophobic residues varying in availability in the primary sequences correspondingly affects the amount of these residues being used in the SSEs in accordance with linear behavioral patterns from empirical assessments of experimentally derived toxins and non-toxins. Subsequent derivation of prediction rules was established with the aim of analyzing molecular structures and mechanisms by means of 114 residue compositions for venom toxins. The obtained results concerning the linear behavioral patterns demonstrated the nature of the information transfer occurring from the primary to secondary structures. A dual action mechanism was established, taking into account steric and hydrophobic interactions. Finally, a new residue composition prediction method for SSEs of toxins was suggested.

Bacterial proteins fold faster than eukaryotic proteins with simple folding kinetics

Protein domain frequency and distribution among kingdoms was statistically analyzed using the SCOP structural database. It appeared that among chosen protein domains with the best resolution, eukaryotic proteins more often belong to α-helical and β-structural proteins, while proteins of bacterial origin belong to α/β structural class. Statistical analysis of folding rates of 73 proteins with known experimental data revealed that bacterial proteins with simple kinetics (23 proteins) exhibit a higher folding rate compared to eukaryotic proteins with simple folding kinetics (27 proteins). Analysis of protein domain amino acid composition showed that the frequency of amino acid residues in proteins of eukaryotic and bacterial origin is different for proteins with simple and complex folding kinetics.

Prediction of functionally important residues in globular proteins from unusual central distances of amino acids

BACKGROUND

Well-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues.

RESULTS

Using a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at http://www.bioinformatics.org/surpresi.

CONCLUSIONS

Probabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.

Structural analysis of alkaline β-mannanase from alkaliphilic Bacillus sp. N16-5: implications for adaptation to alkaline conditions

Significant progress has been made in isolating novel alkaline β-mannanases, however, there is a paucity of information concerning the structural basis for alkaline tolerance displayed by these β-mannanases. We report the catalytic domain structure of an industrially important β-mannanase from the alkaliphilic Bacillus sp. N16-5 (BSP165 MAN) at a resolution of 1.6 Å. This enzyme, classified into subfamily 8 in glycosyl hydrolase family 5 (GH5), has a pH optimum of enzymatic activity at pH 9.5 and folds into a classic (β/α)(8)-barrel. In order to gain insight into molecular features for alkaline adaptation, we compared BSP165 MAN with previously reported GH5 β-mannanases. It was revealed that BSP165 MAN and other subfamily 8 β-mannanases have significantly increased hydrophobic and Arg residues content and decreased polar residues, comparing to β-mannanases of subfamily 7 or 10 in GH5 which display optimum activities at lower pH. Further, extensive structural comparisons show alkaline β-mannanases possess a set of distinctive features. Position and length of some helices, strands and loops of the TIM barrel structures are changed, which contributes, to a certain degree, to the distinctly different shaped (β/α)(8)-barrels, thus affecting the catalytic environment of these enzymes. The number of negatively charged residues is increased on the molecular surface, and fewer polar residues are exposed to the solvent. Two amino acid substitutions in the vicinity of the acid/base catalyst were proposed to be possibly responsible for the variation in pH optimum of these homologous enzymes in subfamily 8 of GH5, identified by sequence homology analysis and pK(a) calculations of the active site residues. Mutational analysis has proved that Gln91 and Glu226 are important for BSP165 MAN to function at high pH. These findings are proposed to be possible factors implicated in the alkaline adaptation of GH5 β-mannanases and will help to further understanding of alkaline adaptation mechanism.

Is protein folding rate dependent on number of folding stages? Modeling of protein folding with ferredoxin-like fold

Statistical analysis of protein folding rates has been done for 84 proteins with available experimental data. A surprising result is that the proteins with multi-state kinetics from the size range of 50-100 amino acid residues (a.a.) fold as fast as proteins with two-state kinetics from the same size range. At the same time, the proteins with two-state kinetics from the size range 101-151 a.a. fold faster than those from the size range 50-100 a.a. Moreover, it turns out unexpectedly that usually in the group of structural homologs from the size range 50-100 a.a., proteins with multi-state kinetics fold faster than those with two-state kinetics. The protein folding for six proteins with a ferredoxin-like fold and with a similar size has been modeled using Monte Carlo simulations and dynamic programming. Good correlation between experimental folding rates, some structural parameters, and the number of Monte Carlo steps has been obtained. It is shown that a protein with multi-state kinetics actually folds three times faster than its structural homologs.

Coupling between properties of the protein shape and the rate of protein folding

There are several important questions on the coupling between properties of the protein shape and the rate of protein folding. We have studied a series of structural descriptors intended for describing protein shapes (the radius of gyration, the radius of cross-section, and the coefficient of compactness) and their possible connection with folding behavior, either rates of folding or the emergence of folding intermediates, and compared them with classical descriptors, protein chain length and contact order. It has been found that when a descriptor is normalized to eliminate the influence of the protein size (the radius of gyration normalized to the radius of gyration of a ball of equal volume, the coefficient of compactness defined as the ratio of the accessible surface area of a protein to that of an ideal ball of equal volume, and relative contact order) it completely looses its ability to predict folding rates. On the other hand, when a descriptor correlates well with protein size (the radius of cross-section and absolute contact order in our consideration) then it correlates well with the logarithm of folding rates and separates reasonably well two-state folders from multi-state ones. The critical control for the performance of new descriptors demonstrated that the radius of cross-section has a somewhat higher predictive power (the correlation coefficient is −0.74) than size alone (the correlation coefficient is −0.65). So, we have shown that the numerical descriptors of the overall shape-geometry of protein structures are one of the important determinants of the protein-folding rate and mechanism.