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1.
Phys Chem Chem Phys ; 21(37): 20678-20692, 2019 Oct 07.
Artigo em Inglês | MEDLINE | ID: mdl-31508628

RESUMO

In this work we present a high-throughput approach to the computation of absorption UV-Vis spectra tailored to mutagenesis studies. The scheme makes use of a single molecular dynamics trajectory of a reference (non-mutated) species. The shifts in absorption energy caused by a residue mutation are evaluated by building an effective potential of the environment and computing a correction term based on perturbation theory. The sampling is only performed in the phase space of the initial protein. We analyze the robustness of the method by comparing different approximations for the effective potential, the sampling of mutant residue geometries and observing the impact in the prediction of both bathocromic and hypsochromic shifts. As a test subject, we consider a red fluorescent protein variant with potential biotechnological applications.


Assuntos
Testes Genéticos/métodos , Luz , Proteínas/química , Proteínas/genética , Análise Espectral , Raios Ultravioleta , Simulação de Dinâmica Molecular , Mutação
2.
Adv Exp Med Biol ; 1148: 115-129, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31482497

RESUMO

Therapeutic proteins are a rapidly growing class of drugs in clinical settings. The pharmacokinetics (PK) of therapeutic proteins relies on their absorption, distribution, metabolism, and excretion (ADME) properties. Moreover, the ADME properties of therapeutic proteins are impacted by their physicochemical characteristics. Comprehensive evaluation of these characteristics and their impact on ADME properties are critical to successful drug development. This chapter summarizes all relevant physicochemical characteristics and their effect on ADME properties of therapeutic proteins.


Assuntos
Proteínas/farmacologia , Proteínas/farmacocinética , Fenômenos Químicos , Proteínas/química , Relação Estrutura-Atividade
3.
BMC Bioinformatics ; 20(1): 419, 2019 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-31409275

RESUMO

BACKGROUND: Alignment of sequence families described by profiles provides a sensitive means for establishing homology between proteins and is important in protein evolutionary, structural, and functional studies. In the context of a steadily growing amount of sequence data, estimating the statistical significance of alignments, including profile-profile alignments, plays a key role in alignment-based homology search algorithms. Still, it is an open question as to what and whether one type of distribution governs profile-profile alignment score, especially when profile-profile substitution scores involve such terms as secondary structure predictions. RESULTS: This study presents a methodology for estimating the statistical significance of this type of alignments. The methodology rests on a new algorithm developed for generating random profiles such that their alignment scores are distributed similarly to those obtained for real unrelated profiles. We show that improvements in statistical accuracy and sensitivity and high-quality alignment rate result from statistically characterizing alignments by establishing the dependence of statistical parameters on various measures associated with both individual and pairwise profile characteristics. Implemented in the COMER software, the proposed methodology yielded an increase of up to 34.2% in the number of true positives and up to 61.8% in the number of high-quality alignments with respect to the previous version of the COMER method. CONCLUSIONS: The more accurate estimation of statistical significance is implemented in the COMER method, which is now more sensitive and provides an increased rate of high-quality profile-profile alignments. The results of the present study also suggest directions for future research.


Assuntos
Modelos Teóricos , Proteínas/química , Algoritmos , Sequência de Aminoácidos , Conformação Proteica , Alinhamento de Sequência
4.
Biol Bull ; 237(1): 26-35, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31441701

RESUMO

In this quantitative proteomics study we determined the variety and relative abundance of toxins present in enriched preparations of two nematocyst types isolated from the primary tentacles of the adult medusa stage of the hydrozoan Olindias sambaquiensis. The two nematocyst types were microbasic mastigophores and microbasic euryteles, and these were recovered from the macerated tentacle tissues by using a differential centrifugation approach. Soluble protein extracts from these nematocysts were tagged with tandem mass tag isobaric labels and putative toxins identified using tandem mass spectrometry coupled with a stringent bioinformatics annotation pipeline. Astonishingly, the venom composition of the two capsule types was nearly identical, and there was also little difference in the comparative abundance of toxins between the two nematocyst preparations. This homogeneity suggested that the same toxin complement was present regardless of the penetrative ability of the nematocyst type. Predicted toxin protein families that constituted the venom closely matched those of the toxic proteome of O. sambaquiensis published four years previously, suggesting that venom composition in this species changes little over time. Retaining an array of different nematocyst types to deliver a single venom, rather than sustaining the high metabolic cost necessary to maintain a dynamically evolving venom, may be more advantageous, given the vastly different interspecific interactions that adult medusa encounter in coastal zones.


Assuntos
Venenos de Cnidários/química , Hidrozoários/química , Animais , Hidrozoários/anatomia & histologia , Nematocisto/anatomia & histologia , Nematocisto/química , Proteínas/química
5.
J Agric Food Chem ; 67(35): 9719-9726, 2019 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-31398015

RESUMO

Pickering high internal phase emulsions (HIPEs) are normally highly concentrated emulsions stabilized by colloidal particles with a minimum internal phase volume fraction of 0.74. They have received considerable attention in many fields, including pharmaceuticals, tissue engineering, foods, and personal care products. The aim of this perspective is to update the current knowledge on the field of protein-based Pickering HIPEs, emphasizing those aspects that need to be explored and clarified. Research progress in constructing HIPEs by protein-type colloid particles and promising research trends in basic research and potential applications were highlighted. Promising studies in this field include (1) clarifying bioavailability and evolution of activity of active ingredients in Pickering HIPEs by oral administration, (2) constructing a Pickering interfacial catalysis platform using protein colloidal particles, and (3) expanding the emerging applications of Pickering HIPEs in fields, such as partially hydrogenated oil replacers, probiotic encapsulation, and the template for porous materials.


Assuntos
Suplementos Nutricionais/análise , Emulsões/química , Proteínas/química , Coloides/química , Sistemas de Liberação de Medicamentos/instrumentação , Sistemas de Liberação de Medicamentos/métodos , Excipientes/química , Nanopartículas/química , Tamanho da Partícula , Porosidade
6.
Phys Chem Chem Phys ; 21(33): 18149-18160, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31389436

RESUMO

Conformational entropies are of great interest when studying the binding of small ligands to proteins or the interaction of proteins. Unfortunately, there are no experimental methods available to measure conformational entropies of all groups in a protein. Instead, they are normally estimated from molecular dynamics (MD) simulations, although such methods show problems with convergence and correlation of motions, and depend on the accuracy of the underlying potential-energy function. Crystallographic atomic displacement parameters (also known as B-factors) are available in all crystal structures and contain information about the atomic fluctuations, which can be converted to entropies. We have studied whether B-factors can be employed to extract conformational entropies for proteins by comparing such entropies to those measured by NMR relaxation experiments or obtained from MD simulations in solution or in the crystal. Unfortunately, our results show that B-factor entropies are unreliable, because they include the movement and rotation of the entire protein, they exclude correlation of the movements and they include contributions other than the fluctuations, e.g. static disorder, as well as errors in the model and the scattering factors. We have tried to reduce the first problem by employing translation-libration-screw refinement, the second by employing a description of the correlated movement from MD simulations, and the third by studying only the change in entropy when a pair of ligands binds to the same protein, thoroughly re-refining the structures in exactly the same way and using the same set of alternative conformations. However, the experimental B-factors seem to be incompatible with fluctuations from MD simulations and the precision is too poor to give any reliable entropies.


Assuntos
Simulação de Dinâmica Molecular , Proteínas/química , Temperatura Ambiente , Cristalografia por Raios X , Entropia , Galectina 3/química , Ligantes , Muramidase/química , Conformação Proteica , Tripsina/química
7.
Chem Commun (Camb) ; 55(70): 10392-10395, 2019 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-31407730

RESUMO

The preference of N,N-aryl, alkyl tertiary amides for cis conformations has been exploited through the use of tertiary squaramides as hairpin turn units that promote the folding of aromatic ß-sheets. Head-to-head aromatic arrangements were shown to prevail in sufficiently long bent aromatic sequences.


Assuntos
Dobramento de Proteína , Proteínas/química , Quinina/análogos & derivados , Cristalografia por Raios X , Conformação Proteica em Folha beta , Quinina/química
8.
Phys Chem Chem Phys ; 21(35): 18850-18865, 2019 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-31432055

RESUMO

Proton detected solid-state NMR under fast magic-angle-spinning (MAS) conditions is currently redefining the applications of solid-state NMR, in particular in structural biology. Understanding the contributions to the spectral linewidth is thereby of paramount importance. When disregarding the sample-dependent inhomogeneous contributions, the NMR proton linewidth is defined by homogeneous broadening, which has incoherent and coherent contributions. Understanding and disentangling these different contributions in multi-spin systems like proteins is still an open issue. The coherent contribution is mainly caused by the dipolar interaction under MAS and is determined by the molecular structure and the proton chemical shifts. Numerical simulation approaches based on numerically exact direct integration of the Liouville-von Neumann equation can give valuable information about the lineshape, but are limited to small spin systems (<12 spins). We present an alternative simulation method for the coherent contributions based on the rapid and partially analytic calculation of the second moments of large spin systems. We first validate the method on a simple system by predicting the 19F linewidth in CaF2 under MAS. We compare simulation results to experimental data for microcrystalline ubiquitin (deuterated 100% back-exchanged at 110 kHz and fully-protonated at 125 kHz). Our results quantitatively explain the observed linewidth per-residue basis for the vast majority of residues.


Assuntos
Simulação por Computador , Modelos Químicos , Proteínas/química , Ressonância Magnética Nuclear Biomolecular , Prótons
9.
Phys Chem Chem Phys ; 21(35): 18958-18969, 2019 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-31453590

RESUMO

Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention in the studies of protein-protein recognition. In this study, we evaluated the impact of enhanced sampling methods and solute dielectric constants on the overall accuracy of the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) approaches for the protein-protein binding free energy calculations. Here, two widely used enhanced sampling methods, including aMD and GaMD, and conventional molecular dynamics (cMD) simulations with two AMBER force fields (ff03 and ff14SB) were used to sample the conformations for 21 protein-protein complexes. The MM/PBSA and MM/GBSA calculation results illustrate that the standard MM/GBSA based on the cMD simulations yields the best Pearson correlation (rp = -0.523) between the predicted binding affinities and the experimental data, which is much higher than that given by MM/PBSA (rp = -0.212). Two enhanced sampling methods (aMD and GaMD) are indeed more efficient for conformational sampling, but they did not improve the binding affinity predictions for protein-protein systems, suggesting that the aMD or GaMD sampling (at least in short timescale simulations) may not be a good choice for the MM/PBSA and MM/GBSA predictions of protein-protein complexes. The solute dielectric constant of 1.0 is recommended to MM/GBSA, but a higher solute dielectric constant is recommended to MM/PBSA, especially for the systems with higher polarity on the protein-protein binding interfaces. Then, a preliminary assessment of the MM/GBSA calculations based on a variable dielectric generalized Born (VDGB) model was conducted. The results highlight the potential power of VDGB in the free energy predictions for protein-protein systems, but more thorough studies should be done in the future.


Assuntos
Técnicas de Química Analítica/métodos , Modelos Químicos , Proteínas/química , Técnicas de Química Analítica/normas , Simulação de Dinâmica Molecular , Ligação Proteica , Conformação Proteica , Reprodutibilidade dos Testes
10.
J Chem Phys ; 151(3): 034102, 2019 Jul 21.
Artigo em Inglês | MEDLINE | ID: mdl-31325945

RESUMO

Nuclear magnetic resonance (NMR) is sensitive to dynamics on a wide range of correlation times. Recently, we have shown that analysis of relaxation rates via fitting to a correlation function with a small number of exponential terms could yield a biased characterization of molecular motion in solid-state NMR due to limited sensitivity of experimental data to certain ranges of correlation times. We introduced an alternative approach based on "detectors" in solid-state NMR, for which detector responses characterize motion for a range of correlation times and reduce potential bias resulting from the use of simple models for the motional correlation functions. Here, we show that similar bias can occur in the analysis of solution-state NMR relaxation data. We have thus adapted the detector approach to solution-state NMR, specifically separating overall tumbling motion from internal motions and accounting for contributions of chemical exchange to transverse relaxation. We demonstrate that internal protein motions can be described with detectors when the overall motion and the internal motions are statistically independent. We illustrate the detector analysis on ubiquitin with typical relaxation data sets recorded at a single high magnetic field or at multiple high magnetic fields and compare with results of model-free analysis. We also compare our methodology to LeMaster's method of dynamics analysis.


Assuntos
Ressonância Magnética Nuclear Biomolecular/métodos , Proteínas/química , Termodinâmica
12.
J Phys Chem A ; 123(28): 5995-6002, 2019 Jul 18.
Artigo em Inglês | MEDLINE | ID: mdl-31268326

RESUMO

High-resolution X-ray crystallography and two-dimensional NMR studies demonstrate that water-mediated conventional hydrogen-bonding interactions (N-H···N, O-H···N, etc.) bridging two or more amino acid residues contribute to the stability of proteins and protein-ligand complexes. In this work, we have investigated single water-mediated selenium hydrogen-bonding interactions (unconventional hydrogen-bonding) between amino acid residues in proteins through extensive protein data bank (PDB) analysis coupled with gas-phase spectroscopy and quantum chemical calculation of a model complex consisting of indole, dimethyl selenide, and water. Here, indole and dimethyl selenide represent the amino acid residues tryptophan and selenomethionine, respectively. The current investigation demonstrates that the most stable structure of the model complex observed in the IR spectroscopy mimics single water-mediated selenium hydrogen-bonded structural motifs present in the crystal structures of proteins. The present work establishes that water-mediated Se hydrogen-bonding interactions are ubiquitous in proteins and the number of these interactions observed in the PDB is more than that of direct Se hydrogen-bonds present there.


Assuntos
Proteínas/química , Selênio/química , Água/química , Biologia Computacional , Cristalografia por Raios X , Bases de Dados de Proteínas , Ligações de Hidrogênio , Indóis/química , Ligantes , Modelos Moleculares , Compostos Organosselênicos/química , Teoria Quântica , Selenometionina/química , Espectrofotometria Infravermelho , Triptofano/química
13.
J Phys Chem Lett ; 10(15): 4382-4400, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31304749

RESUMO

It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, machine learning models (Random Forest (RF), AdaBoost Regressor (ABR), Gradient Boosting Regressor (GBR)), and Deep Learning models were utilized to validate the Docking results, and we obtained an R2 of 0.922 on the training set and 0.804 on the test set in the RF algorithm. For the Deep Learning algorithm, R2 of the training set is 0.90, and R2 of the test set is 0.810. However, these TCM compounds fly away during the molecular dynamics (MD) simulation. We seek another method: peptide design. All peptide database were screened by the Docking process. Modification peptides were optimized the interaction modes, and the affinities were assessed with ZDOCK protocol and Refine Docked protein protocol. The 300 ns MD simulation evaluated the stability of receptor-peptide complexes. The double-site effect appeared on S2, a designed peptide based on a known inhibitor, when complexed with BCL2. S3, a designed peptide referred from endogenous inhibitor P16, competed against cyclin when binding with CDK6. The MDM2 inhibitors S5 and S6 were derived from the P53 structure and stable binding with MDM2. A flexible region of peptides S5 and S6 may enhance the binding ability by changing its own conformation, which was unforeseen. These peptides (S2, S3, S5, and S6) are potentially interesting to treat cancer; however, these findings need to be affirmed by biological testing, which will be conducted in the near future.


Assuntos
Antineoplásicos/química , Aprendizado Profundo , Aprendizado de Máquina , Modelos Moleculares , Peptídeos/química , Proteínas/química , Algoritmos , Sítios de Ligação , Quinase 6 Dependente de Ciclina/química , Inibidor p16 de Quinase Dependente de Ciclina/química , Bases de Dados de Produtos Farmacêuticos , Bases de Dados de Proteínas , Desenho de Drogas , Ligantes , Metaloproteinase 13 da Matriz/química , Mutação , Proteínas Proto-Oncogênicas c-bcl-2/química , Proteínas Proto-Oncogênicas c-mdm2/química , Proteína Supressora de Tumor p53/química , Proteína Supressora de Tumor p53/genética
14.
Bioresour Technol ; 291: 121868, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31357045

RESUMO

To clarify the adsorption behaviors of typical heavy metals onto sludge extracellular polymeric substances (EPS), the adsorption capacities and mechanisms, as well as the contributions of the different EPS components (proteins, humic acids and polysaccharides), to the adsorption of Zn2+, Cu2+ and Cd2+ were separately explored. Overall, proteins exhibited a relatively high adsorption capacity for the three metals ions, followed by humic acid, whereas least for polysaccharides. The adsorption of Cu2+ and Cd2+ onto proteins, humic acid and polysaccharides fit well to the Freundlich isotherm, whereas Langmuir model was the best fit for Zn2+ bindings onto polysaccharides/humic acid. The binding of Cu2+, Zn2+ and Cd2+ onto the three EPS components was exothermically favorable, and significant electrostatic interactions were observed for the heavy metals sorption onto humic acid and proteins. In addition, the effect of metal ions sorption on the spectrum of the proteins, polysaccharides and humic acid was also explored.


Assuntos
Cádmio/química , Cobre/química , Substâncias Húmicas , Polissacarídeos/química , Proteínas/metabolismo , Esgotos , Zinco/química , Adsorção , Cádmio/metabolismo , Cobre/metabolismo , Proteínas/química , Esgotos/química , Zinco/metabolismo
15.
BMC Bioinformatics ; 20(1): 392, 2019 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-31307371

RESUMO

BACKGROUND: Clustering methods are essential to partitioning biological samples being useful to minimize the information complexity in large datasets. Tools in this context usually generates data with greed algorithms that solves some Data Mining difficulties which can degrade biological relevant information during the clustering process. The lack of standardization of metrics and consistent bases also raises questions about the clustering efficiency of some methods. Benchmarks are needed to explore the full potential of clustering methods - in which alignment-free methods stand out - and the good choice of dataset makes it essentials. RESULTS: Here we present a new approach to Data Mining in large protein sequences datasets, the Rapid Alignment Free Tool for Sequences Similarity Search to Groups (RAFTS3G), a method to clustering aiming of losing less biological information in the processes of generation groups. The strategy developed in our algorithm is optimized to be more astringent which reflects increase in accuracy and sensitivity in the generation of clusters in a wide range of similarity. RAFTS3G is the better choice compared to three main methods when the user wants more reliable result even ignoring the ideal threshold to clustering. CONCLUSION: In general, RAFTS3G is able to group up to millions of biological sequences into large datasets, which is a remarkable option of efficiency in clustering. RAFTS3G compared to other "standard-gold" methods in the clustering of large biological data maintains the balance between the reduction of biological information redundancy and the creation of consistent groups. We bring the binary search concept applied to grouped sequences which shows maintaining sensitivity/accuracy relation and up to minimize the time of data generated with RAFTS3G process.


Assuntos
Proteínas/química , Software , Algoritmos , Análise por Conglomerados , Mineração de Dados , Bases de Dados de Proteínas
16.
Nat Commun ; 10(1): 2905, 2019 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-31266953

RESUMO

Delivery into mammalian cells remains a significant challenge for many applications of proteins as research tools and therapeutics. We recently reported that the fusion of cargo proteins to a supernegatively charged (-30)GFP enhances encapsulation by cationic lipids and delivery into mammalian cells. To discover polyanionic proteins with optimal delivery properties, we evaluate negatively charged natural human proteins for their ability to deliver proteins into cultured mammalian cells and human primary fibroblasts. Here we discover that ProTα, a small, widely expressed, intrinsically disordered human protein, enables up to ~10-fold more efficient cationic lipid-mediated protein delivery compared to (-30)GFP. ProTα enables efficient delivery at low- to mid-nM concentrations of two unrelated genome editing proteins, Cre recombinase and zinc-finger nucleases, under conditions in which (-30)GFP fusion or cationic lipid alone does not result in substantial activity. ProTα may enable mammalian cell protein delivery applications when delivery potency is limiting.


Assuntos
Edição de Genes/métodos , Lipossomos/química , Proteínas/química , Edição de Genes/instrumentação , Proteínas de Fluorescência Verde/química , Proteínas de Fluorescência Verde/genética , Proteínas de Fluorescência Verde/metabolismo , Células HeLa , Humanos , Integrases/química , Integrases/genética , Integrases/metabolismo , Lipossomos/metabolismo , Transporte Proteico , Proteínas/genética , Proteínas/metabolismo , Proteínas Recombinantes de Fusão/química , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Nucleases de Dedos de Zinco/química , Nucleases de Dedos de Zinco/genética , Nucleases de Dedos de Zinco/metabolismo
17.
BMC Bioinformatics ; 20(Suppl 13): 381, 2019 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-31337329

RESUMO

BACKGROUND: How can we obtain fast and high-quality clusters in genome scale bio-networks? Graph clustering is a powerful tool applied on bio-networks to solve various biological problems such as protein complexes detection, disease module detection, and gene function prediction. Especially, MCL (Markov Clustering) has been spotlighted due to its superior performance on bio-networks. MCL, however, is skewed towards finding a large number of very small clusters (size 1-3) and fails to detect many larger clusters (size 10+). To resolve this fragmentation problem, MLR-MCL (Multi-level Regularized MCL) has been developed. MLR-MCL still suffers from the fragmentation and, in cases, unrealistically large clusters are generated. RESULTS: In this paper, we propose PS-MCL (Parallel Shotgun Coarsened MCL), a parallel graph clustering method outperforming MLR-MCL in terms of running time and cluster quality. PS-MCL adopts an efficient coarsening scheme, called SC (Shotgun Coarsening), to improve graph coarsening in MLR-MCL. SC allows merging multiple nodes at a time, which leads to improvement in quality, time and space usage. Also, PS-MCL parallelizes main operations used in MLR-MCL which includes matrix multiplication. CONCLUSIONS: Experiments show that PS-MCL dramatically alleviates the fragmentation problem, and outperforms MLR-MCL in quality and running time. We also show that the running time of PS-MCL is effectively reduced with parallelization.


Assuntos
Algoritmos , Proteínas/metabolismo , Análise por Conglomerados , Cadeias de Markov , Mapas de Interação de Proteínas , Proteínas/química
18.
BMC Bioinformatics ; 20(Suppl 13): 383, 2019 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-31337333

RESUMO

BACKGROUND: Drug repurposing has been motivated to ameliorate low probability of success in drug discovery. For the recent decade, many in silico attempts have received primary attention as a first step to alleviate the high cost and longevity. Such study has taken benefits of abundance, variety, and easy accessibility of pharmaceutical and biomedical data. Utilizing the research friendly environment, in this study, we propose a network-based machine learning algorithm for drug repurposing. Particularly, we show a framework on how to construct a drug network, and how to strengthen the network by employing multiple/heterogeneous types of data. RESULTS: The proposed method consists of three steps. First, we construct a drug network from drug-target protein information. Then, the drug network is reinforced by utilizing drug-drug interaction knowledge on bioactivity and/or medication from literature databases. Through the enhancement, the number of connected nodes and the number of edges between them become more abundant and informative, which can lead to a higher probability of success of in silico drug repurposing. The enhanced network recommends candidate drugs for repurposing through drug scoring. The scoring process utilizes graph-based semi-supervised learning to determine the priority of recommendations. CONCLUSIONS: The drug network is reinforced in terms of the coverage and connections of drugs: the drug coverage increases from 4738 to 5442, and the drug-drug associations as well from 808,752 to 982,361. Along with the network enhancement, drug recommendation becomes more reliable: AUC of 0.89 was achieved lifted from 0.79. For typical cases, 11 recommended drugs were shown for vascular dementia: amantadine, conotoxin GV, tenocyclidine, cycloeucine, etc.


Assuntos
Reposicionamento de Medicamentos/métodos , Preparações Farmacêuticas/química , Área Sob a Curva , Interações de Medicamentos , Humanos , Preparações Farmacêuticas/metabolismo , Proteínas/química , Proteínas/metabolismo , Curva ROC , Aprendizado de Máquina Supervisionado
19.
BMC Bioinformatics ; 20(1): 400, 2019 Jul 18.
Artigo em Inglês | MEDLINE | ID: mdl-31319797

RESUMO

BACKGROUND: The CATH database provides a hierarchical classification of protein domain structures including a sub-classification of superfamilies into functional families (FunFams). We analyzed the similarity of binding site annotations in these FunFams and incorporated FunFams into the prediction of protein binding residues. RESULTS: FunFam members agreed, on average, in 36.9 ± 0.6% of their binding residue annotations. This constituted a 6.7-fold increase over randomly grouped proteins and a 1.2-fold increase (1.1-fold on the same dataset) over proteins with the same enzymatic function (identical Enzyme Commission, EC, number). Mapping de novo binding residue prediction methods (BindPredict-CCS, BindPredict-CC) onto FunFam resulted in consensus predictions for those residues that were aligned and predicted alike (binding/non-binding) within a FunFam. This simple consensus increased the F1-score (for binding) 1.5-fold over the original prediction method. Variation of the threshold for how many proteins in the consensus prediction had to agree provided a convenient control of accuracy/precision and coverage/recall, e.g. reaching a precision as high as 60.8 ± 0.4% for a stringent threshold. CONCLUSIONS: The FunFams outperformed even the carefully curated EC numbers in terms of agreement of binding site residues. Additionally, we assume that our proof-of-principle through the prediction of protein binding residues will be relevant for many other solutions profiting from FunFams to infer functional information at the residue level.


Assuntos
Domínios Proteicos , Proteínas/química , Sítios de Ligação , Bases de Dados de Proteínas , Ligação Proteica , Proteínas/classificação , Proteínas/metabolismo
20.
BMC Bioinformatics ; 20(Suppl 14): 335, 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31266447

RESUMO

BACKGROUND: Predicting the effect of single point variations on protein stability constitutes a crucial step toward understanding the relationship between protein structure and function. To this end, several methods have been developed to predict changes in the Gibbs free energy of unfolding (∆∆G) between wild type and variant proteins, using sequence and structure information. Most of the available methods however do not exhibit the anti-symmetric prediction property, which guarantees that the predicted ∆∆G value for a variation is the exact opposite of that predicted for the reverse variation, i.e., ∆∆G(A → B) = -∆∆G(B → A), where A and B are amino acids. RESULTS: Here we introduce simple anti-symmetric features, based on evolutionary information, which are combined to define an untrained method, DDGun (DDG untrained). DDGun is a simple approach based on evolutionary information that predicts the ∆∆G for single and multiple variations from sequence and structure information (DDGun3D). Our method achieves remarkable performance without any training on the experimental datasets, reaching Pearson correlation coefficients between predicted and measured ∆∆G values of ~ 0.5 and ~ 0.4 for single and multiple site variations, respectively. Surprisingly, DDGun performances are comparable with those of state of the art methods. DDGun also naturally predicts multiple site variations, thereby defining a benchmark method for both single site and multiple site predictors. DDGun is anti-symmetric by construction predicting the value of the ∆∆G of a reciprocal variation as almost equal (depending on the sequence profile) to -∆∆G of the direct variation. This is a valuable property that is missing in the majority of the methods. CONCLUSIONS: Evolutionary information alone combined in an untrained method can achieve remarkably high performances in the prediction of ∆∆G upon protein mutation. Non-trained approaches like DDGun represent a valid benchmark both for scoring the predictive power of the individual features and for assessing the learning capability of supervised methods.


Assuntos
Algoritmos , Estabilidade Proteica , Proteínas/química , Sequência de Aminoácidos , Evolução Molecular , Humanos , Mutação Puntual , Proteínas/genética , Termodinâmica
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