Origin of low-frequency motions in biological macromolecules. A view of recent progress in the quasi-continuity model

Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model

Living organisms receive necessary energy substances directly from cellular respiration. The completion of electron storage and transportation requires the process of cellular respiration with the aid of electron transport chains. Therefore, the work of deciphering electron transport proteins is inevitably needed. The identification of these proteins with high performance has a prompt dependence on the choice of methods for feature extraction and machine learning algorithm. In this study, protein sequences served as natural language sentences comprising words. The nominated word embedding-based feature sets, hinged on the word embedding modulation and protein motif frequencies, were useful for feature choosing. Five word embedding types and a variety of conjoint features were examined for such feature selection. The support vector machine algorithm consequentially was employed to perform classification. The performance statistics within the 5-fold cross-validation including average accuracy, specificity, sensitivity, as well as MCC rates surpass 0.95. Such metrics in the independent test are 96.82, 97.16, 95.76 percent, and 0.9, respectively. Compared to state-of-the-art predictors, the proposed method can generate more preferable performance above all metrics indicating the effectiveness of the proposed method in determining electron transport proteins. Furthermore, this study reveals insights about the applicability of various word embeddings for understanding surveyed sequences.

An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule

OBJECTIVE

One of the most challenging and also the most difficult problems is how to formulate a biological sequence with a vector but considerably keep its sequence order information.

METHODS

To address such a problem, the approach of Pseudo Amino Acid Components or PseAAC has been developed.

RESULTS AND CONCLUSION

It has become increasingly clear via the 10-year recollection that the aforementioned proposal has been indeed very powerful.

Progress in the Mechanism and Clinical Application of Cilostazol

Cilostazol is a unique platelet inhibitor that has been used clinically for more than 20 years. As a phosphodiesterase type III inhibitor, cilostazol is capable of reversible inhibition of platelet aggregation and vasodilation, has antiproliferative effects, and is widely used in the treatment of peripheral arterial disease, cerebrovascular disease, percutaneous coronary intervention, etc. This article briefly reviews the pharmacological mechanisms and clinical application of cilostazol.

Scoring function for DNA-drug docking of anticancer and antiparasitic compounds based on spectral moments of 2D lattice graphs for molecular dynamics trajectories

We introduce here a new class of invariants for MD trajectories based on the spectral moments pi(k)(L) of the Markov matrix associated to lattice network-like (LN) graph representations of Molecular Dynamics (MD) trajectories. The procedure embeds the MD energy profiles on a 2D Cartesian coordinates system using simple heuristic rules. At the same time, we associate the LN with a Markov matrix that describes the probabilities of passing from one state to other in the new 2D space. We construct this type of LNs for 422 MD trajectories obtained in DNA-drug docking experiments of 57 furocoumarins. The combined use of psoralens+ultraviolet light (UVA) radiation is known as PUVA therapy. PUVA is effective in the treatment of skin diseases such as psoriasis and mycosis fungoides. PUVA is also useful to treat human platelet (PTL) concentrates in order to eliminate Leishmania spp. and Trypanosoma cruzi. Both are parasites that cause Leishmaniosis (a dangerous skin and visceral disease) and Chagas disease, respectively; and may circulate in blood products collected from infected donors. We included in this study both lineal (psoralens) and angular (angelicins) furocoumarins. In the study, we grouped the LNs on two sets; set1: DNA-drug complex MD trajectories for active compounds and set2: MD trajectories of non-active compounds or no-optimal MD trajectories of active compounds. We calculated the respective pi(k)(L) values for all these LNs and used them as inputs to train a new classifier that discriminate set1 from set2 cases. In training series the model correctly classifies 79 out of 80 (specificity=98.75%) set1 and 226 out of 238 (Sensitivity=94.96%) set2 trajectories. In independent validation series the model correctly classifies 26 out of 26 (specificity=100%) set1 and 75 out of 78 (sensitivity=96.15%) set2 trajectories. We propose this new model as a scoring function to guide DNA-docking studies in the drug design of new coumarins for anticancer or antiparasitic PUVA therapy.

Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks

Since the advent of Molecular Dynamics (MD) in biopolymers science with the study by Karplus et al. on protein dynamics, MD has become the by foremost well established, computational technique to investigate structure and function of biomolecules and their respective complexes and interactions. The analysis of the MD trajectories (MDTs) remains, however, the greatest challenge and requires a great deal of insight, experience, and effort. Here, we introduce a new class of invariants for MDTs based on the spatial distribution of Mean-Energy values ξ_k (L) on a 2D Euclidean space representation of the MDTs. The procedure forces one MD trajectory to fold into a 2D Cartesian coordinates system using a step-by-step procedure driven by simple rules. The ξ_k (L) values are invariants of a Markov matrix (¹ Π), which describes the probabilities of transition between two states in the new 2D space; which is associated to a graph representation of MDTs similar to the lattice networks (LNs) of DNA and protein sequences. We also introduce a new algorithm to perform phylogenetic analysis of peptides based on MDTs instead of the sequence of the polypeptide. In a first experiment, we illustrate this algorithm for 35 peptides present on the Peptide Mass Fingerprint (PMF) of a new protein of Leishmania infantum studied in this work. We report, by the first time, 2D Electrophoresis isolation, MALDI TOF Mass Spectroscopy characterization, and MASCOT search results for this PMF. In a second experiment, we construct the LNs for 422 MDTs obtained in DNA-Drug Docking simulations of the interaction of 57 anticancer furocoumarins with a DNA oligonucleotide. We calculated the respective ξ_k (L) values for all these LNs and used them as inputs to train a new classifier with Accuracy = 85.44% and 84.91% in training and validation respectively. The new model can be used as scoring function to guide DNA-Drug Docking studies in drug design of new coumarins for PUVA therapy. The new phylogenetics analysis algorithms encode information different from sequence similarity and may be used to analyze MDTs obtained in Docking or modeling experiments for any classes of biopolymers. The work opens new perspective on the analysis and applications of MD in polymer sciences.

Internal DNA modes below 25 cm-1: a resonance Raman spectroscopy observation

The first resonance Raman scattering observation of the low-frequency (LF) region (below 40 up to 12 cm-1) of DNA motions is presented. Since the concentration of the studied DNA solution was very low (1 mg/ml), the spectra features reflect internal vibrations of the macromolecule. The decomposition of the spectra into Lorentzians clearly indicate three intrahelical DNA modes: the corresponding peaks are located at the frequencies 16, 19, and 23 (+/- 1) cm-1. This result is in agreement with our quasi-continuity model of the LF B-form DNA dynamics (V. Lisy, P. Miskovsky and P. Schreiber, J. Biomol. Struct. Dyn. 13, 707 (1996)). The fit of the experimental frequencies to the theory, using the Genetic Algorithms approach, allowed us to make some conclusions about the model force constants which could be found by independent conformational energy calculations. Possible positions of five lowest-frequency DNA peaks, predicted by the model, are discussed.

On a simple model of low-frequency vibrations in DNA macromolecules

A simple quasi-continuity model of low-frequency dynamics of DNA macromolecules is presented. The model is based on the phenomenological theory by Volkov and Kosevich (J. Biomol. Struct. Dyn. 8, 1069 (1991)). We propose improvements to their theory by correcting the model energy and corresponding equations of motion, recalculating the model DNA parameters, and estimating the effects of hydration and counterion binding on the masses of DNA subunits. Comparing the calculated low-frequency vibration spectrum and the results of classical Raman scattering experiments from the literature, the values for the model force constants are determined. These values differ significantly from the estimations made by Volkov and Kosevich. A good quantitative agreement with experiment can be obtained both for the case when the "25 cm-1 mode" is an external one, and when it is considered as an intrahelical mode. Problems connected with the qualitative assignments of the calculated and experimentally observed modes are discussed.

Theory of low-frequency vibrations in DNA macromolecules

To describe low-frequency dynamics of DNA macromolecules a model is developed taking into account the hydrogen bond stretching in base pairs, the backbone flexibility and intranucleoside mobility. For double-stranded DNA the normal vibrations are found and the structure of low-frequency spectrum is determined. The agreement between theory and Raman spectroscopy data for B-DNA is demonstrated. Conformational dependences of vibration spectrum during the B----A and helix----coil DNA transitions are studied. The contribution coming from low-frequency mobility to the nucleic-protein recognition processes is discussed.

Quasi-continuum models of twist-like and accordion-like low-frequency motions in DNA

Formulae for calculating low-frequency twist-like and accordion-like modes of DNA molecules have been derived using a quasi-continuum model. The formulae can be employed in essentially all (viz. A, B, C, D, E, and Z) forms of DNA. Calculated results indicate that the experimentally observed low-frequency modes at 22 cm-1 for the A-form octanucleotide (d[CCCCGGGG]) and at 18 cm-1 for the B-form dodecanucleotide (d[CGCAA ATTTGCG]) may result from accordion-like motions, while those observed at 12 cm-1 and 15 cm-1 may result from combinations of twist-like oscillations excited in the intact segments of B- and A-DNA's, respectively. Frequency shifts in the low-frequency modes observed when DNA molecules undergo conformational changes among different forms are also discussed in terms of the current model.

Low-frequency collective motion in biomacromolecules and its biological functions

The occurrence of low-frequency motion in biomacromolecules, which had long been speculated upon with a great deal of skepticism, is now a clearly established phenomenon and has been convincingly demonstrated. The next stage in the process of its elucidation appropriately concerns the determination of its origin, the development of a feasible and effective model for the calculations involved and, more importantly, the extending of investigations on its biological roles in order to gain insights into the various interesting mechanisms underlying the dynamic processes occurring in biomacromolecules. Confronted with such a task, this review has been written with the aim of stimulating further, through a systematic and comprehensive description, developments to open up this exciting frontier of molecular biology, especially from the viewpoint of biological functions.