Analyzing VEGFA/VEGFR1 Interaction: Application of the Resonant Recognition Model-Stockwell Transform Method to Explore Potential Therapeutics for Angiogenesis-Related Diseases.

The interaction between vascular endothelial growth factor A (VEGFA) and VEGF receptor 1(VEGFR1) is a central focus for drug development in pathological angiogenesis, where aberrant angiogenesis underlies various anomalies necessitating therapeutic intervention. Identifying hotspots of these proteins is crucial for developing new therapeutics. Although machine learning techniques have succeeded significantly in prediction tasks, they struggle to pinpoint hotspots linked to angiogenic activity accurately. This study involves the collection of diverse VEGFA and VEGFR1 protein sequences from various species via the UniProt database. Electron-ion interaction Potential (EIIP) values were assigned to individual amino acids and transformed into frequency-domain representations using discrete Fast Fourier Transform (FFT). A consensus spectrum emerged by consolidating FFT data from multiple sequences, unveiling specific characteristic frequencies. Subsequently, the Stockwell Transform (ST) was employed to yield the hotspots. The Resonant Recognition Model (RRM) identified a characteristic frequency of 0.128007 with an associated wavelength of 1570 nm and RRM-ST identified hotspots for VEGFA (Human 36, 46, 48, 67, 71, 74, 82, 86, 89, 93) and VEGFR1 (Human 224, 259, 263, 290, 807, 841, 877, 881, 885, 892, 894, 909, 913, 1018, 1022, 1026, 1043). These findings were cross-validated by Hotspots Wizard 3.0 webserver and Protein Data Bank (PDB). The study proposes using a 1570 nm wavelength for photo bio modulation to boost VEGFA/VEGFR1 interaction in the condition that is needed. It also aims to reduce VEGFA/VEGFR2 interaction, limiting harmful angiogenesis in conditions like diabetic retinopathy. Also, the identified hotspots assist in designing agonistic or antagonistic peptides tailored to specific medical requirements with abnormal angiogenesis.

Photophysical Mechanisms of Photobiomodulation Therapy as Precision Medicine.

Despite a significant focus on the photochemical and photoelectrical mechanisms underlying photobiomodulation (PBM), its complex functions are yet to be fully elucidated. To date, there has been limited attention to the photophysical aspects of PBM. One effect of photobiomodulation relates to the non-visual phototransduction pathway, which involves mechanotransduction and modulation to cytoskeletal structures, biophotonic signaling, and micro-oscillatory cellular interactions. Herein, we propose a number of mechanisms of PBM that do not depend on cytochrome c oxidase. These include the photophysical aspects of PBM and the interactions with biophotons and mechanotransductive processes. These hypotheses are contingent on the effect of light on ion channels and the cytoskeleton, the production of biophotons, and the properties of light and biological molecules. Specifically, the processes we review are supported by the resonant recognition model (RRM). This previous research demonstrated that protein micro-oscillations act as a signature of their function that can be activated by resonant wavelengths of light. We extend this work by exploring the local oscillatory interactions of proteins and light because they may affect global body circuits and could explain the observed effect of PBM on neuro-cortical electroencephalogram (EEG) oscillations. In particular, since dysrhythmic gamma oscillations are associated with neurodegenerative diseases and pain syndromes, including migraine with aura and fibromyalgia, we suggest that transcranial PBM should target diseases where patients are affected by impaired neural oscillations and aberrant brain wave patterns. This review also highlights examples of disorders potentially treatable with precise wavelengths of light by mimicking protein activity in other tissues, such as the liver, with, for example, Crigler-Najjar syndrome and conditions involving the dysregulation of the cytoskeleton. PBM as a novel therapeutic modality may thus behave as "precision medicine" for the treatment of various neurological diseases and other morbidities. The perspectives presented herein offer a new understanding of the photophysical effects of PBM, which is important when considering the relevance of PBM therapy (PBMt) in clinical applications, including the treatment of diseases and the optimization of health outcomes and performance.

Resonant Recognition Model Study for Interactions between SARS CoV 2 and Human Proteins

This study was devoted to the Resonant Recognition Model (RRM) analysis of SARS-CoV-2 proteins and their possible interaction with other human proteins, specifically, SARS CoV replicases and methyl transferases, were tested, via RRM analysis, for possible interactions with host CD4 T receptor proteins and prohibitins which participate in human organism response to viral infections. The following protein sequences were studied: twenty human SARS coronavirus methyltransferase proteins, eight replicase proteins, twenty-one prohibitin proteins, and eleven CD4 -T-cell surface antigens T4 proteins. Results revealed RRM peaks at f1=0.07349 and f2=0.2839. The peak at f1 was also common for interaction between SARS-CoV-2 methyl transferases and human prohibitins, where opposite phase suggest binding between these proteins during viral infection. This interaction was not supported for viral methyltransferase and human CD4 receptors (72.4 o phase shift). Viral replicases exhibited opposite phase interaction with both prohibitins and CD4 receptors. Overall, RRM revealed common RRM frequencies for both replicases and methyl transferases, and added plausibility to interactions between SARSCoV2 methyl transferase and human prohibitin, as well as between SARS Cov2 replicase and human prohibitin and CD4 T-cell receptors(AU)

Este estudio se dedicó al análisis mediante el Modelo de Reconocimiento Resonante (RRM) de las proteínas del SARS-CoV-2 y su posible interacción con otras proteínas humanas, específicamente, fueron analizadas las replicasas de SARS CoV y las metiltransferasas, mediante análisis RRM, para detectar posibles interacciones con las Proteínas del receptor CD4 T y las prohibitinas humanas, las cuales participan en la respuesta del organismo humano a las infecciones virales. Se estudiaron las siguientes secuencias de proteínas: veinte proteínas metiltransferasas del coronavirus del SARS humano, ocho replicasas, veintiuna prohibitinas y once proteínas T4 de antígenos de superficie de células T CD4. Los resultados revelaron picos de RRM en f1 = 0.07349 y f2 = 0.2839. El pico en f1 también fue común para la interacción entre las metiltransferasas del SARS-CoV-2 y las prohibitinas humanas, donde la fase opuesta sugiere la unión entre estas proteínas durante la infección viral. Esta interacción no fue apoyada para la metiltransferasa viral y los receptores CD4 humanos (cambio de fase de 72,4 o). Las réplicas virales exhibieron una interacción de fase opuesta tanto con las prohibitinas como con los receptores CD4. En general, el análisis de RRM reveló frecuencias comunes de RRM para replicasas y metiltransferasas, y apoyó plausibilidad de las interacciones entre la metiltransferasa de SARSCoV2 y la prohibitina humana, así como entre la replicasa de Cov2 del SARS con la prohibitina humana y los receptores de células T CD4(AU)

Studying Protein kinases PKCζ and PKMζ with the Resonant Recognition Model. Implications for the study of Memory Mechanisms / Estudio de proteínas quinasas PKCζ; y PKMζ; mediante el Modelo de Reconocimiento Resonante. Implicaciones para el estudio de los Mecanismos de Memoria

PKMζ is a brain-specific protein kinase that has been suggested as playing a key role in memory consolidation mechanisms. It is identical to catalytic portion of another protein kinase, PKMζ;. Lacking the regulatory end, PKMζ; is several times more active than PKMζ;. However, knowledge about PKMζ; mechanisms in memory consolidation is patchy, and sometimes contradictory. The resonant recognition model (RRM) might shed some light in understanding PKMζ; role on memory consolidation. This is the first attempt in literature to apply the RRM to the study of PKMζ; and PKMζ;. We obtained that PKMζ; presents a spectral peak at the resonant recognition frequency of fRRM= 0.063 (likely, corresponding to the infrared frequency of 3190 nm) and another peak at fRRM =0.211(950 nm in the near infrared). Peak at fRRM= 0.063 is also shared by PKMζ;, and the peak at fRRM =0.211 is similar to the one recently reported in literature for regulatory proteins. We hypothesize that irradiating with a weak light infrared source at these frequencies would modify long term potentiation results. Finally, a scheme for resonant interactions in PKMζ; andPKMζ; is proposed(AU)

PKMζ; es una proteína quinasa específica del cerebro que se ha sugerido que desempeña un papel clave en los mecanismos de consolidación de la memoria. Es idéntica a la porción catalítica de otra proteína quinasa, PKMζ. Al carecer de la porción regulatoria, PKMζ; es varias veces más activa que PKMζ;. Sin embargo, el conocimiento sobre los mecanismos de PKMζ in en la consolidación de la memoria es parcial, y a veces contradictorio. El modelo de reconocimiento resonante (RRM) podría esclarecer la comprensión del papel de PKMζ; en la consolidación de la memoria. Este es el primer intento en la literatura para aplicar el MRR al estudio de PKMζ y PKMζ;. Se obtuvo que PKMζ; presenta un pico espectral a la frecuencia de reconocimiento resonante fRRM = 0,063 (probablemente, correspondiente a la frecuencia infrarroja de 3190 nm) y otro pico a fRRM = 0,211 (950 nm en el infrarrojo cercano). Pico en fRRM = 0,063 es también compartida por PKMζ;, y el pico a fRRM = 0,211 es similar a la recientemente informado en la literatura para las proteínas reguladoras. Se plantea la hipótesis de que la irradiación con una fuente de luz infrarroja débil a estas frecuencias podría modificar los resultados de potenciación a largo plazo. Finalmente, se propone un esquema para interacciones resonantes en PKMζ; y PKC(AU)

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

Analysis of Tumor Necrosis Factor Function Using the Resonant Recognition Model.

The tumor necrosis factor (TNF) is a complex protein that plays a very important role in a number of biological functions including apoptotic cell death, tumor regression, cachexia, inflammation inhibition of tumorigenesis and viral replication. Its most interesting function is that it is an inhibitor of tumorigenesis and inductor of apoptosis. Thus, the TNF could be a good candidate for cancer therapy. However, the TNF has also inflammatory and toxic effects. Therefore, it would be very important to understand complex functions of the TNF and consequently be able to predict mutations or even design the new TNF-related proteins that will have only a tumor inhibition function, but not other side effects. This can be achieved by applying the resonant recognition model (RRM), a unique computational model of analysing macromolecular sequences of proteins, DNA and RNA. The RRM is based on finding that certain periodicities in distribution of free electron energies along protein, DNA and RNA are strongly correlated to the biological function of these macromolecules. Thus, based on these findings, the RRM has capabilities of protein function identification, prediction of bioactive amino acids and protein design with desired biological function. Using the RRM, we separate different functions of TNF as different periodicities (frequencies) within the distribution of free energy electrons along TNF protein. Interestingly, these characteristic TNF frequencies are related to previously identified characteristics of proto-oncogene and oncogene proteins describing TNF involvement in oncogenesis. Consequently, we identify the key amino acids related to the crucial TNF function, i.e. receptor recognition. We have also designed the peptide which will have the ability to recognise the receptor without side effects.

Algorithm, applications and evaluation for protein comparison by Ramanujan Fourier transform.

The amino acid sequence of a protein determines its chemical properties, chain conformation and biological functions. Protein sequence comparison is of great importance to identify similarities of protein structures and infer their functions. Many properties of a protein correspond to the low-frequency signals within the sequence. Low frequency modes in protein sequences are linked to the secondary structures, membrane protein types, and sub-cellular localizations of the proteins. In this paper, we present Ramanujan Fourier transform (RFT) with a fast algorithm to analyze the low-frequency signals of protein sequences. The RFT method is applied to similarity analysis of protein sequences with the Resonant Recognition Model (RRM). The results show that the proposed fast RFT method on protein comparison is more efficient than commonly used discrete Fourier transform (DFT). RFT can detect common frequencies as significant feature for specific protein families, and the RFT spectrum heat-map of protein sequences demonstrates the information conservation in the sequence comparison. The proposed method offers a new tool for pattern recognition, feature extraction and structural analysis on protein sequences.

Phosphocholine-binding antibody activities are hierarchically encoded in the sequence of the heavy-chain variable region: dominance of self-association activity in the T15 idiotype.

A methodology based on the representation of each amino acid of a protein sequence by the electron-ion interaction potential and subsequent analysis by signal processing was used to determine the characteristic or common frequency (in Hz) that reflects the biological activity shared among phosphocholine (PC)-binding antibodies. The common frequency for the variable portion of the heavy chain (VH) of the PC-specific antibodies is found to be at f = 0.37 Hz. The VH sequences of the PC-binding antibodies exhibit three subsites for the PC moiety where hypervariable region 2 (CDR2) plays a role in the interaction with the phosphate group. Mutations in this VH region have an impact on the ability of mutant variants to bind PC and its carrier molecule, as well as on the characteristic frequency shift toward f = 0.12 Hz for mutants failing to bind both hapten and carrier. The VH sequence of mutants that retain the ability to bind PC still shows f = 0.37 Hz, suggesting that this frequency determines PC binding. However, this statement was not confirmed as mutation in another PC subsite impairs PC binding but retains both the phosphate-group recognition and the frequency at f = 0.37 Hz. Herein, this finding is discussed to promote the idea that the VH sequence of the PC-binding antibodies encodes the subsite for phosphate-group binding as a dominant functional activity and that only CDR2 of the T15-idiotype antibodies together with FR3 region form an autonomous self-association function represented by the T15VH50-73 peptide with f = 0.37±0.05 Hz. Thus, these data confirmed that T15VH50-73 peptide might be used in superantibody technology.