The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Synthesis and computational evaluation of the antioxidant activity of pyrrolo[2,3-b]quinoxaline derivatives.

Pyrrolo[2,3-b]quinoxaline derivatives are known to possess antioxidant, anticancer, and antibacterial properties. Here we report the successful synthesis of five derivatives of 3-hydroxy-3-pyrroline-2-one through substitution. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay was employed to evaluate the antioxidant activity of the compounds. Out of these, ethyl 1,2-diphenyl-1H-pyrrolo[2,3-b]quinoxaline-3-carboxylate (3a) demonstrated the greatest potential as a radical scavenger. Thermodynamic and kinetic calculations of the radical scavenging activity indicated that 3a exhibited HO˙ radical scavenging activity with the overall rate constant of 8.56 × 108 M-1 s-1 in pentyl ethanoate; however, it was incapable of scavenging hydroperoxyl radicals in nonpolar media. In non-polar environments, the hydroxyl radical scavenging capability of 3a is fairly similar to that of reference antioxidants such as Trolox, melatonin, indole-3-carbinol, and gallic acid. Hence, in the physiological lipid environment, 3a holds promise as a scavenger of HO˙ radicals.

Applying Machine Learning for Antibiotic Development and Prediction of Microbial Resistance.

Antimicrobial resistance (AMR) poses a serious threat to human health worldwide. It is now more challenging than ever to introduce a potent antibiotic to the market considering rapid emergence of antimicrobial resistance, surpassing the rate of antibiotic drug discovery. Hence, new approaches need to be developed to accelerate the rate of drug discovery process and meet the demands for new antibiotics, while reducing the cost of their development. Machine learning holds immense promise of becoming a useful tool, especially since in the last two decades, exponential growth has occurred in computational power and biological big data analytics. Recent advancements in machine learning algorithms for drug discovery have provided significant clues for potential antibiotic classes. Apart from discovery of new scaffolds, the machine learning protocols will significantly impact prediction of AMR patterns and drug metabolism. In this review, we outline power of machine learning in antibiotic drug discovery, metabolic fate, and AMR prediction to support researchers engaged and interested in this field.

Computational assessment of the radical scavenging activity of cleomiscosin.

Coumarinolignans such as cleomiscosin A (CMA), cleomiscosin B (CMB), and cleomiscosin C (CMC) are secondary metabolites that were isolated from diverse plant species. Cleomiscosins (CMs) have numerous interesting biological activities, including noteworthy cytotoxicity of cancer cell lines along with hepatoprotective and assumed antioxidant activities. In this present study, the antioxidant properties of three cleomiscosins were investigated with a focus on the structure-activity relationship using thermodynamic and kinetic calculations with the M06-2X/6-311++G(d,p) method. The results show that CMs, including CMA, CMB, and CMC, are weak antioxidants in apolar environments, with k overall of 7.52 × 102 to 6.28 × 104 M-1 s-1 for the HOO˙ radical scavenging reaction in the gas phase and 3.47 × 102 to 6.44 × 104 M-1 s-1 in pentyl ethanoate. Remarkably, the difference in the fusion of phenylpropanoid structure with coumarin via two ortho-hydroxyl groups (CMA and CMB) does not cause any noticeable effect on their antioxidant activity, while the presence of a methoxy substitute on the aromatic ring of phenylpropanoid units (CMC) increases the reaction rate to about 61 to 84 times faster than that of CMA. In contrast, the studied CMs exhibit a good antioxidant capacity in polar environments, with a k overall range from 4.03 × 107 to 8.66 × 107 M-1 s-1, 102-103 times faster than that of Trolox, equal to that of ascorbic acid and resveratrol. The angular fusion of the phenylpropanoid and coumarin structures, as well as the methoxy substitution on the aromatic ring of the phenylpropanoid unit of the studied CMs, do not have any considerable effect on their antioxidant activity under the studied conditions.

Molecular dynamics simulations reliably identify vibrational modes in far-IR spectra of phospholipids.

The properties of self-assembled phospholipid membranes are of essential importance in biochemistry and physical chemistry, providing a platform for many cellular life functions. Far-infrared (far-IR) vibrational spectroscopy, on the other hand, is a highly information-rich method to characterize intermolecular interactions and collective behaviour of lipids that can help explain, e.g., chain packing, thermodynamic phase behaviour, and sequestration. However, reliable interpretation of the far-IR spectra is still lacking. Here we present a molecular dynamics (MD) based approach to simulate vibrational modes of individual lipids and in an ensemble. The results are a good match to synchrotron far-IR measurements and enable identification of the molecular motions corresponding to each vibrational mode, thus allowing the correct interpretation of membrane spectra with high accuracy and resolving the longstanding ambiguities in the literature in this regard. Our results demonstrate the feasibility of using MD simulations for interpreting far-IR spectra broadly, opening new avenues for practical use of this powerful method.

The radical scavenging activity of monocaffeoylquinic acids: the role of neighboring hydroxyl groups and pH levels.

Caffeoylquinic acids (CQAs) are well-known antioxidants. However, a key aspect of their radical scavenging activity - the mechanism of action - has not been addressed in detail thus far. Here we report on a computational study of the mechanism of activity of CQAs in scavenging hydroperoxyl radicals. In water at physiological pH, the CQAs demonstrated ≈ 104 times higher HOO˙ antiradical activity than in lipid medium (k(lipid) ≈ 104 M-1 s-1). The activity in the aqueous solution was determined by the hydrogen transfer mechanism of the adjacent hydroxyl group (O6'-H) of the dianion states (Γ = 93.2-95.2%), while the single electron transfer reaction of these species contributed 4.8-6.8% to the total rate constants. The kinetics estimated by the calculations are consistent with experimental findings in water (pH = 7.5), yielding a kcalculated/kexperimental = 2.4, reinforcing the reliability and precision of the computational method and demonstrating its utility for evaluating radical reactions in silico. The results also revealed the pH dependence of the HOO˙ scavenging activity of the CQAs; activity was comparable for all compounds below pH 3, however at higher pH values 5CQA reacted with the HOO˙ with lower activity than 3CQA or 4CQA. It was also found that CQAs are less active than Trolox below pH 4.7, however over pH 5.0 they showed higher activity than the reference. The CQAs had the best HOO˙ antiradical activity at pH values between 5.0 and 8.6. Therefore, in the physiological environment, the hydroperoxyl antiradical capacity of CQAs exhibits similarity to renowned natural antioxidants including resveratrol, ascorbic acid, and Trolox.

The Theoretical and Experimental Insights into the Radical Scavenging Activity of Rubiadin.

Rubiadin (RBD), an anthraquinone derivative, is obtained from Rubia cordifolia, a plant species classified under the Rubiaceae family. Rubiadin has proven beneficial properties, such as anticancer, neuroprotective, anti-inflammatory, and antidiabetic activity. The antioxidant activity of this molecule was suggested by some experimental results but has not been clearly established thus far. In this study, we employ DFT calculations to comprehensively assess the mechanism and kinetics of the HO•/HOO• radical scavenging activity of this compound in relation to solvents. RBD showed moderate HO• radical scavenging activity, with rate constants of 2.95 × 108 and 1.82 × 1010 M-1 s-1 in lipid and polar media, respectively. In the aqueous solution, the compound exhibited remarkable superoxide anion radical scavenging activity (k = 4.93 × 108 M-1 s-1) but modest HOO• antiradical activity. RBD also showed promising antiradical activity against a variety of radicals (CCl3O•, CCl3OO•, NO2, SO4•-, and N3•), while experimental and computational results confirmed that RBD has moderate activity in DPPH/ABTS•+ assays. Thus, RBD is predicted to be a good, albeit selective, radical scavenger.