Identification of Potential Ligands of the Main Protease of Coronavirus SARS-CoV-2 (2019-nCoV) Using Multimodal Generative Neural-Networks

The recent outbreak of coronavirus disease 2019 (COVID-19) is posing a global threat to human population. The pandemic caused by novel coronavirus (2019-nCoV), also called as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2); first emerged in Wuhan city, Hubei province of China in December 2019. The rapid human to human transmission has caused the contagion to spread world-wide affecting 244,385,444 (244.4 million) people globally causing 4,961,489 (5 million) fatalities dated by 27 October 2021. At present, 6,697,607,393 (6.7 billion) vaccine doses have been administered dated by 27 October 2021, for the prevention of COVID-19 infections. Even so, this critical and threatening situation of pandemic and due to various variants’ emergence, the pandemic control has become challenging; this calls for gigantic efforts to find new potent drug candidates and effective therapeutic approaches against the virulent respiratory disease of COVID-19. In the respiratory morbidities of COVID-19, the functionally crucial drug target for the antiviral treatment could be the main protease/3-chymotrypsin protease (Mpro/3CLpro) enzyme that is primarily involved in viral maturation and replication. In view of this, in the current study I have designed a library of small molecules against the main protease (Mpro) of coronavirus SARS-CoV-2 (2019-nCoV) by using multimodal generative neural-networks. The scaffold-based molecular docking of the series of compounds at the active site of the protein was performed; binding poses of the molecules were evaluated and protein-ligand interaction studies followed by the binding affinity calculations validated the findings. I have identified a number of small promising lead compounds that could serve as potential inhibitors of the main protease (Mpro) enzyme of coronavirus SARS-CoV-2 (2019-nCoV). This study would serve as a step forward in the development of effective antiviral therapeutic agents against the COVID-19

Increased throughput in methods for simulating protein ligand binding and unbinding

By incorporating full flexibility and enabling the quantification of crucial parameters such as binding free energies and residence times, methods for investigating protein-ligand binding and unbinding via molecular dynamics provide details on the involved mechanisms at the molecular level. While these advancements hold promise for impacting drug discovery, a notable drawback persists: their relatively time-consuming nature limits throughput. Herein, we survey recent implementations which, employing a blend of enhanced sampling techniques, a clever choice of collective variables, and often machine learning, strive to enhance the efficiency of new and previously reported methods without compromising accuracy. Particularly noteworthy is the validation of these methods that was often performed on systems mirroring real-world drug discovery scenarios

Molecular docking analysis reveals the promising role of apigenin as a potential treatment for neurological disorders

Objectives: Neurological disorders represent a significant global health challenge, necessitating the exploration of novel therapeutic agents. Apigenin, a natural flavonoid abundantly found in various plants, has garnered attention for its potential neuroprotective properties. In this study, we employed molecular docking simulations to investigate the interaction between apigenin and key molecular targets associated with neurological disorders.Methods: The molecular docking analysis focused on receptors implicated in neuroinflammation, oxidative stress, and neurotransmission regulation.Results: Our results reveal a high binding affinity of apigenin towards critical targets, including GABA, mACh, nACh, NMDA, 5HTA, AMPA, insulin, and dopamine receptors. The findings suggest that apigenin may exert its neuroprotective effects through multifaceted mechanisms, including anti-inflammatory, antioxidant, and neurotransmission regulatory pathways. Additionally, the absence of adverse binding poses emphasizes the safety profile of apigenin.Conclusions: This molecular docking study provides valuable insights into the potential therapeutic role of apigenin in mitigating molecular pathways implicated in neurological disorders. Further in vitro and in vivo investigations are warranted to validate and elucidate the neuroprotective mechanisms of apigenin, paving the way for its development as a promising treatment option for various neurological conditions

Synthesis, characterization, DPPH radical scavenging, urease enzyme inhibition, molecular docking simulation, and DFT analysis of imine derivatives of 4-formylpyridine with selective detection of Cu+2 Ions

This study aimed to prepare three imine derivatives (1, 2, and 3) via a condensation reaction of phenyl hydrazine, 2-hydrazino pyridine, and 4-methoxy aniline with 4-formyl pyridine. Electron impact mass spectrometry (EIMS), proton nuclear magnetic resonance (1H-NMR), ultraviolet-visible (UV-Vis) and Fourier transform infrared (FTIR) spectroscopy were utilized for the characterization. The chemosensing properties of [4((2-phenyl hydrazono)methyl) pyridine] (1), [2-(2-(pyridin-4-ylmethylene)hydrazinyl) pyridine] (2), and [4-methoxy-N-yl methylene) aniline] (3) imino bases have been explored for the first time in aqueous media. The photophysical properties of chemosensors (1, 2, and 3) were examined by various cations (Na+, NH4+, Ba+2, Ni+2, Ca+2, Hg+2, Cu+2, Mg+2, Mn+2, and Pd+2). The chemosensor (1) showed very selective binding capability with copper ions at low concentrations (20 μM) without the influence of any other mentioned ions. The maximum complexation was noted with Cu+2 and 1 at pH between 7 to 7.5. The stoichiometry binding ratio between chemosensor (1) and Cu+2 was determined by Job\u27s plot and it was found to be 1:2. The current study explored the use of these Schiff bases for the first time as heterocyclic chemosensors. DPPH radical scavenging, urease enzyme inhibition activities, molecular docking simulation, and density functional theory (DFT) analysis of compounds 1, 2, and 3 were also conducte

Kinetics of protein-ligand unbinding via smoothed potential molecular dynamics simulations

Drug discovery is expensive and high-risk. Its main reasons of failure are lack of efficacy and toxicity of a drug candidate. Binding affinity for the biological target has been usually considered one of the most relevant figures of merit to judge a drug candidate along with bioavailability, selectivity and metabolic properties, which could depend on off-target interactions. Nevertheless, affinity does not always satisfactorily correlate with in vivo drug efficacy. It is indeed becoming increasingly evident that the time a drug spends in contact with its target (aka residence time) can be a more reliable figure of merit. Experimental kinetic measurements are operatively limited by the cost and the time needed to synthesize compounds to be tested, to express and purify the target, and to setup the assays. We present here a simple and efficient molecular-dynamics-based computational approach to prioritize compounds according to their residence time. We devised a multiple-replica scaled molecular dynamics protocol with suitably defined harmonic restraints to accelerate the unbinding events while preserving the native fold. Ligands are ranked according to the mean observed scaled unbinding time. The approach, trivially parallel and easily implementable, was validated against experimental information available on biological systems of pharmacological relevance

Probing Hydration Patterns in Class‑A GPCRs via Biased MD: The A_2A Receptor

Herein, we present a new computational approach for analyzing hydration patterns in biomolecular systems. This protocol aims to efficiently identify regions where structural waters may be located and, in the case of protein–ligand binding, where displacing one or more water molecules could be advantageous in terms of affinity and/or residence time. We validated our approach on the adenosine A_2A receptor, a target of significant pharmaceutical relevance. The results of the approach are enriched with an extensive analysis of hydration in A_2A and other members of the A-family of GPCRs using available crystallographic evidence and reviewing existing literature. As per the protein–ligand complex case, we conducted a more detailed study of a series of triazine analogues inhibiting A_2A. The proposed approach provides results in good agreement with existing data and offers interpretability and simple and fast applicability

Engineering the Ligand Specificity of the Human Galectin-1 by Incorporation of Tryptophan Analogues

Galectin-1 is a β-galactoside-binding lectin with manifold biological functions. A single tryptophan residue (W68) in its carbohydrate binding site plays a major role in ligand binding and is highly conserved among galectins. To fine tune galectin-1 specificity, we introduced several non-canonical tryptophan analogues at this position of human galectin-1 and analyzed the resulting variants using glycan microarrays. Two variants containing 7-azatryptophan and 7-fluorotryptophan showed a reduced affinity for 3’-sulfated oligosaccharides. Their interaction with different ligands was further analyzed by fluorescence polarization competition assay. Using molecular modeling we provide structural clues that the change in affinities comes from modulated interactions and solvation patterns. Thus, we show that the introduction of subtle atomic mutations in the ligand binding site of galectin-1 is an attractive approach for fine-tuning its interactions with different ligands