Theoretical investigation of hydroxylated analogues of valinomycin as potassium transporter.

Valinomycin is a potent ionophore known for its ability to transport potassium ions across biological membranes. The study focuses on the hydroxylated analogues of valinomycin (HyVLMs) and compares their energy profiles and capabilities for transporting potassium ions across phospholipid membranes. Using metadynamics, we investigated the energy profiles of wildtype valinomycin (VLM_1) and its three hydroxylated analogues (VLM_2, VLM_3, and VLM_4). We observed that all analogues exhibited energy maxima in the centre of the membrane and preferred positions below the phospholipid heads. Furthermore, the entry barriers for membrane penetration were similar among the analogues, suggesting that the hydroxyl group did not significantly affect their passage through the membrane. Transition state calculations provided insights into the ability of valinomycin analogues to capture potassium ions, with VLM_4 showing the lowest activation energy and VLM_2 displaying the highest. Our findings contribute to understanding the mechanisms of potassium transport by valinomycin analogues and highlight their potential as ionophores. The presence of the hydroxyl group is of particular importance because it paves the way for subsequent chemical modifications and the synthesis of new antiviral agents with reduced intrinsic toxicity.

GUIDE: A GUI for automated quantum chemistry calculations.

The accuracy of quantum mechanics (QM) simulations depends heavily on the quality of initial input files. Despite the popularity of QM simulation packages, achieving precise results still heavily relies on the user's proficiency in preparing the QM simulation systems. In this work, we present an easy-to-use tool called GUIDE, a YASARA plugin to assist researchers in quantum chemistry workflow automation using ORCA and MOPAC simulation packages. GUIDE lets users compute complex QM calculation workflows via an automated graphical window system. It allows for a more integrated and streamlined research process, as researchers can easily access all the necessary tools within one software without switching between multiple programs. This tool can save time and increase efficiency in computational chemistry methods. GUIDE is written in Python and is freely available for download at https://github.com/YAMACS-SML/GUIDE. The plugin is released under a GPL-3.0 license and is supported on Windows and Linux.

YAMACS: a graphical interface for GROMACS.

SUMMARY: A graphical user interface for the GROMACS program has been developed as plugins for YASARA molecular graphics suite. The most significant GROMACS methods can be run entirely via a windowed menu system, and the results are shown on screen in real time. AVAILABILITY AND IMPLEMENTATION: YAMACS is written in Python and is freely available for download at https://github.com/YAMACS-SML/YAMACS and is supported on Linux. It has been released under GPL-3.0 license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

COVID-19 Infection: Targeting Possibilities for Treatment.

The outbreak of novel coronavirus (nCoV) or severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in December 2019 in Wuhan, China, has posed an international public health emergency worldwide and forced people to be confined in their homes. This virus is of high-risk category and is declared a pandemic by the World Health Organization (WHO). The worldwide researchers and various health professionals are working together to determine the best way to stop its spread or halt this virus's spread and circumvent this pandemic condition threatening millions of human lives. The absence of definitive treatment is possible to explore to reduce virus infection and enhance patient recovery. Along with off-label medicines, plasma therapy, vaccines, the researchers exploit the various plants/herbs and their constituents to effectively treat nCoV infection. The present study aimed to present brief and most informative salient features of the numerous facts regarding the SARS-CoV-2, including the structure, genomic sequence, recent mutation, targeting possibility, and various hurdles in research progress, and off-labeled drugs, convalescent plasma therapy, vaccine and plants/herbs for the treatment of coronavirus disease-2019 (COVID-19). Results showed that off-labeled drugs such as hydroxychloroquine, dexamethasone, tocilizumab, antiviral drug (remdesivir, favipiravir), etc., give positive results and approved for use or approved for restricted use in some countries like India. Future research should focus on these possibilities that may allow the development of an effective treatment for COVID-19.

Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database.

The outbreak of respiratory disease, COVID-19 caused by SARS-CoV-2 has now been spread globally and the number of new infections is rising every moment. There are no specific medications that are currently available to combat the disease. The spike receptor of SARS-CoV-2 facilitates the viral entry into a host cell and initiation of infection. Targeting the viral entry at the initial stage has a better advantage than inhibiting it in later stages of the viral life cycle. This study deals with identification of the potential natural molecule or its derivatives from MolPort Databank as SARS-CoV-2 spike receptor inhibitors using structure-based virtual screening followed by molecular dynamics simulation. On the basis of ADME properties, docking score, MMGBSAbinding energy, 150 ns molecular docking studies, and final molecular dynamics analysis, two natural compounds - 3 (MolPort-002-535-004) docking score -9.10 kcal mol-1 and 4 (MolPort-005-910-183) docking score -8.5 kcal mol-1, are selected as potential in-silico spike receptor inhibitors. Both hits are commercially available and can be further used for in-vitro and in-vivo studies. Findings of this study can facilitate rational drug design against SARS-CoV-2 spike receptor.