Antifungal efficacy of scorpion derived peptide K1K8 against Candida albicans in vitro and in vivo.

As an alternative class of antimicrobial agents, antimicrobial peptides (AMPs) have gained significant attention. In this study, K1K8, a scorpion AMP derivative, showed effective activity against Candida albicans including clinically resistant strains. K1K8 killed C. albicans cells mainly by damaging the cell membrane and inducing necrosis via an ROS-related pathway. K1K8 could also interact with DNA after damaging the nuclear envelope. Moreover, K1K8 inhibited hyphal development and biofilm formation of C. albicans in a dose-dependent manner. In the mouse skin infection model, K1K8 significantly decreased the counts of C. albicans cells in the infection area. Overall, K1K8 is a potential anti-infective agent against skin infections caused by C. albicans.

Metabolism-guided development of Ko143 analogs as ABCG2 inhibitors.

ATP-binding cassette subfamily G member 2 (ABCG2), an efflux transporter, is involved in multiple pathological processes. Ko143 is a potent ABCG2 inhibitor; however, it is quickly metabolized through carboxylesterase 1-mediated hydrolysis of its t-butyl ester moiety. The current work aimed to develop more metabolically stable ABCG2 inhibitors. Novel Ko143 analogs were designed and synthesized by replacing the unstable t-butyl ester moiety in Ko143 with an amide group. The synthesized Ko143 analogs were evaluated for their ABCG2 inhibitory activity, binding mode with ABCG2, cytotoxicity, and metabolic stability. We found that the amide modification of Ko143 led to metabolically stable ABCG2 inhibitors. Among these Ko143 analogs, K2 and K34 are promising candidates with favorable oral pharmacokinetic profiles in mice. In summary, we synthesized novel Ko143 analogs with improved metabolic stability, which can potentially be used as lead compounds for the future development of ABCG2 inhibitors.

Discovery of Novel Chinese Medicine Compounds Targeting 3CL Protease by Virtual Screening and Molecular Dynamics Simulation.

The transmission and infectivity of COVID-19 have caused a pandemic that has lasted for several years. This is due to the constantly changing variants and subvariants that have evolved rapidly from SARS-CoV-2. To discover drugs with therapeutic potential for COVID-19, we focused on the 3CL protease (3CLpro) of SARS-CoV-2, which has been proven to be an important target for COVID-19 infection. Computational prediction techniques are quick and accurate enough to facilitate the discovery of drugs against the 3CLpro of SARS-CoV-2. In this paper, we used both ligand-based virtual screening and structure-based virtual screening to screen the traditional Chinese medicine small molecules that have the potential to target the 3CLpro of SARS-CoV-2. MD simulations were used to confirm these results for future in vitro testing. MCCS was then used to calculate the normalized free energy of each ligand and the residue energy contribution. As a result, we found ZINC15676170, ZINC09033700, and ZINC12530139 to be the most promising antiviral therapies against the 3CLpro of SARS-CoV-2.

Molecular Modeling Study of a Receptor-Orthosteric Ligand-Allosteric Modulator Signaling Complex.

Allosteric modulators (AMs) are considered as a perpetual hotspot in research for their higher selectivity and various effects on orthosteric ligands (OL). They are classified in terms of their functionalities as positive, negative, or silent allosteric modulators (PAM, NAM, or SAM, respectively). In the present work, 11 pairs of three-dimensional (3D) structures of receptor-orthosteric ligand and receptor-orthosteric ligand-allosteric modulator complexes have been collected for the studies, including three different systems: GPCR, enzyme, and ion channel. Molecular dynamics (MD) simulations are applied to quantify the dynamic interactions in both the orthosteric and allosteric binding pockets and the structural fluctuation of the involved proteins. Our results showed that MD simulations of moderately large molecules or peptides undergo insignificant changes compared to crystal structure results. Furthermore, we also studied the conformational changes of receptors that bound with PAM and NAM, as well as the different allosteric binding sites in a receptor. There should be no preference for the position of the allosteric binding pocket after comparing the allosteric binding pockets of these three systems. Finally, we aligned four distinct ß2 adrenoceptor structures and three N-methyl-d-aspartate receptor (NMDAR) structures to investigate conformational changes. In the ß2 adrenoceptor systems, the aligned results revealed that transmembrane (TM) helices 1, 5, and 6 gradually increased outward movement from an enhanced inactive state to an improved active state. TM6 endured the most significant conformational changes (around 11 Å). For NMDAR, the bottom section of NMDAR's ligand-binding domain (LBD) experienced an upward and outward shift during the gradually activating process. In conclusion, our research provides insight into receptor-orthosteric ligand-allosteric modulator studies and the design and development of allosteric modulator drugs using MD simulation.

Virus-CKB 2.0: Viral-Associated Disease-Specific Chemogenomics Knowledgebase.

Transmissible and infectious viruses can cause large-scale epidemics around the world. This is because the virus can constantly mutate and produce different variants and subvariants to counter existing treatments. Therefore, a variety of treatments are urgently needed to keep up with the mutation of the viruses. To facilitate the research of such treatment, we updated our Virus-CKB 1.0 to Virus-CKB 2.0, which contains 10 kinds of viruses, including enterovirus, dengue virus, hepatitis C virus, Zika virus, herpes simplex virus, Andes orthohantavirus, human immunodeficiency virus, Ebola virus, Lassa virus, influenza virus, coronavirus, and norovirus. To date, Virus-CKB 2.0 archived at least 65 antiviral drugs (such as remdesivir, telaprevir, acyclovir, boceprevir, and nelfinavir) in the market, 178 viral-related targets with 292 available 3D crystal or cryo-EM structures, and 3766 chemical agents reported for these target proteins. Virus-CKB 2.0 is integrated with established tools for target prediction and result visualization; these include HTDocking, TargetHunter, blood-brain barrier (BBB) predictor, Spider Plot, etc. The Virus-CKB 2.0 server is accessible at https://www.cbligand.org/g/virus-ckb. By using the established chemogenomic tools and algorithms and newly developed tools, we can screen FDA-approved drugs and chemical compounds that may bind to these proteins involved in viral-associated disease regulation. If the virus strain mutates and the vaccine loses its effect, we can still screen drugs that can be used to treat the mutated virus in a fleeting time. In some cases, we can even repurpose FDA-approved drugs through Virus-CKB 2.0.

In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators.

Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-ß-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.

IsAb: a computational protocol for antibody design.

The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.