CHARMM‐GUI high‐throughput simulator for efficient evaluation of protein–ligand interactions with different force fields

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Fedor J, Feng S, Suo Y, Im W, Lee SY. Mechanisms of sensory adaptation and inhibition of the cold and menthol receptor TRPM8

Our sensory adaptation to cold and chemically induced coolness is mediated by the intrinsic property of TRPM8 channels to desensitize. TRPM8 is also implicated in cold-evoked pain disorders and migraine, highlighting its inhibitors as an avenue for pain relief. Despite the importance, the mechanisms of TRPM8 desensitization and inhibition remained unclear. We found, using cryo-electron microscopy, electrophysiology, and molecular dynamics simulations, that TRPM8 inhibitors bind selectively to the desensitized state of the channel. These inhibitors were used to reveal the overlapping mechanisms of desensitization and inhibition and that cold and cooling agonists share a common desensitization pathway. Furthermore, we identified the structural determinants crucial for the conformational change in TRPM8 desensitization. Our study illustrates how receptor-level conformational changes alter cold sensation, providing insights into therapeutic development.

Exploiting the Fc base of IgG antibodies to create functional nanoparticle conjugates

The structures of the Fc base of various IgG antibodies have been examined with a view to understanding how this region can be used to conjugate IgG to nanoparticles. The base structure is found to be largely consistent across a range of species and subtypes, comprising a hydrophobic region surrounded by hydrophilic residues, some of which are charged at physiological conditions. In addition, atomistic Molecular Dynamics simulations were performed to explore how model nanoparticles interact with the base using neutral and negatively charged gold nanoparticles. Both types of nanoparticle interacted readily with the base, leading to an adaptation of the antibody base surface to enhance the interactions. Furthermore, these interactions left the rest of the domain at the base of the Fc region structurally intact. This implies that coupling nanoparticles to the base of an IgG molecule is both feasible and desirable, since it leaves the antibody free to interact with its surroundings so that antigen-binding functionality can be retained. These results will therefore help guide future attempts to develop new nanotechnologies that exploit the unique properties of both antibodies and nanoparticles.

Synthesis of R-GABA Derivatives via Pd(II) Catalyzed Enantioselective C(sp3)-H Arylation and Virtual Validation with GABAB1 Receptor for Potential leads

GABA (γ-amino butyric acid) analogues like baclofen, tolibut, phenibut, etc., are well-known GABAB1 inhibitors and pharmaceutically important drugs. However, there is a huge demand for more chiral GABA aryl analogues with promising pharmacological actions. Here, we demonstrate the chiral ligand acetyl-protected amino quinoline (APAQ) mediated enantioselective synthesis of GABAB1 inhibitor drug scaffolds from easily accessible GABA via Pd-catalyzed C(sp3)-H activation. The synthetic methodology shows moderate to good yields, up to 74% of ee. We have successfully demonstrated the deprotection and removal of the directing group to synthesize R-tolibut in 86% yield. Further, we employed computation to probe the binding of R-GABA analogues to the extracellular domain of the human GABAB1 receptor. Our Rosetta-based molecular docking calculations show better binding for four R-enantiomers of GABA analogues than R-baclofen and R-phenibut. In addition, we employed GROMACS MD simulations and MMPB(GB)SA calculations to identify per-residue contribution to binding free energy. Our computational results suggest analogues (3R)-4-amino-3-(3,4-dimethylphenyl) butanoic acid, (3R)-4-amino-3-(3-fluorophenyl) butanoic acid, (3R)-3-(4-acetylphenyl)-4-aminobutanoic acid, (3R)-4-amino-3-(4-methoxyphenyl) butanoic acid, and (3R)-4-amino-3-phenylbutanoic acid are potential leads which could be synthesized from our methodology reported here.

Spiropiperidine-Based Oligomycin-Analog Ligands To Counteract the Ischemia-Reperfusion Injury in a Renal Cell Model

Finding a therapy for ischemia-reperfusion injury, which consists of cell death following restoration of blood flowing into the artery affected by ischemia, is a strong medical need. Nowadays, only the use of broad-spectrum molecular therapies has demonstrated a partial efficacy in protecting the organs following reperfusion, while randomized clinical trials focused on more specific drug targets have failed. In order to overcome this problem, we applied a combination of molecular modeling and chemical synthesis to identify novel spiropiperidine-based structures active in mitochondrial permeability transition pore opening inhibition as a key process to enhance cell survival after blood flow restoration. Our results were confirmed by biological assay on an in vitro cell model on HeLa and human renal proximal tubular epithelial cells and pave the way to further investigation on an in vivo model system.

Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities

Alchemical free energy methods can be used for the efficient computation of relative binding free energies during preclinical drug discovery stages. In recent years, this has been facilitated further by the implementation of workflows that enable non-experts to quickly and consistently set up the required simulations. Given the correct input structures, workflows handle the difficult aspects of setting up perturbations, including consistently defining the perturbable molecule, its atom mapping and topology generation, perturbation network generation, running of the simulations via different sampling methods, and analysis of the results. Different academic and commercial workflows are discussed, including FEW, FESetup, FEPrepare, CHARMM-GUI, Transformato, PMX, QLigFEP, TIES, ProFESSA, PyAutoFEP, BioSimSpace, FEP+, Flare, and Orion. These workflows differ in various aspects, such as mapping algorithms or enhanced sampling methods. Some workflows can accommodate more than one molecular dynamics (MD) engine and use external libraries for tasks. Differences between workflows can present advantages for different use cases, however a lack of interoperability of the workflows' components hinders systematic comparisons.

Investigating the role of Sterol C24-Methyl transferase mutation on drug resistance in leishmaniasis and identifying potential inhibitors

Leishmaniasis is a fatal disease caused by the leishmania parasite. For the survival of the leishmania parasite, Sterol C24-Methyl Transferase (SMT) is essential which is an enzyme of the ergosterol pathway. SMT protein mutation is responsible for Amphotericin-B drug resistance in Leishmania, which is the main treatment for visceral leishmaniasis. Amphotericin-B resistance is caused by three mutated residues V131I, V321I and F72C. The underlying mechanisms and structural changes in SMT enzymes responsible for resistance due to mutation are still not well understood. In the current study, the potential mechanism of resistance due to these mutations and the structure variation of wild and mutant SMT proteins were investigated through molecular dynamics simulations and molecular docking analysis. The results showed that AmB established strong bonding interaction with wild SMT as compare to mutants SMT. The binding energy calculation showed that binding energy of AmB with mutants SMT increases as compare to the wild SMT. Further structural based virtual screening was carried out to design potential inhibitors for the mutant SMT. On the basis of structural-based virtual screening four inhibitors (SANC01057, SANC00882, SANC00414, SANC01047) were computationally identified as potential mutant SMT (F72C) inhibitors. This work provides valuable information for improved management of drug resistant Leishmaniasis.Communicated by Ramaswamy H. Sarma.

CHARMM-GUI-Based Induced Fit Docking Workflow to Generate Reliable Protein-Ligand Binding Modes

Molecular docking is a preferred method to predict ligand binding modes and their binding energy to target protein receptors, which is critical in early phase structure-based drug discovery. However, there is a persistent challenge in docking that can be attributed to the induced fit effect, as receptor binding sites undergo induced fit conformational changes upon ligand binding to achieve better binding modes. In this work, based on CHARMM-GUI LBS Finder& Refiner and High-Throughput Simulator, we present a straightforward CHARMM-GUI induced fit docking (CGUI-IFD) workflow to generate reliable protein-ligand binding modes. The CGUI-IFD workflow generates an ensemble of receptor binding site conformations through ligand-binding site (LBS) refinement, runs rigid receptor docking, and performs high-throughput molecular dynamics (MD) simulations of protein-ligand complex structures in explicit solvents. The results are evaluated based on the ligand root-mean-square deviation (RMSD)-based binding stability and the molecular mechanics generalized Born surface area binding energy. For a benchmark test, we used 258 cross-docking protein-ligand pairs across 41 target proteins from the Schrodinger IFD-MD data set. The application of CGUI-IFD on this data set shows 80% success rate (within 2.5 Å RMSD from the experimental structures). We expect that the CGUI-IFD workflow can be useful to generate reliable ligand binding modes for cross-docking cases.

Molecular basis of polyspecific drug and xenobiotic recognition by OCT1 and OCT2

A wide range of endogenous and xenobiotic organic ions require facilitated transport systems to cross the plasma membrane for their disposition. In mammals, organic cation transporter (OCT) subtypes 1 and 2 (OCT1 and OCT2, also known as SLC22A1 and SLC22A2, respectively) are polyspecific transporters responsible for the uptake and clearance of structurally diverse cationic compounds in the liver and kidneys, respectively. Notably, it is well established that human OCT1 and OCT2 play central roles in the pharmacokinetics and drug-drug interactions of many prescription medications, including metformin. Despite their importance, the basis of polyspecific cationic drug recognition and the alternating access mechanism for OCTs have remained a mystery. Here we present four cryo-electron microscopy structures of apo, substrate-bound and drug-bound OCT1 and OCT2 consensus variants, in outward-facing and outward-occluded states. Together with functional experiments, in silico docking and molecular dynamics simulations, these structures uncover general principles of organic cation recognition by OCTs and provide insights into extracellular gate occlusion. Our findings set the stage for a comprehensive structure-based understanding of OCT-mediated drug-drug interactions, which will prove critical in the preclinical evaluation of emerging therapeutics.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

Molecular basis of polyspecific drug binding and transport by OCT1 and OCT2

A wide range of endogenous and xenobiotic organic ions require facilitated transport systems to cross the plasma membrane for their disposition 1, 2 . In mammals, organic cation transporter subtypes 1 and 2 (OCT1 and OCT2, also known as SLC22A1 and SLC22A2, respectively) are polyspecific transporters responsible for the uptake and clearance of structurally diverse cationic compounds in the liver and kidneys, respectively 3, 4 . Notably, it is well established that human OCT1 and OCT2 play central roles in the pharmacokinetics, pharmacodynamics, and drug-drug interactions (DDI) of many prescription medications, including metformin 5, 6 . Despite their importance, the basis of polyspecific cationic drug recognition and the alternating access mechanism for OCTs have remained a mystery. Here, we present four cryo-EM structures of apo, substrate-bound, and drug-bound OCT1 and OCT2 in outward-facing and outward-occluded states. Together with functional experiments, in silico docking, and molecular dynamics simulations, these structures uncover general principles of organic cation recognition by OCTs and illuminate unexpected features of the OCT alternating access mechanism. Our findings set the stage for a comprehensive structure-based understanding of OCT-mediated DDI, which will prove critical in the preclinical evaluation of emerging therapeutics.

ChemFlow─From 2D Chemical Libraries to Protein-Ligand Binding Free Energies

The accurate prediction of protein-ligand binding affinities is a fundamental problem for the rational design of new drug entities. Current computational approaches are either too expensive or inaccurate to be effectively used in virtual high-throughput screening campaigns. In addition, the most sophisticated methods, e.g., those based on configurational sampling by molecular dynamics, require significant pre- and postprocessing to provide a final ranking, which hinders straightforward applications by nonexpert users. We present a novel computational platform named ChemFlow to bridge the gap between 2D chemical libraries and estimated protein-ligand binding affinities. The software is designed to prepare a library of compounds provided in SMILES or SDF format, dock them into the protein binding site, and rescore the poses by simplified free energy calculations. Using a data set of 626 protein-ligand complexes and GPU computing, we demonstrate that ChemFlow provides relative binding free energies with an RMSE < 2 kcal/mol at a rate of 1000 ligands per day on a midsize computer cluster. The software is publicly available at https://github.com/IFMlab/ChemFlow.

CHARMM-GUI Implicit Solvent Modeler for Various Generalized Born Models in Different Simulation Programs

Implicit solvent models are widely used because they are advantageous to speed up simulations by drastically decreasing the number of solvent degrees of freedom, which allows one to achieve long simulation time scales for large system sizes. CHARMM-GUI, a web-based platform, has been developed to support the setup of complex multicomponent molecular systems and prepare input files. This study describes an Implicit Solvent Modeler (ISM) in CHARMM-GUI for various generalized Born (GB) implicit solvent simulations in different molecular dynamics programs such as AMBER, CHARMM, GENESIS, NAMD, OpenMM, and Tinker. The GB models available in ISM include GB-HCT, GB-OBC, GB-neck, GBMV, and GBSW with the CHARMM and Amber force fields for protein, DNA, RNA, glycan, and ligand systems. Using the system and input files generated by ISM, implicit solvent simulations of protein, DNA, and RNA systems produce similar results for different simulation packages with the same input information. Protein-ligand systems are also considered to further validate the systems and input files generated by ISM. Simple ligand root-mean-square deviation (RMSD) and molecular mechanics generalized Born surface area (MM/GBSA) calculations show that the performance of implicit simulations is better than docking and can be used for early stage ligand screening. These reasonable results indicate that ISM is a useful and reliable tool to provide various implicit solvent simulation applications.