Project description:Molecular dynamics simulations and free energy calculation have been performed to study how the single-chain variable fragment (scFv) binds methamphetamine (METH) and amphetamine (AMP). The structures of the scFv:METH and the scFv:AMP complexes are analyzed by examining the time-dependence of their RMSDs, by analyzing the distance between some key atoms of the selected residues, and by comparing the averaged structures with their corresponding crystallographic structures. It is observed that binding an AMP to the scFv does not cause significant changes to the binding pocket of the scFv:ligand complex. The binding free energy of scFv:AMP without introducing an extra water into the binding pocket is much stronger than scFv:METH. This is against the first of the two scenarios postulated in the experimental work of Celikel et al. (Protein Science 18, 2336 (2009)). However, adding a water to the AMP (at the position of the methyl group of METH), the binding free energy of the scFv:AMP-H2O complex, is found to be significantly weaker than scFv:METH. This is consistent with the second of the two scenarios given by Celikel et al. Decomposition of the binding energy into ligand-residue pair interactions shows that two residues (Tyr175 and Tyr177) have nearly-zero interactions with AMP in the scFv:AMP-H2O complex, whereas their interactions with METH in the scFv:METH complex are as large as -0.8 and -0.74 kcal mol(-1). The insights gained from this study may be helpful in designing more potent antibodies in treating METH abuse.
Project description:In the rapidly evolving coronavirus disease (COVID-19) pandemic, repurposing existing drugs and evaluating commercially available inhibitors against druggable targets of the virus could be an effective strategy to accelerate the drug discovery process. The 3C-Like proteinase (3CLpro) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as an important drug target due to its role in viral replication. The lack of a potent 3CLpro inhibitor and the availability of the X-ray crystal structure of 3CLpro (PDB-ID 6LU7) motivated us to perform computational studies to identify commercially available potential inhibitors. A combination of modeling studies was performed to identify potential 3CLpro inhibitors from the protease inhibitor database MEROPS ( https://www.ebi.ac.uk/merops/index.shtml ). Binding energy evaluation identified key residues for inhibitor design. We found 15 potential 3CLpro inhibitors with higher binding affinity than that of an ?-ketoamide inhibitor determined via X-ray structure. Among them, saquinavir and three other investigational drugs aclarubicin, TMC-310911, and faldaprevir could be suggested as potential 3CLpro inhibitors. We recommend further experimental investigation of these compounds.
Project description:The pandemic outbreak of the Corona viral infection has become a critical global health issue. Biophysical and structural evidence shows that spike protein possesses a high binding affinity towards host angiotensin-converting enzyme 2 and viral hemagglutinin-acetylesterase (HE) glycoprotein receptor. We selected HE as a target in this study to identify potential inhibitors using a combination of various computational approaches such as molecular docking, ADMET analysis, dynamics simulations and binding free energy calculations. Virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin as potential HE inhibitors with better binding energy. Furthermore, molecular dynamics simulations for 100 ns time scale revealed that most of the key HE contacts were retained throughout the simulations trajectories. Binding free energy calculations using MM/PBSA approach ranked the top-five potential NPACT compounds which can act as effective HE inhibitors.
Project description:Janus kinase 3 (JAK3) plays a critical role in the JAK/STAT signaling pathway and has become an attractive selective target for the treatment of immune-mediated disorders. Therefore, great efforts have been made for the development of JAK3 inhibitors, but developing selective JAK3 inhibitors remains a great challenge because of the high sequence homology with other kinases. In order to reveal the selective-binding mechanisms of JAK3 and to find the key structural features that refer to specific JAK3 inhibition, a systematic computational method, including 3D-QSAR, molecular dynamics simulation, and free energy calculations, was carried out on a series of JAK3 isoform-selective inhibitors. Necessary pharmacodynamic structures and key residues involved in efficient JAK3-inhibition were then highlighted. Finally, 10 novel JAK3 inhibitors were designed, the satisfactory predicted binding affinity to JAK3 of these analogous demonstrated that this study may facilitate the rational design of novel and selective JAK3 inhibitors.
Project description:Papain-like protease (nsp-3; non-structural protein) of novel corona virus is an ideal target for developing drugs as it plays multiple important functions for viral growth and replication. For instance, role of nsp-3 has been recognized in cleavage of viral polyprotein; furthermore, in infected host it weakens the immune system via downregulating the production of type I interferon. This downregulation is promoted by removal of ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from interferon-responsive factor 3 (IRF3) protein. Among known inhibitors of SARS-CoV-PLpro GRL0617 is by far the most effective inhibitor. As PLpro of SARS-CoV2 is having more than 80% similarity with SARS-CoV-PLpro, GRL0617 is reported to be effective even against SARS-CoV2. Owing to this similarity, certain key amino acids remain the same/conserved in both proteins. Among conserved amino acids Tyr268 for SARS-CoV2 and Tyr269 for SARS-CoV produce important hydrophobic interactions with aromatic rings of GRL0617. Here, in this study antibacterial compounds were collected from ZINC database, and they were filtered to select compounds that are having similar structural features as GRL0617. This filtered library of compound was then docked with SARS-CoV and CoV2-PLpro. Five hits were noted that were able to interact with Tyr268 (SARS-CoV2) and Tyr269 (SARS-CoV). Further, best hit 2-(2-((benzofuran-2-carboxamido)methyl)-5-methoxy-1H-indol-1-yl)acetic acid (ZINC44459905) was studied using molecular dynamic simulation where stability of protein-ligand complex as well as stability of produced interactions was noted.
Project description:Drug-resistance-associated mutation in essential proteins of the viral life cycle is a major concern in anti-retroviral therapy. M46I, a non-active site mutation in HIV-1 protease has been clinically associated with saquinavir resistance in HIV patients. A 100 ns molecular dynamics (MD) simulation and MM-PBSA calculations were performed to study the molecular mechanism of M46I-mutation-based saquinavir resistance. In order to acquire deeper insight into the drug-resistance mechanism, the flap curling, closed/semi-open/open conformations, and active site compactness were studied. The M46I mutation significantly affects the energetics and conformational stability of HIV-1 protease in terms of RMSD, RMSF, Rg, SASA, and hydrogen formation potential. This mutation significantly decreased van der Waals interaction and binding free energy (∆G) in the M46I-saquinavir complex and induced inward flap curling and a wider opening of the flaps for most of the MD simulation period. The predominant open conformation was reduced, but inward flap curling/active site compactness was increased in the presence of saquinavir in M46I HIV-1 protease. In conclusion, the M46I mutation induced structural dynamics changes that weaken the protease grip on saquinavir without distorting the active site of the protein. The produced information may be utilized for the discovery of inhibitor(s) against drug-resistant HIV-1 protease.
Project description:We sought to design a free energy calculation scheme with the hope of saving cost for generating dynamical information that is inherent in trajectories. We demonstrated that snapshots in a converged trajectory set are associated with implicit conformers that have invariant statistical weight distribution (ISWD). Since infinite number of sets of implicit conformers with ISWD may be created through independent converged trajectory sets, we hypothesized that explicit conformers with ISWD may be constructed for complex molecular systems through systematic increase of conformer fineness, and tested the hypothesis in lipid molecule palmitoyloleoylphosphatidylcholine (POPC). Furthermore, when explicit conformers with ISWD were utilized as basic states to define conformational entropy, change of which between two given macrostates was found to be equivalent to change of free energy except a mere difference of a negative temperature factor, and change of enthalpy essentially cancels corresponding change of average intra-conformer entropy. By implicitly taking advantage of entropy enthalpy compensation and forgoing all dynamical information, constructing explicit conformers with ISWD and counting thermally accessible number of which for interested end macrostates is likely to be an efficient and reliable alternative end point free energy calculation strategy.
Project description:A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.
Project description:Accelerated molecular dynamics (aMD) simulations greatly improve the efficiency of conventional molecular dynamics (cMD) for sampling biomolecular conformations, but they require proper reweighting for free energy calculation. In this work, we systematically compare the accuracy of different reweighting algorithms including the exponential average, Maclaurin series, and cumulant expansion on three model systems: alanine dipeptide, chignolin, and Trp-cage. Exponential average reweighting can recover the original free energy profiles easily only when the distribution of the boost potential is narrow (e.g., the range ≤20kBT) as found in dihedral-boost aMD simulation of alanine dipeptide. In dual-boost aMD simulations of the studied systems, exponential average generally leads to high energetic fluctuations, largely due to the fact that the Boltzmann reweighting factors are dominated by a very few high boost potential frames. In comparison, reweighting based on Maclaurin series expansion (equivalent to cumulant expansion on the first order) greatly suppresses the energetic noise but often gives incorrect energy minimum positions and significant errors at the energy barriers (∼2-3kBT). Finally, reweighting using cumulant expansion to the second order is able to recover the most accurate free energy profiles within statistical errors of ∼kBT, particularly when the distribution of the boost potential exhibits low anharmonicity (i.e., near-Gaussian distribution), and should be of wide applicability. A toolkit of Python scripts for aMD reweighting "PyReweighting" is distributed free of charge at http://mccammon.ucsd.edu/computing/amdReweighting/.
Project description:The disease outbreak of Coronavirus disease-19 (COVID-19), caused by the novel SARS-CoV-2 virus, remains a public health concern. COVID-19 is spreading rapidly with a high mortality rate due to unavailability of effective treatment or vaccine for the disease. The high rate of mutation and recombination in SARS-CoV2 makes it difficult for scientist to develop specific anti-CoV2 drugs and vaccines. SARS-CoV-2-Mpro cleaves the viral polyprotein to produce a variety of non-structural proteins, but in human host it also cleaves the nuclear transcription factor kappa B (NF-κB) essential modulator (NEMO), which suppresses the activation of the NF-κB pathway and weakens the immune response. Since the main protease (Mpro) is required for viral gene expression and replication, it is a promising target for antagonists to treat novel coronavirus disease and discovery of high resolution crystal structure of SARS-CoV-2-Mpro provide an opportunity for in silico identification of its possible inhibitors. In this study we intend to find novel and potential Mpro inhibitors from around 1830 chemically diverse and therapeutically important secondary metabolites available in the MeFSAT database by performing molecular docking against the Mpro structure of SARS-CoV-2 (PDB ID: 6LZE). After ADMET (absorption, distribution, metabolism, excretion, and toxicity) profile and binding energy calculation through MM-GBSA for top five hits, Sterenin M was proposed as a SARS-CoV2-Mpro inhibitor with validation of molecular dynamics (MD) simulation study. Sterenin M seems to have the potential to be a promising ligand against SARS-CoV-2, and thus it requires further validation by in vitro and in vivo studies.