Improving the Efficiency of Free Energy Calculations in the Amber Molecular Dynamics Package

GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models

GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.

Structure-Based Discovery of the SARS-CoV-2 Main Protease Noncovalent Inhibitors from Traditional Chinese Medicine

Traditional Chinese medicine (TCM) has been extensively employed for the treatment of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is demand for discovering more SARS-CoV-2 Mpro inhibitors with diverse scaffolds to optimize anti-SARS-CoV-2 lead compounds. In this study, comprehensive in silico and in vitro assays were utilized to determine the potential inhibitors from TCM compounds against SARS-CoV-2 Mpro, which is an important therapeutic target for SARS-CoV-2. The ensemble docking analysis of 18263 TCM compounds against 15 SARS-CoV-2 Mpro conformations identified 19 TCM compounds as promising candidates. Further in vitro testing validated three compounds as inhibitors of SARS-CoV-2 Mpro and showed IC50 values of 4.64 ± 0.11, 7.56 ± 0.78, and 11.16 ± 0.26 μM, with EC50 values of 12.25 ± 1.68, 15.58 ± 0.77, and 29.32 ± 1.25 μM, respectively. Molecular dynamics (MD) simulations indicated that the three complexes remained stable over the last 100 ns of production run. An analysis of the binding mode revealed that the active compounds occupy different subsites (S1, S2, S3, and S4) of the active site of SARS-CoV-2 Mpro via specific poses through noncovalent interactions with key amino acids (e.g., HIS 41, ASN 142, GLY 143, MET 165, GLU 166, or GLN 189). Overall, this study provides evidence indicating that the three natural products obtained from TCM could be further used for anti-COVID-19 research, justifying the investigation of Chinese herbal medicinal ingredients as bioactive constituents for therapeutic targets.

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 ± 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148 (PDB:8BWU), a potent inhibitor of methyltransferase activity at the nanomolar level (IC50 value of 70 ± 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

Development and test of highly accurate endpoint free energy methods. 3: partition coefficient prediction using a Poisson-Boltzmann method combined with a solvent accessible surface area model for SAMPL challenges

Accurately predicting solvation free energy is the key to predict protein-ligand binding free energy. In addition, the partition coefficient (log P), which is an important physicochemical property that determines the distribution of a drug in vivo, can be derived directly from transfer free energies, i.e., the difference between solvation free energies (SFEs) in different solvents. Within the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) 9 challenge, we applied the Poisson-Boltzmann (PB) surface area (SA) approach to predict the toluene/water transfer free energy and partition coefficient (log Ptoluene/water) from SFEs. For each solute, only a single conformation automatically generated by the free software Open Babel was used. The PB calculation directly adopts our previously optimized boundary definition - a set of general AMBER force field 2 (GAFF2) atom-type based sphere radii for solute atoms. For the non-polar SA model, we newly developed the solvent-related molecular surface tension parameters γ and offset b for toluene and cyclohexane targeting experimental SFEs. This approach yielded the highest predictive accuracy in terms of root mean square error (RMSE) of 1.52 kcal mol-1 in transfer free energy for 16 small drug molecules among all 18 submissions in the SAMPL9 blind prediction challenge. The re-evaluation of the challenge set using multi-conformation strategies based on molecular dynamics (MD) simulations further reduces the prediction RMSE to 1.33 kcal mol-1. At the same time, an additional evaluation of our PBSA method on the SAMPL5 cyclohexane/water distribution coefficient (log Dcyclohexane/water) prediction revealed that our model outperformed COSMO-RS, the best submission model with RMSEPBSA = 1.88 versus RMSECOSMO-RS = 2.11 log units. Two external log Ptoluene/water and log Pcyclohexane/water datasets that contain 110 and 87 data points, respectively, are collected for extra validation and provide an in-depth insight into the error source of the PBSA method.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

Computer-aided drug design in seeking viral capsid modulators

Approved or licensed antiviral drugs have limited applications because of their drug resistance and severe adverse effects. By contrast, by stabilizing or destroying the viral capsid, compounds known as capsid modulators prevent viral replication by acting on new targets and, therefore, overcoming the problem of clinical drug resistance. For example. computer-aided drug design (CADD) methods, using strategies based on structures of biological targets (structure-based drug design; SBDD), such as docking, molecular dynamics (MD) simulations, and virtual screening (VS), have provided opportunities for fast and effective development of viral capsid modulators. In this review, we summarize the application of CADD in the discovery, optimization, and mechanism prediction of capsid-targeting small molecules, providing new insights into antiviral drug discovery modalities. Teaser: Computer-aided drug design will accelerate the development of viral capsid regulators, which brings new hope for the treatment of refractory viral diseases.

Identification of a short ACE2-derived stapled peptide targeting the SARS-CoV-2 spike protein

The design and synthesis of a series of peptide derivatives based on a short ACE2 α-helix 1 epitope and subsequent [i - i+4] stapling of the secondary structure resulted in the identification of a 9-mer peptide capable to compete with recombinant ACE2 towards Spike RBD in the micromolar range. Specifically, SARS-CoV-2 Spike inhibitor screening based on colorimetric ELISA assay and structural studies by circular dichroism showed the ring-closing metathesis cyclization being capable to stabilize the helical structure of the 9-mer ³⁴HEAEDLFYQ⁴² epitope better than the triazole stapling via click chemistry. MD simulations showed the stapled peptide being able not only to bind the Spike RBD, sterically interfering with ACE2, but also showing higher affinity to the target as compared to parent epitope.

Replicative bypass studies of l-deoxyribonucleosides in Vitro and in E. coli cell

L-nucleosides were the most important antiviral lead compounds because they can inhibit viral DNA polymerase and DNA synthesis of many viruses, whereas they may lead to mutations in DNA replication and cause genomic instability. In this study, we reported the replicative bypass of L-deoxynucleosides in recombinant DNA by restriction enzyme-mediated assays to examine their impact on DNA replication in vitro and in E. coli cells. The results showed that a template L-dC inhibited Taq DNA polymerase reaction, whereas it can be bypassed by Vent (exo^-) DNA polymerase as well as in cell replication, inserting correct nucleotides opposite L-dC. L-dG can be bypassed by Taq DNA polymerase and in E. coli cells, maintaining insertion of correct incoming nucleotides, and L-dG induced mutagenic replication by Vent (exo^-) DNA polymerase. In contrast, L-dA can induced mutagenic replication in vitro and in E. coli cells. MD simulations were performed to investigate how DNA polymerase affected replicative bypass and mutations when D-nucleosides replaced with L-nucleosides. This study will provide a basis for the ability to assess the cytotoxic and mutagenic properties of the L-nucleoside drugs.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure

Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.

Self-assembling Branched Amphiphilic Peptides for Targeted Delivery of Small Molecule Anticancer Drugs

Water insolubility poses a significant challenge in the clinical applications of many small molecule drugs. To improve the drug delivery efficiency, two branched amphiphilic peptides (BAPs) were designed in a computer-aided manner, for drug-loading through peptide self-assembling. The structures of the two BAPs, bis(LVFFA)-K-RGD (PepV-1) and bis(FHF)-K-RGD (PepV-2), were inspired by phospholipids, containing the RGD sequence as the hydrophilic head and two hydrophobic sequences as the hydrophobic tails. PepV-1 could self-assemble into nano-fibrils with a hydrophobic core and the RGD moiety on the surface. Its drug-loading efficiency (DE%) of three small molecule anticancer drugs (doxorubicin, camptothecin and curcumin) ranged from 9.90% to 11.74%, and entrapment efficiency (EE%) ranged from 37.30% to 43.00%. Pep-V2 could self-assemble into bilayer delimited nano-vesicles. The DE% of PepV-2 for these drugs ranged from 15.87% to 18.55%, and the EE% ranged from 60.45% to 73.23%. Both BAP carriers could prolong the release of the small molecule drugs, and the PepV-2 vesicles also showed pH-triggered increase of drug release due to the histidine residues. Bothe BAP carriers could increase the cytotoxicity against cancer cells, which might be due to the targeting on the cancer overexpressed integrins. The designed BAP carriers represent promising functional drug carriers for targeted drug delivery, and will be useful for improving the clinical use of small molecule drugs, especially for those with poor water solubility.

Total Synthesis of the Antimycobacterial Natural Product Chlorflavonin and Analogs via a Late-Stage Ruthenium(II)-Catalyzed ortho-C(sp2)-H-Hydroxylation

The continuous, worldwide spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) endanger the World Health Organization’s (WHO) goal to end the global TB pandemic by the year 2035. During the past 50 years, very few new drugs have been approved by medical agencies to treat drug-resistant TB. Therefore, the development of novel antimycobacterial drug candidates to combat the threat of drug-resistant TB is urgent. In this work, we developed and optimized a total synthesis of the antimycobacterial natural flavonoid chlorflavonin by selective ruthenium(II)-catalyzed ortho-C(sp²)-H-hydroxylation of a substituted 3′-methoxyflavonoid skeleton. We extended our methodology to synthesize a small compound library of 14 structural analogs. The new analogs were tested for their antimycobacterial in vitro activity against Mycobacterium tuberculosis (Mtb) and their cytotoxicity against various human cell lines. The most promising new analog bromflavonin exhibited improved antimycobacterial in vitro activity against the virulent H37Rv strain of Mtb (Minimal Inhibitory Concentrations (MIC₉₀) = 0.78 μm). In addition, we determined the chemical and metabolic stability as well as the pK_a values of chlorflavonin and bromflavonin. Furthermore, we established a quantitative structure–activity relationship model using a thermodynamic integration approach. Our computations may be used for suggesting further structural changes to develop improved derivatives.

Structural Modelling of KCNQ1 and KCNH2 Double Mutant Proteins, Identified in Two Severe Long QT Syndrome Cases, Reveals New Insights into Cardiac Channelopathies

Congenital long QT syndrome (LQTS) is a cardiac channelopathy characterized by a prolongation of the QT interval and T-wave abnormalities, caused, in most cases, by mutations in KCNQ1, KCNH2, and SCN5A. Although the predominant pattern of LQTS inheritance is autosomal dominant, compound heterozygous mutations in genes encoding potassium channels have been reported, often with early disease onset and more severe phenotypes. Since the molecular mechanisms underlying severe phenotypes in carriers of compound heterozygous mutations are unknown, it is possible that these compound mutations lead to synergistic or additive alterations to channel structure and function. In this study, all-atom molecular dynamic simulations of KCNQ1 and hERG channels were carried out, including wild-type and channels with compound mutations found in two patients with severe LQTS phenotypes and limited family history of the disease. Because channels can likely incorporate different subunit combinations from different alleles, there are multiple possible configurations of ion channels in LQTS patients. This analysis allowed us to establish the structural impact of different configurations of mutant channels in the activated/open state. Our data suggest that channels with these mutations show moderate changes in folding energy (in most cases of stabilizing character) and changes in channel mobility and volume, differentiating them from each other and from WT. This would indicate possible alterations in K⁺ ion flow. Hetero-tetrameric mutant channels showed intermediate structural and volume alterations vis-à-vis homo-tetrameric channels. These findings support the hypothesis that hetero-tetrameric channels in patients with compound heterozygous mutations do not necessarily lead to synergistic structural alterations.

CHARMM-GUI Free Energy Calculator for Practical Ligand Binding Free Energy Simulations with AMBER

Alchemical free energy methods, such as free energy perturbation (FEP) and thermodynamic integration (TI), become increasingly popular and crucial for drug design and discovery. However, the system preparation of alchemical free energy simulation is an error-prone, time-consuming, and tedious process for a large number of ligands. To address this issue, we have recently presented CHARMM-GUI Free Energy Calculator that can provide input and postprocessing scripts for NAMD and GENESIS FEP molecular dynamics systems. In this work, we extended three submodules of Free Energy Calculator to work with the full suite of GPU-accelerated alchemical free energy methods and tools in AMBER, including input and postprocessing scripts. The BACE1 (β-secretase 1) benchmark set was used to validate the AMBER-TI simulation systems and scripts generated by Free Energy Calculator. The overall results of relatively large and diverse systems are almost equivalent with different protocols (unified and split) and with different timesteps (1, 2, and 4 fs), with R² > 0.9. More importantly, the average free energy differences between two protocols are small and reliable with four independent runs, with a mean unsigned error (MUE) below 0.4 kcal/mol. Running at least four independent runs for each pair with AMBER20 (and FF19SB/GAFF2.1/OPC force fields), we obtained a MUE of 0.99 kcal/mol and root-mean-square error of 1.31 kcal/mol for 58 alchemical transformations in comparison with experimental data. In addition, a set of ligands for T4-lysozyme was used to further validate our free energy calculation protocol whose results are close to experimental data (within 1 kcal/mol). In summary, Free Energy Calculator provides a user-friendly web-based tool to generate the AMBER-TI system and input files for high-throughput binding free energy calculations with access to the full set of GPU-accelerated alchemical free energy, enhanced sampling, and analysis methods in AMBER.

A Cloud Computing Platform for Scalable Relative and Absolute Binding Free Energy Predictions: New Opportunities and Challenges for Drug Discovery

Free energy perturbation (FEP) has become widely used in drug discovery programs for binding affinity prediction between candidate compounds and their biological targets. However, limitations of FEP applications also exist, including, but not limited to, high cost, long waiting time, limited scalability, and breadth of application scenarios. To overcome these problems, we have developed XFEP, a scalable cloud computing platform for both relative and absolute free energy predictions using optimized simulation protocols. XFEP enables large-scale FEP calculations in a more efficient, scalable, and affordable way, for example, the evaluation of 5000 compounds can be performed in 1 week using 50-100 GPUs with a computing cost roughly equivalent to the cost for the synthesis of only one new compound. By combining these capabilities with artificial intelligence techniques for goal-directed molecule generation and evaluation, new opportunities can be explored for FEP applications in the drug discovery stages of hit identification, hit-to-lead, and lead optimization based not only on structure exploitation within the given chemical series but also including evaluation and comparison of completely unrelated molecules during structure exploration in a larger chemical space. XFEP provides the basis for scalable FEP applications to become more widely used in drug discovery projects and to speed up the drug discovery process from hit identification to preclinical candidate compound nomination.

Chemical system biology approach to identify multi-targeting FDA inhibitors for treating COVID-19 and associated health complications

In view of many European countries and the USA leading to the second wave of COVID-19 pandemic, winter season, the evolution of new mutations in the spike protein, and no registered drugs and vaccines for COVID-19 treatment, the discovery of effective and novel therapeutic agents is urgently required. The degrees and frequencies of COVID-19 clinical complications are related to uncontrolled immune responses, secondary bacterial infections, diabetes, cardiovascular disease, hypertension, and chronic pulmonary diseases. It is essential to recognize that the drug repurposing strategy so far remains the only means to manage the disease burden of COVID-19. Despite some success of using single-target drugs in treating the disease, it is beyond suspicion that the virus will acquire drug resistance by acquiring mutations in the drug target. The possible synergistic inhibition of drug efficacy due to drug-drug interaction cannot be avoided while treating COVID-19 and allied clinical complications. Hence, to avoid the unintended development drug resistance and loss of efficacy due to drug-drug interaction, multi-target drugs can be promising tools for the most challenging disease. In the present work, we have carried out molecular docking studies of compounds from the FDA approved drug library, and the FDA approved and passed phase -1 drug libraries with ten therapeutic targets of COVID-19. Results showed that known drugs, including nine anti-inflammatory compounds, four antibiotics, six antidiabetic compounds, and one cardioprotective compound, could effectively inhibit multiple therapeutic targets of COVID-19. Further in-vitro, in vivo, and clinical studies will guide these drugs' proper allocation to treat COVID-19.Communicated by Ramaswamy H. Sarma.

Modeling the Binding Mechanism of Remdesivir, Favilavir, and Ribavirin to SARS-CoV-2 RNA-Dependent RNA Polymerase

Recent efforts to repurpose drugs to combat COVID-19 have identified Remdesivir as a candidate. It acts on the RNA-dependent, RNA polymerase (RdRp) of the SARS-CoV-2 virus, a protein complex responsible for mediating replication of the virus's genome. However, its exact action mechanism, and that of other nucleotide analogue inhibitors, is not known. In this study, we examine at the molecular level the interaction of this drug and that of similar nucleotide analogue inhibitors, ribavirin and favilavir, by relying on atomistic molecular simulations and advanced sampling. By analyzing the binding free energies of these different drugs, it is found that all of them bind strongly at the active site. Surprisingly, however, ribavirin and favilavir do not bind the nucleotide on the complementary strand as effectively and seem to act by a different mechanism than remdesivir. Remdesivir exhibits similar binding interactions to the natural base adenine. Moreover, by analyzing remdesivir at downstream positions of the RNA, we also find that, consistent with a "delayed" termination mechanism, additional nucleotides can be incorporated after remdesivir is added, and its highly polar 1'-cyano group induces a set of conformational changes that can affect the normal RdRp complex function. By analyzing the fluctuations of residues that are altered by remdesivir binding, and comparing them to those induced by lethal point mutations, we find a possible secondary mechanism in which remdesivir destabilizes the protein complex and its interactions with the RNA strands.

Uncompetitive nanomolar dimeric indenoindole inhibitors of the human breast cancer resistance pump ABCG2

Multidrug resistance membrane pumps reduce the efficacy of chemotherapies by exporting a wide panel of structurally-divergent drugs. Here, to take advantage of the polyspecificity of the human Breast Cancer Resistance Protein (BCRP/ABCG2) and the dimeric nature of this pump, new dimeric indenoindole-based inhibitors from the monomeric α,β-unsaturated ketone 4b and phenolic derivative 5a were designed. A library of 18 homo/hetero-dimers was synthesised. Homo-dimerization shifted the inhibition efficacy from sub-micromolar to nanomolar range, correlated with the presence of 5a, linked by a 2-6 methylene-long linker. Non-toxic, the best dimers displayed a therapeutic ratio as high as 70,000. It has been found that the high potency of the best compound 7b that displays a K_I of 17 nM is due to an uncompetitive behavior toward mitoxantrone efflux and specific for that drug, compared to Hoechst 33342 efflux. Such property may be useful to target such anticancer drug efflux mediated by ABCG2. Finally, at a molecular level, an uncompetitive mechanism by which substrate promotes inhibitor binding implies that at least 2 ligands should bind simultaneously to the drug-binding pocket of ABCG2.

CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. In this work, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A_2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ∼1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

A fast and high-quality charge model for the next generation general AMBER force field

The General AMBER Force Field (GAFF) has been broadly used by researchers all over the world to perform in silico simulations and modelings on diverse scientific topics, especially in the field of computer-aided drug design whose primary task is to accurately predict the affinity and selectivity of receptor-ligand binding. The atomic partial charges in GAFF and the second generation of GAFF (GAFF2) were originally developed with the quantum mechanics derived restrained electrostatic potential charge, but in practice, users usually adopt an efficient charge method, Austin Model 1-bond charge corrections (AM1-BCC), based on which, without expensive ab initio calculations, the atomic charges could be efficiently and conveniently obtained with the ANTECHAMBER module implemented in the AMBER software package. In this work, we developed a new set of BCC parameters specifically for GAFF2 using 442 neutral organic solutes covering diverse functional groups in aqueous solution. Compared to the original BCC parameter set, the new parameter set significantly reduced the mean unsigned error (MUE) of hydration free energies from 1.03 kcal/mol to 0.37 kcal/mol. More excitingly, this new AM1-BCC model also showed excellent performance in the solvation free energy (SFE) calculation on diverse solutes in various organic solvents across a range of different dielectric constants. In this large-scale test with totally 895 neutral organic solvent-solute systems, the new parameter set led to accurate SFE predictions with the MUE and the root-mean-square-error of 0.51 kcal/mol and 0.65 kcal/mol, respectively. This newly developed charge model, ABCG2, paved a promising path for the next generation GAFF development.

Syk Inhibitors: New Computational Insights into Their Intraerythrocytic Action in Plasmodium falciparum Malaria

Resistance to antimalarial drugs has spread rapidly over the past few decades. The WHO recommends artemisinin-based combination therapies for the treatment of uncomplicated malaria, but unfortunately these approaches are losing their efficacy in large areas of Southeast Asia. In 2016, artemisinin resistance was confirmed in 5 countries of the Greater Mekong subregion. We focused our study on Syk inhibitors as antimalarial drugs. The Syk protein is present in human erythrocytes, and the membrane of protein band 3 is its major target following activation by oxidant stress. Tyr phosphorylation of band 3 occurs during P. falciparum growth, leading to the release of microparticles containing hemicromes and structural weakening of the host cell membrane, simplifying merozoite reinfection. Syk inhibitors block these events by interacting with the Syk protein’s catalytic site. We performed in vitro proteomics and in silico studies and compared the results. In vitro studies were based on treatment of the parasite’s cellular cultures with different concentrations of Syk inhibitors, while proteomics studies were focused on the Tyr phosphorylation of band 3 by Syk protein with the same concentrations of drugs. In silico studies were based on different molecular modeling approaches in order to analyze and optimize the ligand–protein interactions and obtain the highest efficacy in vitro. In the presence of Syk inhibitors, we observed a marked decrease of band 3 Tyr phosphorylation according to the increase of the drug’s concentration. Our studies could be useful for the structural optimization of these compounds and for the design of novel Syk inhibitors in the future.

Molecular characterization of ebselen binding activity to SARS-CoV-2 main protease

There is an urgent need to repurpose drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recent computational-experimental screenings have identified several existing drugs that could serve as effective inhibitors of the virus' main protease, M^pro, which is involved in gene expression and replication. Among these, ebselen (2-phenyl-1,2-benzoselenazol-3-one) appears to be particularly promising. Here, we examine, at a molecular level, the potential of ebselen to decrease M^pro activity. We find that it exhibits a distinct affinity for the catalytic region. Our results reveal a higher-affinity, previously unknown binding site localized between the II and III domains of the protein. A detailed strain analysis indicates that, on such a site, ebselen exerts a pronounced allosteric effect that regulates catalytic site access through surface-loop interactions, thereby inducing a reconfiguration of water hotspots. Together, these findings highlight the promise of ebselen as a repurposed drug against SARS-CoV-2.

Insights into the Mechanism of Ethionamide Resistance in Mycobacterium tuberculosis through an in silico Structural Evaluation of EthA and Mutants Identified in Clinical Isolates

Mutation in the ethionamide (ETH) activating enzyme, EthA, is the main factor determining resistance to this drug, used to treat TB patients infected with MDR and XDR Mycobacterium tuberculosis isolates. Many mutations in EthA of ETH resistant (ETH-R) isolates have been described but their roles in resistance remain uncharacterized, partly because structural studies on the enzyme are lacking. Thus, we took a two-tier approach to evaluate two mutations (Y50C and T453I) found in ETH-R clinical isolates. First, we used a combination of comparative modeling, molecular docking, and molecular dynamics to build an EthA model in complex with ETH that has hallmark features of structurally characterized homologs. Second, we used free energy computational calculations for the reliable prediction of relative free energies between the wild type and mutant enzymes. The ΔΔG values for Y50C and T453I mutant enzymes in complex with FADH2-NADP-ETH were 3.34 (+/−0.55) and 8.11 (+/−0.51) kcal/mol, respectively, compared to the wild type complex. The positive ΔΔG values indicate that the wild type complex is more stable than the mutants, with the T453I complex being the least stable. These are the first results shedding light on the molecular basis of ETH resistance, namely reduced complex stability of mutant EthA.

Exploring the biotransformation of N-(2-hydroxyphenyl)-2-propylpentanamide (an aryl valproic acid derivative) by CYP2C11, using in silico predictions and in vitro studies

OBJECTIVES

N-(2-hydroxyphenyl)-2-propylpentanamide (HO-AAVPA), a derivative of valproic acid (VPA), has been proposed as a potential anticancer agent due to its improved antiproliferative effects in some cancer cell lines. Although there is evidence that VPA is metabolized by cytochrome P450 2C11 rat isoform, HO-AAVPA CYP-mediated metabolism has not yet been fully explored. Therefore, in this work, the biotransformation of HO-AAVPA by CYP2C11 was investigated.

METHODS

Kinetic parameters and spectral interaction between HO-AAVPA and CYP were evaluated using rat liver microsomes. The participation of CYP2C11 in metabolism of HO-AAVPA was confirmed by cimetidine (CIM) inhibition assay. Docking and molecular dynamics simulations coupled to MMGBSA methods were used in theoretical study.

KEY FINDINGS

HO-AAVPA is metabolized by CYP enzymes (K_M  = 38.94 µm), yielding a hydroxylated metabolite according to its HPLC retention time (5.4 min) and MS analysis (252.2 m/z). In addition, CIM inhibition in rat liver microsomes (K_i  = 59.23 µm) confirmed that CYP2C11 is mainly involved in HO-AAVPA metabolism. Furthermore, HO-AAVPA interacts with CYP2C11 as a type I ligand. HO-AAVPA is stabilized at the CYP2C11 ligand recognition site through a map of interactions similar to other typical CYP2C11 substrates.

CONCLUSION

Therefore, rat liver CYP2C11 isoform is able to metabolize HO-AAVPA.

The First 3D Model of the Full-Length KIT Cytoplasmic Domain Reveals a New Look for an Old Receptor

Receptor tyrosine kinases (RTKs) are key regulators of normal cellular processes and have a critical role in the development and progression of many diseases. RTK ligand-induced stimulation leads to activation of the cytoplasmic kinase domain that controls the intracellular signalling. Although the kinase domain of RTKs has been extensively studied using X-ray analysis, the kinase insert domain (KID) and the C-terminal are partially or fully missing in all reported structures. We communicate the first structural model of the full-length RTK KIT cytoplasmic domain, a crucial target for cancer therapy. This model was achieved by integration of ab initio KID and C-terminal probe models into an X-ray structure, and by their further exploration through molecular dynamics (MD) simulation. An extended (2-µs) MD simulation of the proper model provided insight into the structure and conformational dynamics of the full-length cytoplasmic domain of KIT, which can be exploited in the description of the KIT transduction processes.

Exploration of Free Energy Surfaces Across a Membrane Channel Using Metadynamics and Umbrella Sampling

To reach their site of action, it is essential for antibiotic molecules to cross the bacterial outer membrane. The progress of enhanced sampling techniques in molecular dynamics simulations enables us to understand these translocations at an atomic level. To this end, calculations of free energy surfaces for these permeation processes are of key importance. Herein, we investigate the translocation of a variety of anionic solutes through the outer membrane pore OprO of the Gram-negative bacterium Pseudomonas aeruginosa using the metadynamics and umbrella sampling techniques at the all-atom level. Free energy calculations have been performed employing these two distinct methods in order to illustrate the difference in computed free energies, if any. The investigated solutes range from a single atomic chloride ion over a multiatomic monophosphate ion to a more bulky fosmidomycin antibiotic. The role of complexity of the permeating solutes in estimating accurate free energy profiles is demonstrated by performing extensive convergence analysis. For simple monatomic ions, good agreement between the well-tempered metadynamics and the umbrella sampling approaches is achieved, while for the permeation of the monophosphate ion differences start to appear. In the case of larger molecules such as fosmidomycin it is a tough challenge to achieve converged free energy profiles. This issue is mainly due to neglecting orthogonal degrees of freedom during the free energy calculations. Nevertheless, the freely driven metadynamics approach leads to clearly advantageous results. Additionally, atomistic insights of the translocation mechanisms of all three solutes are discussed.

Theoretical understanding of the thermodynamics and interactions in transcriptional regulator TtgR-ligand binding

The transcriptional regulator TtgR belongs to the TetR family of transcriptional repressors. It depresses the transcription of the TtgABC operon and itself and thus regulates the extrusion of noxious chemicals with efflux pumps in bacterial cells. As the ligand-binding domain of TtgR is rather flexible, it can bind with a number of structurally diverse ligands, such as antibiotics, flavonoids and aromatic solvents. In the current work, we perform equilibrium and nonequilibrium alchemical free energy simulation to predict the binding affinities of a series of ligands targeting the TtgR protein and an agreement between the theoretical prediction and the experimental result is observed. End-point methods MM/PBSA and MM/GBSA are also employed for comparison. We further study the interaction maps and contacts between the protein and the ligand and identify important interactions in the protein-ligand binding cases. The dynamics fluctuation and secondary structures are also investigated. The current work sheds light on atomic and thermodynamic understanding of the TtgR-ligand interactions.

Scaffold Simplification Strategy Leads to a Novel Generation of Dual Human Immunodeficiency Virus and Enterovirus-A71 Entry Inhibitors

Currently, there are only three FDA-approved drugs that inhibit human immunodeficiency virus (HIV) entry-fusion into host cells. The situation is even worse for enterovirus EV71 infection for which no antiviral therapies are available. We describe here the discovery of potent entry dual inhibitors of HIV and EV71. These compounds contain in their structure three or four tryptophan (Trp) residues linked to a central scaffold. Critical for anti-HIV/EV71 activity is the presence of extra phenyl rings, bearing one or two carboxylates, at the C2 position of the indole ring of each Trp residue. The most potent derivatives, 22 and 30, inhibit early steps of the replicative cycles of HIV-1 and EV-A71 by interacting with their respective viral surfaces (glycoprotein gp120 of HIV and the fivefold axis of the EV-A71 capsid). The high potency, low toxicity, facile chemical synthesis, and great opportunities for chemical optimization make them useful prototypes for future medicinal chemistry studies.

Dissecting the Energetics of Intrinsically Disordered Proteins via a Hybrid Experimental and Computational Approach

Intrinsically disordered proteins (IDPs) play important roles in biology, but little is known about the energetics of their inter-residue interactions. Methods that have been successfully applied to analyze the energetics of globular proteins are not applicable to the fluctuating partially ordered ensembles populated by IDPs. A combined computational experimental strategy is introduced for analyzing the energetic role of individual residues in the free state of IDPs. The approach combines experimental measurements of the binding of wild-type and mutant IDPs to their partners with alchemical free energy calculations of the structured complexes. These data allow quantitative information to be deduced about the free state via a thermodynamic cycle. The approach is validated by the analysis of the effects of mutations upon the binding free energy of the ovomucoid inhibitor third binding domain to its partners and is applied to the C-terminal domain of the measles virus nucleoprotein, a 125-residue IDP involved in the RNA transcription and replication of measles virus. The analysis reveals significant inter-residue interactions in the unbound IDP and suggests a biological role for them. The work demonstrates that advances in force fields and computational hardware have now led to the point where it is possible to develop methods, which integrate experimental and computational techniques to reveal insights that cannot be studied using either technique alone.

Kinase Activation by Small Conformational Changes

Protein kinases (PKs) are allosteric enzymes that play an essential role in signal transduction by regulating a variety of key cellular processes. Most PKs suffer conformational rearrangements upon phosphorylation that strongly enhance the catalytic activity. Generally, it involves the movement of the phosphorylated loop toward the active site and the rotation of the whole C-terminal lobe. However, not all kinases undergo such a large configurational change: The MAPK extracellular signal-regulated protein kinases ERK1 and ERK2 achieve a 50 000 fold increase in kinase activity with only a small motion of the C-terminal region. In the present work, we used a combination of molecular simulation tools to characterize the conformational landscape of ERK2 in the active (phosphorylated) and inactive (unphosphorylated) states in solution in agreement with NMR experiments. We show that the chemical reaction barrier is strongly dependent on ATP conformation and that the "active" low-barrier configuration is subtly regulated by phosphorylation, which stabilizes a key salt bridge between the conserved Lys52 and Glu69 belonging to helix-C and promotes binding of a second Mg ion. Our study highlights that the on-off switch embedded in the kinase fold can be regulated by small, medium, and large conformational changes.

AMPA Receptor Noncompetitive Inhibitors Occupy a Promiscuous Binding Site

Noncompetitive inhibitors of AMPA receptors have attracted interest in recent years as antiepileptic drugs. However, their development is hindered by a lack of detailed understanding of the protein-inhibitor interaction mechanisms. Recently, structures of AMPA receptor complexes with the structurally dissimilar, noncompetitive, small-molecule inhibitors pyridone perampanel (PMP), GYKI 53655 (GYKI), and CP 465022 (CP) were resolved, revealing that all three share a common binding site. However, due to the low resolution of the ligands, their exact binding modes and protein-ligand interactions remain ambiguous and insufficiently detailed. We carried out molecular dynamics (MD) simulations on X-ray-resolved and docked AMPA receptor complexes, including thermodynamic integration (TI) to compute ligand binding constants, in order to investigate the inhibitor binding modes in detail and identify key protein-ligand interaction mechanisms. Our analysis and simulations show that the ligand binding pocket at the interface of the receptor's transmembrane domain exhibits features also found in the binding pockets of the multidrug-resistance proteins. The inhibitors bind to such promiscuous pockets by forming multiple weak contacts, while the large, flexible pocket undergoes adjustments to accommodate structurally different ligands in different orientations. TI was able to identify a specific more favorable binding mode for GYKI, while PMP, which has a symmetric ring structure, produced several comparable poses indicating that it may bind in several orientations.

Predicting the affinity of halogenated reversible covalent inhibitors through relative binding free energy

Nitrile reversible covalent inhibitors of human cathepsin L (hCatL) bind covalently to the side chain of the catalytic Cys25 residue in the S1 pocket to form thioimidates. Predicting the binding of reversible covalent inhibitors is essential for their practical application in drug design. In this report, five nitrile-based inhibitors coded Neq0570, Neq0710, Neq0802, Neq0803 and Neq0804 had their hCatL inhibition constants, K_i, determined. These analogs of the prototypical Neq0570 are halogenated reversible covalent inhibitors of hCatL, which bear a halogen atom in the meta position of the P3 benzyl ring that can form a halogen bond with the Gly61 of the hCatL. To describe halogen bonding interaction in an inhibitor-hCatL complex, we applied an extra point (EP) of charge to represent the anisotropic distribution of charge on the iodine, bromine and chlorine atoms. Besides, we have used alchemical free energy calculations for evaluating the overall relative binding free energies of these inhibitors using a two-state binding model: noncovalent and covalent bond states. Our results show that free energy perturbation (FEP) can predict the hCatL binding affinities of halogenated reversible covalent inhibitors in close agreement with experiments.

Hydration of Aromatic Heterocycles as an Adversary of π-Stacking

Hydration is one of the key players in the protein-ligand binding process. It not only influences the binding process per se, but also the drug's absorption, distribution, metabolism, and excretion properties. To gain insights into the hydration of aromatic cores, the solvation thermodynamics of 40 aromatic mono- and bicyclic systems, frequently occurring in medicinal chemistry, are investigated. Thermodynamics is analyzed with two different methods: grid inhomogeneous solvation theory (GIST) and thermodynamic integration (TI). Our results agree well with previously published experimental and computational solvation free energies. The influence of adding heteroatoms to aromatic systems and how the position of these heteroatoms impacts the compound's interactions with water is studied. The solvation free energies of these heteroaromatics are highly correlated to their gas phase interaction energies with benzene: compounds showing a high interaction energy also have a high solvation free energy value. Therefore, replacing a compound with one having a higher gas phase interaction energy might not result in the expected improvement in affinity. The desolvation costs counteract the higher stacking interactions, hence weakening or even inverting the expected gain in binding free energy.

Computing Relative Binding Affinity of Ligands to Receptor: An Effective Hybrid Single-Dual-Topology Free-Energy Perturbation Approach in NAMD

An effective hybrid single-dual-topology protocol is designed for the calculation of relative binding affinities of small ligands to a receptor. The protocol was developed as an extension of the NAMD molecular dynamics program, which exclusively supports a dual-topology framework for relative alchemical free-energy perturbation (FEP) calculations. In this protocol, the alchemical end states are represented as two separate molecules sharing a common substructure identified through maximum structural mapping. Within the substructure, an atom-to-atom correspondence is established, and each pair of corresponding atoms is holonomically constrained to share identical coordinates at all time throughout the simulation. The forces are projected and combined at each step for propagation. Following this formulation, a set of illustrative calculations of reliable experiment/simulation data, including relative solvation free energies of small molecules and relative binding affinities of drug compounds to proteins, are presented. To enhance sampling of the dual-topology region, the FEP calculations were carried out within a replica-exchange MD scheme supported by the multiple-copy algorithm module of NAMD, with periodically attempted swapping of the thermodynamic coupling parameter λ between neighboring states. The results are consistent with experiments and benchmarks reported in the literature, lending support to the validity of the current protocol. In summary, this hybrid single-dual-topology approach combines the conceptual simplicity of the dual-topology paradigm with the advantageous sampling efficiency of the single-topology approach, making it an ideal strategy for high-throughput in silico drug design.

Using AMBER18 for Relative Free Energy Calculations

With renewed interest in free energy methods in contemporary structure-based drug design, there is a pressing need to validate against multiple targets and force fields to assess the overall ability of these methods to accurately predict relative binding free energies. We computed relative binding free energies using graphics processing unit accelerated thermodynamic integration (GPU-TI) on a data set originally assembled by Schrödinger, Inc. Using their GPU free energy code (FEP+) and the OPLS2.1 force field combined with the REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol. In our study using GPU-TI from AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 perturbations contained in this data set. A more detailed analysis of our results suggested that the observed differences between the two studies arise from differences in sampling protocols along with differences in the force fields employed. Future work should address the problem of establishing benchmark quality results with robust statistical error bars obtained through multiple independent runs and enhanced sampling, which is possible with the GPU-accelerated features in AMBER.

Studying effects of different protonation states of His11 and His102 in ribose-5-phosphate isomerase of Trypanosoma cruzi: an example of cooperative behavior

The Trypanosoma cruzi ribose-5-phosphate isomerase B (TcRpiB) is a crucial piece in the pentose phosphate pathway and thus is a potential drug target for treatment of Chagas' disease. TcRpiB residues, such as Cys69, Asp45, Glu149 and Pro47, have confirmed their roles in substrate recognition, catalytic reaction and binding site conformation. However, the joint performance of His11 and His102, in the D-ribose-5-phosphate (R5P) in the catalysis is not well understood. In this work, we probed the influence of different protonation states of His11 and His102 on the behavior of the ligand R5P using molecular dynamics simulations, network analysis and thermodynamic integration. Simulations revealed that a protonated His11 combined with a neutral His102 (His11⁺‒His102) was able to stabilize the ligand R5P in the binding site. Moreover, calculated relative free energy differences showed that when protonated His11 was coupled to a neutral His102 an exergonic process takes place. On the other hand, neutral His11 combined with a protonated His102 (His11‒His102⁺), sampled conformations that resembled the catalyzed product D-ribulose-5-phosphate (Ru5P). Network analysis also demonstrated some peculiarities for these systems with some negatively correlated nodes in the binding site for His11‒His102⁺, and exclusive suboptimal paths for His11⁺‒His102. Therefore, the combined approach presented in this paper proposes two suitable protonation states for the TcRpiB catalytic mechanism, where an extra proton in either histidines might favor R5P binding or influence isomerization reaction to Ru5P. Our results may guide further in silico drug discovery studies. Communicated by Ramaswamy H. Sarma.

Synthesis and Cytotoxicity of 7,9-O-Linked Macrocyclic C-Seco Taxoids

A series of novel 7,9-O-linked macrocyclic taxoids together with modification at the C2 position were synthesized, and their cytotoxicities against drug-sensitive and P-glycoprotein and βIII-tubulin overexpressed drug-resistant cancer cell lines were evaluated. It is demonstrated that C-seco taxoids conformationally constrained via carbonate containing-linked macrocyclization display increased cytotoxicity on drug-resistant tumors overexpressing both βIII and P-gp, among which compound 22b, bearing a 2-m-methoxybenzoyl group together with a five-atom linker, was identified as the most potent. Molecular modeling suggested the improved cytotoxicity of 22b results from enhanced favorable interactions with the T7 loop region of βIII.

Understanding Aldose Reductase-Inhibitors interactions with free energy simulation

Aldose Reductase (AR) reduces a variety of substrates, such as aldehydes, aldoses and corticosteroids. It is the first and rate-limiting enzyme of the polyol pathway and is an important target enzyme for diabetes-associated complications, including retinopathy, neuropathy, and nephropathy. Inhibitors targeting this enzyme are structurally different and some of them have side effects. In existing publications, computational techniques are applied to investigate the binding affinities of existing inhibitors and predicting the affinities of newly designed ligands. However, these calculations only employ coarse and approximated methods such as docking and MM/PBSA. Brute force simulations are employed to study the dynamics of the system but no converged statistics is obtained. As a result, these computations provide results not consistent with experimental values and large discrepancies exist. In the current work, we employ the enhanced sampling technique of alchemical free energy simulation to calculate the binding affinities of several ligands targeting AR. The statistical error is defined with care and the correlation in the time-series data is fully considered. The statistically optimal estimators are used to extract the free energy estimates and the predicted results are in agreement with the experimental values. Less computationally demanding end-point free energy methods are also performed to compare their efficiency with the alchemical methods. As is expected, the end-point methods are of less accuracy and reliability compared with the alchemical free energy methods. The decomposition of the free energy difference in each alchemical transformation into the enthalpic and entropic components gives further insights on the thermodynamics. The enthalpy-entropy compensation is observed in this case. As the structural data obtained from experiments are only snapshots and more details are needed to understand the dynamics of the protein-ligand system, the conformational ensemble is analyzed. We identify important residues involved in the protein-ligand binding case and short-lived interactions formed due to fluctuations in the conformational ensemble. The current work shed light on the atomic detailed understanding of the dynamics of AR-inhibitors interactions.

Viral engagement with host receptors blocked by a novel class of tryptophan dendrimers that targets the 5-fold-axis of the enterovirus-A71 capsid

Enterovirus A71 (EV-A71) is a non-polio neurotropic enterovirus with pandemic potential. There are no antiviral agents approved to prevent or treat EV-A71 infections. We here report on the molecular mechanism by which a novel class of tryptophan dendrimers inhibits (at low nanomolar to high picomolar concentration) EV-A71 replication in vitro. A lead compound in the series (MADAL385) prevents binding and internalization of the virus but does not, unlike classical capsid binders, stabilize the particle. By means of resistance selection, reverse genetics and cryo-EM, we map the binding region of MADAL385 to the 5-fold vertex of the viral capsid and demonstrate that a single molecule binds to each vertex. By interacting with this region, MADAL385 prevents the interaction of the virus with its cellular receptors PSGL1 and heparan sulfate, thereby blocking the attachment of EV-A71 to the host cells.

Enterovirus A71 (EV-A71) is the virus responsible for most of the severe forms of hand, foot and mouth disease (HFMD) associated with neurological involvement and mortality in young children under the age of 5. Seasonal outbreaks of HFMD -with a 2–3 years epidemic cycle- are recurring around the world, especially in the Asia-Pacific region. To date, no antiviral agent has been approved for the treatment of EV-A71 infections. Here, we report on a recently uncovered class of tryptophan dendrimers with an extraordinary antiviral activity in vitro against circulating EV-A71 clinical isolates. Mode of action studies revealed that this class of compounds targets the 5-fold vertex of EV-A71, in turn blocking receptor binding. Our finding may open an entirely novel line of research and largely aid in anti-enterovirus drug development.

Understanding PIM-1 kinase inhibitor interactions with free energy simulation

The proviral integration site of the Moloney leukemia virus (PIM) family includes three homologous members. PIM-1 kinase is an important target in effective therapeutic interventions of lymphomas, prostate cancer and leukemia. In the current work, we performed free energy calculations to calculate the binding affinities of several inhibitors targeting this protein. The alchemical method with integration and perturbation-based estimators and the end-point methods were compared. The computational results indicated that the alchemical method can accurately predict the binding affinities, while the end-point methods give relatively unreliable predictions. Decomposing the free energy difference into enthalpic and entropic components with MBAR reweighting enabled us to investigate the detailed thermodynamic parameters with which the entropy-enthalpy compensation in this protein-ligand binding case is identified. We then studied the conformational ensemble, and the important protein-ligand interactions were identified. The current work sheds light on the understanding of the PIM-1-kinase-inhibitor interactions at the atomic level and will be useful in the further development of potential drugs.

Molecular insight into chymotrypsin inhibitor 2 resisting proteolytic degradation

Chymotrypsin inhibitor 2 (CI2) is a special serine protease inhibitor which can resist hydrolysis for several days with a rapid equilibrium between the Michaelis complex and acyl-enzyme intermediate. The energies and conformational changes for subtilisin-catalyzed proteolysis of CI2 were examined in this paper for the first time by employing pseudo bond ab initio QM/MM MD simulations. In the acylation reaction, a low-barrier hydrogen bond between His64 and Asp32 in the transition state together with the lack of covalent backbone constraints makes the peptide bonds of CI2 break more easily than in other serine protease inhibitors. After acyl-enzyme formation, molecular dynamics simulations showed that the access of hydrolytic water to the active site requires partial dissociation of the leaving group. However, retention of the leaving group mainly by the intra- and inter-molecular H-bonding networks hinders the access of water and retards the deacylation reaction. Instead of the dissociation constant of inhibitors, we suggest employing the free energy at the acyl-enzyme state to predict the relative hydrolysis rates of CI2 mutants, which are testified by the experimental relative hydrolysis rates.

Reproducibility of Free Energy Calculations across Different Molecular Simulation Software Packages

Alchemical free energy calculations are an increasingly important modern simulation technique to calculate free energy changes on binding or solvation. Contemporary molecular simulation software such as AMBER, CHARMM, GROMACS, and SOMD include support for the method. Implementation details vary among those codes, but users expect reliability and reproducibility, i.e., for a given molecular model and set of force field parameters, comparable free energy differences should be obtained within statistical bounds regardless of the code used. Relative alchemical free energy (RAFE) simulation is increasingly used to support molecule discovery projects, yet the reproducibility of the methodology has been less well tested than its absolute counterpart. Here we present RAFE calculations of hydration free energies for a set of small organic molecules and demonstrate that free energies can be reproduced to within about 0.2 kcal/mol with the aforementioned codes. Absolute alchemical free energy simulations have been carried out as a reference. Achieving this level of reproducibility requires considerable attention to detail and package-specific simulation protocols, and no universally applicable protocol emerges. The benchmarks and protocols reported here should be useful for the community to validate new and future versions of software for free energy calculations.

Binding free energies in the SAMPL6 octa-acid host-guest challenge calculated with MM and QM methods

We have estimated free energies for the binding of eight carboxylate ligands to two variants of the octa-acid deep-cavity host in the SAMPL6 blind-test challenge (with or without endo methyl groups on the four upper-rim benzoate groups, OAM and OAH, respectively). We employed free-energy perturbation (FEP) for relative binding energies at the molecular mechanics (MM) and the combined quantum mechanical (QM) and MM (QM/MM) levels, the latter obtained with the reference-potential approach with QM/MM sampling for the MM → QM/MM FEP. The semiempirical QM method PM6-DH+ was employed for the ligand in the latter calculations. Moreover, binding free energies were also estimated from QM/MM optimised structures, combined with COSMO-RS estimates of the solvation energy and thermostatistical corrections from MM frequencies. They were performed at the PM6-DH+ level of theory with the full host and guest molecule in the QM system (and also four water molecules in the geometry optimisations) for 10-20 snapshots from molecular dynamics simulations of the complex. Finally, the structure with the lowest free energy was recalculated using the dispersion-corrected density-functional theory method TPSS-D3, for both the structure and the energy. The two FEP approaches gave similar results (PM6-DH+/MM slightly better for OAM), which were among the five submissions with the best performance in the challenge and gave the best results without any fit to data from the SAMPL5 challenge, with mean absolute deviations (MAD) of 2.4-5.2 kJ/mol and a correlation coefficient (R²) of 0.77-0.93. This is the first time QM/MM approaches give binding free energies that are competitive to those obtained with MM for the octa-acid host. The QM/MM-optimised structures gave somewhat worse performance (MAD = 3-8 kJ/mol and R² = 0.1-0.9), but the results were improved compared to previous studies of this system with similar methods.

Structure-Based Virtual Screening of High-Affinity ATP-Competitive Inhibitors Against Human Lemur Tyrosine Kinase-3 (LMTK3) Domain: A Novel Therapeutic Target for Breast Cancer

Human lemur tyrosine kinase-3 (LMTK3) is an oncogenic kinase known to regulate ER-α through phosphorylation and is considered to be a novel therapeutic target for breast cancer. In this work, we have studied the ATP-binding mechanism with LMTK3 domain and also carried out virtual screening on LMTK3 to identify lead compounds using Dock blaster server. The top scored compounds obtained from Dock blaster were then narrowed down further to six lead compounds (ZINC37996511, ZINC83363046, ZINC3745998, ZINC50456700, ZINC83351792 and ZINC83364581) based on high-binding affinity and non-bonding interactions with LMTK3 using Autodock 4.2 program. We found in comparison to ATP, the lead compounds bind relatively stronger to LMTK3. The relative binding free energy results from MM-PBSA/GBSA method further indicate the strong binding affinity of lead compounds over ATP to LMTK3 in the dynamic system. Further, potential of mean force (PMF) study for ATP and lead compounds with LMTK3 have been performed to explore the unbinding processes and the free energy barrier. From the PMF results, we observed that the lead compounds have higher dissociation energy barriers than the ATP. Our findings suggest that these lead compounds may compete with ATP, and could act as probable potential inhibitors for LMTK3.