P-loop conformation governed crizotinib resistance in G2032R-mutated ROS1 tyrosine kinase: clues from free energy landscape

Molecular dynamics simulations reveal phosphorylation-induced conformational dynamics of the fibroblast growth factor receptor 1 kinase

The Fibroblast Growth Factor Receptor1 (FGFR1) kinase wields exquisite control on cell fate, proliferation, differentiation, and homeostasis. An imbalance of FGFR1 signaling leads to several pathogeneses of diseases ranging from multiple cancers to allergic and neurodegenerative disorders. In this study, we investigated the phosphorylation-induced conformational dynamics of FGFR1 in apo and ATP-bound states via all-atom molecular dynamics simulations. All simulations were performed for 2 × 2 µs. We have also investigated the energetics of the binding of ATP to FGFR1 using the molecular mechanics Poisson-Boltzmann scheme. Our study reveals that the FGFR1 kinase can reach a fully active configuration through phosphorylation and ATP binding. A 3-10 helix formation in the activation loop signifies its rearrangement leading to stability upon ATP binding. The interaction of phosphorylated tyrosine (pTyr654) with positively charged residues forms strong salt-bridge interactions, driving the compactness of the structure. The dynamic cross-correlation map reveals phosphorylation enhances correlated motions and reduces anti-correlated motions between different domains. We believe that the mechanistic understanding of large-conformational changes upon the activation of the FGFR1 kinase will aid the development of novel targeted therapeutics.Communicated by Ramaswamy H. Sarma.

Exhaustively Exploring the Prevalent Interaction Pathways of Ligands Targeting the Ligand-Binding Pocket of Farnesoid X Receptor via Combined Enhanced Sampling

It is well-known that the potency of a drug is heavily associated with its kinetic and thermodynamic properties with the target. Nuclear receptors (NRs), as an important target family, play important roles in regulating a variety of physiological processes in vivo. However, it is hard to understand the drug-NR interaction process because of the closed structure of the ligand-binding domain (LBD) of the NR proteins, which apparently hinders the rational design of drugs with controllable kinetic properties. Therefore, understanding the underlying mechanism of the ligand-NR interaction process seems necessary to help NR drug design. However, it is usually difficult for experimental approaches to interpret the kinetic process of drug-target interactions. Therefore, in silico methods were utilized to explore the optimal binding/dissociation pathways of the NR ligands. Specifically, farnesoid X receptor (FXR) is considered here as the target system since it has been an important target for the treatment of bile acid metabolism-associated diseases, and a series of structures cocrystallized with diverse scaffold ligands were resolved. By using random acceleration molecular dynamics (RAMD) simulation and umbrella sampling (US), 5 main dissociation pathways (pathways I-V) were identified in 11 representative FXR ligands, with most of them (9/11) preferring to go through Pathway III and the remaining two favoring escaping from Pathway I and IV. Furthermore, key residues functioning in the three main dissociation pathways were revealed by the kinetic residue energy analysis (KREA) based on the US trajectories, which may serve as road-marker residues for rapid identification of the (un)binding pathways of FXR ligands. Moreover, the preferred pathways explored by RAMD simulations are in good agreement with the minimum free energy path identified by the US simulations with the Pearson R = 0.76 between the predicted binding affinity and the experimental data, suggesting that RAMD is suitable for applying in large-scale (un)binding-pathway exploration in the case of ligands with obscure binding tunnels to the target.

Applying molecular docking to pesticides

Pesticide creation is related to the development of sustainable agricultural and ecological safety, and molecular docking technology can effectively help in pesticide innovation. This paper introduces the basic theory behind molecular docking, pesticide databases, and docking software. It also summarizes the application of molecular docking in the pesticide field, including the virtual screening of lead compounds, detection of pesticides and their metabolites in the environment, reverse screening of pesticide targets, and the study of resistance mechanisms. Finally, problems with the use of molecular docking technology in pesticide creation are discussed, and prospects for the future use of molecular docking technology in new pesticide development are discussed. © 2023 Society of Chemical Industry.

Deciphering the Shared and Specific Drug Resistance Mechanisms of Anaplastic Lymphoma Kinase via Binding Free Energy Computation

Anaplastic lymphoma kinase (ALK), a tyrosine receptor kinase, has been proven to be associated with the occurrence of numerous malignancies. Although there have been already at least 3 generations of ALK inhibitors approved by FDA or in clinical trials, the occurrence of various mutations seriously attenuates the effectiveness of the drugs. Unfortunately, most of the drug resistance mechanisms still remain obscure. Therefore, it is necessary to reveal the bottom reasons of the drug resistance mechanisms caused by the mutations. In this work, on the basis of verifying the accuracy of 2 main kinds of binding free energy calculation methodologies [end-point method of Molecular Mechanics with Poisson-Boltzmann/Generalized Born and Surface Area (MM/PB(GB)SA) and alchemical method of Thermodynamic Integration (TI)], we performed a systematic analysis on the ALK systems to explore the underlying shared and specific drug resistance mechanisms, covering the one-drug-multiple-mutation and multiple-drug-one-mutation cases. Through conventional molecular dynamics (cMD) simulation in conjunction with MM/PB(GB)SA and umbrella sampling (US) in conjunction with contact network analysis (CNA), the resistance mechanisms of the in-pocket, out-pocket, and multiple-site mutations were revealed. Especially for the out-pocket mutation, a possible transfer chain of the mutation effect was revealed, and the reason why different drugs exhibited various sensitivities to the same mutation was also uncovered. The proposed mechanisms may be prevalent in various drug resistance cases.

Cooperation of structural motifs controls drug selectivity in cyclin-dependent kinases: an advanced theoretical analysis

Understanding drug selectivity mechanism is a long-standing issue for helping design drugs with high specificity. Designing drugs targeting cyclin-dependent kinases (CDKs) with high selectivity is challenging because of their highly conserved binding pockets. To reveal the underlying general selectivity mechanism, we carried out comprehensive analyses from both the thermodynamics and kinetics points of view on a representative CDK12 inhibitor. To fully capture the binding features of the drug-target recognition process, we proposed to use kinetic residue energy analysis (KREA) in conjunction with the community network analysis (CNA) to reveal the underlying cooperation effect between individual residues/protein motifs to the binding/dissociating process of the ligand. The general mechanism of drug selectivity in CDKs can be summarized as that the difference of structural cooperation between the ligand and the protein motifs leads to the difference of the energetic contribution of the key residues to the ligand. The proposed mechanisms may be prevalent in drug selectivity issues, and the insights may help design new strategies to overcome/attenuate the drug selectivity associated problems.

Structural insights into Nirmatrelvir (PF-07321332)-3C-like SARS-CoV-2 protease complexation: a ligand Gaussian accelerated molecular dynamics study

Coronavirus 3C-like protease (3CLpro) is found in SARS-CoV-2 virus, which causes COVID-19. 3CLpro controls virus replication and is a major target for target-based antiviral discovery. As reported by Pfizer, Nirmatrelvir (PF-07321332) is a competitive protein inhibitor and a clinical candidate for orally delivered medication. However, the binding mechanisms between Nirmatrelvir and 3CLpro complex structures remain unknown. This study incorporated ligand Gaussian accelerated molecular dynamics, the one-dimensional and two-dimensional potential of mean force, normal molecular dynamics, and Kramers' rate theory to determine the binding and dissociation rate constants (k_off and k_on) associated with the binding of the 3CLpro protein to the Nirmatrelvir inhibitor. The proposed approach addresses the challenges in designing small-molecule antiviral drugs.

Phosphorylation-Induced Conformational Dynamics and Inhibition of Janus Kinase 1 by Suppressors of Cytokine Signaling 1

The dysfunction of the JAK/STAT (Janus kinase/signal transducers and activators of transcription) pathway results in several pathophysiological conditions, including autoimmune disorders. The negative feedback regulators of the JAK/STAT signaling pathway, suppressors of cytokine signaling (SOCS), act as a natural inhibitor of JAK and inhibit aberrant activity. SOCS1 is the most potent member of the SOCS family, whose kinase inhibitory region targets the substrate-binding groove of JAK with high affinity and blocks the phosphorylation of JAK kinases. Overall, we performed an aggregate of 13 μs molecular dynamics simulations on the activation loop's three different phosphorylation (double and single) states. Results from our simulations show that the single Tyr¹⁰³⁴ phosphorylation could stabilize the JAK1/SOCS1 complex as well as the flexible activation segment. The phosphate-binding loop (P-loop) shows conformational variability at dual and single phosphorylated states. Principal component analysis and protein structure network (PSN) analysis reveal that the different phosphorylation states and SOCS1 binding induce intermediate inactive conformations of JAK1, which could be a better target for future JAK1 selective drug design. PSN analysis suggests that the com-pY1034 system is stabilized due to higher values of network hubs than the other two complex systems. Moreover, the binding free energy calculations suggest that pTyr¹⁰³⁴ states show a higher affinity toward SOCS1 than the dual and pTyr¹⁰³⁵ states. We believe that the mechanistic understanding of JAK1/SOCS1 complexation will aid future studies related to peptide inhibitors based on SOCS1.

First Principles Calculation of Protein-Protein Dimer Affinities of ALS-Associated SOD1 Mutants

Cu,Zn superoxide dismutase (SOD1) is a 32 kDa homodimer that converts toxic oxygen radicals in neurons to less harmful species. The dimerization of SOD1 is essential to the stability of the protein. Monomerization increases the likelihood of SOD1 misfolding into conformations associated with aggregation, cellular toxicity, and neuronal death in familial amyotrophic lateral sclerosis (fALS). The ubiquity of disease-associated mutations throughout the primary sequence of SOD1 suggests an important role of physicochemical processes, including monomerization of SOD1, in the pathology of the disease. Herein, we use a first-principles statistical mechanics method to systematically calculate the free energy of dimer binding for SOD1 using molecular dynamics, which involves sequentially computing conformational, orientational, and separation distance contributions to the binding free energy. We consider the effects of two ALS-associated mutations in SOD1 protein on dimer stability, A4V and D101N, as well as the role of metal binding and disulfide bond formation. We find that the penalty for dimer formation arising from the conformational entropy of disordered loops in SOD1 is significantly larger than that for other protein–protein interactions previously considered. In the case of the disulfide-reduced protein, this leads to a bound complex whose formation is energetically disfavored. Somewhat surprisingly, the loop free energy penalty upon dimerization is still significant for the holoprotein, despite the increased structural order induced by the bound metal cations. This resulted in a surprisingly modest increase in dimer binding free energy of only about 1.5 kcal/mol upon metalation of the protein, suggesting that the most significant stabilizing effects of metalation are on folding stability rather than dimer binding stability. The mutant A4V has an unstable dimer due to weakened monomer-monomer interactions, which are manifested in the calculation by a separation free energy surface with a lower barrier. The mutant D101N has a stable dimer partially due to an unusually rigid β-barrel in the free monomer. D101N also exhibits anticooperativity in loop folding upon dimerization. These computational calculations are, to our knowledge, the most quantitatively accurate calculations of dimer binding stability in SOD1 to date.

Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations

Designing a reliable computational methodology to calculate protein:ligand standard binding free energies is extremely challenging. The large change in configurational enthalpy and entropy that accompanies the association of ligand and protein is notoriously difficult to capture in naive brute-force simulations. Addressing this issue, the present protocol rests upon a rigorous statistical mechanical framework for the determination of protein:ligand binding affinities together with the comprehensive Binding Free-Energy Estimator 2 (BFEE2) application software. With the knowledge of the bound state, available from experiments or docking, application of the BFEE2 protocol with a reliable force field supplies in a matter of days standard binding free energies within chemical accuracy, for a broad range of protein:ligand complexes. Limiting undesirable human intervention, BFEE2 assists the end user in preparing all the necessary input files and performing the post-treatment of the simulations towards the final estimate of the binding affinity.

Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives

Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.

How DNA affects the hyperthermophilic protein Ape10b2 for oligomerization: an investigation using multiple short molecular dynamics simulations

Alba2 is a hyperthermophilic DNA-binding protein, and DNA plays a crucial role in the Alba2 oligomerization process. It is a pity that there is limited research in terms of how DNA affects the conformational change of Alba2 in oligomerization. Herein, we complement the crystal structure of the Ape10b2 (belongs to Alba2)-dsDNA complex (PDB ID: 3U6Y) and employ multiple short molecular dynamics (MSMD) simulations to illuminate the influence of DNA on Ape10b2 at four temperatures (300, 343, 363, and 373 K). Our results indicate that DNA could cause the conformational changes of two important regions (loop1 and loop5), which may be beneficial for protein oligomerization. The results of hydrogen bond analysis show that the increasing number of hydrogen bonds between two monomers of Ape10b2 may also be a favorable factor for oligomerization. In addition, Ape10b2 can stabilize DNA by electrostatic interactions with an increase in temperature, and five residues (Arg40, Arg42, Asn43, Asn45, and Arg46) play a stabilizing role during protein binding to DNA. Our findings could help in understanding the favorable factors leading to protein oligomerization, which contributes to enzyme engineering research from an industrial perspective.

Exploring the thermodynamic, kinetic and inhibitory mechanisms of 5-iTU targeting mitotic kinase haspin by integrated molecular dynamics

As a human mitotic kinase, haspin is considered as a promising target for various diseases including cancers. However, no inhibitors targeting haspin have entered clinical trials presently. 5-iTU (5-iodotubercidin) is a useful and classical chemical probe for the investigation of haspin activity, but its inhibitory mechanism remains unclear. In this study, integrated molecular dynamics (MD) of conventional MD, extended adaptive biasing force (eABF), random acceleration MD and well-tempered metadynamics were applied to investigate the thermodynamic and kinetic features of 5-iTU and three derivatives targeting haspin. To emphasize the importance of gatekeeper Phe605, two haspin mutants (F605Y and F605T) were also built. The results showed that the binding affinity of 5-iTU and haspin was highest in all wild type (WT) systems, relying on the strong halogen aromatic π interaction between 5-iTU and gatekeeper Phe605. Gatekeeper mutations, because of damage to this interaction, led to the rearrangement of water distributions at the binding site and the decrease of 5-iTU residence times. Additionally, compared with the smaller 5-fTU, 5-iTU dissociated from WT haspin with more difficulty through distinct unbinding pathways. These findings will provide crucial guidance for the design and development of novel haspin inhibitors and the rational modification of existing inhibitors.

The Perturbed Free-Energy Landscape: Linking Ligand Binding to Biomolecular Folding

The effects of ligand binding on biomolecular conformation are crucial in drug design, enzyme mechanisms, the regulation of gene expression, and other biological processes. Descriptive models such as "lock and key", "induced fit", and "conformation selection" are common ways to interpret such interactions. Another historical model, linked equilibria, proposes that the free-energy landscape (FEL) is perturbed by the addition of ligand binding energy for the bound population of biomolecules. This principle leads to a unified, quantitative theory of ligand-induced conformation change, building upon the FEL concept. We call the map of binding free energy over biomolecular conformational space the "binding affinity landscape" (BAL). The perturbed FEL predicts/explains ligand-induced conformational changes conforming to all common descriptive models. We review recent experimental and computational studies that exemplify the perturbed FEL, with emphasis on RNA. This way of understanding ligand-induced conformation dynamics motivates new experimental and theoretical approaches to ligand design, structural biology and systems biology.

Pharmacophore based virtual screening, molecular docking and molecular dynamic simulation studies for finding ROS1 kinase inhibitors as potential drug molecules

Proto-oncogene receptor tyrosine kinase ROS-1 is one of the clinically important biomarker and plays a crucial role in regulation of a number of cellular functions including cell proliferation, migration and angiogenesis. Recently, inhibition of ROS1 kinase has proven to be a promising target of anticancer drugs for non-small cell lung cancer (NSCLC). The very few compounds have been used as potent drug molecules so far and the selective ROS1 inhibitors are relatively rare. Besides the currently available drugs such as Crizotinib and PF-06463922 are becoming sensitive due to mutations in the ROS1 protein. To curtail the problem of the resistant, present study was designed to identify the potent inhibitors against ROS1. Three different screening approaches such as structure based, Atom-based and pharmacophore based screening were carried out against commercially available databases and the retrieved best hits were further evaluated by Lipinski's filter. Thereafter the lead molecule was subjected to pocket specific docking with ROS1. The results show that, total of 9 molecules (3 from each screening) has good docking score (with range of -9.288 to -12.49 Kcal/Mol) and binding interactions within the active site of ROS1. In order to analyze the stability of the ligand- protein complexes, molecular dynamics simulation was performed. Thus, these identified potential lead molecules with good binding score and binding affinity with ROS1 may act as the potent ROS1 inhibitor, and that are worth considering for further experimental studies.Communicated by Ramaswamy H. Sarma.

Pharmacophore-based designing of putative ROS-1 targeting agents for NSCLC

Non-small cell lung cancer (NSCLC) is a fatal non-immunogenic malignancy, and proto-oncogene receptor tyrosine kinase (ROS-1) is one of its clinically relevant biomarkers. In this context, herein, we report a series of benzimidazol-2-amine derivatives which were synthesized on the basis of the pharmacophore of ROS-1 and evaluated for anti-proliferative activity. For this, the in silico receptor-ligand pharmacophore model of ROS-1, previously published by our own group, was utilized to screen out an in-house database of small molecule heterocycles. Docking analysis of the selected compounds was carried out within the active site of wild-type (WT) ROS-1 as well as Gly2032Arg mutant ROS-1 protein, which confirmed the retention of conserved interaction between selected molecules and hinge region amino acids Glu2027 and Met2029. Docking was followed by molecular dynamics simulations for the stability of the complexes and calculation of the MM-GBSA score for binding affinity. Finally, compounds were synthesized and the anti-proliferative potential of compounds was evaluated using the A549 cell line. Compounds 3a and 3b presented significant GI₅₀ values between 23.0 and 25.4 μM, among all the tested compounds.

Dimerization energetics of the G-protein coupled bile acid receptor TGR5 from all-atom simulations

We describe the first extensive energetic evaluation of GPCR dimerization on the atomistic level by means of potential of mean force (PMF) computations and implicit solvent/implicit membrane end-point free energy calculations (MM-PBSA approach). Free energies of association computed from the PMFs show that the formation of both the 1/8 and 4/5 interface is energetically favorable for TGR5, the first GPCR known to be activated by hydrophobic bile acids and neurosteroids. Furthermore, formation of the 1/8 interface is favored over that of the 4/5 interface. Both results are in line with our previous FRET experiments in live cells. Differences in lipid-protein interactions are identified to contribute to the observed differences in free energies of association. A per-residue decomposition of the MM-PBSA effective binding energy reveals hot spot residues specific for both interfaces that form clusters. This knowledge may be used to guide the design of dimerization inhibitors or perform mutational studies to explore physiological consequences of distorted TGR5 association. Finally, we characterized the role of Y111, located in the conserved (D/E)RY motif, as a facilitator of TGR5 interactions. The types of computations performed here should be transferable to other transmembrane proteins that form dimers or higher oligomers as long as good structural models of the dimeric or oligomeric states are available. Such computations may help to overcome current restrictions due to an imperfect energetic representation of protein association at the coarse-grained level. © 2019 Wiley Periodicals, Inc.

Drug Discovery Targeting Anaplastic Lymphoma Kinase (ALK)

As a receptor tyrosine kinase of insulin receptor (IR) subfamily, anaplastic lymphoma kinase (ALK) has been validated to play important roles in various cancers, especially anaplastic large cell lymphoma (ALCL), nonsmall cell lung cancer (NSCLC), and neuroblastomas. Currently, five small-molecule inhibitors of ALK, including Crizotinib, Ceritinib, Alectinib, Brigatinib, and Lorlatinib, have been approved by the U.S. Food and Drug Administration (FDA) against ALK-positive NSCLCs. Novel type-I¹/₂ and type-II ALK inhibitors with improved kinase selectivity and enhanced capability to combat drug resistance have also been reported. Moreover, the "proteolysis targeting chimera" (PROTAC) technique has been successfully applied in developing ALK degraders, which opened a new avenue for targeted ALK therapies. This review provides an overview of the physiological and biological functions of ALK, the discovery and development of drugs targeting ALK by focusing on their chemotypes, activity, selectivity, and resistance as well as potential therapeutic strategies to overcome drug resistance.

Importance of protein flexibility in ranking ERK2 Type I1/2 inhibitor affinities: a computational study

Extracellular-regulated kinase (ERK2) has been regarded as an essential target for various cancers, especially melanoma. Recently, pyrrolidine piperidine derivatives were reported as Type I1/2 inhibitors of ERK2, which occupy both the ATP binding pocket and the allosteric pocket. Due to the dynamic behavior of ERK2 upon the binding of Type I1/2 inhibitors, it is difficult to predict the binding structures and relative binding potencies of these inhibitors with ERK2 accurately. In this work, the binding mechanism of pyrrolidine piperidines was discussed by using different simulation techniques, including molecular docking, ensemble docking based on multiple receptor conformation, molecular dynamics simulations and free energy calculations. Our computational results show that the traditional docking method cannot predict the relative binding ability of the studied inhibitors with high accuracy, but incorporating ERK2 protein flexibility into docking is an effective method to improve the prediction accuracy. It is worth noting that the binding free energies predicted by MM/GBSA or MM/PBSA based on the MD simulations for the docked poses have the highest correlation with the experimental data, which highlights the importance of protein flexibility for accurately predicting the binding ability of Type I1/2 inhibitors of ERK2. In addition, the comprehensive analysis of several representative inhibitors indicates that hydrogen bonds and hydrophobic interactions are of significance for improving the binding affinities of the inhibitors. We hope this work will provide valuable information for further design of novel and efficient Type I1/2 ERK2 inhibitors.

Importance of Incorporating Protein Flexibility in Molecule Modeling: A Theoretical Study on Type I1/2 NIK Inhibitors

NF-κB inducing kinase (NIK), which is considered as the central component of the non-canonical NF-κB pathway, has been proved to be an important target for the regulation of the immune system. In the past few years, NIK inhibitors with various scaffolds have been successively reported, among which type I^1/2 inhibitors that can not only bind in the ATP-binding pocket at the DFG-in state but also extend into an additional back pocket, make up the largest proportion of the NIK inhibitors, and are worthy of more attention. In this study, an integration protocol that combines molecule docking, MD simulations, ensemble docking, MM/GB(PB)SA binding free energy calculations, and decomposition was employed to understand the binding mechanism of 21 tricyclic type I^1/2 NIK inhibitors. It is found that the docking accuracy is largely dependent on the selection of docking protocols as well as the crystal structures. The predictions given by the ensemble docking based on multiple receptor conformations (MRCs) and the MM/GB(PB)SA calculations based on MD simulations showed higher linear correlations with the experimental data than those given by conventional rigid receptor docking (RRD) methods (Glide, GOLD, and Autodock Vina), highlighting the importance of incorporating protein flexibility in predicting protein–ligand interactions. Further analysis based on MM/GBSA demonstrates that the hydrophobic interactions play the most essential role in the ligand binding to NIK, and the polar interactions also make an important contribution to the NIK-ligand recognition. A deeper comparison of several pairs of representative derivatives reveals that the hydrophobic interactions are vitally important in the structural optimization of analogs as well. Besides, the H-bond interactions with some key residues and the large desolvation effect in the back pocket devote to the affinity distinction. It is expected that our study could provide valuable insights into the design of novel and potent type I^1/2 NIK inhibitors.

Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

The catalytic activity of Abl1 single and compound mutations: Implications for the mechanism of drug resistance mutations in chronic myeloid leukaemia

BACKGROUND

Abl1 is a protein tyrosine kinase whose aberrant activation due to mutations is the culprit of several cancers, most notably chronic myeloid leukaemia. Several Abl1 inhibitors are used as anti-cancer drugs. Unfortunately, drug resistance limits their effectiveness. The main cause for drug resistance is mutations in the kinase domain (KD) of Abl1 that evolve in patients. The T315I mutation confers resistance against all clinically-available inhibitors except ponatinib. Resistance to ponatinib can develop by compound (double) mutations.

METHODS

Kinetic measurements of the KD of Abl1 and its mutants were carried out to examine their catalytic activity. Specifically, mutants that lead to drug resistance against ponatinib were considered. Molecular dynamics simulations and multiple sequence analysis were used for explanation of the experimental findings.

RESULTS

The catalytic efficiency of the T315I pan-resistance mutant is more than two times lower than that of the native KD. All ponatinib resistant mutations restore the catalytic efficiency of the enzyme. Two of them (G250E/T315I and Y253H/E255V) have a catalytic efficiency that is more than five times that of the native KD.

CONCLUSIONS

The measurements and analysis suggest that resistance is at least partially due to the development of a highly efficient kinase through subsequent mutations. The simulations highlight modifications in two structurally important regions of Abl1, the activation and phosphate binding loops, upon mutations.

GENERAL SIGNIFICANCE

Experimental and computational methods were used together to explain how mutations in the kinase domain of Abl1 lead to resistance against the most advanced drug currently in use to treat chronic myeloid leukaemia.

Insight on mutation-induced resistance to anaplastic lymphoma kinase inhibitor ceritinib from molecular dynamics simulations

Ceritinib, an advanced anaplastic lymphoma kinase (ALK) next-generation inhibitor, has been proved excellent antitumor activity in the treatment of ALK-associated cancers. However, the accumulation of acquired resistance mutations compromise the therapeutic efficacy of ceritinib. Despite abundant mutagenesis data, the structural determinants for reduced ceritinib binding in mutants remains elusive. Focusing on the G1123S and F1174C mutations, we applied molecular dynamics (MD) simulations to study possible reasons for drug resistance caused by these mutations. The MD simulations predict that the studied mutations allosterically impact the configurations of the ATP-binding pocket. An important hydrophobic cluster is identified that connects P-loop and the αC-helix, which has effects on stabilizing the conformation of ATP-binding pocket. It is suggested, in this study, that the G1123S and F1174C mutations can induce the conformational change of P-loop thereby causing the reduced ceritinib affinity and causing drug resistance.

Comparative study of the binding mode between cytochrome P450 17A1 and prostate cancer drugs in the absence of haem iron

According to the X-ray crystal structures of CYP17A1 (including its complexes with inhibitors), it is shown that a hydrogen bond exists between CYP17A1 and its inhibitors (such as abiraterone and TOK-001). Previous short MD simulations (50 ns) suggested that the binding of abiraterone to CYP17A1 is stronger than that of TOK-001. In this work, by carrying out long atomistic MD simulations (200 ns) of CYP17A1 and its complexes with abiraterone and TOK-001, we observed a binding mode between CYP17A1 and abiraterone, which is different from the binding mode between CYP17A1 and TOK-001. In the case of abiraterone binding, the unfilled volume in the active site cavity increases the freedom of movement of abiraterone within CYP17A1, leading to the collective motions of the helices G and B' as well as the breaking of hydrogen bond existing between the 3β-OH group of abiraterone and N202 of CYP17A1. However, the unfilled volume in the active site cavity can be occupied by the benzimidazole ring of TOK-001, restraining the motion of TOK-001. By pulling the two inhibitors (abiraterone and TOK-001) out of the binding pocket in CYP17A1, we discovered that abiraterone and TOK-001 were moved from their binding sites to the surface of protein similarly through the channels formed by the helices G and B'. In addition, based on the free energy calculations, one can see that it is energetically favorable for the two inhibitors (abiraterone and TOK-001) to enter into the binding pocket in CYP17A1.

Gaussian accelerated molecular dynamics for elucidation of drug pathways

INTRODUCTION

Understanding pathways and mechanisms of drug binding to receptors is important for rational drug design. Remarkable advances in supercomputing and methodological developments have opened a new era for application of computer simulations in predicting drug-receptor interactions at an atomistic level. Gaussian accelerated molecular dynamics (GaMD) is a computational enhanced sampling technique that works by adding a harmonic boost potential to reduce energy barriers. GaMD enables free energy calculations without the requirement of predefined collective variables. GaMD has proven useful in biomolecular simulations, in particular, the prediction of drug-receptor interactions. Areas covered: Herein, the authors review recent GaMD simulation studies that elucidated pathways of drug binding to proteins including the G-protein-coupled receptors and HIV protease. Expert opinion: GaMD is advantageous for enhanced simulations of, amongst many biological processes, drug binding to target receptors. Compared with conventional molecular dynamics, GaMD speeds up biomolecular simulations by orders of magnitude. GaMD enables routine drug binding simulations using personal computers with GPUs or common computing clusters. GaMD and, more broadly, enhanced sampling simulations are expected to dramatically increase our capabilities to determine the mechanisms of drug binding to a wide range of receptors in the near future. This will greatly facilitate computer-aided drug design.

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.

Conformational Transition of Key Structural Features Involved in Activation of ALK Induced by Two Neuroblastoma Mutations and ATP Binding: Insight from Accelerated Molecular Dynamics Simulations

Deregulated kinase activity of anaplastic lymphoma kinase (ALK) has been observed to be implicated in the development of tumor progression. The activation mechanism of ALK is proposed to be similar to other receptor tyrosine kinases (RTKs), but the distinct static X-ray crystal conformation of ALK suggests its unique conformational transition. Herein, we have illustrated the dynamic conformational property of wild-type ALK as well as the kinase activation equilibrium variation induced by two neuroblastoma mutations (R1275Q and Y1278S) and ATP binding by performing enhanced sampling accelerated Molecular Dynamics (aMD) simulations. The results suggest that the wild-type ALK is mostly favored in the inactive state, whereas the mutations and ATP binding promote a clear shift toward the active-like conformation. The R1275Q mutant stabilizes the active conformation by rigidifying the αC-in conformation. The Y1278S mutant promotes activation at the expense of a π-stacking hydrophobic cluster, which plays a critical role in the stabilization of the inactive conformation of native ALK. ATP produces a more compact active site and thereby facilitates the activation of ALK. Taken together, these findings not only elucidate the diverse conformations in different ALKs but can also shed light on new strategies for protein engineering and structural-based drug design for ALK.

Binding mechanism of kinase inhibitors to EGFR and T790M, L858R and L858R/T790M mutants through structural and energetic analysis

Experimental studies have demonstrated that L858R mutation in the EGF receptor (EGFR) confers tumor sensitivity whereas T790M and L858R/T790M mutations cause resistance to tyrosine kinase inhibitors in patients with non-small cell lung cancer. Theoretical studies have been carried out to try to clarify the structural and energetic details linked to acquired resistance to Gefitinib, Erlotinib or Lapatinib, however, some of these studies are contradictory with each other and with experimental reports and did not mention whether the study was performed by considering the inactive or active EGFR states. In this study, we combined structural data and molecular dynamic simulations coupled to a molecular mechanics generalized Born surface area approach to provide insight into the binding mechanism between three FDA-approved drugs (Erlotinib, Gefitinib and Lapatinib) that target the wild-type and T790M, L858R and L858R/T790M mutants of EGFR. Structural analysis showed that the drugs impact differently the conformational space of active and inactive EGFR. Energetic analysis pointed out that some ligands have better affinity for the inactive EGFR than the active EGFR state. Comparative analysis of the molecular recognition of Gefitinib, Erlotinib and Lapatinib provided insight into the drug sensitivity or resistance observed for the three FDA-approved drugs evaluated.

Sequential ALK Inhibitors Can Select for Lorlatinib-Resistant Compound ALK Mutations in ALK-Positive Lung Cancer

The cornerstone of treatment for advanced ALK-positive lung cancer is sequential therapy with increasingly potent and selective ALK inhibitors. The third-generation ALK inhibitor lorlatinib has demonstrated clinical activity in patients who failed previous ALK inhibitors. To define the spectrum of ALK mutations that confer lorlatinib resistance, we performed accelerated mutagenesis screening of Ba/F3 cells expressing EML4-ALK. Under comparable conditions, N-ethyl-N-nitrosourea (ENU) mutagenesis generated numerous crizotinib-resistant but no lorlatinib-resistant clones harboring single ALK mutations. In similar screens with EML4-ALK containing single ALK resistance mutations, numerous lorlatinib-resistant clones emerged harboring compound ALK mutations. To determine the clinical relevance of these mutations, we analyzed repeat biopsies from lorlatinib-resistant patients. Seven of 20 samples (35%) harbored compound ALK mutations, including two identified in the ENU screen. Whole-exome sequencing in three cases confirmed the stepwise accumulation of ALK mutations during sequential treatment. These results suggest that sequential ALK inhibitors can foster the emergence of compound ALK mutations, identification of which is critical to informing drug design and developing effective therapeutic strategies.Significance: Treatment with sequential first-, second-, and third-generation ALK inhibitors can select for compound ALK mutations that confer high-level resistance to ALK-targeted therapies. A more efficacious long-term strategy may be up-front treatment with a third-generation ALK inhibitor to prevent the emergence of on-target resistance. Cancer Discov; 8(6); 714-29. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 663.

Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches

Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode analysis (NMA). Here, we systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to estimate the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, we found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpynmode_min_9Å) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calculated based on the minimized structures (enthalpymin). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielectric constant (εin = 4) or the interaction entropy method for εin = 1-4. In terms of reproducing the absolute binding free energies, the binding free energies estimated by including the truncated-NMA entropies based on the MD trajectories (ΔGnmode_md_9Å) give the lowest average absolute deviations against the experimental data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (ΔGnmode_md_9Å) for a relatively high dielectric constant gave the overall best result and the lowest average absolute deviations against the experimental data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any additional computational cost and can give comparable (at high dielectric constant, εin = 4) or even better (at low dielectric constant, εin = 1-2) results than the truncated-NMA entropy (ΔGnmode_md_9Å), the interaction entropy approach is recommended to estimate the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, especially for a diverse dataset. Furthermore, we compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and gaff with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.

Molecular Mechanism Behind the Resistance of the G1202R-Mutated Anaplastic Lymphoma Kinase to the Approved Drug Ceritinib

Anaplastic lymphoma kinase (ALK) has been regarded as an essential target for the treatment of nonsmall cell lung cancer (NSCLC). However, the emergence of the G1202R solvent front mutation that confers resistance to the drugs was reported for the first as well as the second generation ALK inhibitors. It was thought that the G1202R solvent front mutation might hinder the drug binding. In this study, a different fact could be clarified by multiple molecular modeling methodologies through a structural analogue of ceritinib (compound 10, Cpd-10) that is reported to be a potent inhibitor against the G1202R mutation. Herein, molecular docking, accelerated molecular dynamics (aMD) simulations in conjunction with principal component analysis (PCA), and free energy map calculations were used to produce reasonable and representative initial conformations for the conventional MD simulations. Compared with Cpd-10, the binding specificity of ceritinib between ALK wild-type (ALK^WT) and ALK G1202R (ALK^G1202R) are primarily controlled by the conformational change of the P-loop- and A-loop-induced energetic redistributions, and the variation is nonpolar interactions, as indicated by conventional MD simulations, PCA, dynamic cross-correlation map (DCCM) analysis, and free energy calculations. Furthermore, the umbrella sampling (US) simulations were carried out to make clear the principle of the dissociation processes of ceritinib and Cpd-10 toward ALK^WT and ALK^G1202R. The calculation results suggest that Cpd-10 has similar dissociation processes from both ALK^WT and ALK^G1202R, but ceritinib is more easily dissociated from ALK^G1202R than from ALK^WT, thus less residence time is responsible for the ceritinib resistance. Our results suggest that both the binding specificity and the drug residence time should be emphasized in rational drug design to overcome the G1202R solvent front mutation of ALK resistance.

Importance of protein flexibility on molecular recognition: modeling binding mechanisms of aminopyrazine inhibitors to Nek2

NIMA-related kinase 2 (Nek2) plays a significant role in cell cycle regulation, and overexpression of Nek2 has been observed in several types of carcinoma, suggesting it is a potential target for cancer therapy. In this study, we attempted to gain more insight into the binding mechanisms of a series of aminopyrazine inhibitors of Nek2 through multiple molecular modeling techniques, including molecular docking, molecular dynamics (MD) simulations and free energy calculations. The simulation results showed that the induced fit docking and ensemble docking based on multiple protein structures yield better predictions than conventional rigid receptor docking, highlighting the importance of incorporating receptor flexibility into the accurate predictions of the binding poses and binding affinities of Nek2 inhibitors. Additionally, we observed that the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculations did not show better performance than the docking scoring to rank the binding affinities of the studied inhibitors, suggesting that MM/GBSA is system-dependent and may not be the best choice for the Nek2 systems. Moreover, the detailed information on protein-ligand binding was characterized by the MM/GBSA free energy decomposition, and a number of derivatives with improved docking scores were designed. It is expected that our study can provide valuable information for the future rational design of novel and potent inhibitors of Nek2.

Revealing vilazodone's binding mechanism underlying its partial agonism to the 5-HT1A receptor in the treatment of major depressive disorder

It has been estimated that major depressive disorder (MDD) will become the second largest global burden among all diseases by 2030. Various types of drugs, including selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and serotonin receptor partial agonist/reuptake inhibitors (SPARIs), have been approved and become the primary or first-line medications prescribed for MDD. SPARI was expected to demonstrate more enhanced drug efficacy and a rapid onset of action as compared to SSRI and SNRI. As one of the most famous SPARIs, vilazodone was approved by the FDA for the treatment of MDD. Because of the great clinical importance of vilazodone, its binding mechanism underlying its partial agonism to the 5-HT_1A receptor (5-HT_1AR) could provide valuable information to SPARIs' drug-like properties. However, this mechanism has not been reported to date; consequently, the rational design of new efficacious SPARI-based MDD drugs is severely hampered. To explore the molecular mechanism of vilazodone, an integrated computational strategy was adopted in this study to reveal its binding mechanism and prospective structural feature at the agonist binding site of 5-HT_1AR. As a result, 22 residues of this receptor were identified as hotspots, consistently favoring the binding of vilazodone and its analogues, and a common binding mechanism underlying their partial agonism to 5-HT_1AR was, therefore, discovered. Moreover, three main interaction features between vilazodone and 5-HT_1AR have been revealed and schematically summarized. In summary, this newly identified binding mechanism will provide valuable information for medicinal chemists working in the field of rational design of novel SPARIs for MDD treatment.

Zinc ion-induced conformational changes in new Delphi metallo-β-lactamase 1 probed by molecular dynamics simulations and umbrella sampling

The hydrolysis of a β-lactam core ring caused by new Delphi metallo-β-lactamase 1 (NDM-1) with the help of two zinc cofactors induces significant resistance toward β-lactam antibiotics. Molecular dynamics (MD) simulations and the umbrella sampling method are integrated to study the conformational change mechanism of NDM-1 mediated by zinc ion binding. The statistical analyses of interaction contacts of the antibiotic ampicillin (AMP) with residues based on MD trajectories suggest that two Zn ions are essential for maintaining the binding of AMP with NDM-1. Umbrella sampling simulations further reveal that double-Zn coordination exerts strong restriction on the motions of loop L10 relative to loops L3 and L4. Principal component (PC) analysis also demonstrates that zinc ion binding totally inhibits the motion extent of NDM-1 and changes internal motion modes in NDM-1. We expect that the current study can provide significant dynamical information involving conformational changes of NDM-1 for the development of efficient inhibitors to decrease drug resistance of NDM-1 toward antibiotics.

Theoretical studies on FGFR isoform selectivity of FGFR1/FGFR4 inhibitors by molecular dynamics simulations and free energy calculations

The activation and overexpression of fibroblast growth factor receptors (FGFRs) are highly correlated with a variety of cancers. Most small molecule inhibitors of FGFRs selectively target FGFR1-3, but not FGFR4. Hence, designing highly selective inhibitors towards FGFR4 remains a great challenge because FGFR4 and FGFR1 have a high sequence identity. Recently, two small molecule inhibitors of FGFRs, ponatinib and AZD4547, have attracted huge attention. Ponatinib, a type II inhibitor, has high affinity towards FGFR1/4 isoforms, but AZD4547, a type I inhibitor of FGFR1, displays much reduced inhibition toward FGFR4. In this study, conventional molecular dynamics (MD) simulations, molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculations and umbrella sampling (US) simulations were carried out to reveal the principle of the binding preference of ponatinib and AZD4547 towards FGFR4/FGFR1. The results provided by MM/GBSA illustrate that ponatinib has similar binding affinities to FGFR4 and FGFR1, while AZD4547 has much stronger binding affinity to FGFR1 than to FGFR4. A comparison of the individual energy terms suggests that the selectivity of AZD4547 towards FGFR1 versus FGFR4 is primarily controlled by the variation of the van der Waals interactions. The US simulations reveal that the PMF profile of FGFR1/AZD4547 has more peaks and valleys compared with that of FGFR4/AZD4547, suggesting that the dissociation process of AZD4547 from FGFR1 are easily trapped into local minima. Moreover, it is observed that FGFR1/AZD4547 has much higher PMF depth than FGFR4/AZD4547, implying that it is more difficult for AZD4547 to escape from FGFR1 than from FGFR4. The physical principles provided by this study extend our understanding of the binding mechanisms and provide valuable guidance for the rational design of FGFR isoform selective inhibitors.

Importance of protein flexibility in molecular recognition: a case study on Type-I1/2 inhibitors of ALK

Anaplastic lymphoma kinase (ALK) has been regarded as a promising target for the therapy of various cancers.

Classical molecular dynamics and metadynamics simulations decipher the mechanism of CBP30 selectively inhibiting CBP/p300 bromodomains

The selective inhibition mechanism of CBP30 towards CBP/p300 over BRD4-BD1/BD2 bromodomains was revealed by conventional molecular dynamics and metadynamics simulations.

ALK and ROS1 as targeted therapy paradigms and clinical implications to overcome crizotinib resistance

During the past decade, more than 10 targetable oncogenic driver genes have been validated in non-small cell lung cancer (NSCLC). Anaplastic lymphoma kinase (ALK) and ROS1 kinase are two new driver genes implicated in ALK- and ROS1-rearranged NSCLC. Inhibition of ALK and ROS1 by crizotinib has been reported to be highly effective and well tolerated in these patients. However, resistance to crizotinib emerges years after treatment, and increasing efforts have been made to overcome this issue. Here, we review the biology of ALK and ROS1 and their roles in cancer progression. We also summarize the ongoing and completed clinical trials validating ALK and ROS1 as targets for cancer treatment. In the last section of the review, we will discuss the molecular mechanisms of crizotinib resistance and focus approaches to overcome it. This review describes an exciting new area of research and may provide new insights for targeted cancer therapies.

Flavonoids as potent allosteric inhibitors of protein tyrosine phosphatase 1B: molecular dynamics simulation and free energy calculation

Protein tyrosine phosphatase 1B (PTP1B) is a member of the PTP superfamily which is considered to be a negative regulator of insulin receptor (IR) signaling pathway. PTP1B is a promising drug target for the treatment of type 2 diabetes, obesity, and cancer. The existence of allosteric site in PTP1B has turned the researcher's attention to an alternate strategy for inhibition of this enzyme. Herein, the molecular interactions between the allosteric site of PTP1B with three non-competitive flavonoids, (MOR), (MOK), and (DPO) have been investigated. Three ligands were docked into allosteric site of the enzyme. The resulting protein-ligand complexes were used for molecular dynamics studies. Principal component and free-energy landscape (FEL) as well as cluster analyses were used to investigate the conformational and dynamical properties of the protein and identify representative enzyme substrates bounded to the inhibitors. Per residue energy decomposition analysis attributed dissimilar affinities of three inhibitors to the several hydrogen bonds and non-bonded interactions. In conclusion, our results exhibited an inhibitory pattern of the ligands against PTP1B.

Molecular Dynamics Simulations and Dynamic Network Analysis Reveal the Allosteric Unbinding of Monobody to H-Ras Triggered by R135K Mutation

Ras proteins, as small GTPases, mediate cell proliferation, survival and differentiation. Ras mutations have been associated with a broad spectrum of human cancers and thus targeting Ras represents a potential way forward for cancer therapy. A recently reported monobody NS1 allosterically disrupts the Ras-mediated signaling pathway, but its efficacy is reduced by R135K mutation in H-Ras. However, the detailed mechanism is unresolved. Here, using molecular dynamics (MD) simulations and dynamic network analysis, we explored the molecular mechanism for the unbinding of NS1 to H-Ras and shed light on the underlying allosteric network in H-Ras. MD simulations revealed that the overall structures of the two complexes did not change significantly, but the H-Ras–NS1 interface underwent significant conformational alteration in the mutant Binding free energy analysis showed that NS1 binding was unfavored after R135K mutation, which resulted in the unfavorable binding of NS1. Furthermore, the critical residues on H-Ras responsible for the loss of binding of NS1 were identified. Importantly, the allosteric networks for these important residues were revealed, which yielded a novel insight into the allosteric regulatory mechanism of H-Ras.

Investigation on the binding mechanism of loratinib with the c-ros oncogene 1 (ROS1) receptor tyrosine kinase via molecular dynamics simulation and binding free energy calculations

The c-ros oncogene 1 (ROS1) has proven to be an important cancer target for the treatment of various human cancers. The anaplastic lymphoma kinase inhibitor crizotinib has been granted approval for the treatment of patients with ROS1 positive metastatic non-small-cell lung cancer by the Food and Drug Administration on 2016. However, serious resistance due to the secondary mutation of glycine 2032 to arginine (G2032R) was developed in clinical studies. Loratinib (PF-06463922), a macrocyclic analog of crizotinib, showed significantly improved inhibitory activity against wild-type (WT) ROS1 and ROS1^G2032R mutant. To provide insights into the inhibition mechanism, molecular dynamics simulations and free energy calculations were carried out for the complexes of loratinib with WT and G2032R mutated ROS1. The apo-ROS1^WT and apo-ROS1^G2032R systems showed similar RMSF distributions, while ROS1^G2032R-loratinib showed significantly higher than that of WT ROS1-loratinib, which revealed that the binding of loratinib to ROS1^G2032R significantly interfered the fluctuation of protein. Calculations of binding free energies indicate that G2032R mutation significantly reduces the binding affinity of loratinib for ROS1, which arose mostly from the increase of conformation entropy and the decrease of solvation energy. Furthermore, detailed per-residue binding free energies highlighted the increased and decreased contributions of some residues in the G2032R mutated systems. The present study revealed the detailed inhibitory mechanism of loratinib as potent WT and G2032R mutated ROS1 inhibitor, which was expected to provide a basis for rational drug design.

Characterizing Drug-Target Residence Time with Metadynamics: How To Achieve Dissociation Rate Efficiently without Losing Accuracy against Time-Consuming Approaches

Drug-target residence time plays a vital role in drug efficacy. However, there is still no effective strategy to predict drug residence time. Here, we propose to use the optimized (or minimized) structures derived from holo-state proteins to calculate drug residence time, which could give a comparable or even better prediction accuracy compared with those calculated utilizing a large number of molecular dynamics (MD) structures based on the Poisson process. Besides, in addition to the Poisson process, one may use fewer samples for predicting residence time due to the reason that, in a large extent, the calculated drug residence time is stable and independent of the number of samples used for the prediction. With remarkably reduced computational load, the proposed strategy may be promising for large-scale drug residence time prediction, such as post-processing in virtual screening (VS) and lead compound optimization.

Differentiating physicochemical properties between NDRIs and sNRIs clinically important for the treatment of ADHD

BACKGROUND

Drugs available for treating attention-deficit hyperactivity disorder (ADHD) are mainly selective norepinephrine (sNRIs) and dual norepinephrine-dopamine (NDRIs) reuptake inhibitors. The major problem of sNRIs lines in their delayed onset of action and partial- or non-responses, which makes NDRIs distinguished in drug efficacy. Understanding of the differential binding modes of these 2 types of drugs to their corresponding targets can give great insights into the discovery of privileged drug-like scaffolds with improved efficacy. So far, no such study has been carried out.

METHODS

A combinatorial computational strategy, integrating homology modeling, molecular docking, molecular dynamics (MD) and binding free energy calculation, was employed to analyze the binding modes of 8 clinically important ADHD drugs in their targets.

RESULTS

Binding modes of 2 types of ADHD drugs (sNRIs and NDRIs) in their targets was identified for the first time by MD simulation, and 15 hot spot residues were discovered as crucial for NDRIs' binding in hNET and hDAT. Comparing to sNRIs, a clear reduction in the hydrophobic property of NDRIs' one functional group was observed, and the depth of drugs' aromatic ring stretched into the pocket of both targets was further identified as key contributors to drugs' selectivity.

CONCLUSIONS

The hydrophobic property of NDRI ADHD drugs' one functional group contributes to their selectivity when bind hNET and hDAT.

GENERAL SIGNIFICANCE

These results provide insights into NDRI ADHD drugs' binding mechanisms, which could be utilized as structural blueprints for assessing and discovering more efficacious drugs for ADHD therapy.