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Ruxolitinib (RUX) is extensively used in myelofibrosis (MF). Despite its early efficacy, most patients lose response over time and, after discontinuation, have a worse overall survival (OS). Currently, response criteria able to predict OS in RUX-treated patients are lacking, leading to uncertainty regarding the switch to second-line treatments. In this study, we investigated predictors of survival collected after 6 months of RUX in 209 MF patients participating in the real-world ambispective observational RUXOREL-MF study (NCT03959371). Multivariable analysis identified the following risk factors: (1) RUX dose <20 mg twice daily at baseline, months 3 and 6 (hazard ratio [HR], 1.79; 95% confidence interval [CI], 1.07-3.00; P = .03), (2) palpable spleen length reduction from baseline ≤30% at months 3 and 6 (HR, 2.26; 95% CI, 1.40-3.65; P = .0009), (3) red blood cell (RBC) transfusion need at months 3 and/or 6 (HR, 1.66; 95% CI, 0.95-2.88; P = .07), and (4) RBC transfusion need at all time points (ie, baseline and months 3 and 6; HR, 2.32; 95% CI, 1.19-4.54; P = .02). Hence, we developed a prognostic model, named Response to Ruxolitinib After 6 Months (RR6), dissecting 3 risk categories: low (median OS, not reached), intermediate (median OS, 61 months; 95% CI, 43-80), and high (median OS, 33 months; 95% CI, 21-50). The RR6 model was validated and confirmed in an external cohort comprised of 40 MF patients. In conclusion, the RR6 prognostic model allows for the early identification of RUX-treated MF patients with impaired survival who might benefit from a prompt treatment shift.

Ruxolitinib (RUX) is extensively used in myelofibrosis (MF). Despite its early efficacy, most patients lose response over time and, after discontinuation, have a worse overall survival (OS). Currently, response criteria able to predict OS in RUX-treated patients are lacking, leading to uncertainty regarding the switch to second-line treatments. In this study, we investigated predictors of survival collected after 6 months of RUX in 209 MF patients participating in the real-world ambispective observational RUXOREL-MF study (NCT03959371). Multivariable analysis identified the following risk factors: (1) RUX dose <20 mg twice daily at baseline, months 3 and 6 (hazard ratio [HR], 1.79; 95% confidence interval [CI], 1.07-3.00; P= .03), (2) palpable spleen length reduction from baseline ≤30% at months 3 and 6 (HR, 2.26; 95% CI, 1.40-3.65; P= .0009), (3) red blood cell (RBC) transfusion need at months 3 and/or 6 (HR, 1.66; 95% CI, 0.95-2.88; P= .07), and (4) RBC transfusion need at all time points (ie, baseline and months 3 and 6; HR, 2.32; 95% CI, 1.19-4.54; P= .02). Hence, we developed a prognostic model, named Response to Ruxolitinib After 6 Months (RR6), dissecting 3 risk categories: low (median OS, not reached), intermediate (median OS, 61 months; 95% CI, 43-80), and high (median OS, 33 months; 95% CI, 21-50). The RR6 model was validated and confirmed in an external cohort comprised of 40 MF patients. In conclusion, the RR6 prognostic model allows for the early identification of RUX-treated MF patients with impaired survival who might benefit from a prompt treatment shift.

The extracellular loop 2 (ECL2) is the longest and the most diverse loop among class A G protein-coupled receptors (GPCRs). It connects the transmembrane (TM) helices 4 and 5 and contains a highly conserved cysteine through which it is bridged with TM3. In this paper, experimental ECL2 structures were analyzed based on their sequences, shapes, and intramolecular contacts. To take into account the flexibility, we incorporated into our analyses information from the molecular dynamics trajectories available on the GPCRmd website. Despite the high sequence variability, shapes of the analyzed structures, defined by the backbone volume overlaps, can be clustered into seven main groups. Conformational differences within the clusters can be then identified by intramolecular interactions with other GPCR structural domains. Overall, our work provides a reorganization of the structural information of the ECL2 of class A GPCR subfamilies, highlighting differences and similarities on sequence and conformation levels.

Molecular dynamics simulations provide a mechanistic description of molecules by relying on empirical potentials. The quality and transferability of such potentials can be improved leveraging data-driven models derived with machine learning approaches. Here, we present TorchMD, a framework for molecular simulations with mixed classical and machine learning potentials. All force computations including bond, angle, dihedral, Lennard-Jones, and Coulomb interactions are expressed as PyTorch arrays and operations. Moreover, TorchMD enables learning and simulating neural network potentials. We validate it using standard Amber all-atom simulations, learning an ab initio potential, performing an end-to-end training, and finally learning and simulating a coarse-grained model for protein folding. We believe that TorchMD provides a useful tool set to support molecular simulations of machine learning potentials. Code and data are freely available at github.com/torchmd.

Protein–protein interactions are the basis of many important physiological processes and are currently promising, yet difficult, targets for drug discovery. In this context, inhibitor of apoptosis proteins (IAPs)-mediated interactions are pivotal for cancer cell survival; the interaction of the BIR1 domain of cIAP2 with TRAF2 was shown to lead the recruitment of cIAPs to the TNF receptor, promoting the activation of the NF-κB survival pathway. In this work, using a combined in silico–in vitroapproach, we identified a drug-like molecule, NF023, able to disrupt cIAP2 interaction with TRAF2. We demonstrated in vitroits ability to interfere with the assembly of the cIAP2-BIR1/TRAF2 complex and performed a thorough characterization of the compound’s mode of action through 248 parallel unbiased molecular dynamics simulations of 300 ns (totaling almost 75 μs of all-atom sampling), which identified multiple binding modes to the BIR1 domain of cIAP2 viaclustering and ensemble docking. NF023 is, thus, a promising protein–protein interaction disruptor, representing a starting point to develop modulators of NF-κB-mediated cell survival in cancer. This study represents a model procedure that shows the use of large-scale molecular dynamics methods to typify promiscuous interactors.

G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.

HTMD is a programmable scientific platform intended to facilitate simulation-based research in molecular systems. This paper presents the functionalities of HTMD for the preparation of a molecular dynamics simulation starting from PDB structures, building the system using well-known force fields, and applying standardized protocols for running the simulations. We demonstrate the framework’s flexibility for high-throughput molecular simulations by applying a preparation, building, and simulation protocol with multiple force-fields on all of the seven hundred eukaryotic membrane proteins resolved to-date from the orientation of proteins in membranes (OPM) database. All of the systems are available on www.playmolecule.org.

•We present real-world data on all ruxolitinib-treated myelofibrosis patients in a 10-million-resident region, with a follow-up of 2 years.•We found no evidence of an increased risk of developing lymphomas.

Bio-molecular dynamics (MD) simulations based on graphical processing units (GPUs) were first released to the public in the early 2009 with the code ACEMD. Almost 8 years after, applications now encompass a broad range of molecular studies, while throughput improvements have opened the way to millisecond sampling timescales. Based on an extrapolation of the amount of sampling in published literature, the second timescale will be reached by the year 2022, and therefore we predict that molecular dynamics is going to become one of the main tools in drug discovery in both academia and industry. Here, we review successful applications in the drug discovery domain developed over these recent years of GPU-based MD. We also retrospectively analyse limitations that have been overcome over the years and give a perspective on challenges that remain to be addressed.

Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative option for patients with primary myelofibrosis (PMF), but information on its net advantage over conventional therapies is lacking. Using ad hoc statistical analysis, we determined outcomes in 438 patients <65 years old at diagnosis who received allogenic SCT (n = 190) or conventional therapies (n = 248). Among patients at low risk per the Dynamic International Prognostic Scoring System (DIPSS) model, the relative risk of death after allogenic SCT vs those treated with nontransplant modalities was 5.6 (95% CI, 1.7-19; P = .0051); for intermediate-1 risk it was 1.6 (95% CI, 0.79-3.2; P = .19), for intermediate-2 risk, 0.55 (95% CI, 0.36-0.83; P = .005), and for high risk, 0.37 (95% CI, 0.21-0.66; P = .0007). Thus, patients with intermediate-2 or high-risk PMF clearly benefit from allogenic SCT. Patients at low risk should receive nontransplant therapy, whereas individual counseling is indicated for patients at intermediate-1 risk.

Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative option for patients with primary myelofibrosis (PMF), but information on its net advantage over conventional therapies is lacking. Using ad hoc statistical analysis, we determined outcomes in 438 patients <65 years old at diagnosis who received allogenic SCT (n = 190) or conventional therapies (n = 248). Among patients at low risk per the Dynamic International Prognostic Scoring System (DIPSS) model, the relative risk of death after allogenic SCT vs those treated with nontransplant modalities was 5.6 (95% CI, 1.7-19; P= .0051); for intermediate-1 risk it was 1.6 (95% CI, 0.79-3.2; P= .19), for intermediate-2 risk, 0.55 (95% CI, 0.36-0.83; P= .005), and for high risk, 0.37 (95% CI, 0.21-0.66; P= .0007). Thus, patients with intermediate-2 or high-risk PMF clearly benefit from allogenic SCT. Patients at low risk should receive nontransplant therapy, whereas individual counseling is indicated for patients at intermediate-1 risk.

Steered molecular dynamics (SMD) simulations for the calculation of free energies are well suited for high-throughput molecular simulations on a distributed infrastructure due to the simplicity of the setup and parallel granularity of the runs. However, so far, the computational cost limited the estimation of the free energy typically over just a few pullings, thus impeding the evaluation of statistical uncertainties involved. In this work, we performed two thousand pulls for the permeation of a potassium ion in the gramicidin A pore by all-atom molecular dynamics in order to assess the bidirectional SMD protocol with a proper amount of sampling. The estimated free energy profile still shows a statistical error of several kcal/mol, while the work distributions are estimated to be non-Gaussian at pulling speeds of 10 Å/ns. We discuss the methodology and the confidence intervals in relation to increasing amounts of computed trajectories and how different permeation pathways for the potassium ion, knock-on and sideways, affect the sampling and the free energy estimation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Background: Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms (MPN) that can progress to post-PV (PPV) myelofibrosis (MF) and post-ET (PET) MF, from now on referred to as secondary myelofibrosis (SMF). Recent studies have shown an increased risk of developing solid tumors (ST) in MPN patients in comparison to the general population. Information on development of ST in SMF is scant.

Rambaldi: Roche: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Italfarmaco: Consultancy; Omeros: Consultancy; Amgen Inc.: Consultancy; Pfizer: Consultancy. Komrokji:Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding. Gotlib:Kartos: Consultancy; Promedior: Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Blueprint Medicines: Consultancy, Honoraria, Research Funding; Deciphera: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Kiladjian:Celgene: Membership on an entity's Board of Directors or advisory committees; AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Cervantes:Hospital Clinic Barcelona: Employment; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees. Devos:Celgene: Consultancy; Novartis: Consultancy; Takeda: Consultancy. Palandri:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Passamonti:Janssen: Consultancy, Speakers Bureau; Roche: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Speakers Bureau.

Vannucchi: Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Research Funding.

No relevant conflicts of interest to declare.

Background:Primary myelofibrosis (PMF) can have a very heterogeneous clinical course and outcome, rendering prognostic stratification tools a relevant aid for treatment-related decision-making, both at diagnosis and during the progression of the disease. Prognostic categorizations such as the IPSS (International Prognostic Scoring System) (Cervantes etal, Blood 2009) and DIPSS (Dynamic IPSS) (Passamonti et al, Blood 2010) distinguish four risk groups with progressively worsening survival and have the advantage of including clinical and laboratory variables available worldwide [namely age >65 years, presence of constitutional symptoms, hemoglobin (Hb) level <10 g/dL, leukocyte (WBC) count >25 x109/L, and circulating blast cells 1% or greater]. PMF prognostication has been recently supplemented with genetic [e.g., karyotype banding in DIPSS-Plus (Gangat et al, J Clin Oncol 2011)] and molecular (e.g., somatic mutations in ASXL1, SRSF2, IDH1/2, EZH2, CALR) data.

Introduction