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Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures., PLoS Computational Biology, 10 (1), ISSN:1553-734X, ISSN:1553-7358

Background Structure-based virtual screening techniques can help to identify new lead structures and complement other screening approaches in drug discovery. Prior to docking, the data (protein crystal structures and ligands) should be prepared with great attention to molecular and chemical details. Results Using a subset of 18 diverse targets from the recently introduced DEKOIS 2.0 benchmark set library, we found differences in the virtual screening performance of two popular docking tools (GOLD and Glide) when employing two different commercial packages (e.g. MOE and Maestro) for preparing input data. We systematically investigated the possible factors that can be responsible for the found differences in selected sets. For the Angiotensin-I-converting enzyme dataset, preparation of the bioactive molecules clearly exerted the highest influence on VS performance compared to preparation of the decoys or the target structure. The major contributing factors were different protonation states, molecular flexibility, and differences in the input conformation (particularly for cyclic moieties) of bioactives. In addition, score normalization strategies eliminated the biased docking scores shown by GOLD (ChemPLP) for the larger bioactives and produced a better performance. Generalizing these normalization strategies on the 18 DEKOIS 2.0 sets, improved the performances for the majority of GOLD (ChemPLP) docking, while it showed detrimental performances for the majority of Glide (SP) docking. Conclusions In conclusion, we exemplify herein possible issues particularly during the preparation stage of molecular data and demonstrate to which extent these issues can cause perturbations in the virtual screening performance. We provide insights into what problems can occur and should be avoided, when generating benchmarks to characterize the virtual screening performance. Particularly, careful selection of an appropriate molecular preparation setup for the bioactive set and the use of score normalization for docking with GOLD (ChemPLP) appear to have a great importance for the screening performance. For virtual screening campaigns, we recommend to invest time and effort into including alternative preparation workflows into the generation of the master library, even at the cost of including multiple representations of each molecule. Graphical Abstract Using DEKOIS 2.0 benchmark sets in structure-based virtual screening to probe the impact of molecular preparation and score normalization. Electronic supplementary material The online version of this article (doi:10.1186/s13321-015-0074-6) contains supplementary material, which is available to authorized users.

Half of human cancers harbor TP53 mutations that render p53 inactive as a tumor suppressor. In these cancers, reactivation of mutant p53 (mutp53) through restoration of wild-type-like function constitutes a valuable anticancer therapeutic strategy. In order to search for mutp53 reactivators, a small library of tryptophanol-derived oxazoloisoindolinones was synthesized and the potential of these compounds as mutp53 reactivators and anticancer agents was investigated in human tumor cells and xenograft mouse models. By analysis of their anti-proliferative effect on a panel of p53-null NCI-H1299 tumor cells ectopically expressing highly prevalent mutp53, the compound SLMP53-2 was selected based on its potential reactivation of multiple structural mutp53. In mutp53-Y220C-expressing hepatocellular carcinoma (HCC) cells, SLMP53-2-induced growth inhibition was mediated by cell cycle arrest, apoptosis, and endoplasmic reticulum stress response. In these cells, SLMP53-2 restored wild-type-like conformation and DNA-binding ability of mutp53-Y220C by enhancing its interaction with the heat shock protein 70 (Hsp70), leading to the reestablishment of p53 transcriptional activity. Additionally, SLMP53-2 displayed synergistic effect with sorafenib, the only approved therapy for advanced HCC. Notably, it exhibited potent antitumor activity in human HCC xenograft mouse models with a favorable toxicological profile. Collectively, SLMP53-2 is a new mutp53-targeting agent with promising antitumor activity, particularly against HCC.

Background: Complement factor D (FD) is the rate-limiting enzyme of the alternative complement pathway. Previous reports of FD deficiency featured absent plasma FD (type I deficiency) and susceptibility to meningococcal infection. A new FD mutant, which is non-functional but fully expressed, was identified in a patient with invasive meningococcal disease. Objectives: We sought to investigate the molecular features of this novel FD mutant. Methods: We performed complement haemolytic assays, western blot analysis of serum FD and Sanger sequencing of the CFD gene. Recombinant mutant FD was assessed by in vitro catalytic assays, circular dichroism, thermal shift assays, esterolytic assays and surface plasmon resonance. Molecular dynamics simulation was used to visualise the structural changes in mutant FD. Results: A homozygous single-nucleotide variation of the CFD gene in the patient and their sibling resulted in an arginine to proline (R176P) substitution in FD. While R176P FD was stable and fully expressed in blood, it had minimal catalytic activity. Mutation R176P caused key FD-C3bB binding exosite loop 156-162 to lose its binding-competent conformation and stabilised the inactive conformation of FD. Consequently, R176P FD was unable to bind its natural substrate, C3bB. Neither patient nor sibling demonstrated the glucose homeostasis impairment that occurs in FD-null mice. Conclusions: Here, we report the first genetically confirmed functional, or type III, deficiency of an activating complement serine protease. This novel mechanism of FD inhibition can inform further development of alternative pathway inhibitors to treat common inflammatory diseases such as age-related macular degeneration.

Half of human cancers harbor TP53 mutations that render p53 inactive as a tumor suppressor. In these cancers, reactivation of mutant p53 (mutp53) through restoration of wild-type-like function constitutes a valuable anticancer therapeutic strategy. In order to search for mutp53 reactivators, a small library of tryptophanol-derived oxazoloisoindolinones was synthesized and the potential of these compounds as mutp53 reactivators and anticancer agents was investigated in human tumor cells and xenograft mouse models. By analysis of their anti-proliferative effect on a panel of p53-null NCI-H1299 tumor cells ectopically expressing highly prevalent mutp53, the compound SLMP53-2 was selected based on its potential reactivation of multiple structural mutp53. In mutp53-Y220C-expressing hepatocellular carcinoma (HCC) cells, SLMP53-2-induced growth inhibition was mediated by cell cycle arrest, apoptosis, and endoplasmic reticulum stress response. In these cells, SLMP53-2 restored wild-type-like conformation and DNA-binding ability of mutp53-Y220C by enhancing its interaction with the heat shock protein 70 (Hsp70), leading to the reestablishment of p53 transcriptional activity. Additionally, SLMP53-2 displayed synergistic effect with sorafenib, the only approved therapy for advanced HCC. Notably, it exhibited potent antitumor activity in human HCC xenograft mouse models with a favorable toxicological profile. Collectively, SLMP53-2 is a new mutp53-targeting agent with promising antitumor activity, particularly against HCC., Authors acknowledge the financial support from European Union (FEDER funds POCI/01/0145/FEDER/007728 through Programa Operacional Factores de Competitividade—COMPETE) and National Funds (FCT/MEC, Fundação para a Ciência e Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreement UID/DTP/04138/2019 (iMed.ULisboa), UID/NEU/04539/2013, UID/NEU/04539/2019. CENTRO-01-0145-FEDER-000012-HealthyAging2020, UID/BIO/04469/2019, BioTecNorte operation (NORTE-01-0145-FEDER-000004), and the projects (3599-PPCDT) PTDC/DTP-FTO/1981/2014—POCI-01-0145-FEDER-016581, and POCI-01-0145-FEDER-028736. We also thank FCT for the financial support through the grant CEECIND/01772/2017 (M. M. M. Santos), and fellowships SFRH/BD/96189/2013 (S. Gomes), PD/BD/143126/2019 (V. Barcherini), SFRH/BD/117949/2016 (L. Raimundo), SFRH/BD/119144/2016 (H. Ramos), SFRH/BD/128673/2017 (J. B. Loureiro), and the Programa Operacional Potencial Humano (POCH), specifically the BiotechHealth Programme (Doctoral Programme on Cellular and Molecular Biotechnology Applied to Health Sciences; PD/00016/2012). We also acknowledge the support from the Italian Association for Cancer Research, AIRC (IG#18985 to AI).