Publications

2023

• Saftić Martinović, L., Birkić, N., Miletić, V., Antolović, R., Štanfel, D. & Wittine, K. Antioxidant Activity, Stability in Aqueous Medium and Molecular Docking/Dynamics Study of 6-Amino- and N-Methyl-6-amino-L-ascorbic Acid. Int. J. Mol. Sci. 24(2), 1410 (2023). doi:10.3390/ijms24021410 (WoS-SCIE, Q1 (2021), JIF: 6.208 (2021))

  Abstract

  The antioxidant activity and chemical stability of 6-amino-6-deoxy-L-ascorbic acid (D1) and N-methyl-6-amino-6-deoxy-L-ascorbic acid (D2) were examined with ABTS and DPPH assays and compared with the reference L-ascorbic acid (AA). In addition, the optimal storing conditions, as well as the pH at which the amino derivatives maintain stability, were determined using mass spectrometry. Comparable antioxidant activities were observed for NH-bioisosteres and AA. Moreover, D1 showed higher stability in an acidic medium than the parent AA. In addition, AA, D1, and D2 share the same docking profile, with wild-type human peroxiredoxin as a model system. Their docking scores are similar to those of dithiothreitol (DTT). This suggests a similar binding affinity to the human peroxiredoxin binding site.

2022

• Turalija, M., Petrović, M. & Kovačić, B. Towards General-Purpose Long-Timescale Molecular Dynamics Simulation on Exascale Supercomputers with Data Processing Units. in 2022 45th Jubilee International Convention on Information, Communication, and Electronic Technology (MIPRO), 300–306 (2022). doi:10.23919/MIPRO55190.2022.9803537

  Abstract

  Molecular dynamics (MD) simulation provides the atomic-level characterization of biomolecular systems and their transitions, such as conformational changes in proteins. The computational demands of such simulations and limits of parallelization techniques have prevented simulations of real-world systems from reaching the microsecond timescales, which are relevant for real-world applications. The notable exceptions are the supercomputers specifically designed for MD simulations. An example of such supercomputers is the Anton supercomputer, nowadays in its third iteration, which uses a substantial number of application-specific integrated circuits (ASICs) for MD simulation and is not generally available. Recent advances in algorithms, software, and hardware towards exascale supercomputing have made microsecond-timescale simulations of practically relevant biomolecular systems reachable within days. Data processing units (DPUs) are already being used in data centers for the in-flight processing of network packets (e.g. encryption, decryption, and intrusion detection) and are expected to be used in future exascale supercomputers in some form. The usage of DPUs in the supercomputers unlocks the potential to accelerate MD simulations that were previously available only in networking ASICs in supercomputers such as Anton. This paper proposes the usage of DPUs for MD simulation acceleration in an innovative way inspired by the Anton supercomputer.

2021

• Miletić, V., Nikolić, P. & Kinkela, D. Structure-based Molecular Docking in the Identification of Novel Inhibitors Targeting SARS-CoV-2 Main Protease. in 2021 44th International Convention on Information, Communication, and Electronic Technology (MIPRO), 435–440 (2021). doi:10.23919/MIPRO52101.2021.9596660

  Abstract

  There have been several studies of natural compounds used as SARS-CoV-2 inhibitors. Among those, we selected the most viable natural anti-viral compound, rutin, as a basis for structure-based molecular docking campaign using databases of commercially available compounds that are potential ligands. The known and well-studied SARS-CoV-2 main protease structure was used as a target and Asinex screening library was filtered to select structurally similar and pharmacokinetically feasible compounds. Before screening campaing, the protein was minimized and selected compounds were protonated and parametrized. A modified version of rDock high-throughput virtual screening tool called RxDock was used for molecular docking. RxDock was developed to enable running large molecular docking studes on modern computer systems, including supercomputers and clouds. Our approach combines traditional approach of pharmaceutical industry where natural compounds are used as a template to develop novel inhibitors while using novel high-throughput virtual screening techniques and validation tests. It promises to pave a way to develop an agnostic approach in development of novel inhibitors while keeping the cost of both the computational protocols and bioassays lower than the current drug discovery pipeline.

• Svedružić, Ž. M, Vrbnjak, K., Martinović, M. & Miletić, V. Structural Analysis of the Simultaneous Activation and Inhibition of γ-Secretase Activity in the Development of Drugs for Alzheimer's Disease. Pharmaceutics 13(4), 514 (2021). doi:10.3390/pharmaceutics13040514 (WoS-SCIE, Q1, JIF: 6.525; times cited: 3)

  Abstract

  Significance: The majority of the drugs which target membrane-embedded protease γ-secretase show an unusual biphasic activation–inhibition dose-response in cells, model animals, and humans. Semagacestat and avagacestat are two biphasic drugs that can facilitate cognitive decline in patients with Alzheimer's disease. Initial mechanistic studies showed that the biphasic drugs, and pathogenic mutations, can produce the same type of changes in γ-secretase activity. Results: DAPT, semagacestat LY-411,575, and avagacestat are four drugs that show different binding constants, and a biphasic activation–inhibition dose-response for amyloid-β-40 products in SH-SY5 cells. Multiscale molecular dynamics studies have shown that all four drugs bind to the most mobile parts in the presenilin structure, at different ends of the 29 Å long active site tunnel. The biphasic dose-response assays are a result of the modulation of γ-secretase activity by the concurrent binding of multiple drug molecules at each end of the active site tunnel. The drugs activate γ-secretase by facilitating the opening of the active site tunnel, when the rate-limiting step is the tunnel opening, and the formation of the enzyme–substrate complex. The drugs inhibit γ-secretase as uncompetitive inhibitors by binding next to the substrate, to dynamic enzyme structures which regulate processive catalysis. The drugs can modulate the production of different amyloid-β catalytic intermediates by penetration into the active site tunnel, to different depths, with different flexibility and different binding affinity. Conclusions: Biphasic drugs and pathogenic mutations can affect the same dynamic protein structures that control processive catalysis. Successful drug-design strategies must incorporate transient changes in the γ-secretase structure in the development of specific modulators of its catalytic activity.

2020

• Miletić, V., Ašenbrener Katić, M. & Svedružić, Ž. High-throughput Virtual Screening Web Service Development for SARS-CoV-2 Drug Design. in 2020 43rd International Convention on Information, Communication, and Electronic Technology (MIPRO), 371–376 (2020). doi:10.23919/MIPRO48935.2020.9245082

  Abstract

  The available structures of viral proteins and RNA molecules related to SARS-CoV-2 are used to screen and design a new set of drugs using the commercial databases and molecular docking protocols. The selected molecules are then studied further using molecular dynamics. Based on our earlier experiences we can target proteases, enzymes in DNA and RNA metabolism, and protein-protein interactions. In this paper we describe the planned research and development efforts for efficient screening and design of new drugs. Prior to the screening campaign, we will develop new open-source computational infrastructure, with two major outcomes. A new database containing all commercially available small-molecule ligands will be developed. A docking server with a web-based user interface will be developed and interfaced with the compound database. The docking server will use the database for sourcing of the molecules for the high-throughput virtual screening. Our approach offers major advantages that can bypass the problems that have traditionally plagued the pharmaceutical industry: our protocols are faster, cheaper, versatile, and offer minimal risks. We are developing new drugs using commercial databases, which allows us to buy the lead compounds for affordable prices that can bypass expensive and slow organic synthesis protocols.

2019

• Herrera-Rodríguez, A., Miletić, V., Aponte-Santamaría, C. & Gräter, F. Molecular dynamics simulations of molecules in uniform flow. Biophys. J. 116(6), 621–632 (2019). doi:10.1016/j.bpj.2018.12.025 (WoS-SCIE, Q1, JIF: 3.854; times cited: 7)

  Abstract

  Flow at the molecular level induces shear-induced unfolding of single proteins and can drive their assembly, the mechanisms of which are not completely understood. To be able to analyze the role of flow on molecules, we present uniform-flow molecular dynamics simulations at atomic level. The pull module of the GRoningen MAchine for Chemical Simulations package was extended to be able to force-group atoms within a defined layer of the simulation box. Application of this external enforcement to explicit water molecules, together with the coupling to a thermostat, led to a uniform terminal velocity of the solvent water molecules. We monitored the density of the whole system to establish the conditions under which the simulated flow is well-behaved. A maximal velocity of 1.3 m/s can be generated if a pull slice of 8 nm is used, and high velocities would require larger pull slices to still maintain a stable density. As expected, the target velocity increases linearly with the total external force applied. Finally, we suggest an appropriate setup to stretch a protein by uniform flow, in which protein extensions depend on the flow conditions. Our implementation provides an efficient computational tool to investigate the effect of the flow at the molecular level.

Author: Vedran Miletić