In silico approaches for better understanding cysteine cathepsin-glycosaminoglycan interactions.

Cysteine cathepsins constitute the largest cathepsin family, with 11 proteases in human that are present primarily within acidic endosomal and lysosomal compartments. They are involved in the turnover of intracellular and extracellular proteins. They are synthesized as inactive procathepsins that are converted to mature active forms. Cathepsins play important roles in physiological and pathological processes and, therefore, receive increasing attention as potential therapeutic targets. Their maturation and activity can be regulated by glycosaminoglycans (GAGs), long linear negatively charged polysaccharides composed of recurring dimeric units. In this review, we summarize recent computational progress in the field of (pro)cathepsin-GAG complexes analyses.

In silico insights into procathepsin S maturation mediated by glycosaminoglycans.

Procathepsins, inactive precursors of cathepsins are present in the extracellular matrix (ECM) and in lysosomes. Their active forms are involved in a number of biologically relevant processes, including bone resorption, intracellular proteolysis and regulation of programmed cell death. These processes might be mediated by glycosaminoglycans (GAGs), long unbranched periodic negatively charged polysaccharides. GAGs are also present in ECM and play important role in anticoagulation, angiogenesis and tissue regeneration. GAGs not only mediate the enzymatic activity of cathepsins but can also regulate the process of procathepsin maturation, as it was shown for procathepsin B and S. In this study, we propose the molecular mechanism underlying the biological role of GAGs in procathepsin S maturation and compare our findings with computational data obtained for procathepsin B. We rigorously analyse procathepsin S-GAG complexes in terms of their dynamics, free energy and potential allosteric regulation. We conclude that the GAG binding region might have an effect on the dynamics of procathepsin S structure and so affect its maturation by two different mechanisms.

Explicit solvent repulsive scaling replica exchange molecular dynamics (RS-REMD) in molecular modeling of protein-glycosaminoglycan complexes.

Glycosaminoglcyans (GAGs), linear anionic periodic polysaccharides, are crucial for many biologically relevant functions in the extracellular matrix. By interacting with proteins GAGs mediate processes such as cancer development, cell proliferation and the onset of neurodegenerative diseases. Despite this eminent importance of GAGs, they still represent a limited focus for the computational community in comparison to other classes of biomolecules. Therefore, there is a lack of modeling tools designed specifically for docking GAGs. One has to rely on existing docking software developed mostly for small drug molecules substantially differing from GAGs in their basic physico-chemical properties. In this study, we present an updated protocol for docking GAGs based on the Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) that includes explicit solvent description. The use of this water model improved docking performance both in terms of its accuracy and speed. This method represents a significant computational progress in GAG-related research.

Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment.

The UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES-contact group), and (iii) template-assisted (the UNRES-template group). For most of the targets, the contact restraints were derived from the server models top-ranked by the DeepQA method, while the DNCON2 method was used for 11 targets. Our consensus-fragment procedure was used to run template-assisted predictions. Each group also processed the Nuclear Magnetic Resonance (NMR)- and Small Angle X-Ray Scattering (SAXS)-data assisted targets. The average Global Distance Test Total Score (GDT_TS) of the 'Model 1' predictions were 29.17, 39.32, and 56.37 for the UNRES, UNRES-contact, and UNRES-template predictions, respectively, increasing by 0.53, 2.24, and 3.76, respectively, compared to CASP13. It was also found that the GDT_TS of the UNRES models obtained in ab initio mode and in the contact-assisted mode decreases with the square root of chain length, while the exponent in this relationship is 0.20 for the UNRES-template group models and 0.11 for the best performing AlphaFold2 models, which suggests that incorporation of database information, which stems from protein evolution, brings in long-range correlations, thus enabling the correction of force-field inaccuracies.

Role of Oligosaccharide Chain Polarity in Protein-Glycosaminoglycan Interactions.

Glycosaminoglycans (GAGs) are long unbranched anionic polysaccharides made up of repetitive disaccharide units involved in biologically relevant processes in the extracellular matrix such as cell proliferation and communication. A GAG can be bound in antiparallel energetically comparable orientations on the protein surface, and these orientations are, therefore, difficult to distinguish both experimentally and computationally. In this study, for the first time we analyzed the impact of the GAG chain polarity on the interactions with Fibroblast Growth Factors-1 and -2 (FGF-1 and FGF-2). We performed a series of 1 µs molecular dynamics simulations of the FGF-1 and FGF-2 complexes with heparin (HP), a GAG representative, of different length. We analyzed the relationship between the HP orientation, energetic, and conformational space characteristics of FGF-1-HP and FGF-2-HP complexes. We concluded that HP can be bound by these proteins in the same binding sites but in different orientations, while the orientation present in the experimental structure might be favorable. Our data presented in this study provide a novel view on the impact of GAG polarity on the specificity of protein-GAG complex formation, which is an essential aspect for the proper understanding of the intermolecular interactions in these systems.

The abnormal accumulation of heparan sulfate in patients with mucopolysaccharidosis prevents the elastolytic activity of cathepsin V.

Mucopolysaccharidosis (MPS) are rare inherited diseases characterized by accumulation of lysosomal glycosaminoglycans, including heparan sulfate (HS). Patients exhibit progressive multi-visceral dysfunction and shortened lifespan mainly due to a severe cardiac/respiratory decline. Cathepsin V (CatV) is a potent elastolytic protease implicated in extracellular matrix (ECM) remodeling. Whether CatV is inactivated by HS in lungs from MPS patients remained unknown. Herein, CatV colocalized with HS in MPS bronchial epithelial cells. HS level correlated positively with the severity of respiratory symptoms and negatively to the overall endopeptidase activity of cysteine cathepsins. HS bound tightly to CatV and impaired its activity. Withdrawal of HS by glycosidases preserved exogenous CatV activity, while addition of Surfen, a HS antagonist, restored elastolytic CatV-like activity in MPS samples. Our data suggest that the pathophysiological accumulation of HS may be deleterious for CatV-mediated ECM remodeling and for lung tissue homeostasis, thus contributing to respiratory disorders associated to MPS diseases.

Role of Glycosaminoglycans in Procathepsin B Maturation: Molecular Mechanism Elucidated by a Computational Study.

Procathepsins are an inactive, immature form of cathepsins, predominantly cysteine proteases present in the extracellular matrix (ECM) and in lysosomes that play a key role in various biological processes such as bone resorption or intracellular proteolysis. The enzymatic activity of cathepsins can be mediated by glycosaminoglycans (GAGs), long unbranched periodic negatively charged polysaccharides found in ECM that take part in many biological processes such as anticoagulation, angiogenesis, and tissue regeneration. In addition to the known effects on mature cathepsins, GAGs can mediate the maturation process of procathepsins, in particular, procathepsin B. However, the detailed mechanism of this mediation at the molecular level is still unknown. In this study, for the first time, we aimed to unravel the role of GAGs in this process using computational approaches. We rigorously analyzed procathepsin B-GAG complexes in terms of their dynamics, energetics, and potential allosteric regulation. We revealed that GAGs can stabilize the conformation of the procathepsin B structure with the active site accessible for the substrate and concluded that GAGs most probably bind to procathepsin B once the zymogen adopts the enzymatically active conformation. Our data provided a novel mechanistic view of the maturation process of procathepsin B, while the approaches elaborated here might be useful to study other procathepsins. Furthermore, our data can serve as a rational guide for experimental work on procathepsin-GAG systems that are not characterized in vivo and in vitro yet.

Rat cathepsin K: Enzymatic specificity and regulation of its collagenolytic activity.

Human cathepsin K (hCatK), which is highly expressed in osteoclasts, has the noteworthy ability to cleave type I and II collagens in their helical domain. Its collagenase potency depends strictly on the formation of an oligomeric complex with chondroitin 4-sulfate (C4-S). Accordingly, hCatK is a pivotal protease involved in bone resorption and is an attractive target for the treatment of osteoporosis. As rat is a common animal model for the evaluation of hCatK inhibitors, we conducted a comparative analysis of rat CatK (rCatK) and hCatK, which share a high degree of identity (88%) and similarity (93%). The pH activity profile of both enzymes displayed a similar bell-shaped curve (optimal pH: 6.4). Presence of Ser134 and Val160 in the S2 pocket of rCatK instead of Ala and Leu residues, respectively, in hCatK, led to a weaker peptidase activity, as observed for mouse CatK. Also, regardless of the presence of C4-S, rCatK cleaved in the nonhelical telopeptide regions of both type I (tail) and type II (articular joint) rat collagens. Structure-based computational analyses (electrostatic potential, molecular docking, molecular dynamics, free energy calculations) sustained that the C4-S mediated collagenolytic activity of rCatK obeys distinct molecular interactions from those of hCatK. Additionally, T-kininogen (a.k.a. thiostatin), a unique rat serum acute phase molecule, acted as a tight-binding inhibitor of hCatK (Ki = 0.11 ± 0.05 nM). Taken into account the increase of T-Kininogen level in inflamed rat sera, this may raise the question of the appropriateness to evaluate pharmacological hCatK inhibitors in this peculiar animal model.

Analysis of Procollagen C-Proteinase Enhancer-1/Glycosaminoglycan Binding Sites and of the Potential Role of Calcium Ions in the Interaction.

In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, to predict GAG binding poses for various GAG lengths, types and sulfation patterns, and to determine the effect of calcium ions on the binding. The computational data are analyzed and discussed in the context of the experimental results previously obtained using surface plasmon resonance binding assays. We also provide experimental data on PCPE-1/GAG interactions obtained using inhibition assays with GAG oligosaccharides ranging from disaccharides to octadecasaccharides. Our results predict the localization of GAG-binding sites at the amino acid residue level onto PCPE-1 and is the first attempt to describe the effects of ions on protein-GAG binding using modeling approaches. In addition, this study allows us to get deeper insights into the in silico methodology challenges and limitations when applied to GAG-protein interactions.

Local and long range potentials for heparin-protein systems for coarse-grained simulations.

Heparin belongs to glycosaminoglycans (GAGs), a class of periodic linear anionic polysaccharides, which are functionally important components of the extracellular matrix owing to their interactions with various protein targets. Heparin is known to be involved in many cell signaling processes, while the experimental data available for heparin are significantly more abundant than for other GAGs. At the same time, the length and conformational flexibility of the heparin represent major challenges for its theoretical analysis. Coarse-grained (CG) approaches, which enable us to extend the size- and time-scale by orders of magnitude owing to reduction of system representation, appear, therefore, to be useful in simulating these systems. In this work, by using umbrella-sampling molecular dynamics simulations, we derived and parameterized the CG backbone-local potentials of heparin chains and the orientational potentials for the interactions of heparin with amino acid side chains to be further included in the physics-based Unified Coarse-Grained Model of biological macromolecules. With these potentials, simulations of extracellular matrix processes where both heparin and multiple proteins participate will be possible.

Molecular dynamics insights into protein-glycosaminoglycan systems from microsecond-scale simulations.

Heparin is a key player in cell signaling via its physical interactions with protein targets in the extracellular matrix. However, basic molecular level understanding of these highly biologically relevant intermolecular interactions is still incomplete. In this study, for the first time, microsecond-scale MD simulations are reported for a complex between fibroblast growth factor 1 and heparin. We rigorously analyze this molecular system in terms of the conformational space, structural, energetic, and dynamic characteristics. We reveal that the conformational selection mechanism of binding denotes a recognition specificity determinant. We conclude that the length of the simulation could be crucial for evaluation of some of the analyzed parameters. Our data provide novel significant insights into the interactions in the fibroblast growth factor 1 complex with heparin, in particular, and into the physical-chemical nature of protein-glycosaminoglycan systems in general, which have potential applicability for biomaterials development in the area of regenerative medicine.

Use of the UNRES force field in template-assisted prediction of protein structures and the refinement of server models: Test with CASP12 targets.

Knowledge-based methods are, at present, the most effective ones for the prediction of protein structures; however, their results heavily depend on the similarity of a target sequence to those of proteins with known structures. On the other hand, the physics-based methods, although still less accurate and more expensive to execute, are independent of databases and give reasonable results where the knowledge-based methods fail because of weak sequence similarity. Therefore, a plausible approach seems to be the use of knowledge-based methods to determine the sections of the structures that correspond to sufficient sequence similarity and physics-based methods to determine the remaining structure. By participating in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12) as the KIAS-Gdansk group, we tested our recently developed hybrid approach, in which protein-structure prediction is carried out by using the physics-based UNRES coarse-grained energy function, with restraints derived from the server models. Best predictions among all groups were obtained for 2 targets and 80% of our models were in the upper 50% of the models submitted to CASP. Our method was also able to exclude, with about 70% confidence, the information from the servers that performed poorly on a given target. Moreover, the method resulted in the best models of 2 refinement targets and performed remarkably well on oligomeric targets.