Investigation of structural dynamics and the function of membrane proteins with computational techniques

Pant, Shashank

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https://hdl.handle.net/2142/113116 Copy

Description

Title

Investigation of structural dynamics and the function of membrane proteins with computational techniques

Author(s)

Pant, Shashank

Issue Date

2021-05-25

Director of Research (if dissertation) or Advisor (if thesis)

Tajkhorshid, Emad

Doctoral Committee Chair(s)

Tajkhorshid, Emad

Committee Member(s)

• Shukla, Diwakar
• Chung, Hee Jung
• Pogorelov, Taras

Department of Study

School of Molecular & Cell Bio

Discipline

Biophysics & Quant Biology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Membrane Protein
• Free Energy
• Transporters
• Molecular Dynamics
• Accelerated Membrane
• Membrane Binding
• Lipid protein interactions
• Neurotransmitter Transporters
• Ion-channels

Abstract

With the development of more accurate force fields and powerful computers, molecular dynamics (MD) has become a ubiquitous tool to study complex structural, thermodynamic and kinetic processes of real world systems across disciplines. MD has a long history of being employed to enhance our understanding and guide experiments by unravelling fine details at high spatial and temporal resolution. This unique feature of MD offers insights to the highly specific interactions that dictate various biological processes. This dissertation entails the use and development of advanced simulation techniques by employing synergies between statistical mechanics, computer simulations and artificial intelligence (AI) to study the complex biological processes at the interface of the biological membranes.Through the use of accelerated membrane models, which enhanced phospholipid diffusion and reorganization in the membrane using an atomistic representation, we captured repeated and spontaneous insertion of human signalling proteins, in a lipid-dependent manner. More specifically, simulations of GRP1-PH domain allowed us to capture differential binding and conformational dynamics of the PH domain in the presence of membranes containing PC,PS, and PIP3lipids in varying compositions. Interestingly, the use of Highly Mobile Membrane Mimetic (HMMM) allowed us to capture, for the first time, two distinct PIP3 binding modes,suggesting the possibility of simultaneous binding of multiple anionic lipids might dictate the recruitment and stabilization of the domain. In a separate study, membrane-binding simulations of ASAP1-PH domain shows that the overall electrostatic environment of the membrane drives the membrane recruitment of the protein and specific binding to the rare PIP2lipids, leads to its allosteric modulation. We believe that this allosteric modulation plays a very important role in the downstream signalling events.Integral membrane proteins in their native environment are also presented. As a major class of integral membrane proteins, secondary active neurotransmitter transporters strictly couple the uphill transport of the substrate, with Na+and/or H+ ions. To achieve their functional role, these transporters undergo large-scale transition between outward-facing (OF) and inward-facing (IF) states, following the so-called “alternating-access model”. To address the key role of alternating access model and elucidate the molecular mechanism of the transport cycle, we performed MD simulations combined with advanced simulation techniques on human and bacterial glutamate transporters, involved in the neurotransmission of the brain. As the human glutamate transporter is proton coupled, we first employed constant pH MD simulations to capture the proton binding site and its binding sequence. The results obtained from these simulations were further verified by our experimental collaborators. Also, we were able to uncover how the strict coupling between the substrate, Na+and H+dictates the transition cycle of the human transporter. Next, we combined the power of concerted structural biology and computational biophysics to unravel the alter-ego of a transporter.We were able to uncover, for the first time, how a transporter develops an ion channel property right in the middle of its transport cycle. Finally, the section on neurotransmitter transporters concludes with the lipid-dependent energetic characterization of conformational transitions in human glutamate transporters. These extensive free energy calculations allowed us to capture, in atomic details, the forward transition cycle and specific intermediates which might play an important role in designing novel therapeutics against various neurological disorders. We applied our protocol to capture large-scale conformational transitions in P-glycoprotein, with the aim to uncover novel binding sites for the third-generation inhibitor. Based on this study, we were able to propose a novel inhibitory mechanism for third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters. Lastly, in this section we employed MD simulations in combination with electrophysiology experiments to capture lipid-mediated conformational regulation of an epilepsy-causing voltage-gated potassium channel, Kv7.2.In the last section, we have developed an AI-based approach which can be combined with MD simulations to mitigate the problem of sampling. Typically, MD simulations, per construction, suffer from limited sampling and thus limited data. As such, the use of AI in molecular simulations can suffer from a dangerous situation where the AI optimization could get stuck in spurious regimes, leading to incorrect characterization of the reaction coordinate (RC) for the problem at hand. To deal with this problem of spurious AI solutions,we developed an automated approach which combines the idea from statistical physics, including the concept of maximum caliber to differentiate between the fast and the slow processes. We show the applicability of this protocol for three classic benchmark problems, namely, the conformational dynamics of a model peptide, ligand unbinding from a protein, and folding/unfolding energy landscape of a peptide.

Graduation Semester

2021-08

Type of Resource

Thesis

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http://hdl.handle.net/2142/113116

Copyright and License Information

Copyright 2021 Shashank Pant

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