Greater Boston Area Theoretical Chemistry Lecture Series

2018-2019 Speaker Schedule

Enhanced Sampling methods for studying and designing cyclic peptides

09/19/18 4:15pm

MIT Building 4, Room 237

Yu-Shan Lin

Tufts University, Boston




Yu-Shan Lin

Protein–protein interactions (PPIs) play critical roles in many important and disease-relevant biological processes. Modulating PPIs thus provides a means to control diverse cellular functions for both fundamental research and therapeutic intervention. Unfortunately, protein–protein interfaces are challenging targets for traditional small molecules because the interfaces are relatively large and flat. Cyclic peptides (CPs) offer a promising solution for targeting PPIs, owing to their inherently large surface area and their ability to easily mimic functional groups and structures at protein interfaces. However, the high potential applicability of CPs is currently severely limited by our poor capacity to accurately predict CP structures. We recently developed an enhanced sampling method that uses metadynamics to target the coupled two-dihedral motions during conformational switches of cyclic peptides. This technique enables efficient simulations of CPs using even all-atom force fields and explicit solvent models and thus allows more accurate description of CP structures and energetics to be used during their rational design. In this talk, we describe how we used MD simulations and enhanced sampling methods to achieve the first accurate de novo structure prediction of cyclic penta- and hexapeptides, and our current progress in developing a platform for designing CPs to target PPIs.

Fragment-based Quantum Chemical Methods for Calculating Accurate Energies and Properties of Large Molecules and Nanoscale Systems

09/26/18 4:15pm

MIT Building 4, Room 237

Krishnan Raghavachari

Indiana University Bloomington




Krishnan Raghavachari

The development of accurate and broadly applicable models for large molecules is a major challenge in quantum chemistry. We are presently developing a hierarchy of novel fragment-based methods for the accurate description of the electronic structures and properties of large molecules. The electronic energies, molecular geometries, reactive potential energy surfaces, and many spectroscopic properties of a variety of large molecules have been investigated by our new methods. Our methods are also beginning to find applications in problems involving computer-aided design of receptors and drug molecules. We will describe the key ideas behind our Molecules-in-Molecules (MIM) fragment-based method, and present results from novel applications on a range of large molecules and nanoscale systems.

Insights into Complex Molecular Processes from Quantitative Atomistic Simulations

10/24/18 4:15pm

MIT Building 4, Room 237

Markus Meuwly

University of Basel




Markus Meuwly

Molecular dynamics simulations are a powerful means to provide molecular-level insights into processes ranging from gas-phase reaction dynamics to complex non-reactive and reactive rearrangements in biological systems. The utility of such simulations depends sensitively on the accuracy with which the intermolecular interactions are represented. In this seminar I will discuss recent progress in force field development including multipolar force fields, reproducing kernel Hilbert space techniques and machine learning and their application to spectroscopy and reactive processes in the condensed phase. The focus is on directly linking experimental observations with computations which provides molecular level understanding of spectroscopic observables and time scales from state-of-the art experiments. A typical example will be the relationship between structure and dynamics for infrared and X-ray absorption spectroscopy of biomolecules or the thermodynamics of reversed phase liquid chromatography.

Molecular simulations of lipid membrane sensing and shaping

11/14/18 4:15pm

MIT Building 4, Room 237

Gerhard Hummer

Max Planck Institute of Biophysics, Germany




Gerhard Hummer

Living cells need to exert tight control over their lipid membranes to maintain their internal structure, to guard their outside boundary, to establish potential and concentration gradients as their energy source, and to transmit signals between their compartments and to the outside. As a consequence, elaborate machineries have evolved that allow cells to sense and regulate the composition, shape and physical characteristics of their lipid membranes. In my talk I will give an overview of the physics and chemistry used by these machineries, as identified by molecular dynamics simulations combined with experiments.

11/28/18 4:15pm

MIT Building 4, Room 237

Jianzhi George Zhang

University of Michigan




Jianzhi George Zhang

Part 1. What determines the rate of protein sequence evolution and why The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what determines the functional constraint has remained unclear. The increasing availability of genomic data has enabled much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses has identified multiple mechanisms behind these observations and demonstrated a prominent role in protein evolution of selection against errors in molecular and cellular processes. Part 2. Multi-environment fitness landscapes of a yeast tRNA gene Fitness landscapes describe genotype-fitness relationships and are important for explaining and predicting evolution. But fitness landscapes are hard to map due to the sheer size of the genotype space coupled with the difficulty in accurately measuring fitness. In this talk, I describe our development of a high-throughput method for mapping fitness landscapes. We used this method to quantify the fitness in multiple environments for tens of thousands of yeast strains, each carrying a unique variant of a tRNA gene at its native genomic location. The obtained data allowed us to study the mechanistic basis of fitness landscapes and probe the impact of the environment on mutational effects. Some simple rules appear to underlie seemingly complex fitness landscapes.

TBD

01/30/19 4:15pm

MIT Building 4, Room 237

Benedetta Mennucci

University of Pisa, Italy




Benedetta Mennucci

TBD

TBD

02/13/19 4:15pm

MIT Building 4, Room 237

Robert Best

NIH




Robert Best

TBD

TBD

02/20/19 4:15pm

MIT Building 4, Room 237

Daniel Crawford

Virginia Tech




Daniel Crawford

TBD

TBD

02/27/19 4:15pm

MIT Building 4, Room 237

Laura Gagliardi

University of Minnesota




Laura Gagliardi

TBD

TBD

03/06/19 4:15pm

MIT Building 4, Room 237

Dan Tawfik

Weizmann Institute of Science




Dan Tawfik

TBD

TBD

03/20/19 4:15pm

MIT Building 4, Room 237

Mike Harms

University of Oregon




Mike Harms

TBD

TBD

03/27/19 4:15pm

MIT Building 4, Room 237

Huan-Xiang Zhou

University of Illinois at Chicago




Huan-Xiang Zhou

TBD

TBD

05/08/19 4:15pm

MIT Building 4, Room 237

Andy McCammon

UC San Diego




Andy McCammon

TBD

Past Schedules