#bioRxiv Subject Collection: Biophysics

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Transferable tICA-Metadynamics: Efficient sampling of protein mutants by transferring information from the wild type's Markov state model

We recently showed that the time-structure based independent component analysis method from Markov state model literature provided a set of variationally optimal slow collective variables for Metadynamics (tICA-Metadynamics). In this paper, we extend the methodology towards efficient sampling of protein mutants by borrowing ideas from transfer learning methods in machine learning. Our method explicitly assumes that a similar set of slow modes and states are found in both the wild type and its mutants. Under this assumption, we describe a few simple techniques using sequence mapping for transferring the slow modes and structural information contained in the wild type simulation to a mutant model for performing enhanced sampling. The resulting simulations can then be reweighted onto the full-phase space using MBAR, allowing for thermodynamic comparison against the wild type. We first benchmark our methodology by re-capturing alanine dipeptide dynamics across a range of different atomistic force fields after learning a set of slow modes using Amber ff99sb-ILDN. We next extend the method by including structural data from the wild type simulation and apply the technique to recapturing the affects of the GTT mutation on the FIP35 WW domain. — bioRxiv Subject Collection: Biophysics

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Predicting DNA Hybridization Kinetics from Sequence

Hybridization is a key molecular process in biology and biotechnology, but to date there is no predictive model for accurately determining hybridization rate constants based on sequence information. To approach this problem systematically, we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (subsequences of the CYCS and VEGF genes) at temperatures ranging from 28C to 55C. Next, we rationally designed 38 features computable based on sequence, each feature individually correlated with hybridization kinetics. These features are used in our implementation of a weighted neighbor voting (WNV) algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants (a.k.a. labeled instances). Automated feature selection and weighting optimization resulted in a final 6-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 2 with {approx}74% accuracy and within a factor of 3 with {approx}92% accuracy, based on leave-one-out cross-validation. Predictive understanding of hybridization kinetics allows more efficient design of nucleic acid probes, for example in allowing sparse hybrid-capture panels to more quickly and economically enrich desired regions from genomic DNA. — bioRxiv Subject Collection: Biophysics

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Rational design of proteins that exchange on functional timescales

Proteins are intrinsically dynamic molecules that can exchange between multiple conformational states, enabling them to carry out complex molecular processes with extreme precision and efficiency. Attempts to design novel proteins with tailored functions have mostly failed to yield efficiencies matching those found in nature because standard methods do not allow for the design of exchange between necessary conformational states on a functionally-relevant timescale. Here, we develop a broadly-applicable computational method to engineer protein dynamics that we term meta-multistate design. We used this methodology to design spontaneous exchange between two novel conformations introduced into the global fold of Streptococcal protein G domain {beta}1. The designed proteins, named DANCERs, for Dynamic And Native Conformational ExchangeRs, are stably folded and exchange between predicted conformational states on the millisecond timescale. The successful introduction of defined dynamics on functional timescales opens the door to new applications requiring a protein to spontaneously access multiple conformational states. — bioRxiv Subject Collection: Biophysics

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Molecular Simulation of Nonfacilitated MembranePermeation [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics

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Connecting the sequence-space of bacterial signaling proteins to phenotypes using coevolutionary landscapes [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics

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The genomic basis of electrotaxis in Dictyostelium discoideum: Electric field sensitive amino acids are dynamically encoded en masse for the streaming-stage proteome [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics

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Too packed to change: site-specific substitution rates and side-chain packing in protein evolution [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics

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Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics

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Relationship between protein thermodynamic constraints and variation of evolutionary rates among sites [NEW RESULTS]

— bioRxiv Subject Collection: Biophysics